Publications

Anthony, TTC & Ha, Q 2018, A Quadratic Constraint Approach to Model Predictive Control of Interconnected Systems, Springer, Germany.
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This book focuses on the stabilization and model predictive control of interconnected systems with mixed connection configurations.

Argha, A, Su, S, Li, L, Nguyen, HT & Celler, BG 2018, Advances in Discrete-Time Sliding Mode Control Theory and Applications, CRC Press.
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The focus of this book is on the design of a specific control strategy using digital computers.

Ashraf, J, Hussain, OK, Hussain, FK & Chang, EJ 2018, Measuring and Analysing the Use of Ontologies, Springer International Publishing, Switzerland.
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Cao, L 2018, Data Science Thinking, Springer International Publishing.
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Indraratna, B & Ngo, T 2018, Ballast Railroad Design: SMART-UOW Approach, CRC Press.
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Liu, B, Zhou, W, Zhu, T, Xiang, Y & Wang, K 2018, Location Privacy in Mobile Applications, Springer Singapore.
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McLuckie, D & Sayers, P 2018, Strategic Management of Flood Risk.

Pham, TT 2018, Applying Machine Learning for Automated Classification of Biomedical Data in Subject-independent Settings, Springer.

Plant, R, Maurel, P, Barbe, E & Brennan, J 2018, Les terres agricoles face à l’urbanisation —De la donnée à l’action, quels rôles pour l’information ?, Update Sciences Technologies, Éditions Quae, Versailles.
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La perte de terres agricoles liées à l’urbanisationconstitue l’une des facettes de la consommation des terres. Commencé dans lesannées 1970, ce phénomène – essentiellement dû à l’étalement urbain –prend des proportions jusque-là inégalées. Les conséquences de ces processusd’artificialisation sont multiples et portent à la fois sur la production etsur la sécurité alimentaire ainsi que sur la perte de biodiversité. Cesprocessus interrogent aussi les formes de solidarité territoriale entre lesvilles et les espaces péri-urbains et ruraux.Issu d’une collaboration scientifique lancée au début desannées 2010 entre l’Université de technologie de Sydney (University ofTechnology Sydney, UTS) et l’Institut national de recherche en sciences ettechnologies pour l’environnement et l’agriculture (Irstea), cet ouvrage abordedes points clés de la problématique de la consommation des terres en sefocalisant sur les terres agricoles en France et en Australie. Plutôt que d’offrirune analyse comparative approfondie de la planification des terres agricolespériurbaines entre les deux pays, il propose une exploration des « boîtesà outils » de l’ingénierie territoriale développées et mobilisées pourfaire face à l’enjeu de la perte de terres agricoles liée à l’urbanisation. Iloffre également un « arrêt sur image » dans un panorama de champs derecherche en pleine évolution, autant du point de vue théorique queméthodologique.

Shannon, AG & Leyendekkers, JV 2018, The fibonacci numbers and integer structure: Foundations for a modern quadrivium.
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In the study of integers over many centuries, simple but very useful data have often been overlooked or at least sparingly used. The development of modular rings provides a means to shed light on such data. A modular ring is effectively an array of integers which can be uniquely identified by columns and rows with the aid of linear equations. Thus the modular ring Z4 has 4 columns (or classes), and its first two rows are 0,1,2,3 and 4,5,6,7, respectively. In turn, its columns can be identified by the classes. This notation is suggestive and transparent, and the notation itself becomes a tool of thought. The book contains a collection of readily accessible classical problems, most of which can be linked to the sequence of Fibonacci integers and explained with integer structure analysis. Modular rings are used to solve, prove and extend a variety of number theory problems associated with generalized Fibonacci numbers, golden ratio families and primes, and distinctions between prime and composite integers, as well as the classical conjectures of Brocard-Ramanujan and Erdös-Strauss. Thus (though mathematically, the golden ratio is a humble surd), replacing its argument shows that it has an infinity for close relatives that can be a source of further exploration, particularly with generalizations of Fibonacci numbers. Another important structural feature is the right-end-digit (RED) of an integer - its value modulo 10. No matter the sizes of integers, operations with their REDs are stable; for instance, the sum of the integers abcde2 and ghabj5 has a RED of 7. This stability is exploited in several chapters so that powers are reduced to 4 types in the ring modulo 4 which, for example, clarifies Fermat’s Last Theorem for some powers. The context of this book is the teaching and learning of mathematics. This happens in historical and sociological contexts, and the text has sufficient historical and philosophical allusions for anyone to see that mathematics per...

Stewart, MG & Mueller, J 2018, Are We Safe Enough?, Elsevier.
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Are We Safe Enough? Measuring and Assessing Aviation Security explains how standard risk analytic and cost-benefit analysis can be applied to aviation security in systematic and easy-to-understand steps. The book evaluates and puts into sensible context the risks associated with air travel, the risk appetite of airlines and regulators and the notion of acceptable risk. It does so by describing the effectiveness, risk reduction and cost of each layer of aviation security, from policing and intelligence to checkpoint passenger screening to arming pilots on the flight deck.

Wu, C, Li, J & Su, Y 2018, Development of Ultra-High Performance Concrete against Blasts: From Materials to Structures.
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Development of Ultra-High Performance Concrete against Blasts: From Materials to Structures presents a detailed overview of UHPC development and its related applications in an era of rising terrorism around the world. Chapters present case studies on the novel development of the new generation of UHPC with nano additives. Field blast test results on reinforced concrete columns made with UHPC and UHPC filled double-skin tubes columns are also presented and compiled, as is the residual load-carrying capacities of blast-damaged structural members and the exceptional performance of novel UHPC materials that illustrate its potential in protective structural design. As a notable representative, ultra-high performance concrete (UHPC) has now been widely investigated by government agencies and universities. UHPC inherits many positive aspects of ultra-high strength concrete (UHSC) and is equipped with improved ductility as a result of fiber addition. These features make it an ideal construction material for bridge decks, storage halls, thin-wall shell structures, and other infrastructure because of its protective properties against seismic, impact and blast loads.

Zhou, J 2018, Multimodal behavioral and physiological signals as indicators of cognitive load.

Achenbach, M, Busch, F, Deuse, J & Weisner, K 2018, 'Gestaltung sozio-technischer Arbeitssysteme für Industrie 4.0' in Digitalisierung industrieller Arbeit, Nomos Verlagsgesellschaft mbH & Co. KG, pp. 195-214.
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Aguilera, RP, Acuna, P, Konstantinou, G, Vazquez, S & Leon, JI 2018, 'Basic Control Principles in Power Electronics' in Blaabjerg, F (ed), Control of Power Electronic Converters and Systems, Elsevier, USA, pp. 31-68.
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In this chapter, basic principles and methods of control with a view toward applications in power electronics are provided. Control targets from a power electronics viewpoint are presented in order to take them into account when designing a controller. The standard approach to control power converters that use a linear controller to define a desired closed-loop dynamic along with a modulator to finally handle the power converter switches is discussed in detail. For this purpose, several modulation techniques are explored. Moreover, a design procedure for linear controllers to track constant and sinusoidal references is formally derived. This design considers the fact that the controller can be implemented ether in analog or digital form. Finally, some insights into controllers that do not follow this standard approach are also provided.

Altaee, A, Alanezi, AA & Hawari, AH 2018, 'Forward osmosis feasibility and potential future application for desalination' in Gude, G (ed), Emerging Technologies for Sustainable Desalination Handbook, Elsevier, Mississippi State University, pp. 35-54.
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© 2018 Elsevier Inc. All rights reserved. Forward Osmosis has been intensively investigated for seawater desalination in the past decade. However, the application of technology is still limited apart from a number of pilot and small commercial plants. Initially, forward osmosis was proposed as a breakthrough in the desalination technologies due to its potential for reducing the power consumption to the thermodynamic seawater limits. Lately, experimental studies have demonstrated that first insights underestimated the technology's energy efficiency and feasibility for desalination. Membrane fouling, back salt diffusion, membrane mechanical strength, draw solution, and many other factors were behind the loss of interest in forward osmosis technology. Conversely, field experiments have shown that forward osmosis membrane fouling was not a major problem, and water flux met the expectation when a full-scale hollow fiber membrane was provided. However, there were insufficient data regarding the cost and energy efficiency of the membrane regeneration stage. For thermal regeneration using a thermolytic draw solution, the major concerns were the ease of application and residual draw solution in the feed solution. The current study addresses the pros and cons of forward osmosis and the primary reason behind the technology being less successful, despite the large amount of money and efforts invested over the past decade.

Altaee, A, Alanezi, AA, Alazmi, R, Hawari, AH & Mascialino, C 2018, 'Effect of the Draw Solution on the Efficiency of Two-Stage FO-RO/BWRO for Seawater and Brackish Water Desalination' in Mujtaba, I, Majozi, T & Mutiu Kolade Amosa, MK (eds), Water Management, CRC Press, pp. 73-87.
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With 30 chapters authored by internationally renowned experts, this work offers readers a comprehensive view of both social and technological outlooks to help solve this global issue.

Altaee, A, Saiyed R. Wahadj, SR, Adel O. Sharif, AO, Zaragoza, G, Hamdan, M & Maryam Aryafar, M 2018, 'Forward Osmosis for irrigation Water Supply Using Hybrid Membrane System for Draw Solution Regeneration' in I. M. Mujtaba, IM, R. Srinivasan, R & N. O. Elbashir, NO (eds), The Water-Food-Energy Nexus: Processes, Technologies and Challenges, CRC Press, USA, pp. 56-68.
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Forward Osmosis (FO) process was applied for irrigation water supply using fertilizers and seawater as the draw and feed solutions. Four agents, KNO3, Na2SO4, CaNO3, and MgCl2, plus 35 g/L seawater were used as the draw and feed solutions of the FO process. Net Driving Pressure (NDP) in FO process was manipulated either by increasing the concentration of draw solution (FO process) or by increasing feed pressure (Pressure Assisted FO; PAFO process). Series of NF and RO membranes were used for the regeneration of draw solution. The results showed that PAFO was more energy efficient than FO provided using the low energy of brine flow from the NF/RO membrane for pressurizing the feed solution of PAFO process. Furthermore, the study suggested using a mixture of a primary draw solution, MgCl2, and a secondary draw solution, KNO3, for NO3 supply into the irrigation water. As such, MgCl2 provided the driving force for fresh water extraction while KNO3 is the source of fertilizer for irrigation water. Results showed that water quality provided by MgCl2+KNO3 mixture draw solution was better than that from KNO3 or Ca(NO3)2. The concentrations of NO3 and SO4 in irrigation water were within the recommended level when the diluted draw solution was regenerated by a dual stage low pressure RO process.

Althuwaynee, OF & Pradhan, B 2018, 'Landslides' in Natural Hazards, CRC Press, pp. 363-396.
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Argha, A, Su, S, Li, L, Nguyen, HT & Celler, BG 2018, 'DSMC for NCSs involving consecutive measurement packet losses' in Advances in Discrete-Time Sliding Mode Control, CRC Press, USA, pp. 69-86.
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This chapter develops a stabilizing sliding mode control for systems involving uncertainties as well as measurement data packet dropouts. In contrast to the existing literature that designs the switching function by using unavailable system states, a novel linear sliding function is constructed by employing only the available communicated system states for the systems involving measurement packet losses. This also equips us with the possibility to build a novel switching component for discrete-time sliding mode control DSMC by using only available system states. Finally, a numerical example is given to evaluate the performance of the designed DSMC for networked systems.

Argha, A, Su, S, Li, L, Nguyen, HT & Celler, BG 2018, 'Sparse Observer-based discrete-time SMC for NCSs' in Advances in Discrete-Time Sliding Mode Control, CRC Press, pp. 113-139.
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Asif, MB, Hai, FI, Price, WE & Nghiem, LD 2018, 'Impact of Pharmaceutically Active Compounds in Marine Environment on Aquaculture' in Sustainable Aquaculture, Springer International Publishing, pp. 265-299.
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Bastidas-Arteaga, E & Stewart, MG 2018, 'Climate change impact on RC structures subjected to chloride ingress and carbonation-induced corrosion' in Routledge Handbook of Sustainable and Resilient Infrastructure, Routledge, pp. 626-645.
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Chloride ingress and carbonation lead to corrosion of reinforcing bars and therefore reduce the service life of reinforced concrete (RC) structures. Both deterioration mechanisms are highly influenced by environmental and climatic conditions of the surrounding environment. Consequently, the changes in environmental temperature, relative humidity and carbon dioxide concentration induced by climate change can increase corrosion risks resulting in more widespread corrosion damage and loss of structural safety. This chapter proposes a comprehensive methodology to assess the impact of climate change on the durability of RC structures subjected to chloride ingress and carbonation under a changing climate. The methodology combines probabilistic models able to account for climate change variations with predictions (CO2 concentration, temperature, and relative humidity) for various climate change scenarios. Two numerical examples illustrate the application of the methodology for the assessment of the effects of climate change on the reliability of RC structures. For chloride-induced corrosion, it was found that climate could reduce the time to failure by up to 31 per cent, or shorten service life by up to 15 years for moderate levels of aggressiveness. Concerning carbonation-induced corrosion, it was found that carbonation is very sensitive to local climate and climate change scenarios. To enhance resiliency, specific design improvement and/or adaptation strategies should therefore consider exposure and specific climate of each structural location.

Bastidas-Arteaga, E & Stewart, MG 2018, 'Cost-effective design to address climate change impacts' in Eco-Efficient Repair and Rehabilitation of Concrete Infrastructures, Elsevier, pp. 613-636.
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Beydoun, G, Voinov, A & Sugumaran, V 2018, 'Beyond Service-Oriented Architectures' in Sugumaran, V (ed), Advances in Computational Intelligence and Robotics, IGI Global, USA, pp. 16-27.
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Predictions for Service Oriented Architectures (SOA) to deliver transformational results to the role and capabilities of IT for businesses have fallen short. Unforeseen challenges have often emerged in SOA adoption. They fall into two categories: technical issues stemming from service components reuse difficulties and organizational issues stemming from inadequate support or understanding of what is required from the executive management in an organization to facilitate the technical rollout. This paper first explores and analyses the hindrances to the full exploitation of SOA. It then proposes an alternative service delivery approach that is based on even a higher degree of loose coupling than SOA. The approach promotes knowledge services and agent-based support for integration and identification of services. To support the arguments, this chapter sketches as a proof of concept the operationalization of such a service delivery system in disaster management.

Brennan, J & Murrell, A 2018, 'La disponibilité des données sur les sols en Australie' in Plant, R, Maurel, P, Barbe, E & Brennan, J (eds), Les terres agricoles face à l’urbanisation De la donnée à l’action, quels rôles pour l’information ?, Quae, pp. 91-106.
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This chapter takes a closer look at both the extent to which urban sprawl and soil sealing are already mapped in Australia, and the accessibility of soil information through soil databases such as the New South Wales Soil and Land Information System (SALIS). Urban sprawl and associated soil sealing are a worldwide phenomenon, which greatly affects the availability of agricultural land. Hence, land use planning requires a far greater understanding of these phenomena and consideration of soil quality than what is currently the practise. In order to make soil information more accessible, it can be used to create soil landscape maps incorporating constraints and limitations imposed by different soil and geological conditions. Soil capability maps are examples for this, and provide easily accessible information on soil quality for planners.

Campbell, M, Chabria, M, Figtree, GA, Polonchuk, L & Gentile, C 2018, 'Stem Cell-Derived Cardiac Spheroids as 3D In Vitro Models of the Human Heart Microenvironment' in Methods in Molecular Biology, Springer New York, Switzerland, pp. 51-59.
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Our laboratory has recently developed a novel three-dimensional in vitro model of the human heart, which we call the vascularized cardiac spheroid (VCS). These better recapitulate the human heart's cellular and extracellular microenvironment compared to the existing in vitro models. To achieve this, human-induced pluripotent stem cell (iPSC)-derived cardiomyocytes, cardiac fibroblasts, and human coronary artery endothelial cells are co-cultured in hanging drop culture in ratios similar to those found in the human heart in vivo. The resulting three-dimensional cellular organization, extracellular matrix, and microvascular network formation throughout the VCS has been shown to mimic the one present in the human heart tissue. Therefore, VCSs offer a promising platform to study cardiac physiology, disease, and pharmacology, as well as bioengineering constructs to regenerate heart tissue.

Campbell, M, Surija, L, Peceros, K, Sharma, P, Figtree, G & Gentile, C 2018, 'Stem Cell Spheroids' in Reference Module in Biomedical Sciences, Elsevier, pp. 387-393.
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Stem cells are undifferentiated cells that reside in a dynamic, specialized microenvironment (or niche) and play a fundamental role in embryogenesis, tissue homeostasis and regeneration. Three-dimensional stem cell spheroid cultures have emerged as a promising alternative to culture, maintain and differentiate stem cells in vitro by better mimicing the in vivo stem cell niche. These spheroid cultures recapitulate cellular and extracellular features of the in vivo stem cell niche, including biochemical and biophysical cues, which regulate stem cell self-renewal and differentiation potential. This review will provide an overview of the essential features of the niche typical of different stem cell types, to better engineer in vitro culture systems for enhanced stem viability and better control over stem cell behavior and fate. Finally, this review will delve into the many exciting applications of stem cell spheroid culture, including in vitro models of human disease, high-throughput drug discovery and toxicity assays, as well stem-cell based regenerative therapies and 3D bioprinting of organs for transplantation.

Cecez-Kecmanovic, D & Marjanovic, O 2018, 'Reconfiguration of Information Flows by Public Sector IT Systems: The Question of Fairness and Ethics' in Mitev, N, Morgan Thomas, A, Lorino, P, DeVaujany, FX & Nama, Y (eds), Materiality and Managerial Techniques, Springer International Publishing, pp. 133-164.
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Chen, Y & Jupp, J 2018, 'Model-Based Systems Engineering and Through-Life Information Management in Complex Construction' in IFIP Advances in Information and Communication Technology, Springer International Publishing, pp. 80-92.
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© IFIP International Federation for Information Processing 2018. With increasing maturity in model-based design and construction, a concomitant increase in the need for system-based methodologies and toolsets to support systems integration, requirements management, verification and validation and configuration management is evident if model-based information is to serve the operations of complex buildings and civil infrastructure projects. There is much to learn from best practices reported in complex discrete manufacturing. In particular, closed-loop product lifecycle management (PLM), systems engineering (SE) and model-based systems engineering (MBSE) are key to systems approaches to digital complex construction delivery and the reuse of model-based information for operations and maintenance (O&M). The paper reviews related research and investigates the role of the V-model in the development process, discussing its significance to structuring a through-life approach to information management. A discussion of Erasmus’ PLM aligned V-model is presented, and missing links in current BIM-enabled environments are identified relative to requirements engineering, verification and validation, and configuration management. The paper closes with a discussion of the gaps in supporting model-based tool ecologies and lack of a central structuring infrastructure, as well as the deficiencies in current process and data standards. Closing with the identification of a future research agenda.

Cotta, C, Mathieson, L & Moscato, P 2018, 'Memetic Algorithms' in Resende, MGC, Marti, R & Pardalos, PM (eds), Handbook of Heuristics, Springer International Publishing, Switzerland, pp. 607-638.
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© Springer International Publishing AG, part of Springer Nature 2018. All rights reserved. Memetic algorithms provide one of the most effective and flexible metaheuristic approaches for tackling hard optimization problems. Memetic algorithms address the difficulty of developing high-performance universal heuristics by encouraging the exploitation of multiple heuristics acting in concert, making use of all available sources of information for a problem. This approach has resulted in a rich arsenal of heuristic algorithms and metaheuristic frameworks for many problems. This chapter discusses the philosophy of the memetic paradigm, lays out the structure of a memetic algorithm, develops several example algorithms, surveys recent work in the field, and discusses the possible future directions of memetic algorithms.

Deuse, J, Heuser, C, Konrad, B, Lenze, D, Maschek, T, Wiegand, M & Willats, P 2018, 'Pushing the Limits of Lean Thinking–Design and Management of Complex Production Systems' in Lecture Notes in Management and Industrial Engineering, Springer International Publishing, pp. 335-342.
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Dickson-Deane, C & Chen, H-LO 2018, 'Understanding User Experience' in Encyclopedia of Information Science and Technology, Fourth Edition, IGI Global, pp. 7599-7608.
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User experience determines the quality of an interaction being used by an actor in order to achieve a specific outcome. The actor can have varying roles and evolving needs thus reviewing and predicting experiences are important. As an actor uses and gains feedback, the feedback guides individual and group behavior thus becoming pertinent to how interactions occur. This then questions how artefacts are designed to promote such interactions and what processes should be incorporated to ensure successful interpretation, use, [physical] reaction and conation. This chapter discusses the effects of user experiences today based on societal needs and expectations. It shows how the field is delineated into numerous sub-topics all of which can stand on their own yet, still draw from each other. The discussions will include fields such as cognitive science, human computer interaction, learning sciences and even ergonomics to show how design and subsequently interactions can assist in having successful user experiences

Dickson-Deane, C, Tolbert, D, McMahon, T & Funk, C 2018, 'Structuring and Resourcing Your eLearning Unit' in Leading and Managing e-Learning, Springer International Publishing, pp. 61-72.
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Ding, GKC 2018, 'Embodied Carbon in Construction, Maintenance and Demolition in Buildings' in Pomponi, F, de Wolf, C & Moncaster, A (eds), Embodied Carbon in Buildings, Springer International Publishing, pp. 217-245.
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Due to the rapid growth of the construction industry during the last decades, building-related waste has become a major source of concern from governments both nationally and internationally. Construction, maintenance and demolition waste is often neglected as it is perceived as less important than waste generated from operating activities. However, research studies reveal that waste is generated at all different stages of the building’s lifecycle and this has a profound impact not only in terms of increasing project cost but also adding to environmental pollution as the common type of treatments for wastes is landfilling and/or incineration. Reducing waste will reduce energy use, minimise degradation of the environment and reduce embodied carbon emissions. This chapter reviews the nature, characteristic and magnitude of construction, maintenance and demolition waste of buildings and their associated embodied carbon emissions. It also examines policies, initiatives and international regulations in dealing with the problem of waste and the calculation methods for the assessment of embodied carbon of waste in the various stages of a building’s life; it ends with a discussion on strategies of reducing waste and a case study.

Durick, J & Leung, L 2018, 'Designing Augmented, Domestic Environments to Support Ageing in Place' in Huber, J, Shilkrot, R, Maes, R & Nanayakkara, S (eds), Cognitive Science and Technology, Springer Singapore, Singapore, pp. 117-129.
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Fauzi, H, Metselaar, HSC, Mahlia, TMI, Silakhori, M & Ong, HC 2018, 'Investigation of Thermal Characteristic of Eutectic Fatty Acid/Damar Gum as a Composite Phase Change Material (CPCM)' in Green Energy and Technology, Springer International Publishing, Switzerland, pp. 607-616.
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© 2018, Springer International Publishing AG, part of Springer Nature. A composite phase change material (CPCM) of myristic acid/palmitic acid/sodium myristate (MA/PA/SM) has been proposed by impregnating a porous material of purified damar gum, also called Shorea javanica (SJ), to improve the thermal conductivity of CPCM. The thermal properties, thermal conductivity and thermal stability, of CPCM were measured using differential scanning calorimetry (DSC) thermal analysis, hot-disc thermal conductivity analyzer, and simultaneous thermal analyzer (STA). Moreover, a chemical reaction between fatty acid binary mixture and SJ in CPCM was evaluated by Fourier transform infra-red (FT-IR) spectrophotometer. The results of this study showed that the thermal conductivity of MA/PA/SM/SJ composite phase change material (CPCM) was improved by addition of 3 wt.% of Shorea javanica into MA/PA/SM eutectic mixture without showing a significant change in the thermophysical properties of CPCM. Moreover, the eutectic CPCM also does not show occurrence of chemical reaction between MA/PA/SM and SJ, and it has a good thermal performance and thermal stability. Therefore, the MA/PA/SM/SJ CPCM proposed in this study can be recommended as a new novelty material for thermal energy storage application.

Gil-Lafuente, AM, Merigó, JM, Dass, BK & Verma, R 2018, 'Preface', pp. v-vii.

Golembiewski, B, Sick, N & Bröring, S 2018, 'Patterns of convergence within the emerging bioeconomy - The case of the agricultural and energy sector' in Technology Roadmapping, World Scientific, Singapore, pp. 425-460.
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In light of an emerging bioeconomy, fading boundaries between the so far distinct agricultural and energy sector indicate a convergence process leading to a new competitive setting between established value chains requiring dynamic capabilities of the affected firms. On the basis of understanding convergence as a process within research-intensive industries, patent analyses can be applied to identify whether there are trends of convergence associated with the emerging bioeconomy. This study focuses on examining the nexus of agricultural and energy sector with regard to German biogas applications. Although different disciplinary activities within the field of biogas technologies can be confirmed, for now, biogas (as well as other bioenergy) applications seem to rather build a sub-segment within the energy value chain than forming a new inter-industry segment.

Guo, YJ, Karmokar, DK & Bird, TS 2018, 'Reconfigurable leaky-wave antennas' in Developments in Antenna Analysis and Design: Volume 1, Institution of Engineering and Technology, pp. 129-170.
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Guo, YJ, Pei-Yuan Qin & Mittra, R 2018, 'Reconfigurable high-gain antennas for wireless communications' in Developments in Antenna Analysis and Design: Volume 1, Institution of Engineering and Technology, pp. 171-201.
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Hastings, C & Weate, J 2018, 'Local Governments and Social Enterprise: Meeting Community Challenges Together?' in Social Capital and Enterprise in the Modern State, Springer International Publishing, pp. 117-146.
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© The Editor(s) (if applicable) and The Author(s) 2018. Even though the role of local government was established in Australia in the early nineteenth century as a mechanism for tailored local service delivery provision within a narrow range of administrative functions, since World War II, local government’s roles have expanded to include town-planning and a range of welfare and leisure services that have continued to diversify to the present day. Expansion in function has not been matched by expansion in funding, with this being a particular issue in rural and regional councils. A result of these pressures has been increased interest in new models of networked governance, involving more players in the process of service delivery so that local governments are not required to ‘go it alone’. Social enterprises have increasingly been included as one of these other players, but there has been limited discussion in the literature about the roles social enterprises are playing for councils. This chapter situates an analysis of local government-social enterprise relationships within the theoretical frameworks of network governance and public value, with reference to examples of such relationships in regional New South Wales (NSW). It aims to stimulate discussion about the possibilities for local government-social enterprise relationships to deliver positive social and economic outcomes within regional Australia.

Hengstebeck, A, Barthelmey, A & Deuse, J 2018, 'Reconfiguration Assistance for Cyber-Physical Production Systems' in Tagungsband des 3. Kongresses Montage Handhabung Industrieroboter, Springer Berlin Heidelberg, pp. 177-186.
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Hengstebeck, A, Weisner, K, Deuse, J, Rossmann, J & Kuhlenkötter, B 2018, 'Betriebliche Auswirkungen industrieller Servicerobotik am Beispiel der Kleinteilemontage' in Zukunft der Arbeit – Eine praxisnahe Betrachtung, Springer Berlin Heidelberg, pp. 51-61.
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Indraratna, B, Haque, A & Gale, W 2018, 'Evaluation of jointed rock permeability using a high pressure triaxial apparatus' in Mechanics of Jointed and Faulted Rock, Routledge, pp. 561-566.
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Johnston, A & Bluff, A 2018, 'Collaborative Creation in Interactive Theatre' in Candy, L, Edmonds, E & Poltronieri, F (eds), Springer Series on Cultural Computing, Springer London, London, pp. 341-351.
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© 2018, Springer-Verlag London Ltd., part of Springer Nature. This article describes the collaboration between two digital artist/researchers from the Creativity and Cognition Studios at the University of Technology Sydney and the Australian based physical theatre company, Stalker Theatre. This collaboration has been under way since 2011 and has resulted in the creation of five major works that have toured internationally.

Juang, C-F, Chang, Y-C & Chung, I-F 2018, 'Optimization of Recurrent Neural Networks Using Evolutionary Group-based Particle Swarm Optimization for Hexapod Robot Gait Generation' in Series in Machine Perception and Artificial Intelligence, WORLD SCIENTIFIC, pp. 227-256.
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Khalilpour, KR 2018, 'Preface' in Polygeneration with Polystorage: For Chemical and Energy Hubs, pp. xiii-xvii.
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Khalilpour, KR 2018, 'Preface' in Polygeneration with Polystorage: For Chemical and Energy Hubs, pp. xiii-xvii.
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Lawson, J & Hadgraft, R 2018, 'Building Global Awareness in Remote Locations' in McLaughlin, P & Kennedy, B (eds), The Global Canopy Stories of Discipline-Based Learning Interactions to Promote Global Mobility, The Writing Bureau, pp. 75-84.

Li, J, Chen, Z & Ma, Z 2018, 'Learning Colours from Textures by Effective Representation of Images' in Yurish, SY (ed), Advances in Signal Processing: Reviews, International Frequency Sensor Association (IFSA) Publishing, Spain, pp. 277-304.
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Arguably the majority of existing image and video analytics are done based on the texture. However, the other important aspect, colours, must also be considered for comprehensive analytics. Colours do not only make images feel more vivid to viewers, they also contains important visual clues of the image [20, 54, 24]. Although a modern point-and-shoot digital camera can easily capture colour images, there are circumstances where we need to recover the chromatic information in an image. For example, photography in the old days was monochrome and provided only gray-scale images. Adding colours can rejuvenate these old pictures and make them more adorable as personal memoir or more accessible as archival documents for public or educational purposes. For a colour image, re-coloursation may be necessary if the white balance was poorly set when shooting the picture. In this case, a particular colour channel can be severely over- or under- exposure, and makes infeasible to adjust the white balance based on the recorded colours. A possible rescue of the picture is to keep only the luminance and re-colourise the image. Another example of the application of colourisation arises from the area of specialised imaging, where the sensors capture signals that are out of the visible spectrum of light, e.g. X-ray, MRI, near infrared images. Pseudo colours for these images make them more readily for interpretation by human experts, and can also indicate potentially interesting regions.

Li, Z & Wang, Y 2018, 'Domain Knowledge in Predictive Maintenance for Water Pipe Failures' in Human–Computer Interaction Series, Springer International Publishing, pp. 437-457.
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Lim, S & Shon, HK 2018, 'Characterization of Membranes for Membrane-Based Salinity-Gradient Processes' in Membrane-Based Salinity Gradient Processes for Water Treatment and Power Generation, Elsevier, The Netherlands, pp. 125-154.
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Pressure retarded osmosis (PRO) is one of the alternative applications for harvesting renewable energy by a natural phenomenon. As a particular free energy, the salinity gradient energy (SGE) from saline solutions with different concentrations has recently been revitalized as a renewable energy source. In recent studies for development of PRO membranes, various attempts and novel applications have been conducted for enhancing energy production as well as an ease of the membrane modulation. At this stage, newly developed PRO membranes should be clearly characterized and evaluated to find the reason why novel approaches are attractive for its performance improvement compared to commercial and existing PRO membranes. In this chapter, therefore we would like to suggest the guideline for PRO membrane characterization in which most of contents are made of various attempts and investigations in literature. This chapter aims to understand various characterizations for PRO membranes to confirm the proof of the performance improvement for its purpose.

Liu, S, Wang, X, Zhou, L, Guan, J, Li, Y, He, Y, Duan, R & Ying, M 2018, 'Q|SI⟩ : A Quantum Programming Environment.' in Jones, CB, Wang, J & Zhan, N (eds), Symposium on Real-Time and Hybrid Systems, Springer, Switzerland, pp. 133-164.
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© Springer Nature Switzerland AG 2018. This paper describes a quantum programming environment, named Q| SI⟩, to support quantum programming using a quantum extension of the while -language. Embedded in the.Net framework, the Q| SI⟩ platform includes a quantum while -language compiler and a suite of tools to simulate quantum computation, optimize quantum circuits, analyze and verify quantum programs. This paper demonstrates Q| SI⟩ in use. Quantum behaviors are simulated on classical platforms with a combination of components and the compilation procedures for different back-ends are described in detail. Q| SI⟩ bridges the gap between quantum hardware and software. As a scalable framework, this platform allows users to code and simulate customized functions, optimize them for a range of quantum circuits, analyze the termination of a quantum program, and verify the program’s correctness (The software of Q| SI⟩ is available at http://www.qcompiler.com.).

Loban, R 2018, 'Torres Strait Virtual Reality: Virtual Reality' in Harle, J, Abdilla, A & Newman, A (eds), Decolonising the Digital: Technology As Cultural Practice.

McLaughlin, P, Baglin, J, Chester, A, Davis, P, Saha, S, Mills, A, Poronnik, P, Hinton, T, Lawson, J & Hadgraft, R 2018, 'The Global Canopy: Propagating Discipline-Based Global Mobility' in The Globalisation of Higher Education, Springer International Publishing, Germany, pp. 79-100.
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As Australian universities welcome significant numbers of inbound international students and increasingly encourage outbound domestic student mobility, the opportunities for global discipline connectedness, cross-cultural understandings, and fertile learning interactions abound. Yet these two “strands” of students rarely engage in deliberately organized discipline-based activities. They are passing “as ships in the night,” with opportunities for long-term relationships, improved discipline-based networks, and global mobility opportunities unrealized or operating coincidently at the margins of their curriculum. This chapter reports upon the outcomes of a range of approaches to discipline-based teaching and learning between these two cohorts at Australian universities, which illustrate how separate cohorts of inbound and outbound students can interrelate to build discipline-based competencies for navigating tomorrow’s world.

Nguyen, TV & Eisman, JA 2018, 'Pharmacogenetics and Pharmacogenomics of Osteoporosis: Personalized Medicine Outlook' in Genetics of Bone Biology and Skeletal Disease, Elsevier, pp. 139-157.
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© 2018 Elsevier Inc. All rights reserved. Osteoporosis and its consequence of fragility fracture are complex traits resulting from interactions of multiple genetic and environmental factors. Moreover, the response to antiosteoporotic therapies is highly variable among individuals, and this variability may also be partly determined by genetic factors. In the past decade, there has been substantial progress in the genetics and genomics of osteoporosis, but few advances in pharmacogenetics and pharmacogenomics of osteoporosis. Several genetic variants associated with bone mineral density and fracture risk have been identified by genome-wide association studies (GWAS). However, no genetic variants have been conclusively shown to be associated with response to antiosteoporotic therapies. Although the possibility of gene-based individualized assessment of fracture risk and personalized therapy in osteoporosis care is not yet realized, progress that has been made is reviewed.

Nöhring, F, Wöstmann, R & Deuse, J 2018, 'Auswahlhilfe für Industrie 4.0-Lösungen' in Industrie 4.0 für die Praxis, Springer Fachmedien Wiesbaden, pp. 67-87.
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Perry, S 2018, 'Image and Video Noise: An Industry Perspective' in Bertalmio, M (ed), Advances in Computer Vision and Pattern Recognition, Springer International Publishing, Switzerland, pp. 207-234.
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This unique text/reference presents a detailed review of noise removal for photographs and video. An international selection of expert contributors provide their insights into the fundamental challenges that remain in the field of denoising, examining how to properly model noise in real scenarios, how to tailor denoising algorithms to these models, and how to evaluate the results in a way that is consistent with perceived image quality. The book offers comprehensive coverage from problem formulation to the evaluation of denoising methods, from historical perspectives to state-of-the-art algorithms, and from fast real-time techniques that can be implemented in-camera to powerful and computationally intensive methods for off-line processing. Topics and features: describes the basic methods for the analysis of signal-dependent and correlated noise, and the key concepts underlying sparsity-based image denoising algorithms; reviews the most successful variational approaches for image reconstruction, and introduces convolutional neural network-based denoising methods; provides an overview of the use of Gaussian priors for patch-based image denoising, and examines the potential of internal denoising; discusses selection and estimation strategies for patch-based video denoising, and explores how noise enters the imaging pipeline; surveys the properties of real camera noise, and outlines a fast approximation of nonlocal means filtering; proposes routes to improving denoising results via indirectly denoising a transform of the image, considering the right noise model and taking into account the perceived quality of the outputs. This concise and clearly written volume will be of great value to researchers and professionals working in image processing and computer vision. The book will also serve as an accessible reference for advanced undergraduate and graduate students in computer science, applied mathematics, and related fields.

Plant, RA, Maurel, P, Ruoso, LE, Barbe, E & Brennan, J 2018, 'Synthèse : de la donnée à l’intelligence collective sur les terres agricoles péri-urbaines – quels rôles pour l’information, les savoirs et l’action ? [Synthesis: from data to collective intelligence on peri-urban agricultural land – what roles for information, knowledge and action?]' in Plant, R, Maurel, P, Barbe, E & Brennan, J (eds), Les terres agricoles face à l’urbanisation —De la donnée à l’action, quels rôles pour l’information ? [Agricultural land facing urbanization — From data to action, what roles for information?], Éditions Quae, Versailles.
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Keeping peri-urban farmland and associated activities close to growing urban centers is a global concern. In the face of ever-increasing demand for land development, the challenge of conserving peri-urban farmland - our main concern in this book - continues to be debated.The recent literature presents various initiatives that have, or could be, adopted to protect and conserve these lands. For example, Akimowicz et al. (2016) have critically assessed the merits of the Greenbelt Act in Ontario (USA) regarding farmers' adaptation and investment strategies. Inwood and Sharp (2012) reported on the resilience of farms in peri-urban areas by studying the succession patterns and adaptation of farms in the United States. As such, this study does not propose initiatives that could be put in place to protect and conserve peri-urban agricultural land, but rather an analysis of how to explain the maintenance of farms in peri-urban areas. From the study of conflicts around agricultural uses in the Greater Paris region, Darly and Torre (2013) analyze the experiences of farmers and the media coverage of, and present innovative mechanisms for conflict resolution.

Pradhan, B & Sameen, MI 2018, 'Manifestation of SVM-Based Rectified Linear Unit (ReLU) Kernel Function in Landslide Modelling' in Space Science and Communication for Sustainability, Springer Singapore, pp. 185-195.
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Ranga, Y, Esselle, KP & Matekovits, L 2018, 'Making UWB Antennas Unidirectional: Phase Coherence with an Ultra-Wide Band Frequency Selective Surface Reflector' in The World of Applied Electromagnetics, Springer International Publishing, pp. 227-258.
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Schallow, J, Hengstebeck, A & Deuse, J 2018, 'Industrie 4.0 – eine Bestandsaufnahme' in Industrie 4.0 für die Praxis, Springer Fachmedien Wiesbaden, pp. 15-28.
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Siwakoti, YP, Forouzesh, M & Ha Pham, N 2018, 'Power Electronics Converters—An Overview' in Control of Power Electronic Converters and Systems, Elsevier, pp. 3-29.
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The book explores how to manipulate components of power electronics converters and systems to produce a desired effect by controlling system variables.

Stewart, MG & Mueller, J 2018, 'Asking the Right Questions About Terrorism' in Are We Safe Enough?, Elsevier, pp. 1-18.
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Stewart, MG & Mueller, J 2018, 'Evaluating Aviation Security' in Are We Safe Enough?, Elsevier, pp. 19-53.
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Stewart, MG & Mueller, J 2018, 'Improving Checkpoint Efficiency: Evaluating PreCheck' in Are We Safe Enough?, Elsevier, pp. 135-153.
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Stewart, MG & Mueller, J 2018, 'Layers of Aviation Security: Examining Their Individual Contribution to Risk Reduction' in Are We Safe Enough?, Elsevier, pp. 55-97.
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Stewart, MG & Mueller, J 2018, 'Policing and Protecting Airports' in Are We Safe Enough?, Elsevier, pp. 155-186.
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Stewart, MG & Mueller, J 2018, 'Preface' in Are We Safe Enough?, Elsevier, pp. xi-xii.
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Stewart, MG & Mueller, J 2018, 'Reducing Costs Without Reducing Security: Comparing the Value of Individual Layers' in Are We Safe Enough?, Elsevier, pp. 99-133.
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Tahmassebi, A & Gandomi, AH 2018, 'Genetic Programming Based on Error Decomposition: A Big Data Approach' in Genetic and Evolutionary Computation, Springer International Publishing, pp. 135-147.
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Tay, AKP, Khoo, BL & Warkiani, ME 2018, 'Microfluidics for Fast and Frugal Diagnosis of Malaria, Sepsis, and HIV/AIDS' in Frugal Innovation in Bioengineering for the Detection of Infectious Diseases, Springer International Publishing, Switzerland, pp. 57-75.
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© Springer International Publishing AG 2018. Rapid diagnosis of infectious diseases is necessary for timely treatment and to control spread of diseases. Conventional laboratory approaches are often labor-intensive and associated with time delays that are unacceptable in medical practice. Recent advances in micro-/nanotechnologies have facilitated the development of low-cost microfluidic devices with high sensitivity and throughput that can help reduce healthcare costs and pave the way toward personalized therapy. This chapter covers recent advances in point-of-care (POC) technologies with an emphasis on demonstrated and commercially available systems for diagnosis and treatment of malaria, sepsis, and human immunodeficiency virus (HIV) infection/acquired immune deficiency syndrome (AIDS). The current challenges to practical implementation of these technologies are discussed together with some future perspectives.

Tong, L & Luo, Q 2018, 'Analytical Approach' in Handbook of Adhesion Technology, Springer International Publishing, Switzerland, pp. 665-700.
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© Springer International Publishing AG, part of Springer Nature 2018. All rights are reserved. This chapter presents analytical approach for determining stress and strength of adhesively bonded joints. Selected applications of adhesively bonded joints are discussed first, and then mathematical models for stress analysis of these joints are outlined. Various closed-form solutions for adhesive stresses and edge bending moment for balanced single-lap joints are presented and compared. The method for finding analytical solutions for asymmetric and unbalanced adhesive joints is also discussed. Explicit expressions for mode I and mode II energy release rates for cohesive failure and interfacial debonding are presented for asymmetric joints with a semi-infinitive length subjected to general load combinations.

Tran, B, Center, JR & Nguyen, TV 2018, 'Translational Genetics of Osteoporosis' in Primer on the Metabolic Bone Diseases and Disorders of Mineral Metabolism, Wiley, pp. 385-392.
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© 2019 American Society for Bone and Mineral Research. This chapter focuses on the clinical aspects and management of osteoporosis in postmenopausal women, men, young women, and various forms of secondary osteoporosis. Dual energy X-ray absorptiometry is an important tool for clinical research, including clinical trials of bisphosphonates and other drugs. There is strong consensus, based on solid clinical trial evidence, that postmenopausal women, and probably older men, who have experienced fragility fractures of the spine and hip are definite candidates for pharmacological therapy, irrespective of other risk factors. Patients with nonhip, nonspine fractures are also at higher risk for fracture and deserve, at least, to be evaluated for other risk factors and as potential candidates for therapy. Finite element analysis of routine CT scans of the hip and spine provides accurate in vivo measurement of skeletal strength. The anticipated availability of abaloparatide and romosozumab will be the first new treatments for osteoporosis.

Tri Tran C., A & Ha, Q 2018, 'Quadratic Constraint for Decentralised Model Predictive Control' in Studies in Systems, Decision and Control, Springer Singapore, pp. 31-57.
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© 2018, Springer Nature Singapore Pte Ltd. The asymptotically positive realness constraint (APRC) and quadratic dissipativity constraint (QDC) are introduced in this chapter as an effective tool for designing decentralised control systems, especially the decentralised model predictive control, in the discrete-time domain. We derive the convergence conditions for interconnected systems on the grounds of global system dissipation, subsystem dissipation, coupling structure, and dissipation-based constraints (APRC or QDC in the case of quadratic constraints) of all controlled subsystems. These conditions are suitable for the decentralised and distributed control of interconnected systems that prohibit artificial constraints on the unmeasurable coupling vectors. A convex quadratic constraint on the current-time control vector is subsequently developed from the dissipation-based constraint and applied to the model predictive control (MPC) as an enforced attractivity constraint. The attractivity constraints for controlled subsystems can be fully decoupled in this approach. Only linear-time-invariant (LTI) interconnected systems are under the scope of this chapter.

Woo, YC, Yao, M, Tijing, LD, Lee, S-E & Shon, HK 2018, 'Recent Progress in the Fabrication of Electrospun Nanofiber Membranes for Membrane Distillation' in Advanced Materials for Membrane Fabrication and Modification, CRC Press, pp. 71-100.
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Xu, G, Wu, Z, Cao, J & Tao, H 2018, 'Models for Community Dynamics' in Encyclopedia of Social Network Analysis and Mining, Springer New York, pp. 1378-1392.
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Yu, K, Berkovsky, S, Conway, D, Taib, R, Zhou, J & Chen, F 2018, 'Do I Trust a Machine? Differences in User Trust Based on System Performance' in Human–Computer Interaction Series, Springer International Publishing, Switzerland, pp. 245-264.
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Trust plays an important role in various user-facing systems and applications. It is particularly important in the context of decision support systems, where the system’s output serves as one of the inputs for the users’ decision making processes. In this chapter, we study the dynamics of explicit and implicit user trust in a simulated automated quality monitoring system, as a function of the system accuracy. We establish that users correctly perceive the accuracy of the system and adjust their trust accordingly. The results also show notable differences between two groups of users and indicate a possible threshold in the acceptance of the system. This important learning can be leveraged by designers of practical systems for sustaining the desired level of user trust.

Za’in, C, Pratama, M, Prasad, M, Puthal, D, Lim, CP & Seera, M 2018, 'Motor Fault Detection and Diagnosis Based on a Meta-cognitive Random Vector Functional Link Network' in Fault Diagnosis of Hybrid Dynamic and Complex Systems, Springer International Publishing, Switzerland, pp. 15-44.
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Zhang, B, Guo, T, Zhang, L, Lin, P, Wang, Y, Zhou, J & Chen, F 2018, 'Water Pipe Failure Prediction: A Machine Learning Approach Enhanced By Domain Knowledge' in Human–Computer Interaction Series, Springer International Publishing, Switzerland, pp. 363-383.
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Zhang, Y & Xu, G 2018, 'Singular Value Decomposition' in Encyclopedia of Database Systems, Springer New York, pp. 3506-3508.
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Zhang, Y, Guo, K, Yang, Q, Winnie, P, Cao, K, Wang, Q, Savkin, A, Celler, B, Nguyen, H, Xu, P, Xu, L, Yao, D & Su, S 2018, 'Multi-Loop Integral Control-Based Heart Rate Regulation for Fast Tracking and Faulty-Tolerant Control Performance in Treadmill Exercises' in Adaptive Robust Control Systems, InTech.
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Zheng, J & Luo, Z 2018, 'Reliability-Based Topology Optimization for Continuum Structures with Non-probabilistic Uncertainty' in Advances in Structural and Multidisciplinary Optimization, Springer International Publishing, Switzerland, pp. 390-395.
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A non-probabilistic reliability-based topology optimization (NRBTO) method for continuum structures is proposed for structures with correlated interval parameters based on the multidimensional parallelepiped (MP) model. A topology optimization model is formulated to minimize volume of structure under displacement constraints. An equivalent optimization model is given and solved based on the efficient performance measurement approach (PMA). A numerical example is used to demonstrate the effectiveness of the proposed method.

Zhou, J & Chen, F 2018, '2D Transparency Space—Bring Domain Users and Machine Learning Experts Together' in Human–Computer Interaction Series, Springer International Publishing, Germany, pp. 3-19.
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Machine Learning (ML) is currently facing prolonged challenges with the user acceptance of delivered solutions as well as seeing system misuse, disuse, or even failure. These fundamental challenges can be attributed to the nature of the “black-box” of ML methods for domain users when offering ML-based solutions. That is, transparency of ML is essential for domain users to trust and use ML confidently in their practices. This chapter argues for a change in how we view the relationship between human and machine learning to translate ML results into impact. We present a two-dimensional transparency space which integrates domain users and ML experts together to make ML transparent. We identify typical Transparent ML (TML) challenges and discuss key obstacles to TML, which aim to inspire active discussions of making ML transparent with a systematic view in this timely field.

Zhou, J, Yu, K & Chen, F 2018, 'Human and Machine Learning' in Zhou, J & Chen, F (eds), Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent, Springer International Publishing, Switzerland, pp. 225-244.
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Zhou, J, Yu, K, Chen, F, Wang, Y & Arshad, SZ 2018, 'Multimodal behavioral and physiological signals as indicators of cognitive load' in Oviatt, S, Schuller, B, Cohen, P, Sonntag, D, Potamianos, G & Krueger, A (eds), The Handbook of Multimodal-Multisensor Interfaces: Foundations, User Modeling, and Common Modality Combinations - Volume 2, Association for Computing Machinery, New York, NY, USA, pp. 287-329.
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This chapter evaluates cognitive load from the perspective of human responses, which is a data-driven approach for cognitive load measurement.Human responses can be characterised by various behavioral and physiological signals which are recorded and analysed. Taking the speech modality as an example, it is a natural form of communication between human beings. Besides linguistic interpretation, speech also conveys information such as speaker identity and mental state related information, e.g., cognitive load [Yin et al. 2008]. As shown in Figure 10.2, speech is an acoustic signal, generated by the airflow from the lungs considered to be the voice source which then passes through to the pharynx and the oral and nasal cavities, collectively known as the vocal tract filter. The features of the voice source and the vocal tract filter vary based on the content of the utterance to be pronounced as well as the mental state of the speaker [Yin et al. 2008].

Abas, AEP & Mahlia, TMI 2018, 'Development of energy labels based on consumer perspective: Room air conditioners as a case study in Brunei Darussalam', Energy Reports, vol. 4, pp. 671-681.
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© 2018 The Authors For the past years, Brunei Darussalam has seen an increase in its electricity consumption with an average annual rate of increase of 3% per annum from the year 2011 to 2015. Like other developing countries with tropical climates, electricity consumption from air conditioning systems contributes a big part to this electricity consumption. The Energy Department of the Prime Minister's Office is considering the implementation of energy label for air-conditioning system; to provide guideline for consumers to compare efficiencies of their systems, encourage manufacturers to improve the energy efficiency of their systems and ultimately, to reduce the overall energy consumption of the country. This paper proposes a suitable energy label for air conditioning system in this country based on an online survey. Data from the survey shall be analysed to come up with consumers’ preferred energy label with suggestions used for its improvement. This label is also suitable for other electrical systems without major modification.

Abbas, SM, Desai, SC, Esselle, KP, Volakis, JL & Hashmi, RM 2018, 'Design and Characterization of a Flexible Wideband Antenna Using Polydimethylsiloxane Composite Substrate', International Journal of Antennas and Propagation, vol. 2018, pp. 1-6.
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The design and characterization of a simple, flexible wideband antenna using polydimethylsiloxane (PDMS) composite are presented. Conductive fibers are used to construct the metallic parts on a PDMS composite. To characterize the performance, two identical antennas are designed, one using the PDMS composite while the other on conventional dielectric materials. It was observed that both antennas behave well in terms of the matched bandwidth; however, the radiation towards the broadside direction is reduced when using the PDMS composite as substrate, particularly at higher frequencies. The antenna exhibits a matched bandwidth of 59.9%, ranging from 3.43 to 11.1 GHz. Moreover, the bending analysis carried out for different scenarios show that the wideband behavior of the antenna is well preserved and the variation reaches a maximum of 1% variation.

Abbasi, M & Tousi, B 2018, 'Performance evaluation of switched-diode symmetric, asymmetric and cascade multilevel converter topologies: A case study', Journal of Engineering Science and Technology, vol. 13, no. 5, pp. 1165-1180.
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In this paper, a precise study is presented on switched-diode symmetric, asymmetric and cascade multilevel converter topologies, which have been introduced and published recently. According to the published papers, these topologies have many advantages over other topologies in the same class. However, it is proved here that the mentioned switched-diode topologies suffer from main problems, which make them completely impractical. First, a brief study is presented on a typical sub-multilevel converter that consists of a basic unit and an H-bridge converter. Then, extended inverter topologies based on the switched-diode basic unit and their problems are studied. It is revealed in this section that the main problem is because of the basic unit. Finally, comprehensive experimental and simulation results are presented to validate the analysis. The simulations have been performed in MATLAB/SIMULINK environment.

Abbasi, M, Khazaee, S & Tousi, B 2018, 'Application of an online controller for statcom to mitigate the SSR oscillations', Journal of Engineering Science and Technology, vol. 13, no. 9, pp. 2945-2963.
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This paper presents an on-line controller for a Static Synchronous Shunt Compensator (STATCOM) to damp subsynchronous frequency oscillations. Series capacitors in transmission lines can increase stability margin and power transfer capability but also result in shaft failure or fatigue in a thermal production unit. Flexible AC Transmission System (FACTS) devices are widely employed to control several features of the power system. Recent surveys demonstrated that FACTS devices, equipped with well-designed controllers, can be effective in damping Subsynchronous Resonance (SSR) oscillations. To achieve this goal, PI controllers are mostly used that are simple controllers. However, they need exact and accurate information about the power system, which is hard to get. Therefore, they lose their desired performance by changing the operating conditions. The proposed on-line controller is based on an identifier and a pole-shifting controller. This controller estimates system parameters on-line and shifts the location of system poles radially with a factor (α) to guarantee the system stability. The considered structure for the system is Autoregressive Moving Average Exogenous (ARMAX) model and the used identifier is Recursive Least Squares (RLS) method. Simulations have been performed by MATLAB/SIMULINK. The eigenvalue analysis has been obtained to study the SSR characteristics of the power system and the studied system is IEEE first benchmark model on SSR.

Abbasi, M, Khazaee, S & Tousi, B 2018, 'Application of an online controller for statcom to mitigate the SSR oscillations', Journal of Engineering Science and Technology, vol. 13, pp. 2945-2963.
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This paper presents an on-line controller for a Static Synchronous Shunt Compensator (STATCOM) to damp subsynchronous frequency oscillations. Series capacitors in transmission lines can increase stability margin and power transfer capability but also result in shaft failure or fatigue in a thermal production unit. Flexible AC Transmission System (FACTS) devices are widely employed to control several features of the power system. Recent surveys demonstrated that FACTS devices, equipped with well-designed controllers, can be effective in damping Subsynchronous Resonance (SSR) oscillations. To achieve this goal, PI controllers are mostly used that are simple controllers. However, they need exact and accurate information about the power system, which is hard to get. Therefore, they lose their desired performance by changing the operating conditions. The proposed on-line controller is based on an identifier and a pole-shifting controller. This controller estimates system parameters on-line and shifts the location of system poles radially with a factor (α) to guarantee the system stability. The considered structure for the system is Autoregressive Moving Average Exogenous (ARMAX) model and the used identifier is Recursive Least Squares (RLS) method. Simulations have been performed by MATLAB/SIMULINK. The eigenvalue analysis has been obtained to study the SSR characteristics of the power system and the studied system is IEEE first benchmark model on SSR.

Abbasi, M, Tousi, B & Abbasi, M 2018, 'A Novel Controller Based on Single-Phase Instantaneous p-q Power Theory for a Cascaded PWM Transformerless STATCOM for Voltage Regulation', Journal of Operation and Automation in Power Engineering, vol. 6, no. 1, pp. 80-88.
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In this paper, dynamic performance of a transformerless cascaded PWM static synchronous shunt compensator (STATCOM) based on a novel control scheme is investigated for bus voltage regulation in a 6.6kV distribution system. The transformerless STATCOM consists of a thirteen-level cascaded H-bridge inverter, in which each voltage source H-bridge inverter should be equipped with a floating and isolated capacitor without any power source. The proposed control algorithm uses instantaneous p-q power theory in an innovative way that devotes itself not only to meet the reactive power demand but also to balance the dc link voltages at the same time. DC link voltage balancing control consists of two main parts: cluster and individual balancing. The control algorithm based on a phase shifted carrier modulation strategy has no restriction on the number of cascaded voltage source H-bridge inverters. Comprehensive simulations are presented in MATLAB/ SIMULINK environment for validating the performance of proposed transformerless STATCOM.

Abbasnejad, B, Thorby, W, Razmjou, A, Jin, D, Asadnia, M & Ebrahimi Warkiani, M 2018, 'MEMS piezoresistive flow sensors for sleep apnea therapy', Sensors and Actuators A: Physical, vol. 279, pp. 577-585.
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© 2018 Elsevier B.V. A MEMS liquid crystal polymer (LCP), used in the membrane-based pressure sensor, has been found highly useful as a flow sensor. Here we conducted a set of elaborate experiments using an air flow generator to investigate the potential of our LCP flow sensor for sleep apnea therapy. Critical properties of the LCP flow sensor, including flow range, resolution (sensitivity), accuracy, and response time, have been systematically characterized. As a result, LCP flow sensor achieves a limit of detection of 8 LPM to measure flow rate, better than the commercial flow sensor (>10 LPM). Our LCP flow sensor shows a favourable response in a large flow range (8–160 LPM) with a sensitivity of detecting a linear voltage response of 0.004 V per 1 LPM flow rate. With minimum detectable flow, high sensitivity and resolution, we further demonstrated our LCP flow sensor for detecting human respiration. Moreover, using a two- dimensional simulation in COMSOL Multiphysics, we demonstrated the deformation of LCP membrane in response to different flow velocities which leads to resistance change in sensor's strain gauge.

Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2018, 'Quantification of Runoff as Influenced by Morphometric Characteristics in a Rural Complex Catchment', Earth Systems and Environment, vol. 2, no. 1, pp. 145-162.
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This study addresses the critical scientific question of assessing the relationship between morphometric features and the hydrological factors that increase the risk of flooding in Kelantan River basin, Malaysia. Two hypotheses were developed to achieve this aim, namely: the alternate hypothesis (runoff, is influenced by morphometric characteristics in the study watershed) and the null hypothesis (runoff is not influenced by morphometric characteristics). First, the watershed was delineated into four major catchments, namely: Galas, Pergau, Lebir, and Nenggiri. Next, quantitative morphometric characters such as linear aspects, areal aspects, and relief aspects were determined on each of these catchments. Furthermore, HEC–HMS and flood response analyses were employed to simulate the hydrological response of the catchments. From the results of morphometric analysis, profound spatial changes were observed between runoff features of Kelantan River and the morphometric characteristics. The length of overflow that was related to drainage density and constant channel maintenance was found to be 0.12 in Pergau, 0.04 in both Nenggiri and Lebir, and 0.03 in Galas. Drainage density as influenced by geology and vegetation density was found to be low in all the catchments (0.07–0.24). Results of hydrological response indicated that Lebir, Nenggiri, Galas, and Pergau recorded a flood response factor of 0.75, 0.63, 0.40, and 0.05, respectively. Therefore, Lebir and Nenggiri are more likely to be flooded during a rainstorm. There was no clear indication with regard to the catchment that emerged as the most prevailing in all the morphological features. Hence, the alternate hypothesis was affirmed. This study can be replicated in other catchments with different hydrologic setup.

Abdulkareem, JH, Pradhan, B, Sulaiman, WNA & Jamil, NR 2018, 'Review of studies on hydrological modelling in Malaysia', Modeling Earth Systems and Environment, vol. 4, no. 4, pp. 1577-1605.
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Hydrological models are vital component and essential tools for water resources and environmental planning and management. In recent times, several studies have been conducted with a view of examining the compatibility of model results with streamflow measurements. Some modelers are of the view that even the use of complex modeling techniques does not give better assessment due to soil heterogeneity and climatic changes that plays vital roles in the behavior of streamflow. In Malaysia, several public domain hydrologic models that range from physically-based models, empirical models and conceptual models are in use. These include hydrologic modeling system (HEC-HMS), soil water assessment tool (SWAT), MIKE-SHE, artificial neural network (ANN). In view of this, a study was conducted to evaluate the hydrological models used in Malaysia, determine the coverage of the hydrological models in major river basins and to identify the methodologies used (specifically model performance and evaluation). The results of the review showed that 65% of the studies conducted used physical-based models, 37% used empirical models while 6% used conceptual models. Of the 65% of physical-based modelling studies, 60% utilized HEC-HMS an open source models, 20% used SWAT (public domain model), 9% used MIKE-SHE, MIKE 11 and MIKE 22, Infoworks RS occupied 7% while TREX and IFAS occupy 2% each. Thus, indicating preference for open access models in Malaysia. In the case of empirical models, 46% from the total of empirical researches in Malaysia used ANN, 13% used Logistic Regression (LR), while Fuzzy logic, Unit Hydrograph, Auto-regressive integrated moving average (ARIMA) model and support vector machine (SVM) contributed 8% each. Whereas the remaining proportion is occupied by Numerical weather prediction (NWP), land surface model (LSM), frequency ratio (FR), decision tree (DT) and weight of evidence (WoE). Majority of the hydrological modelling studies utilized one or more statis...

Abdulkareem, JH, Sulaiman, WNA, Pradhan, B & Jamil, NR 2018, 'Long-Term Hydrologic Impact Assessment of Non-point Source Pollution Measured Through Land Use/Land Cover (LULC) Changes in a Tropical Complex Catchment', Earth Systems and Environment, vol. 2, no. 1, pp. 67-84.
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The contribution of non-point source pollution (NPS) to the contamination of surface water is an issue of growing concern. Non-point source (NPS) pollutants are of various types and altered by several site-specific factors making them difficult to control due to complex uncertainties involve in their behavior. Kelantan River basin, Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/land cover (LULC) changes making the area consistently flood prone thereby deteriorating the surface water quality in the area. This study was conducted to determine the spatio-temporal variation of NPS pollutant loads among different LULC changes and to establish a NPS pollutant loads relationships among LULC conditions and sub-basins in each catchment. Four pollutants parameters such as total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and ammonia nitrogen (AN) were chosen with their corresponding event mean concentration values (EMC). Soil map and LULC change maps corresponding to 1984, 2002 and 2013 were used for the calculation of runoff and NPS pollutant loads using numeric integration in a GIS environment. Analysis of Variance (ANOVA) was conducted for the comparison of NPS pollutant loads among the three LULC conditions used and the sub-basins in each catchment. The results showed that the spatio-temporal variation of pollutant loads in almost all the catchments increased with changes in LULC condition as one moves from 1984 to 2013, with 2013 LULC condition found as the dominant in almost all cases. NPS pollutant loads among different LULC changes also increased with changes in LULC condition from 1984 to 2013. While urbanization was found to be the dominant LULC change with the highest pollutant load in all the catchments. Results from ANOVA reveals that statistically most significant (p < 0.05) pollutant loads were obtained from 2013 LULC conditions, while statistically least significant (p < 0.05) pollutant...

Abdulkareem, JH, Sulaiman, WNA, Pradhan, B & Jamil, NR 2018, 'Relationship between design floods and land use land cover (LULC) changes in a tropical complex catchment', Arabian Journal of Geosciences, vol. 11, no. 14.
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© 2018, Saudi Society for Geosciences. Rainfall characteristics are directly related to the climate of a basin, but this can only be noticed after a long period. Human activities, such as deforestation, tend to play a major role in transforming the land use land cover (LULC). Knowledge of the relationship between design floods and LULC is important in modeling and designing watershed management strategies. A study was conducted in the Kelantan River basin, Malaysia, to determine the impact of past and present LULC changes on peak discharge and runoff volumes. To achieve this, the basin was delineated into four catchments (Galas, Pergau, Nenggiri, and Lebir) due to its size and increased precision. Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was calibrated based on December 20–30th, 2014, flood in Kelantan. Flood hydrographs corresponding to 1984, 2002, and 2013 LULC conditions were simulated, and relative changes in peak discharge and runoff volume were determined for different return periods (2, 5, 10, 20, 50, 100 years). Results of LULC analysis showed that Galas recorded highest deforestation (54.35%). When the four catchments were compared with respect to highest contribution of outlet peak discharge, Lebir under 2013 LULC condition was the highest with 2847.70 m3/s. This was followed by Nenggiri (2196.90 m3/s), Galas (1252.7 m3/s), and Pergau (328.7 m3/s), all under the 2013 LULC condition. Results of unit response approach applied based on 50-year return period to the catchments for ranking their sub-basins revealed that the novel fa index developed in this study provides a better way of ranking sub-basins with respect to their contribution to the outlet and therefore is recommended for use. Methodologies developed in this study may be useful to land use planners from around the world which when applied can provide alternatives that will minimize the adverse effects of floods.

Abdullahi, S & Pradhan, B 2018, 'Land use change modeling and the effect of compact city paradigms: integration of GIS-based cellular automata and weights-of-evidence techniques', Environmental Earth Sciences, vol. 77, no. 6.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. In recent decades, attaining urban sustainability is the primary goal for urban planners and decision makers. Among various aspects of urban sustainability, environmental protection such as agricultural and forest conservations is very important in tropical countries like Malaysia. In this regard, compact urban development due to high density, rural development containment is known as the most sustainable urban forms. This paper attempts to propose an integrated modeling approach to predict the future land use changes by considering city compactness paradigms. First, the cellular automata (CA) were applied for calculating land use conversion. Next, weights-of-evidence (WoE) which is based on Bayes theory was utilized to calibrate CA model and to support the transitional rule assessment. Several urban-related parameters as well as compact city indicators were utilized to estimate the future land use maps. The results showed how compact development parameters and site characteristics can be combined using the WoE model to predict the probability of land use changes. The modeling approach supports the essential logic of probabilistic methods and indicates that spatial autocorrelation of various land use types and accessibility is the main drivers of urban land use changes.

Abdullahi, S, Pradhan, B & Mojaddadi, H 2018, 'City Compactness: Assessing the Influence of the Growth of Residential Land Use', Journal of Urban Technology, vol. 25, no. 1, pp. 21-46.
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© 2017 The Society of Urban Technology. In the urban sprawl paradigm, residential land use exhibits a more significant growth than other categories. Consequently, large proportions of the natural environment are converted to residential areas, particularly in tropical countries. Compact urban development is one of the most sustainable urban forms with environmental perspectives, such as rural development containment and natural environment preservation. However, no proper investigation of the relationship and influence of residential growth and city compactness is available. This study evaluated and forecasted the residential development of Kajang City in Malaysia based on compact development. First, the relationship between residential land use change and city compactness was evaluated. Second, residential growth was projected by utilizing the land transformation model (LTM) and the statistical-based weight of evidence (WoE) using various spatial parameters. Both models were evaluated with respect to observed land use and compactness maps. Results indicated that most of the newly developed residential areas were in zones where the degrees of compactness increase during certain periods. In addition, LTM performed better and provided a more accurate modeling of residential growth than the WoE. However, WoE provided clearer and more informative results than LTM in terms of functional relationships between dependent and independent variables related to city compactness.

Abeywickrama, HV, Jayawickrama, BA, He, Y & Dutkiewicz, E 2018, 'Comprehensive Energy Consumption Model for Unmanned Aerial Vehicles, Based on Empirical Studies of Battery Performance', IEEE Access, vol. 6, pp. 58383-58394.
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© 2018 IEEE. Unmanned aerial vehicles (UAVs) are fast gaining popularity in a wide variety of areas and are already being used for a range of tasks. Despite their many desirable features, a number of drawbacks hinder the potential of UAV applications. As typical UAVs are powered by on-board batteries, limited battery lifetime is identified as a key limitation in UAV applications. Thus, in order to preserve the available energy, planning UAV missions in an energy efficient manner is of utmost importance. For energy efficient UAV mission planning, it is necessary to predict the energy consumption of specific UAV manoeuvring actions. Accurate energy prediction requires a reliable and realistic energy consumption model. In this paper, we present a consistent and complete energy consumption model for UAVs based on empirical studies of battery usage for various UAV activities. We considered the impact of different flight scenarios and conditions on UAV energy consumption when developing the proposed model. The energy consumption model presented in this paper can be readily used for energy efficient UAV mission planning.

Abolbashari, MH, Chang, E, Hussain, OK & Saberi, M 2018, 'Smart Buyer: A Bayesian Network modelling approach for measuring and improving procurement performance in organisations', Knowledge-Based Systems, vol. 142, pp. 127-148.
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© 2017 Elsevier B.V. Procurement, the act of buying goods or services from an external supplier, plays an important role in any organisation. To measure how well an organisation undertakes this activity, it needs to measure all associated Key Performance Indicators (KPIs). The current literature's major drawback in performing such a measurement is how to integrate the different KPIs, each of which captures a specific aspect of the organisation's performance. In this paper, we highlight this drawback and present our proposed Smart Buyer framework that is based on a Bayesian Network (BN) model capable of capturing and integrating the different KPIs. The measured procurement performance value can then be used by organisations to identify the areas in which they need to improve and develop plans to achieve this. Four scenarios are presented to show how the proposed BN model can be further used for analysis and decision making within organisations. Finally, a recent real-world procurement example is studied to demonstrate the applicability of the proposed Smart Buyer framework.

Abolhasan, M, Abdollahi, M, Ni, W, Jamalipour, A, Shariati, N & Lipman, J 2018, 'A Routing Framework for Offloading Traffic From Cellular Networks to SDN-Based Multi-Hop Device-to-Device Networks', IEEE Transactions on Network and Service Management, vol. 15, no. 4, pp. 1516-1531.
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© 2004-2012 IEEE. Device-to-device (D2D) communications are set to form an integral part of future 5G wireless networks. D2D communications have a number of benefits such as improving energy efficiency and spectrum utilization. Until now much of the D2D research in LTE and 5G-type network scenarios have focused on direct (one-hop) communications between two adjacent mobile devices. In this paper, we propose a new routing framework called virtual ad hoc routing protocol (VARP). This framework introduces significant advantages such as better security, lower routing overheads, and higher scalability, when compared to conventional ad hoc routing protocols. It also reduces traffic overhead in LTE networks using multi-hop D2D communications under management of a software defined networking (SDN)-controller. Further, it enables the development of various types of routing protocols for different networking scenarios. To this end, a source-routing based protocol was developed on top of VARP, referred to as VARP-S. We present a detailed analytical study of routing overhead in the VARP-S protocol, as compared to overhead analysis of our previous proposed hybrid SDN architecture for wireless distributed networks (HSAW) Our results show that VARP-S, compared to HSAW, achieves higher network scalability and lower power consumption for mobile nodes.

Aboulkheyr Es, H, Montazeri, L, Aref, AR, Vosough, M & Baharvand, H 2018, 'Personalized Cancer Medicine: An Organoid Approach', Trends in Biotechnology, vol. 36, no. 4, pp. 358-371.
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Personalized cancer therapy applies specific treatments to each patient. Using personalized tumor models with similar characteristics to the original tumors may result in more accurate predictions of drug responses in patients. Tumor organoid models have several advantages over pre-existing models, including conserving the molecular and cellular composition of the original tumor. These advantages highlight the tremendous potential of tumor organoids in personalized cancer therapy, particularly preclinical drug screening and predicting patient responses to selected treatment regimens. Here, we highlight the advantages, challenges, and translational potential of tumor organoids in personalized cancer therapy and focus on gene–drug associations, drug response prediction, and treatment selection. Finally, we discuss how microfluidic technology can contribute to immunotherapy drug screening in tumor organoids.

Aboutorab, H, Saberi, M, Asadabadi, MR, Hussain, O & Chang, E 2018, 'ZBWM: The Z-number extension of Best Worst Method and its application for supplier development', Expert Systems with Applications, vol. 107, pp. 115-125.
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© 2018 Elsevier Ltd Best Worst Method (BWM) has recently been proposed as a method for Multi Criteria Decision Making (MCDM). Studies show that BWM compared with other methods such as Analytic Hierarchy Process (AHP), leads to lower inconsistency of the results while reducing the number of required pairwise comparisons. MCDM methods such as BWM require accurate information. However, it often happens in practice that a level of uncertainty accompanies the information. The main aim of this paper is to address this problem and provide an integration of BWM and Z-numbers, namely ZBWM. Providing BWM with Z-numbers enables the BWM method to handle the uncertainty of information of a multi-criteria decision. Additionally, the capabilities of the proposed method in the process of utilizing the linguistic information dealing with big data are highlighted. The proposed method is examined to address a supplier development problem. By experimental results, we show that ZBWM results lower inconsistency when compared with BWM. A Z-number contains subjectivity in its fuzzy part, which can be addressed in future applications of ZBWM.

Acosta, E, Wight, NM, Smirnov, V, Buckman, J & Bennett, NS 2018, 'Hydrogenated Nano-/Micro-Crystalline Silicon Thin-Films for Thermoelectrics', Journal of Electronic Materials, vol. 47, no. 6, pp. 3077-3084.
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© 2017, The Minerals, Metals & Materials Society. Thermoelectric technology has not yet been able to reach full-scale market penetration partly because most commercial materials employed are scarce/costly, environmentally unfriendly and in addition provide low conversion efficiency. The necessity to tackle some of these hurdles leads us to investigate the suitability of n-type hydrogenated microcrystalline silicon (μc-Si: H) in the fabrication of thermoelectric devices, produced by plasma enhanced chemical vapour deposition (PECVD), which is a mature process of proven scalability. This study reports an approach to optimise the thermoelectric power factor (PF) by varying the dopant concentration by means of post-annealing without impacting film morphology, at least for temperatures below 550°C. Results show an improvement in PF of more than 80%, which is driven by a noticeable increase of carrier mobility and Seebeck coefficient in spite of a reduction in carrier concentration. A PF of 2.08 × 10−4 W/mK2 at room temperature is reported for n-type films of 1 μm thickness, which is in line with the best values reported in recent literature for similar structures.

Adnan, R, Sabri Adlan, Z, Munir, FA, Indra, TM & Masjuki, HH 2018, 'Effects of equivalence ratio on performance and emissions of diesel engine with hydrogen and water injection system at variable injection timing', International Journal of Mechanical and Mechatronics Engineering, vol. 18, no. 1, pp. 106-111.
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This paper aims to develop a comprehensive development and research for performance and emissions of diesel engine fueled with hydrogen and water at variable injection timing. Experiments have been conducted to compare the performance and emissions between diesel alone, diesel with hydrogen and hydrogen-diesel and water injection pressure. addition of hydrogen into diesel engine resulted in higher pressure which lead to huge indicated work. Furthermore, injecting water into diesel engine with hydrogen mixture indicated a desirable outcome. Existence of water in combustion slightly decreased the amount of emissions but opposite in term of performance. The fact is water injection exist in combustion will absorb a portion of heat release which will result low in combustion process thus lead to low in performance production otherwise production of NOx emission is low. In conclusion, humidification in combustion engine is a great idea toward a high performance and low in emissions production compared to diesel alone operation which leads to a green technology production.

Aerts, D, Geriente, S, Moreira, C & Sozzo, S 2018, 'Testing ambiguity and Machina preferences within a quantum-theoretic framework for decision-making', Journal of Mathematical Economics, vol. 78, pp. 176-185.
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Afzal, MU, Esselle, KP & Lalbakhsh, A 2018, 'A Methodology to Design a Low-Profile Composite-Dielectric Phase-Correcting Structure', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 7, pp. 1223-1227.
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© 2002-2011 IEEE. A methodology to synthesize a low-profile composite-dielectric phase-correcting structure (CD PCS) is presented. The CD PCS, in function, is similar to an all-dielectric varying-height PCS and transforms a nonuniform aperture phase distribution of a low-gain antenna to a nearly uniform phase distribution. The methodology is aimed at reducing the maximum height of all-dielectric PCSs by using a combination of commercially available transmissive dielectric materials. The principle of operation has been demonstrated by designing a CD PCS using two dielectric materials. A higher permittivity dielectric material is used in the central region of the CD PCS, which requires a larger phase delay, while a lower permittivity dielectric material is used in the outer region, which requires a smaller phase delay. The height of the CD PCS is 43\% less and its weight is 25\% less than the single-dielectric PCS, but both have similar radiation performance.

Afzal, MU, Lalbakhsh, A & Esselle, KP 2018, 'Electromagnetic-wave beam-scanning antenna using near-field rotatable graded-dielectric plates', Journal of Applied Physics, vol. 124, no. 23, pp. 234901-234901.
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The paper proposes an electromagnetic-wave beam-scanning antenna system using a simple rotation of a pair of near-field graded-dielectric plates (GDPs). The antenna system requires an electromagnetic (EM) illuminator, with nearly symmetric aperture field distribution, as the base antenna and two types of GDPs: one radially graded dielectric (RGD) and two linearly graded dielectric (LGD) plates. The RGD first focuses the beam of the base antenna in the broadside direction, and the LGD then tilts the focused beam at an offset angle. For some types of base antennas, having fairly uniform aperture phase distributions, an RGD may not be required and only a pair of LGDs are sufficient. Irrespective of the antenna configuration, using a simple rotation of the two LGDs, the beam can be scanned to any position within a large conical region. The antenna system presented as a proof of concept has a resonant-cavity antenna as the base antenna and three graded-dielectric plates. The aperture length of the antenna system is 6λ0 and its height is 2.2λ0. The results predicted by numerical simulations indicate that the antenna system has highest peak directivity of 21 dBi. The beam can be scanned to any direction within a cone having an apex angle of 20°.

Agrawal, DP, Gupta, BB, Wang, H, Chang, X, Yamaguchi, S & Perez, GM 2018, 'Guest Editorial Deep Learning Models for Industry Informatics', IEEE Transactions on Industrial Informatics, vol. 14, no. 7, pp. 3166-3169.
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Ahmadirouhani, R, Karimpour, M-H, Rahimi, B, Malekzadeh-Shafaroudi, A, Pour, AB & Pradhan, B 2018, 'Integration of SPOT-5 and ASTER satellite data for structural tracing and hydrothermal alteration mineral mapping: implications for Cu–Au prospecting', International Journal of Image and Data Fusion, vol. 9, no. 3, pp. 237-262.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The integration of information extracted from the Syste`m Pour l’Observation de la Terre (SPOT) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, comprehensive field and mineralogy studies demonstrates that phyllic alteration zone associated with northwestern (NW)–southeastern (SE) structural fractures is a high potential zone for Cu–Fe–Au vein-type mineralisation in the Bajestan region, the Lut block, east Iran. The fractal pattern was calculated for fractures map using the Box-Counting algorithm to the SPOT-5 data. Statistical parameters of fractures, such as density, intensity and fractures’ intersection were also determined. Band composition, specialised band ratio and Spectral Angle Mapper (SAM) classification methods were implemented to the ASTER dataset for detecting hydrothermal alteration zones, such as propylitic, phyllic, argillic and gossan. Results indicate that the maximum value of the fractal dimension, intensity, density and the intersection of the fractures are concentrated in the NW and SE parts of SPOT image maps. In the other hand, phyllic alteration zone containing sericite, alunite, kaolinite and jarosite mineral assemblages was also identified in several zones of the NW and SE parts of the ASTER image maps. Integration of the results indicates the high potential zones for the occurrence of Cu–Fe–Au mineralisation in the Bajestan region.

Ahmed, A, Abu Bakar, MS, Azad, AK, Sukri, RS & Mahlia, TMI 2018, 'Potential thermochemical conversion of bioenergy from Acacia species in Brunei Darussalam: A review', Renewable and Sustainable Energy Reviews, vol. 82, pp. 3060-3076.
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© 2017 Elsevier Ltd As the demand for energy increases and fossil fuel resources are depleted, the search for clean sources of energy has intensified worldwide. This is coupled with a strong global desire to reduce CO2 emissions to curb global warming. Brunei Darussalam is committed to reduce its CO2 emissions but currently utilizes fossil fuels to meet almost all of its energy requirements. This situation provides good incentives to search for renewable and sustainable resources to produce energy in the country. Acacia species are exotic species that have invaded and spread to natural habitats in Brunei Darussalam. Acacia species are a sustainable source of high quality biomass feedstock to produce bioenergy in the country. Hot tropical weather of the country is highly suitable for the rapid growth of Acacias without requiring any major agricultural input. This study reviews the thermochemical conversion of Acacia species especially; Acacia mangium and Acacia auriculiformis to produce biofuels and bio-products. The prospective of using Acacia biomass as feedstock in pyrolysis, gasification, liquefaction and combustion is also discussed. Acacia biomass is a sustainable and renewable energy resource for Brunei Darussalam to be exploited for energy requirements and can be beneficial for the economy of the country by providing new investment and employment opportunities.

Ahmed, AA, Pradhan, B, Sameen, MI & Makky, AM 2018, 'An optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data', Arabian Journal of Geosciences, vol. 11, no. 11.
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© 2018, Saudi Society for Geosciences. This study proposed a workflow for an optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data. The method is validated on a set of data captured over a part of Selangor located in the Peninsular Malaysia. The method comprised four components including image segmentation, Taguchi optimization, attribute selection using random forest, and rule-based feature extraction. Results indicated the robustness of the proposed approach as the area under curve of forest; grassland, old oil palm, rubber, urban tree, and young oil palm were calculated as 0.90, 0.89, 0.87, 0.87, 0.80, and 0.77, respectively. In addition, results showed that SAR data is very useful for extracting rubber and young oil palm trees (given by random forest importance values). Finally, further research is suggested to improve segmentation results and extract more features from the scene.

Ahmed, JB & Pradhan, B 2018, 'Termite mounds as bio-indicators of groundwater: Prospects and constraints', Pertanika Journal of Science and Technology, vol. 26, no. 2, pp. 479-498.
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Reliance on modern sophisticated equipment for making ‘discoveries’ has limited the human power of observing subtle clues in the environment that are capable of saving cost and labour that come with researching new resources and methods to improve life for all. Due to the growing scarcity of potable water, especially in African and Asian countries, newer, cheaper and reliable methods of investigating groundwater resources are becoming critical. One such potentially promising method is mapping the distribution of termite mounds in the environment. Termite mounds are conspicuous landscape features in tropical and sub-tropical regions of the world. Built from surrounding soils by several species of termite, the properties of mound soil are relatively different from the surrounding soil in most cases, indicating improved hydraulic properties. In this paper, the aim is to review the possibility of employing termite mounds as prospecting tools for groundwater search from three spatial scales of observation. From assessing the smallest to the highest scale of observation, it can be concluded that termite mounds’ prospect as surface indicators of groundwater is apparent. Review findings indicate increased surface water infiltration, presence of riparian tree vegetation and other trees with tap-root system around termite mounds, linear assemblage of termite mounds along aquiferous dykes and seep-lines as well as the dependence of termites on water but avoidance of places with risk of inundation. Whether they indicate permanent groundwater reserves in all cases or whether all species depend largely on water for their metabolism is a subject for further research.

Ahmed, MB, Johir, MAH, Khourshed, C, Zhou, JL, Ngo, HH, Nghiem, DL, Moni, M & Sun, L 2018, 'Sorptive removal of dissolved organic matter in biologically-treated effluent by functionalized biochar and carbon nanotubes: Importance of sorbent functionality', Bioresource Technology, vol. 269, pp. 9-17.
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© 2018 Elsevier Ltd The sorptive removal of dissolved organic matter (DOM) in biologically-treated effluent was studied by using multi-walled carbon nanotube (MWCNT), carboxylic functionalised MWCNT (MWCNT-COOH), hydroxyl functionalized MWCNT (MWCNT-OH) and functionalized biochar (fBC). DOM was dominated by hydrophilic fraction (79.6%) with a significantly lower hydrophobic fraction (20.4%). The sorption of hydrophobic DOM was not significantly affected by the sorbent functionality (∼10.4% variation) and sorption capacity followed the order of MWCNT > MWCNT-COOH > MWCNT-OH > fBC. In comparison, the sorption of hydrophilic fraction of DOM changed significantly (∼37.35% variation) with the change of sorbent functionality with adsorption capacity decreasing as MWCNT-OH > MWCNT-COOH > MWCNT > fBC. Furthermore, the affinity of adsorbents toward a hydrophilic compound (dinitrobenzene), a hydrophobic compound (pyrene) and humic acid was also evaluated to validate the proposed mechanisms. The results provided important insights on the type of sorbents which are most effective to remove different DOM fractions.

Ahmed, MB, Zhou, JL, Ngo, HH, Johir, MAH & Sornalingam, K 2018, 'Sorptive removal of phenolic endocrine disruptors by functionalized biochar: Competitive interaction mechanism, removal efficacy and application in wastewater', Chemical Engineering Journal, vol. 335, pp. 801-811.
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© 2017 Elsevier B.V. Sorptive removal of six phenolic endocrine disrupting chemicals (EDCs) estrone (E1), 17β-estradiol (E2), estriol (E3), 17α-ethynylestradiol (EE2), bisphenol A (BPA) and 4-tert-butylphenol (4tBP) by functionalized biochar (fBC) through competitive interactions was investigated. EDC sorption was pH dependent with the maximum sorption at pH 3.0–3.5 due to hydrogen bonds and π-π interactions as the principal sorptive mechanism. Sorption isotherm of the EDCs was fitted to the Langmuir model. Sorption capacities and distribution coefficient values followed the order E1 > E2 ≥ EE2 > BPA > 4tBP > E3. The findings suggested that EDC sorption occurred mainly through pseudo-second order and external mass transfer diffusion processes, by forming H-bonds along with π-π electron-donor–acceptor (EDA) interactions at different pH. The complete removal of ∼500 μg L−1 of each EDC from different water decreased in the order: deionised water > membrane bioreactor (MBR) sewage effluent > synthetic wastewater. The presence of sodium lauryl sulphonate and acacia gum in synthetic wastewater significantly suppressed sorption affinity of EDCs by 38–50%, hence requiring more fBC to maintain removal efficacy.

Ahmed, MB, Zhou, JL, Ngo, HH, Johir, MAH, Sun, L, Asadullah, M & Belhaj, D 2018, 'Sorption of hydrophobic organic contaminants on functionalized biochar: Protagonist role of π-π electron-donor-acceptor interactions and hydrogen bonds', Journal of Hazardous Materials, vol. 360, pp. 270-278.
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© 2018 Elsevier B.V. The sorption of five potent endocrine disruptors as representative hydrophobic organic contaminants (HOCs) namely estrone (E1), 17β-estradiol (E2), estriol (E3), 17α-ethynylestradiol (EE2) and bisphenol A (BPA) on functionalized biochar (fBC) was systematically examined, with a particular focus on the importance of π-electron-donor (phenanthrene: PHEN) and π-electron-acceptors (1,3-dinitrobenzene: DNB, p-amino benzoic acid: PABA) on sorption. Experimental results suggested that hydrogen-bond formation and π-π-electron-donor-acceptor (EDA) interactions were the dominant sorption mechanisms. The sorption of HOCs decreased as E1 > E2 > EE2 > E3 > BPA based on the Freundlich and Polanyi-Mane-models. The comparison of adsorption coefficient (Kd) normalized against hexadecane-water partition coefficient (KHW) between HOCs and PHEN indicated strong π-π-EDA interactions. π-π interactions among DNB, PHEN and HOCs were verified by the observed upfield frequency (Hz) shifts using proton nuclear magnetic resonance (1H NMR) which identified the specific direction of π-π interactions. UV–vis spectra showed charge-transfer bands for π-donors (PHEN and HOCs) with the model π-acceptor (DNB) also demonstrating the role of π-π EDA interactions. The role of π-electron-donor and π-electron-acceptor domains in fBC was identified at different solution pH.

Ahmmad, MS, Haji Hassan, MB & Kalam, MA 2018, 'Comparative corrosion characteristics of automotive materials in Jatropha biodiesel', International Journal of Green Energy, vol. 15, no. 6, pp. 393-399.
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Ait Lamqadem, A, Pradhan, B, Saber, H & Rahimi, A 2018, 'Desertification Sensitivity Analysis Using MEDALUS Model and GIS: A Case Study of the Oases of Middle Draa Valley, Morocco', Sensors, vol. 18, no. 7, pp. 2230-2230.
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Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of 13 indices that affect desertification processes were identified and analyzed using a geographic information system. The Mediterranean desertification and land use approach; which has been widely used in the Mediterranean regions due to its simplicity; flexibility and rapid implementation strategy; was applied. All the indices were grouped into four main quality indices; i.e., soil quality; climate quality; vegetation quality and management quality indices. Each quality index was constructed by the combination of several sub-indicators. In turn; the geometric mean of the four quality index maps was used to construct a map of desertification-sensitive areas; which were classified into four classes (i.e., low; moderate; high and very high sensitivity). Results indicated that only 16.63% of the sites in the study were classified as least sensitive to desertification; and 50.34% were classified as highly and very highly sensitive areas. Findings also showed that climate and human pressure factors are the most important indicators affecting desertification sensitivity in the MDV. The framework used in this research provides suitable results and can be easily implemented in similar oasis arid areas.

Akbari, MA, Aghaei, J, Barani, M, Niknam, T, Ghavidel, S, Farahmand, H, Korpas, M & Li, L 2018, 'Convex Models for Optimal Utility-Based Distributed Generation Allocation in Radial Distribution Systems', IEEE Systems Journal, vol. 12, no. 4, pp. 3497-3508.
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© 2007-2012 IEEE. This paper introduces various models for optimal and maximal utility-based distributed generation penetration in the radial distribution systems. Several problems with different probabilistic indices as objective functions constrained by power flow equations, distributed generation penetration, voltage, and thermal limits are proposed to obtain the optimal penetration of distributed generations on rural distribution networks. There are tradeoffs between interests and risks that the distribution network operators or distribution companies may be willing to take on. Thus, to have an effective method for maximal allocation of distributed generations, new indices are proposed, and the problems are formulated as a risk-constrained optimization model. The obtained problems have mixed-integer nonlinear programming and nonconvex forms because of nonlinearity and nonconvexity of the optimal power flow (OPF) equations and indices, leading to computationally nondeterministic polynomial-time-hard problems. Accordingly, in this paper, convex relaxations of OPF are introduced instead of the conventional nonlinear equations. Efficient linear equivalents of the objective function and constraints are introduced to reduce the computational burden. Test results of the proposed models on a radial distribution system are presented and discussed.

Akther, N, Daer, S & Hasan, SW 2018, 'Effect of flow rate, draw solution concentration and temperature on the performance of TFC FO membrane, and the potential use of RO reject brine as a draw solution in FO–RO hybrid systems', Desalination and Water Treatment, vol. 136, pp. 65-71.
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Al Muderis, MM, Lu, WY, Li, JJ, Kaufman, K, Orendurff, M, Highsmith, MJ, Lunseth, PA & Kahle, JT 2018, 'Clinically Relevant Outcome Measures Following Limb Osseointegration; Systematic Review of the Literature', Journal of Orthopaedic Trauma, vol. 32, no. 2, pp. e64-e75.
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Objectives: The current standard of care for an amputee is a socket-based prostheses. An osseointegrated implant (OI) is an alternative for prosthetic attachment. Osseointegration addresses reported problems related to wearing a socket interface, such as skin issues, discomfort, diminished function, quality of life, prosthetic use, and abandonment. The purpose of this report is to systematically review current literature regarding OI to identify and categorize the reported clinically relevant outcome measures, rate the quality of available evidence, and synthesize the findings. Data sources: A multidisciplinary team used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methods. Search methodology was based on identifying clinically relevant articles. Three databases were searched: PubMed, CINAHL, and Web of Science. Study Selection: Clinical studies with aggregated data reporting at least 1 clinically relevant outcome measure were included. Data Extraction: The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criterion was used for critical appraisal and recommendations. Conclusions: This review identified 21 clinically relevant observational studies. Outcome measures were categorized into the following 9 categories: vibratory stimulation, complications, biomechanics, economics, patient-reported outcome measures, electromyography, x-ray, physical functional performance, and energy consumption. This systemat...

Alabd, R, Safavi-Naeini, M, Wilson, KJ, Rosenfeld, AB & Franklin, DR 2018, 'A simulation study of BrachyShade, a shadow-based internal source tracking system for HDR prostate brachytherapy', Physics in Medicine & Biology, vol. 63, no. 20, pp. 205019-205019.
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This paper presents a simulation study of BrachyShade, a proposed internal source-tracking system for real time quality assurance in high dose rate prostate brachytherapy. BrachyShade consists of a set of spherical tungsten occluders located above a pixellated silicon photodetector. The source location is estimated by minimising the mean squared error between a parametric model of the shadow image and acquired images of the shadows projected on the detector plane. A novel algorithm is finally employed to correct the systemic error resulting from Compton scattering in the medium. The worst-case error obtained with BrachyShade for a 13.5 ms image acquisition is less than 1.3 mm in the most distant part of the treatment volume, while for 75% of source locations an error of less than 0.42 mm was achieved.

Alajlouni, D, Bliuc, D, Tran, T, Pocock, N, Nguyen, TV, Eisman, JA & Center, JR 2018, 'Nonstandard Lumbar Region in Predicting Fracture Risk', Journal of Clinical Densitometry, vol. 21, no. 2, pp. 220-226.
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© 2017 The International Society for Clinical Densitometry Femoral neck (FN) bone mineral density (BMD) is the most commonly used skeletal site to estimate fracture risk. The role of lumbar spine (LS) BMD in fracture risk prediction is less clear due to osteophytes that spuriously increase LS BMD, particularly at lower levels. The aim of this study was to compare fracture predictive ability of upper L1–L2 BMD with standard L2–L4 BMD and assess whether the addition of either LS site could improve fracture prediction over FN BMD. This study comprised a prospective cohort of 3016 women and men over 60 yr from the Dubbo Osteoporosis Epidemiology Study followed up for occurrence of minimal trauma fractures from 1989 to 2014. Dual-energy X-ray absorptiometry was used to measure BMD at L1–L2, L2–L4, and FN at baseline. Fracture risks were estimated using Cox proportional hazards models separately for each site. Predictive performances were compared using receiver operating characteristic curve analyses. There were 565 women and 179 men with a minimal trauma fracture during a mean of 11 ± 7 yr. L1–L2 BMD T-score was significantly lower than L2–L4 T-score in both genders (p < 0.0001). L1–L2 and L2–L4 BMD models had a similar fracture predictive ability. LS BMD was better than FN BMD in predicting vertebral fracture risk in women [area under the curve 0.73 (95% confidence interval, 0.68–0.79) vs 0.68 (95% confidence interval, 0.62–0.74), but FN was superior for hip fractures prediction in both women and men. The addition of L1–L2 or L2–L4 to FN BMD in women increased overall and vertebral predictive power compared with FN BMD alone by 1% and 4%, respectively (p < 0.05). In an elderly population, L1–L2 is as good as but not better than L2–L4 site in predicting fracture risk. The addition of LS BMD to FN BMD provided a modest additional benefit in overall fracture risk. Further studies in individuals with spinal degenerative disease are needed.

Alavi Nezhad Khalil Abad, SV, Yilmaz, M, Jahed Armaghani, D & Tugrul, A 2018, 'Prediction of the durability of limestone aggregates using computational techniques', Neural Computing and Applications, vol. 29, no. 2, pp. 423-433.
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Alavi, AH, Cui, Z, Gandomi, AH, Gao, X-Z, Wang, G-G & Lim, M-H 2018, 'Editorial', Memetic Computing, vol. 10, no. 2, pp. 121-122.
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Alazigha, DP, Indraratna, B, Vinod, JS & Heitor, A 2018, 'Mechanisms of stabilization of expansive soil with lignosulfonate admixture', Transportation Geotechnics, vol. 14, pp. 81-92.
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Aldebei, K, He, X, Jia, W & Yeh, W 2018, 'SUDMAD: Sequential and unsupervised decomposition of a multi‐author document based on a hidden markov model', Journal of the Association for Information Science and Technology, vol. 69, no. 2, pp. 201-214.
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Decomposing a document written by more than one author into sentences based on authorship is of great significance due to the increasing demand for plagiarism detection, forensic analysis, civil law (i.e., disputed copyright issues), and intelligence issues that involve disputed anonymous documents. Among existing studies for document decomposition, some were limited by specific languages, according to topics or restricted to a document of two authors, and their accuracies have big room for improvement. In this paper, we consider the contextual correlation hidden among sentences and propose an algorithm for Sequential and Unsupervised Decomposition of a Multi‐Author Document (SUDMAD) written in any language, disregarding topics, through the construction of a Hidden Markov Model (HMM) reflecting the authors' writing styles. To build and learn such a model, an unsupervised, statistical approach is first proposed to estimate the initial values of HMM parameters of a preliminary model, which does not require the availability of any information of author's or document's context other than how many authors contributed to writing the document. To further boost the performance of this approach, a boosted HMM learning procedure is proposed next, where the initial classification results are used to create labeled training data to learn a more accurate HMM. Moreover, the contextual relationship among sentences is further utilized to refine the classification results. Our proposed approach is empirically evaluated on three benchmark datasets that are widely used for authorship analysis of documents. Comparisons with recent state‐of‐the‐art approaches are also presented to demonstrate the significance of our new ideas and the superior performance of our approach.

Alderighi, T, Malomo, L, Giorgi, D, Pietroni, N, Bickel, B & Cignoni, P 2018, 'Metamolds: computational design of silicone molds.', ACM Trans. Graph., vol. 37, no. 4, pp. 136-136.
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Alexander, TB, Gu, Z, Iacobucci, I, Dickerson, K, Choi, JK, Xu, B, Payne-Turner, D, Yoshihara, H, Loh, ML, Horan, J, Buldini, B, Basso, G, Elitzur, S, de Haas, V, Zwaan, CM, Yeoh, A, Reinhardt, D, Tomizawa, D, Kiyokawa, N, Lammens, T, De Moerloose, B, Catchpoole, D, Hori, H, Moorman, A, Moore, AS, Hrusak, O, Meshinchi, S, Orgel, E, Devidas, M, Borowitz, M, Wood, B, Heerema, NA, Carrol, A, Yang, Y-L, Smith, MA, Davidsen, TM, Hermida, LC, Gesuwan, P, Marra, MA, Ma, Y, Mungall, AJ, Moore, RA, Jones, SJM, Valentine, M, Janke, LJ, Rubnitz, JE, Pui, C-H, Ding, L, Liu, Y, Zhang, J, Nichols, KE, Downing, JR, Cao, X, Shi, L, Pounds, S, Newman, S, Pei, D, Guidry Auvil, JM, Gerhard, DS, Hunger, SP, Inaba, H & Mullighan, CG 2018, 'The genetic basis and cell of origin of mixed phenotype acute leukaemia', Nature, vol. 562, no. 7727, pp. 373-379.
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Mixed phenotype acute leukaemia (MPAL) is a high-risk subtype of leukaemia with myeloid and lymphoid features, limited genetic characterization, and a lack of consensus regarding appropriate therapy. Here we show that the two principal subtypes of MPAL, T/myeloid (T/M) and B/myeloid (B/M), are genetically distinct. Rearrangement of ZNF384 is common in B/M MPAL, and biallelic WT1 alterations are common in T/M MPAL, which shares genomic features with early T-cell precursor acute lymphoblastic leukaemia. We show that the intratumoral immunophenotypic heterogeneity characteristic of MPAL is independent of somatic genetic variation, that founding lesions arise in primitive haematopoietic progenitors, and that individual phenotypic subpopulations can reconstitute the immunophenotypic diversity in vivo. These findings indicate that the cell of origin and founding lesions, rather than an accumulation of distinct genomic alterations, prime tumour cells for lineage promiscuity. Moreover, these findings position MPAL in the spectrum of immature leukaemias and provide a genetically informed framework for future clinical trials of potential treatments for MPAL.

Alfaro-García, VG, Merigó, JM, Gil-Lafuente, AM & Kacprzyk, J 2018, 'Logarithmic aggregation operators and distance measures', International Journal of Intelligent Systems, vol. 33, no. 7, pp. 1488-1506.
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© 2018 Wiley Periodicals, Inc. The Hamming distance is a well-known measure that is designed to provide insights into the similarity between two strings of information. In this study, we use the Hamming distance, the optimal deviation model, and the generalized ordered weighted logarithmic averaging (GOWLA) operator to develop the ordered weighted logarithmic averaging distance (OWLAD) operator and the generalized ordered weighted logarithmic averaging distance (GOWLAD) operator. The main advantage of these operators is the possibility of modeling a wider range of complex representations of problems under the assumption of an ideal possibility. We study the main properties, alternative formulations, and families of the proposed operators. We analyze multiple classical measures to characterize the weighting vector and propose alternatives to deal with the logarithmic properties of the operators. Furthermore, we present generalizations of the operators, which are obtained by studying their weighting vectors and the lambda parameter. Finally, an illustrative example regarding innovation project management measurement is proposed, in which a multi-expert analysis and several of the newly introduced operators are utilized.

Ali, A & Lee, JE-Y 2018, 'Piezoelectric-on-Silicon Square Wine-Glass Mode Resonator for Enhanced Electrical Characterization in Water', IEEE Transactions on Electron Devices, vol. 65, no. 5, pp. 1925-1931.
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Ali, AR, Gabrys, B & Budka, M 2018, 'Cross-domain Meta-learning for Time-series Forecasting', Procedia Computer Science, vol. 126, pp. 9-18.
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© 2018 The Author(s). There are many algorithms that can be used for the time-series forecasting problem, ranging from simple (e.g. Moving Average) to sophisticated Machine Learning approaches (e.g. Neural Networks). Most of these algorithms require a number of user-defined parameters to be specified, leading to exponential explosion of the space of potential solutionS. since the trial-and-error approach to finding a good algorithm for solving a given problem is typically intractable, reSearchers and practitioners need to resort to a more intelligent Search strategy, with one option being to constraint the Search space using past experience - an approach known as Meta-learning. Although potentially attractive, Meta-learning comes with its own challengeS. Gathering a sufficient number of Meta-examples, which in turn requires collecting and processing multiple datasets from each problem domain under consideration is perhaps the most prominent issue. In this paper, we are investigating the situations in which the use of additional data can improve performance of a Meta-learning System, with focus on cross-domain transfer of Meta-knowledge. A similarity-based cluster analysis of Meta-features has also been performed in an attempt to discover homogeneous groups of time-series with respect to Meta-learning performance. Although the experiments revealed limited room for improvement over the overall best base-learner, the Meta-learning approach turned out to be a safe choice, minimizing the risk of selecting the least appropriate base-learner.

Ali, SM, Kim, JE, Phuntsho, S, Jang, A, Choi, JY & Shon, HK 2018, 'Forward osmosis system analysis for optimum design and operating conditions', Water Research, vol. 145, pp. 429-441.
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© 2018 Elsevier Ltd Low energy consumption and less fouling propensity of forward osmosis (FO) processes have been attractive as a promising water filtration technology. The performance of this process is however significantly influenced by its operating conditions. Moreover, these operating parameters have both favourable and adverse effects on its performance. Therefore, it is very important to optimize its performance for efficient and economic operation. This study aims to develop a software to analyze a full-scale FO system for optimum performance. A comprehensive theoretical framework was developed to estimate the performance of FO system. Analysis results were compared with the experimental results to validate the models. About 5% deviation of simulation results and the experimental findings shows a very good agreement between them. A novel optimization algorithm was then developed to estimate the minimum required draw solution (DS) inlet flowrate and the number of elements in a pressure vessel to attain the design objectives (i.e. desired final DS concentration and recovery rate at a specific feed solution (FS) flowrate). A detailed parametric study was also conducted to determine the optimum operating conditions for different objectives. It showed that for a specific design objective, higher recovery rate can be achieved by increasing the DS flowrate and number of elements in a pressure vessel. In contrast, lower final concentration can be obtained by lowering the DS flowrate and increasing the number of elements. Finally, a MATLAB based software with graphical user interface was developed to make the analysis process easier and efficient.

Alidadi, H, Dolatabadi, M, Davoudi, M, Barjasteh-Askari, F, Jamali-Behnam, F & Hosseinzadeh, A 2018, 'Enhanced removal of tetracycline using modified sawdust: Optimization, isotherm, kinetics, and regeneration studies', Process Safety and Environmental Protection, vol. 117, pp. 51-60.
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Alizadeh, M, Hashim, M, Alizadeh, E, Shahabi, H, Karami, MR, Beiranvand Pour, A, Pradhan, B & Zabihi, H 2018, 'Multi-Criteria Decision Making (MCDM) Model for Seismic Vulnerability Assessment (SVA) of Urban Residential Buildings', ISPRS International Journal of Geo-Information, vol. 7, no. 11, pp. 444-444.
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Earthquakes are among the most catastrophic natural geo-hazards worldwide and endanger numerous lives annually. Therefore, it is vital to evaluate seismic vulnerability beforehand to decrease future fatalities. The aim of this research is to assess the seismic vulnerability of residential houses in an urban region on the basis of the Multi-Criteria Decision Making (MCDM) model, including the analytic hierarchy process (AHP) and geographical information system (GIS). Tabriz city located adjacent to the North Tabriz Fault (NTF) in North-West Iran was selected as a case study. The NTF is one of the major seismogenic faults in the north-western part of Iran. First, several parameters such as distance to fault, percent of slope, and geology layers were used to develop a geotechnical map. In addition, the structural construction materials, building materials, size of building blocks, quality of buildings and buildings-floors were used as key factors impacting on the building’s structural vulnerability in residential areas. Subsequently, the AHP technique was adopted to measure the priority ranking, criteria weight (layers), and alternatives (classes) of every criterion through pair-wise comparison at all levels. Lastly, the layers of geotechnical and spatial structures were superimposed to design the seismic vulnerability map of buildings in the residential area of Tabriz city. The results showed that South and Southeast areas of Tabriz city exhibit low to moderate vulnerability, while some regions of the north-eastern area are under severe vulnerability conditions. In conclusion, the suggested approach offers a practical and effective evaluation of Seismic Vulnerability Assessment (SVA) and provides valuable information that could assist urban planners during mitigation and preparatory phases of less examined areas in many other regions around the world.

Alizadeh, M, Ngah, I, Hashim, M, Pradhan, B & Pour, AB 2018, 'A Hybrid Analytic Network Process and Artificial Neural Network (ANP-ANN) Model for Urban Earthquake Vulnerability Assessment', Remote Sensing, vol. 10, no. 6, pp. 975-975.
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Vulnerability assessment is one of the prerequisites for risk analysis in disaster management. Vulnerability to earthquakes, especially in urban areas, has increased over the years due to the presence of complex urban structures and rapid development. Urban vulnerability is a result of human behavior which describes the extent of susceptibility or resilience of social, economic, and physical assets to natural disasters. The main aim of this paper is to develop a new hybrid framework using Analytic Network Process (ANP) and Artificial Neural Network (ANN) models for constructing a composite social, economic, environmental, and physical vulnerability index. This index was then applied to Tabriz City, which is a seismic-prone province in the northwestern part of Iran with recurring devastating earthquakes and consequent heavy casualties and damages. A Geographical Information Systems (GIS) analysis was used to identify and evaluate quantitative vulnerability indicators for generating an earthquake vulnerability map. The classified and standardized indicators were subsequently weighed and ranked using an ANP model to construct the training database. Then, standardized maps coupled with the training site maps were presented as input to a Multilayer Perceptron (MLP) neural network for producing an Earthquake Vulnerability Map (EVM). Finally, an EVM was produced for Tabriz City and the level of vulnerability in various zones was obtained. South and southeast regions of Tabriz City indicate low to moderate vulnerability, while some zones of the northeastern tract are under critical vulnerability conditions. Furthermore, the impact of the vulnerability of Tabriz City on population during an earthquake was included in this analysis for risk estimation. A comparison of the result produced by EVM and the Population Vulnerability (PV) of Tabriz City corroborated the validity of the results obtained by ANP-ANN. The findings of this paper are useful for decisi...

Allioux, F-M, David, O, Merenda, A, Maina, JW, Benavides, ME, Tanaka, AP & Dumée, LF 2018, 'Catalytic nickel and nickel–copper alloy hollow-fiber membranes for the remediation of organic pollutants by electrocatalysis', Journal of Materials Chemistry A, vol. 6, no. 16, pp. 6904-6915.
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Electrocatalytic membrane reactors are becoming a viable solution for the treatment of wastewater contaminated with persistent organic pollutants and compounds.

Alsahafi, YA & Gay, V 2018, 'An overview of electronic personal health records', Health Policy and Technology, vol. 7, no. 4, pp. 427-432.
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© 2018 Electronic Personal Health Record systems are providing health consumers with greater access and control to their health records by shifting these records from being a health provider-centred Electronic Health Record, to a patient-centred, Electronic Personal Health Record (ePHR). Based on the delivery system, ePHR systems are classified into standalone, tethered, and integrated or unified ePHRs. While national approaches of implementing integrated ePHR vary, the middle out method has been recognised as the ideal approach. It is worth considering the adoption of ePHRs has been slow due to several factors, including technical, individual, environmental, social, and legal factors. This paper provides a representative overview of an ePHR system, outlining its definition, types, architectures, and nationwide approaches of its implementation. Additionally, the drivers and hindrances to health consumer adoption are discussed.

Alshehri, MD, Hussain, FK & Hussain, OK 2018, 'Clustering-Driven Intelligent Trust Management Methodology for the Internet of Things (CITM-IoT)', Mobile Networks and Applications, vol. 23, no. 3, pp. 419-431.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The growth and adoption of the Internet of Things (IoT) is increasing day by day. The large number of IoT devices increases the risk of security threats such as (but not limited to) viruses or cyber-attacks. One possible approach to achieve IoT security is to enable a trustworthy IoT environment in IoT wherein the interactions are based on the trust value of the communicating nodes. Trust management and trust assessment has been extensively studied in distributed networks in general and the IoT in particular, but there are still outstanding pressing issues such as bad-mouthing of trust values which prevent them from being used in practical IoT applications. Furthermore, there is no research in ensuring that the developed IoT trust solutions are scalable across billions of IoT nodes. To address the above-mentioned issues, we propose a methodology for scalable trust management solution in the IoT. The methodology addresses practical and pressing issues related to IoT trust management such as trust-based IoT clustering, intelligent methods for countering bad-mouthing attacks on trust systems, issues of memory-efficient trust computation and trust-based migration of IoT nodes from one cluster to another. Experimental results demonstrate the effectiveness of the proposed approaches.

Altaee, A 2018, 'Osmotic Power Plant: Process Innovation and Future Potential', Recent Advances in Petrochemical Science, vol. 4, no. 3, pp. 1-1.
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Osmotic power plant operating by Pressure Retarded Osmosis (PRO) is a promising technology for power generation from renewable resources. A wealth of literature has been published in PRO feasibility to replace conventional fossil fuel power plants. In this paper the PRO and the new innovative Dual Stage PRO process are briefly reviewed with the authors’ insight on the future development and application of the PRO power plants.

Altaee, A, Zaragoza, G, Millar, GJ, Sharif, AO & Alanezi, AA 2018, 'Limitations of osmotic gradient resource and hydraulic pressure on the efficiency of dual stage PRO process', Desalination and Water Treatment, vol. 105, pp. 11-22.
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© 2018 Desalination Publications. All rights reserved. A dual stage PRO process has been proposed for power generation from a salinity gradient across a semi-permeable membrane. Both closed-loop and open-loop dual stage PRO system were evaluated using 2 M NaCl and Dead Sea as draw solutions, whereas the feed solution was either fresh water or seawater. The impact of feed salinity gradient resource and feed pressure on the net power generation and water flux were evaluated. The results showed that power density in stage one reached a maximum amount at ΔP = p/2, but the maximum net power generation occurred at ΔP = p/2. This result was mainly attributed to the variation of net driving pressure in stage one and two of the PRO process. The dual stage PRO process was found to perform better at high osmotic pressure gradient across the PRO membrane, for example when Dead Sea brine or highly concentrated NaCl was the draw solution. Total power generation in the dual stage PRO process was up to 40% higher than that in the conventional PRO process. This outcome was achieved through harvesting the rest of the energy remaining in the diluted draw solution. Therefore, a dual stage PRO process has the potential of maximizing power generation from a salinity gradient resource.

Alzoubi, YI, Gill, AQ & Moulton, B 2018, 'A measurement model to analyze the effect of agile enterprise architecture on geographically distributed agile development.', J. Softw. Eng. Res. Dev., vol. 6, no. 4, pp. 4-4.
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Al-Zubaydi, AYT & Hong, G 2018, 'Experimental investigation of counter flow heat exchangers for energy recovery ventilation in cooling mode', International Journal of Refrigeration, vol. 93, pp. 132-143.
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© 2018 Elsevier Ltd and IIR Ventilation heat recovery is a system that requires low power to operate and has a high capacity to reduce the energy consumption and increase the overall efficiency for air conditioning. This paper reports the experimental investigation of air-to-air heat exchangers employed for heat recovery ventilation in cooling mode. The two main objective of this research are to design, fabricate and testing two polymers heat exchangers of different plate geometries and to evaluate and compare the thermal performance two quasi-counter flow plate heat exchangers. The key aims were to evaluate the effect of the surface geometry of the plates heat exchanger on the performance parameters specified in ANSI/ASHRAE Standard 84 and ANSI/AHRI Standard 1060 and narrow the gap of the limited experimental comparison of polymers sensible heat exchanger in cooling mode. The experiments were conducted on two polymer heat exchangers, one with a flat plate and the other with a dimpled surface plate. The experimental results showed that the cooling capacity of the dimpled surface heat exchanger as ventilation heat recovery system in cooling mode was 50–60% better than that of the flat surface plate heat exchanger. In addition, the sensible efficiency of the dimpled surface heat exchanger was higher than that of the flat surface plates heat exchanger at lower air velocities and higher air initial temperatures. The highest COP was 6.6 achieved with dimpled surface heat exchanger under primary air operating temperature of 32.6 °C.

Amjadipour, M, Tadich, A, Boeckl, JJ, Lipton-Duffin, J, MacLeod, J, Iacopi, F & Motta, N 2018, 'Quasi free-standing epitaxial graphene fabrication on 3C–SiC/Si(111)', Nanotechnology, vol. 29, no. 14, pp. 145601-145601.
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Growing graphene on SiC thin films on Si is a cheaper alternative to the growth on bulk SiC, and for this reason it has been recently intensively investigated. Here we study the effect of hydrogen intercalation on epitaxial graphene obtained by high temperature annealing on 3C-SiC/Si(111) in ultra-high vacuum. By using a combination of core-level photoelectron spectroscopy, low energy electron diffraction, and near-edge x-ray absorption fine structure (NEXAFS) we find that hydrogen saturates the Si atoms at the topmost layer of the substrate, leading to free-standing graphene on 3C-SiC/Si(111). The intercalated hydrogen fully desorbs after heating the sample at 850 °C and the buffer layer appears again, similar to what has been reported for bulk SiC. However, the NEXAFS analysis sheds new light on the effect of hydrogen intercalation, showing an improvement of graphene's flatness after annealing in atomic H at 600 °C. These results provide new insight into free-standing graphene fabrication on SiC/Si thin films.

Anaissi, A, Khoa, NLD & Wang, Y 2018, 'Automated parameter tuning in one-class support vector machine: an application for damage detection', International Journal of Data Science and Analytics, vol. 6, no. 4, pp. 311-325.
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Anaissi, A, Khoa, NLD, Rakotoarivelo, T, Alamdari, MM & Wang, Y 2018, 'Adaptive Online One-Class Support Vector Machines with Applications in Structural Health Monitoring', ACM Transactions on Intelligent Systems and Technology, vol. 9, no. 6, pp. 1-20.
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One-class support vector machine (OCSVM) has been widely used in the area of structural health monitoring, where only data from one class (i.e., healthy) are available. Incremental learning of OCSVM is critical for online applications in which huge data streams continuously arrive and the healthy data distribution may vary over time. This article proposes a novel adaptive self-advised online OCSVM that incrementally tunes the kernel parameter and decides whether a model update is required or not. As opposed to existing methods, this novel online algorithm does not rely on any fixed threshold, but it uses the slack variables in the OCSVM to determine which new data points should be included in the training set and trigger a model update. The algorithm also incrementally tunes the kernel parameter of OCSVM automatically based on the spatial locations of the edge and interior samples in the training data with respect to the constructed hyperplane of OCSVM. This new online OCSVM algorithm was extensively evaluated using synthetic data and real data from case studies in structural health monitoring. The results showed that the proposed method significantly improved the classification error rates, was able to assimilate the changes in the positive data distribution over time, and maintained a high damage detection accuracy in all case studies.

Andrade-Valbuena, NA & Merigo, JM 2018, 'Outlining new product development research through bibliometrics', Journal of Strategy and Management, vol. 11, no. 3, pp. 328-350.
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PurposeNew product development (NPD) is a noteworthy field that has attracted the attention of scholars for its relevance for firm success. Based on bibliometric indicators and spatial distance network analysis, the authors outline the general structure overview of NPD research through the last 40 years of scientific production; identify and categorize key articles, authors, journals, institutions, and countries related to NPD research; identify and map the research subareas that have mostly contributed to the construction of NPD intellectual structure. The paper aims to discuss these issues.Design/methodology/approachThe work uses the Web of Science Core Collection and the visualization of similarities viewer software. The analysis searches for all the documents connected to NPD available in the database. The graphical visualization maps the bibliographic data in terms of bibliographic coupling and co-citation.FindingsThe general NPD citation pattern evidences a construction of knowledge and learning, as evidenced in different subjects, such as biology or physics. Relevant contributions and contributors are highlighted as journals, articles, researchers, countries and institutions in overall NPD research and in its constituent subfields. Five subareas related to the NPD field based on journals and authors network are identified: marketing; operations and production; strategy; industrial engineering and operations; and management.Originality/valueThis paper contributes to the NPD literature by offering a global perspective on the field by using bibliometric data graphical networks, provid...

Ansari, AJ, Hai, FI, He, T, Price, WE & Nghiem, LD 2018, 'Physical cleaning techniques to control fouling during the pre-concentration of high suspended-solid content solutions for resource recovery by forward osmosis', Desalination, vol. 429, pp. 134-141.
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Ansari, AJ, Hai, FI, Price, WE, Ngo, HH, Guo, W & Nghiem, LD 2018, 'Assessing the integration of forward osmosis and anaerobic digestion for simultaneous wastewater treatment and resource recovery', Bioresource Technology, vol. 260, pp. 221-226.
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© 2018 This study assessed the performance and key challenges associated with the integration of forward osmosis (FO) and anaerobic digestion for wastewater treatment and resource recovery. Using a thin film composite polyamide FO membrane, maximising the pre-concentration factor (i.e. system water recovery) resulted in the enrichment of organics and salinity in wastewater. Biomethane potential evaluation indicated that methane production increased correspondingly with the FO pre-concentration factor due to the organic retention in the feed solution. At 90% water recovery, about 10% more methane was produced when using NaOAc compared with NaCl because of the contribution of biodegradable reverse NaOAc flux. No negative impact on anaerobic digestion was observed when wastewater was pre-concentrated ten-fold (90% water recovery) for both draw solutes. Interestingly, the unit cost of methane production using NaOAc was slightly lower than NaCl due to the lower reverse solute flux of NaOAc, although NaCl is a much cheaper chemical.

Anshu, A, Berta, M, Jain, R & Tomamichel, M 2018, 'Partially smoothed information measures', IEEE Trans. Inf. Theory, vol. 66, pp. 5022-5036.
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Smooth entropies are a tool for quantifying resource trade-offs in (quantum)information theory and cryptography. In typical bi- and multi-partite problems,however, some of the sub-systems are often left unchanged and this is notreflected by the standard smoothing of information measures over a ball ofclose states. We propose to smooth instead only over a ball of close stateswhich also have some of the reduced states on the relevant sub-systems fixed.This partial smoothing of information measures naturally allows to give morerefined characterizations of various information-theoretic problems in theone-shot setting. In particular, we immediately get asymptotic second-ordercharacterizations for tasks such as privacy amplification against classicalside information or classical state splitting. For quantum problems like statemerging the general resource trade-off is tightly characterized by partiallysmoothed information measures as well.

Apkon, SD, Alman, B, Birnkrant, DJ, Fitch, R, Lark, R, Mackenzie, W, Weidner, N & Sussman, M 2018, 'Orthopedic and Surgical Management of the Patient With Duchenne Muscular Dystrophy', Pediatrics, vol. 142, no. Supplement_2, pp. S82-S89.
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Orthopedic care is an important aspect of the overall management of patients with Duchenne muscular dystrophy (DMD). In addition to progressive muscle weakness and loss of function, patients may develop joint contractures, scoliosis, and osteoporosis, causing fractures; all of these necessitate intervention by a multidisciplinary team including an orthopedic surgeon as well as rehabilitation specialists such as physio- and occupational therapists. The causes of these musculoskeletal complications are multifactorial and are related to primary effects on the muscles from the disease itself, secondary effects from weak muscles, and the related side effects of treatments, such as glucocorticoid use that affect bone strength. The musculoskeletal manifestations of DMD change over time as the disease progresses, and therefore, musculoskeletal management needs change throughout the life span of an individual with DMD. In this review, we target pediatricians, neurologists, orthopedic surgeons, rehabilitation physicians, anesthesiologists, and other individuals involved in the management of patients with DMD by providing specific recommendations to guide clinical practice related to orthopedic issues and surgical management in this setting.

Ara, P, Yu, K, Cheng, S, Dutkiewicz, E & Heimlich, MC 2018, 'Human Abdomen Path-Loss Modeling and Location Estimation of Wireless Capsule Endoscope Using Round-Trip Propagation Loss', IEEE Sensors Journal, vol. 18, no. 8, pp. 3266-3277.
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Arabameri, A, Pradhan, B, Pourghasemi, HR & Rezaei, K 2018, 'Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 1129-1155.
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Arabameri, A, Pradhan, B, Pourghasemi, HR, Rezaei, K & Kerle, N 2018, 'Spatial Modelling of Gully Erosion Using GIS and R Programing: A Comparison among Three Data Mining Algorithms', Applied Sciences, vol. 8, no. 8, pp. 1369-1369.
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Gully erosion triggers land degradation and restricts the use of land. This study assesses the spatial relationship between gully erosion (GE) and geo-environmental variables (GEVs) using Weights-of-Evidence (WoE) Bayes theory, and then applies three data mining methods—Random Forest (RF), boosted regression tree (BRT), and multivariate adaptive regression spline (MARS)—for gully erosion susceptibility mapping (GESM) in the Shahroud watershed, Iran. Gully locations were identified by extensive field surveys, and a total of 172 GE locations were mapped. Twelve gully-related GEVs: Elevation, slope degree, slope aspect, plan curvature, convergence index, topographic wetness index (TWI), lithology, land use/land cover (LU/LC), distance from rivers, distance from roads, drainage density, and NDVI were selected to model GE. The results of variables importance by RF and BRT models indicated that distance from road, elevation, and lithology had the highest effect on GE occurrence. The area under the curve (AUC) and seed cell area index (SCAI) methods were used to validate the three GE maps. The results showed that AUC for the three models varies from 0.911 to 0.927, whereas the RF model had a prediction accuracy of 0.927 as per SCAI values, when compared to the other models. The findings will be of help for planning and developing the studied region.

Arandiyan, H, Wang, Y, Scott, J, Mesgari, S, Dai, H & Amal, R 2018, 'In Situ Exsolution of Bimetallic Rh–Ni Nanoalloys: a Highly Efficient Catalyst for CO₂ Methanation', ACS Applied Materials & Interfaces, vol. 10, no. 19, pp. 16352-16357.
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© 2018 American Chemical Society. Unique CO2 methanation catalysts comprising bimetallic Ni-Rh nanoalloy/3DOM LaAlO3 have been successfully prepared via a poly(methyl methacrylate) microsphere colloidal crystal-templating route, followed by the in situ growth of Ni nanoparticles (NPs). Here, we show that unlike traditional Ni particles deposited on a perovskite support, the exsolution of Ni occurs on both the external and internal surface of the porous perovskite substrate, leading to a strong metal-support interaction. Owing to the exsolution of Ni and the formation of Ni-Rh nanoalloys, a 52% enhancement in the methanation turnover frequency was obtained over the Ni-Rh/3DOM LaAlO3 [13.9 mol/(mol h)] compared to Rh/3DOM LaNi0.08Al0.92O3 [9.16 mol/(mol h)] before reduction treatment. The results show that the low-temperature reducibility, rich surface adsorbed oxygen species, and basic sites of the catalyst greatly improve its activity toward CO2 methanation. The hierarchically porous structure of the perovskite support provides a high dispersion of bimetallic Ni-Rh NPs.

Argha, A, Li, L & Su, SW 2018, '‐based optimal sparse sliding mode control for networked control systems', International Journal of Robust and Nonlinear Control, vol. 28, no. 1, pp. 16-30.
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SummaryThis paper is devoted to the problem of designing a sparsely distributed sliding mode control for networked systems. Indeed, this note uses a distributed sliding mode control framework by exploiting (some of) other subsystems' information to improve the performance of each local controller so that it can widen the applicability region of the given scheme. To do so, different from the traditional schemes in the literature, a novel approach is proposed to design the sliding surface, in which the level of required control effort is taken into account during the sliding surface design based on the control. We then use this novel scheme to provide an innovative less‐complex procedure that explores sparse control networks to satisfy the underlying control objective. Besides, the proposed scheme to design the sliding surface makes it possible to avoid unbounded growth of control effort during the sparsification of the control network structure. Illustrative examples are presented to show the effectiveness of the proposed approach.

Argha, A, Li, L, Su, SW & Nguyen, H 2018, 'Sparsely distributed sliding mode control for interconnected systems', Journal of the Franklin Institute, vol. 355, no. 14, pp. 6191-6214.
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© 2018 The Franklin Institute This paper proposes a framework for the design of sparsely distributed output feedback discrete-time sliding mode control (ODSMC) for interconnected systems. The major target here is to develop an observer based discrete-time sliding mode controller employing a sparsely distributed control network structure in which local controllers exploit some other sub-systems’ information as well as its own local information. As the local controllers/observers have access to some other sub-systems’ states, the control performance will be improved and the applicability region will be widened compared to the decentralised structure. As the first step, a stability condition is derived for the overall closed-loop system obtained from applying ODSMC to the underlying interconnected system, by assuming a priori known structure for the control/observer network. The developed LMI based controller design scheme provides the possibility to employ different information patterns such as fully distributed, sparsely distributed and decentralised patterns. In the second step, we propose a methodology to identify a sparse control/observer network structure with the least possible number of communication links that satisfies the stability condition given in the first step. The boundedness of the obtained overall closed-loop system is analysed and a bound is derived for the augmented system state which includes the closed-loop system state and the switching function.

Argha, A, Su, SW, Savkin, A & Celler, BG 2018, 'Mixed H2/H∞-based actuator selection for uncertain polytopic systems with regional pole placement', International Journal of Control, vol. 91, no. 2, pp. 320-336.
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© 2017 Informa UK Limited, trading as Taylor & Francis GroupThis paper is devoted to the problem of designing an (Formula presented.) and/or (Formula presented.) row-sparse static output feedback controller for continuous linear time-invariant systems with polytopic uncertainty. The immediate application of the proposed approach lies within the problem of the optimal selection of a subset of available actuators during the fault accommodation stage of a fault-tolerant control scheme. Incorporating an extra term for penalising the number of actuators into the optimisation objective function, we propose an explicit scheme and two iterative procedures according to the reweighted ℓ1 (REL1) and reweighted iterative support detection (RISD) algorithms for the purposes of identifying the favourable row-sparse feedback gains. Furthermore, this problem formulation allows us to incorporate additional constraints into the designing problem such as regional pole placement constraints which provide more control over the satisfactory transient behaviour and closed-loop pole locations. In this paper, we present two examples which demonstrate the remarkable performance and broad applicability of the proposed approaches.

Argha, A, Su, SW, Savkin, A & Celler, BG 2018, 'Novel frameworks for the design of fault‐tolerant control using optimal sliding‐mode control', International Journal of Robust and Nonlinear Control, vol. 28, no. 8, pp. 3015-3032.
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SummaryThis paper describes 2 schemes for a fault‐tolerant control using a novel optimal sliding‐mode control, which can also be employed as actuator redundancy management for overactuated uncertain linear systems. By using the effectiveness level of the actuators in the performance indexes, 2 schemes for redistributing the control effort among the remaining (redundant or nonfaulty) set of actuators are constructed based on an ‐based optimal sliding‐mode control. In contrast to the current sliding‐mode fault‐tolerant control design methods, in these new schemes, the level of control effort required to maintain sliding is penalised. The proposed optimal sliding‐mode fault‐tolerant control design schemes are implemented in 2 stages. In the first stage, a state feedback gain is derived using an LMI‐based scheme that can assign a number of the closed‐loop eigenvalues to a known value whilst satisfying performance specifications. The sliding function matrix related to the particular state feedback derived in the first stage is obtained in the second stage. The difference between the 2 schemes proposed for the sliding‐mode fault‐tolerant control is that the second one includes a separate control allocation module, which makes it easier to apply actuator constraints to the problem. Moreover, it will be shown that, with the second scheme, we can deal with actuator faults or even failures without controller reconfiguration. We further discuss the advantages and disadvantages of the 2 schemes in more details. The effectiveness of the proposed schemes are illustrated with numerical examples.

Arias, M, Vink, J, de Gasperin, F, Salas, P, Oonk, JBR, van Weeren, RJ, van Amesfoort, AS, Anderson, J, Beck, R, Bell, ME, Bentum, MJ, Best, P, Blaauw, R, Breitling, F, Broderick, JW, Brouw, WN, Brüggen, M, Butcher, HR, Ciardi, B, de Geus, E, Deller, A, van Dijk, PCG, Duscha, S, Eislöffel, J, Garrett, MA, Grießmeier, JM, Gunst, AW, van Haarlem, MP, Heald, G, Hessels, J, Hörandel, J, Holties, HA, van der Horst, AJ, Iacobelli, M, Juette, E, Krankowski, A, van Leeuwen, J, Mann, G, McKay-Bukowski, D, McKean, JP, Mulder, H, Nelles, A, Orru, E, Paas, H, Pandey-Pommier, M, Pandey, VN, Pekal, R, Pizzo, R, Polatidis, AG, Reich, W, Röttgering, HJA, Rothkaehl, H, Schwarz, DJ, Smirnov, O, Soida, M, Steinmetz, M, Tagger, M, Thoudam, S, Toribio, MC, Vocks, C, van der Wiel, MHD, Wijers, RAMJ, Wucknitz, O, Zarka, P & Zucca, P 2018, 'Low-frequency radio absorption in Cassiopeia A', Astronomy & Astrophysics, vol. 612, pp. A110-A110.
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Context.Cassiopeia A is one of the best-studied supernova remnants. Its bright radio and X-ray emission is due to shocked ejecta. Cas A is rather unique in that the unshocked ejecta can also be studied: through emission in the infrared, the radio-active decay of44Ti, and the low-frequency free-free absorption caused by cold ionised gas, which is the topic of this paper.Aims.Free-free absorption processes are affected by the mass, geometry, temperature, and ionisation conditions in the absorbing gas. Observations at the lowest radio frequencies can constrain a combination of these properties.Methods.We used Low Frequency Array (LOFAR) Low Band Antenna observations at 30–77 MHz and Very Large Array (VLA)L-band observations at 1–2 GHz to fit for internal absorption as parametrised by the emission measure. We simultaneously fit multiple UV-matched images with a common resolution of 17″ (this corresponds to 0.25 pc for a source at the distance of Cas A). The ample frequency coverage allows us separate the relative contributions from the absorbing gas, the unabsorbed front of the shell, and the absorbed back of the shell to the emission spectrum. We explored the effects that a temperature lower than the ~100–500 K proposed from infrared observations and a high degree of clumping can have on the derived physical properties of the unshocked material, such as its mass and density. We also compiled integrated radio flux density measurements, fit for the absorption processes that occur in the radio band, and considered their effect on the secular decline of the source.Results.We find a mass in the unshocked ejecta ofM= 2.95 ± 0.48M⊙for an assumed gas temperatureofT

Armaghani, DJ, Faradonbeh, RS, Rezaei, H, Rashid, ASA & Amnieh, HB 2018, 'Settlement prediction of the rock-socketed piles through a new technique based on gene expression programming', Neural Computing and Applications, vol. 29, no. 11, pp. 1115-1125.
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Armaghani, DJ, Hasanipanah, M, Amnieh, HB & Mohamad, ET 2018, 'Feasibility of ICA in approximating ground vibration resulting from mine blasting', Neural Computing and Applications, vol. 29, no. 9, pp. 457-465.
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Asadabadi, MR, Saberi, M & Chang, E 2018, 'Targets of Unequal Importance Using the Concept of Stratification in a Big Data Environment', International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1373-1384.
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© 2017, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. The concept of stratification (CST) has recently been proposed as an innovative approach in problem solving. CST takes a recursive approach to solve problems. It considers a system which has to transition through states until it arrives to a state which belongs to a desired set of states, namely a target set. The states can be stratified by enlarging the target (absorbing adjacent states). Incremental enlargement is a means to identify possible paths to achieve the target. Such an enlargement can also be used to degrade the target when the original target is not reachable. Although the characteristics of the concept, such as incremental enlargement, enhance its potential application in robotics, artificial intelligence, and planning and monitoring, there is a major shortcoming in the approach, namely its inability to consider targets of unequal importance. This study considers two targets of unequal importance for the system in CST, labelled Bi-Objective CST model (BOCST). In comparison with the original proposed CST model in this research, a version of CST with finite states which is much easier to apply than the original CST is proposed, labelled fuzzy CST. Following that, a combination of Fuzzy CST and BOCST (FBO-CST) is proposed. The model is then employed to address a restaurant selection problem using data from Google. The example illustrates how the model should be applied in a big data environment. By defining finite state CST and considering targets of unequal importance, this study is expected to facilitate future applications of CST.

Asif, MB, Hai, FI, Dhar, BR, Ngo, HH, Guo, W, Jegatheesan, V, Price, WE, Nghiem, LD & Yamamoto, K 2018, 'Impact of simultaneous retention of micropollutants and laccase on micropollutant degradation in enzymatic membrane bioreactor', Bioresource Technology, vol. 267, pp. 473-480.
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Asif, MB, Hai, FI, Kang, J, van de Merwe, JP, Leusch, FDL, Price, WE & Nghiem, LD 2018, 'Biocatalytic degradation of pharmaceuticals, personal care products, industrial chemicals, steroid hormones and pesticides in a membrane distillation-enzymatic bioreactor', Bioresource Technology, vol. 247, pp. 528-536.
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© 2017 Elsevier Ltd Laccase-catalyzed degradation of a broad spectrum of trace organic contaminants (TrOCs) by a membrane distillation (MD)-enzymatic membrane bioreactor (EMBR) was investigated. The MD component effectively retained TrOCs (94–99%) in the EMBR, facilitating their continuous biocatalytic degradation. Notably, the extent of TrOC degradation was strongly influenced by their molecular properties. A significant degradation (above 90%) of TrOCs containing strong electron donating functional groups (e.g., hydroxyl and amine groups) was achieved, while a moderate removal was observed for TrOCs containing electron withdrawing functional groups (e.g., amide and halogen groups). Separate addition of two redox-mediators, namely syringaldehyde and violuric acid, further improved TrOC degradation by laccase. However, a mixture of both showed a reduced performance for a few pharmaceuticals such as primidone, carbamazepine and ibuprofen. Mediator addition increased the toxicity of the media in the enzymatic bioreactor, but the membrane permeate (i.e., final effluent) was non-toxic, suggesting an added advantage of coupling MD with EMBR.

Asikin-Mijan, N, Lee, HV, Juan, JC, Noorsaadah, AR, Ong, HC, Razali, SM & Taufiq-Yap, YH 2018, 'Promoting deoxygenation of triglycerides via Co-Ca loaded SiO 2 -Al 2 O 3 catalyst', Applied Catalysis A: General, vol. 552, pp. 38-48.
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Askari, G, Pour, AB, Pradhan, B, Sarfi, M & Nazemnejad, F 2018, 'Band Ratios Matrix Transformation (BRMT): A Sedimentary Lithology Mapping Approach Using ASTER Satellite Sensor', Sensors, vol. 18, no. 10, pp. 3213-3213.
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Remote sensing imagery has become an operative and applicable tool for the preparation of geological maps by reducing the costs and increasing the precision. In this study, ASTER satellite remote sensing data were used to extract lithological information of Deh-Molla sedimentary succession, which is located in the southwest of Shahrood city, Semnan Province, North Iran. A robust and effective approach named Band Ratio Matrix Transformation (BRMT) was developed to characterize and discriminate the boundary of sedimentary rock formations in Deh-Molla region. The analysis was based on the forward and continuous division of the visible-near infrared (VNIR) and the shortwave infrared (SWIR) spectral bands of ASTER with subsequent application of principal component analysis (PCA) for producing new transform datasets. The approach was implemented to ASTER spectral band ratios for mapping dominated mineral assemblages in the study area. Quartz, carbonate, and Al, Fe, Mg –OH bearing-altered minerals such as kaolinite, alunite, chlorite and mica were appropriately mapped using the BRMT approach. The results match well with geology map of the study area, fieldwork data and laboratory analysis. Accuracy assessment of the mapping result represents a reasonable kappa coefficient (0.70%) and appropriate overall accuracy (74.64%), which verified the robustness of the BRMT approach. This approach has great potential and capability for mapping sedimentary succession with diverse local–geological–physical characteristics around the world.

Asl, PF, Monjezi, M, Hamidi, JK & Armaghani, DJ 2018, 'Optimization of flyrock and rock fragmentation in the Tajareh limestone mine using metaheuristics method of firefly algorithm', Engineering with Computers, vol. 34, no. 2, pp. 241-251.
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Atiquzzaman, M & Kandasamy, J 2018, 'Robustness of Extreme Learning Machine in the prediction of hydrological flow series', Computers & Geosciences, vol. 120, pp. 105-114.
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Avilés-Ochoa, E, León-Castro, E, Perez-Arellano, LA & Merigó, JM 2018, 'Government transparency measurement through prioritized distance operators', Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2783-2794.
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© 2018 - IOS Press and the authors. All rights reserved. The prioritized induced probabilistic ordered weighted average distance (PIPOWAD) has been developed. This new operator is an extension of the ordered weighted average (OWA) operator that can be used in cases where we have two sets of data that want to be compared. Some of the main characteristics of this new operator are: 1) Not all the decision makers are equally important, so the information needs to be prioritized, 2) The information has a probability to occur and 3) The decision makers can change the importance of the information based in an induced variable. Additionally, characteristics and families of the PIPOWAD operator are presented. Finally, an application of the PIPOWAD operator in order to measure government transparency in Mexico is presented.

Awadallah, M, Tawadros, P, Walker, P & Zhang, N 2018, 'Comparative fuel economy, cost and emissions analysis of a novel mild hybrid and conventional vehicles', Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol. 232, no. 13, pp. 1846-1862.
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Mild hybrid vehicles have been explored as a potential pathway to reduce vehicle emissions cost-effectively. The use of manual transmissions to develop novel hybrid vehicles provides an alternate route to producing low cost electrified powertrains. In this paper, a comparative analysis examining a conventional vehicle and a mild hybrid electric vehicle is presented. The analysis considers fuel economy, capital and ongoing costs and environmental emissions, and includes developmental analysis and simulation using mathematical models. Vehicle emissions (nitrogen oxides, carbon monoxide and hydrocarbons) and fuel economy are computed, analysed and compared using a number of alternative driving cycles and their weighted combination. Different driver styles are also evaluated. Studying the relationship between the fuel economy and driveability, where driveability is addressed using fuel-economical gear shift strategies. Our simulation suggests the hybrid concept presented can deliver fuel economy gains of between 5 and 10%, as compared to the conventional powertrain.

Ayachit, A, Siwakoti, YP, Galigekere, VPN, Kazimierczuk, MK & Blaabjerg, F 2018, 'Steady-State and Small-Signal Analysis of A-Source Converter', IEEE Transactions on Power Electronics, vol. 33, no. 8, pp. 7118-7131.
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© 1986-2012 IEEE. This paper presents a detailed steady-state analysis and ac small-signal modeling of the power stage of pulse-width modulated A-source converter. The voltage and current waveforms along with their corresponding expressions describing the converter operation are presented in detail. The input-to-output and input-to-capacitor dc voltage transfer functions are determined. The minimum inductance required to ensure continuous conduction mode is derived. The expressions for the semiconductor devices stresses are also presented. The dc, averaged equivalent circuit is derived using the circuit averaging technique. A complete derivation of the small-signal model including the converter parasitic resistances are presented followed by the power stage transfer functions relevant to the capacitor voltage loop, such as: 1) duty cycle-to-capacitor voltage; and 2) input-to-capacitor voltage. In addition, the expressions for the network input impedance and output impedance are derived. Finally, experimental validations of the derived small-signal models are performed, both in frequency and time domain for a laboratory prototype of an A-source converter. The theoretical predictions were in good agreement with the experimental results over a wide range of frequencies.

Azeez, OS, Pradhan, B & Shafri, HZM 2018, 'Vehicular CO Emission Prediction Using Support Vector Regression Model and GIS', Sustainability, vol. 10, no. 10, pp. 3434-3434.
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Transportation infrastructures play a significant role in the economy as they provide accessibility services to people. Infrastructures such as highways, road networks, and toll plazas are rapidly growing based on changes in transportation modes, which consequently create congestions near toll plaza areas and intersections. These congestions exert negative impacts on human health and the environment because vehicular emissions are considered as the main source of air pollution in urban areas and can cause respiratory and cardiovascular diseases and cancer. In this study, we developed a hybrid model based on the integration of three models, correlation-based feature selection (CFS), support vector regression (SVR), and GIS, to predict vehicular emissions at specific times and locations on roads at microscale levels in an urban areas of Kuala Lumpur, Malaysia. The proposed model comprises three simulation steps: first, the selection of the best predictors based on CFS; second, the prediction of vehicular carbon monoxide (CO) emissions using SVR; and third, the spatial simulation based on maps by using GIS. The proposed model was developed with seven road traffic CO predictors selected via CFS (sum of vehicles, sum of heavy vehicles, heavy vehicle ratio, sum of motorbikes, temperature, wind speed, and elevation). Spatial prediction was conducted based on GIS modelling. The vehicular CO emissions were measured continuously at 15 min intervals (recording 15 min averages) during weekends and weekdays twice per day (daytime, evening-time). The model’s results achieved a validation accuracy of 80.6%, correlation coefficient of 0.9734, mean absolute error of 1.3172 ppm and root mean square error of 2.156 ppm. In addition, the most appropriate parameters of the prediction model were selected based on the CFS model. Overall, the proposed model is a promising tool for traffic CO assessment on roads.

Aziz, N, Rasekh, H, Mirzaghorbanali, A, Yang, G, Khaleghparast, S & Nemcik, J 2018, 'An Experimental Study on the Shear Performance of Fully Encapsulated Cable Bolts in Single Shear Test', Rock Mechanics and Rock Engineering, vol. 51, no. 7, pp. 2207-2221.
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A set of single shear tests on fully encapsulated cable bolts was carried out using a newly developed and integrated Megabolt single shear apparatus. The instrument is designed to determine the pure shear strength of cable bolts where there is no contact between the host body faces during the shearing process. Eight different types of cable bolt were encapsulated in 40 MPa concrete cylinders, using Stratabinder HS grout. Prior to encapsulation, cable bolts were pretensioned at the desired value using a manual pretensioner. Effects of surface profile, pretension value and debonding on shear strength of cable bolts were investigated. It was found that the shear strength of spiral/indented cable bolts was lower than that of plain cable bolts. Increasing the pretension load decreased the peak shear load of cable bolts. In general, no debonding was observed for spiral/indented cable bolts during shear testing; however, all tested plain cable bolts were debonded.

Azizivahed, A, Barani, M, Razavi, S, Ghavidel, S, Li, L & Zhang, J 2018, 'Energy storage management strategy in distribution networks utilised by photovoltaic resources', IET Generation, Transmission & Distribution, vol. 12, no. 21, pp. 5627-5638.
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Large penetration of electrical energy storage (EES) units and renewable energy resources in distribution systems can help to improve network profiles (e.g. bus voltage and branch current profiles), and to reduce operational cost as well as power losses. On the other hand, unsecure system operation as a result of involving these units is another challenge to network operators. Therefore, establishing a trade‐off between operational cost and security is very important. This study presents a new approach to determine the optimal charging/discharging schedule of EES units in distribution systems by employing multi‐objective optimisation methods, which will effectively reduce operational cost and enhance distribution network security. In this regard, a voltage stability index (VSI) is converted into a security index to improve the radial network security. This VSI index is treated as a separate objective function, and a multi‐objective strategy is implemented to obtain a set of non‐dominated solutions instead of a single optimal solution, which simultaneously minimise both of the operational cost and security index. In order to assess the effectiveness and applicability of the proposed method, it is applied to IEEE standard 33‐bus and 136‐bus distribution test systems, and then the obtained results are compared with those of existing methodologies.

Azuma, K, Sun, J, Choo, Y, Rokhlenko, Y, Dwyer, JH, Schweitzer, B, Hayakawa, T, Osuji, CO & Gopalan, P 2018, 'Self-Assembly of an Ultrahigh-χ Block Copolymer with Versatile Etch Selectivity', Macromolecules, vol. 51, no. 16, pp. 6460-6467.
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We report the successful synthesis of previously inaccessible poly(3-hydroxystyrene)-block-poly(dimethylsiloxane) (P3HS-b-PDMS) block copolymers (BCPs) with varying volume fractions, molecular weights, and narrow dispersities by sequential living anionic polymerization. The chemical structure and molecular weight were fully characterized by 1H NMR and gel permeation chromatography. The BCP phase behavior was investigated using small-angle X-ray scattering (SAXS) and transmission electron microscopy. Temperature-resolved SAXS measurements from symmetric disordered sample were used to determine the interaction parameter (χ) using mean-field theory. The results provide an estimate for interaction parameter, χHS/DMS(T) = 33.491/T + 0.3126, with an upper bound value of 0.39 at 150 °C. The calculated χ for P3HS-b-PDMS is approximately 4 times higher than that observed in a commonly studied high-χ system, PS-b-PDMS. The ultrahigh interaction parameter observed here affords the formation of well-ordered materials at remarkably low molecular weight. The presence of both PDMS and P3HS provides significant versatility in terms of etch selectivity, while the hydroxystyrene domain offers additional functionality as it can be exploited for immobilizing functional organic moieties.

Baartman, JEM, Temme, AJAM & Saco, PM 2018, 'The effect of landform variation on vegetation patterning and related sediment dynamics', Earth Surface Processes and Landforms, vol. 43, no. 10, pp. 2121-2135.
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AbstractSemi‐arid ecosystems are often spatially self‐organized in typical patterns of vegetation bands with high plant cover interspersed with bare soil areas, also known as ‘tiger bush’. In modelling studies, most often, straight planar slopes were used to analyse vegetation patterning. The effect of slope steepness has been investigated widely, and some studies investigated the effects of microtopography and hillslope orientation. However, at the larger catchment scale, the overall form of the landscape may affect vegetation patterning and these more complex landscapes are much more prevalent than straight slopes. Hence, our objective was to determine the effect of landform variation on vegetation patterning and sediment dynamics. We linked two well‐established models that simulate (a) plant growth, death and dispersal of vegetation, and (b) erosion and sedimentation dynamics. The model was tested on a straight planar hillslope and then applied to (i) a set of simple synthetic topographies with varying curvature and (ii) three more complex, real‐world landscapes of distinct morphology. Results show banded vegetation patterning on all synthetic topographies, always perpendicular to the slope gradient. Interestingly, we also found that movement of bands – a debated phenomenon – seems to be dependent on curvature. Vegetation banding was simulated on the slopes of the alluvial fan and along the valley slopes of the dissected and rolling landscapes. In all landscapes, local valleys developed a full vegetation cover induced by water concentration, which is consistent with observations worldwide. Finally, banded vegetation patterns were found to reduce erosion significantly as compared to other vegetation configurations. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

Baba, AA, Hashmi, RH, Esselle, KP & Weily, AR 2018, 'Improving radiation performance of extremely truncated RCAs through near‐field analysis', IET Microwaves, Antennas & Propagation, vol. 12, no. 12, pp. 1954-1959.
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This paper studies the cause of low‐broadside directivity and high sidelobe levels (SLLs) in compact resonant‐cavity antennas (RCAs) (footprint ). An approach to determine an optimal near‐field distribution to significantly improve the broadside directivity and SLL of RCAs is presented. A near‐field to far‐field transformation routine developed in MATLAB is used to study the individual effects of amplitude and phase distributions, above the partially reflecting superstrate (PRS) of RCAs. Unlike the direct use of a full‐wave simulator design, this new approach allows the designers to understand the individual effects of amplitude and phase distributions in the radiating near‐field region, on the broadside directivity and on the SLL in the far‐field radiation pattern. A method to realise a desired complex near‐field distribution is demonstrated, using a dielectric PRS. The RCA with the new PRS showed a significant improvement of 5.0 and 6.4 dB in the broadside directivity and SLL, respectively, compared with a uniform PRS without compromising the footprint and profile of the antenna. The predictions of MATLAB are validated using computer simulation technology (CST) microwave studio (MWS) and experiments

Baba, AA, Hashmi, RM, Esselle, KP & Weily, AR 2018, 'Compact High-Gain Antenna With Simple All-Dielectric Partially Reflecting Surface', IEEE Transactions on Antennas and Propagation, vol. 66, no. 8, pp. 4343-4348.
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Babaee, M & Castel, A 2018, 'Chloride diffusivity, chloride threshold, and corrosion initiation in reinforced alkali-activated mortars: Role of calcium, alkali, and silicate content', Cement and Concrete Research, vol. 111, pp. 56-71.
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The aim of this study is to investigate systematically the chloride diffusivity and chloride threshold of a wide range of calcium-rich and fly ash-dominated alkali-activated samples in light of their compositional differences. To this end, the effects of various fly ash (FA)-to-slag ratios, of alkali concentrations and of silicate content in the activator were investigated. The electrochemical aspects of the passive samples were also assessed. Results show the prominent role of calcium in the matrix to reduce the chloride diffusivity. While higher alkali concentration increased the porosity and chloride diffusivities in general, lower modulus ratios provided considerably better performance in the FA-dominated samples. Chloride threshold values range between 0.19 (wt% binder mass) for calcium-rich mortars fabricated at low levels of alkalinities and 0.69 for FA-dominated mortars fabricated with highly alkaline activators. Half-cell potential and polarization resistance of alkali-activated samples were in general lower than their Portland cement counterparts.

Babaee, M & Castel, A 2018, 'Water vapor sorption isotherms, pore structure, and moisture transport characteristics of alkali-activated and Portland cement-based binders', Cement and Concrete Research, vol. 113, pp. 99-120.
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Babaee, M, Khan, MSH & Castel, A 2018, 'Passivity of embedded reinforcement in carbonated low-calcium fly ash-based geopolymer concrete', Cement and Concrete Composites, vol. 85, pp. 32-43.
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Babar, A, Bunker, D & Qumer Gill, A 2018, 'Investigating the Relationship between Business Analysts’ Competency and IS Requirements Elicitation: A Thematic-analysis Approach', Communications of the Association for Information Systems, vol. 42, no. 1, pp. 334-362.
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© 2018 by the Association for Information Systems. Researchers and practitioners have consistently reported poor requirements elicitation (RE) as one of the major reasons for information system (IS) project failures. In the last two decades, RE research and practice have focused predominantly on developing tools and techniques for business analysts (BAs) to use and improve RE; however, they have paid little attention to the importance of the competency of the BAs involved in RE. We investigate the relationship between the BAs’ competency and RE through an exploratory study. We applied a thematic network analysis approach, along with a four-stage qualitative data-analysis process, to discover four business view and six system view themes and their relationships to BAs’ competency. Our results indicate that senior, intermediate, and junior BAs performed similarly in selecting stakeholders’ viewpoints and collecting requirements from them; however, senior BAs focused more on high-level requirements than the low-level technical requirements of the system. The results suggest that BAs’ competency play a significant role in RE and that organizations that clearly define BAs’ competency can help them to identify the right BA for the right job.

Babbush, R, Berry, DW, Sanders, YR, Kivlichan, ID, Scherer, A, Wei, AY, Love, PJ & Aspuru-Guzik, A 2018, 'Exponentially more precise quantum simulation of fermions in the configuration interaction representation', Quantum Science and Technology, vol. 3, no. 1, pp. 015006-015006.
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We present a quantum algorithm for the simulation of molecular systems that is asymptotically more efficient than all previous algorithms in the literature in terms of the main problem parameters. As in Babbush et al (2016 New Journal of Physics 18, 033032), we employ a recently developed technique for simulating Hamiltonian evolution using a truncated Taylor series to obtain logarithmic scaling with the inverse of the desired precision. The algorithm of this paper involves simulation under an oracle for the sparse, first-quantized representation of the molecular Hamiltonian known as the configuration interaction (CI) matrix. We construct and query the CI matrix oracle to allow for on-the-fly computation of molecular integrals in a way that is exponentially more efficient than classical numerical methods. Whereas second-quantized representations of the wavefunction require qubits, where N is the number of single-particle spin-orbitals, the CI matrix representation requires qubits, where is the number of electrons in the molecule of interest. We show that the gate count of our algorithm scales at most as .

Bach, Q-V, Le, VT, Yoon, YS, Bui, XT, Chung, W, Chang, SW, Ngo, HH, Guo, W & Nguyen, DD 2018, 'A new hybrid sewage treatment system combining a rolled pipe system and membrane bioreactor to improve the biological nitrogen removal efficiency: A pilot study', Journal of Cleaner Production, vol. 178, pp. 937-946.
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© 2018 Elsevier Ltd A new hybrid pilot plant configuration based on a modularized rolled pipe system (RPS) combined with a submerged flat sheet membrane bioreactor (MBR) was investigated to enhance the sewage treatment and membrane performance. The system was operated under actual conditions for more than four months, that is, at a constant flow rate of 30 m³/d and with two internal recycling ratios. The results indicate that the hybrid system produces an excellent effluent quality and considerably mitigated membrane fouling. The average concentrations of SS, COD, TN, NH4+-N, NO3−-N, and PO43--P remained below 2.81, 8.29, 8.77, 0.15, 8.17, and 1.49 mg/L, respectively. It was estimated that the periodic chemical cleaning of the membrane could be extended to approximately six months. The MBR and RPS can virtually complete nitrification and denitrification, respectively. The highest average denitrification rate of the RPS is 116.95 mg NO3-N/(g MLVSS d), with a hydraulic retention time of 1.05 h. Therefore, the RPS–MBR hybrid system has potential to improve the sewage treatability. The emerging RPS technique can obtain high rates of denitrification coupled with a compact design, ease of installation, and small footprint.

Bah, AO, Qin, P-Y, Ziolkowski, RW, Cheng, Q & Guo, YJ 2018, 'Realization of an Ultra-thin Metasurface to Facilitate Wide Bandwidth, Wide Angle Beam Scanning', Scientific Reports, vol. 8, no. 1.
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AbstractA wide bandwidth, ultra-thin, metasurface is reported that facilitates wide angle beam scanning. Each unit cell of the metasurface contains a multi-resonant, strongly-coupled unequal arm Jerusalem cross element. This element consists of two bent-arm, orthogonal, capacitively loaded strips. The wide bandwidth of the metasurface is achieved by taking advantage of the strong coupling within and between its multi-resonant elements. A prototype of the proposed metasurface has been fabricated and measured. The design concept has been validated by the measured results. The proposed metasurface is able to alleviate the well-known problem of impedance mismatch caused by mutual coupling when the main beam of an array is scanned. In order to validate the wideband and wide scanning ability of the proposed metasurface, it is integrated with a wideband antenna array as a wide angle impedance matching element. The metasurface-array combination facilitates wide angle scanning over a 6:1 impedance bandwidth without the need for bulky dielectrics or multi-layered structures.

Bai, F, Vidal-Calleja, T & Huang, S 2018, 'Robust Incremental SLAM Under Constrained Optimization Formulation', IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 1207-1214.
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© 2016 IEEE. In this letter, we propose a constrained optimization formulation and a robust incremental framework for the simultaneous localization and mapping problem (SLAM). The new SLAM formulation is derived from the nonlinear least squares (NLS) formulation by mathematically formulating loop-closure cycles as constraints. Under the constrained SLAM formulation, we study the robustness of an incremental SLAM algorithm against local minima and outliers as a constraint/loop-closure cycle selection problem. We find a constraint metric that can predict the objective function growth after including the constraint. By the virtue of the constraint metric, we select constraints into the incremental SLAM according to a least objective function growth principle to increase robustness against local minima and perform χ 2 difference test on the constraint metric to increase robustness against outliers. Finally, using sequential quadratic programming (SQP) as the solver, an incremental SLAM algorithm (iSQP) is proposed. Experimental validations are provided to illustrate the accuracy of the constraint metric and the robustness of the proposed incremental SLAM algorithm. Nonetheless, the proposed approach is currently confined to datasets with sparse loop-closures due to its computational cost.

Bai, L, Wang, J, Ma, X & Lu, H 2018, 'Air Pollution Forecasts: An Overview', International Journal of Environmental Research and Public Health, vol. 15, no. 4, pp. 780-780.
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Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

Baidya, R, Aguilera, RP, Acuna, P, Vazquez, S & Mouton, HDT 2018, 'Multistep Model Predictive Control for Cascaded H-Bridge Inverters: Formulation and Analysis', IEEE Transactions on Power Electronics, vol. 33, no. 1, pp. 876-886.
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© 1986-2012 IEEE. In this paper, a suitable long prediction horizon (multistep) model predictive control (MPC) formulation for cascaded H-bridge inverters is proposed. The MPC is formulated to include the full steady-state system information in terms of output current and output voltage references. Generally, basic single-step predictive controllers only track the current references. As a distinctive feature, the proposed MPC also tracks the control input references, which in this case is designed to minimize the common-mode voltage (CMV). This allows the controller to address both output current and CMV targets in a single optimization. To reduce the computational effort introduced by a long prediction horizon implementation, the proposed MPC formulation is transformed into an equivalent optimization problem that can be solved by a fast sphere decoding algorithm. Moreover, the benefits of including the control input references in the proposed formulation are analyzed based on this equivalent optimization problem. This analysis is key to understand how the proposed MPC formulation can handle both control targets. Experimental results show that the proposal provides an improved steady-state performance in terms of current distortion, inverter voltages symmetry, and CMV.

Baier-Fuentes, H, Cascón-Katchadourian, J, Sánchez, ÁM, Herrera-Viedma, E & Merigó, J 2018, 'A Bibliometric Overview of the International Journal of Interactive Multimedia and Artificial Intelligence', International Journal of Interactive Multimedia and Artificial Intelligence, vol. 5, no. 3, pp. 9-9.
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Bajan, S, Johnston, M & Hutvagner, G 2018, 'Destabilisation of Argonaute 2 generates a truncated protein: halfAgo2', Matters.
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The Argonaute 2 (Ago2) protein is an essential effector protein in miRNA-mediated mechanisms that regulate gene expression. Ago2 directly binds to the miRNA, forming the RISC. RISC function is critical to controlling key biological processes and when dysregulated can result in disease pathogenesis. Understanding Ago2 protein stability and turnover will further our understanding in how RISC function is regulated. In human cells, we discovered a previously unidentified ~55 kDa protein that is a truncated form of Ago2, that is formed from proteolytic cleavage of the full length Ago2 protein. Further experiments are needed to determine (i) the detailed mechanism that forms halfAgo2 (ii) the cellular or environmental triggers or stresses that initiate halfAgo2 production and (iii) if halfAgo2 has a potentially new role in gene regulation.

Balathanigaimani, MS, Haider, MB, Jha, D, Kumar, R, Lee, SJ, Shim, WG, Shon, HK, Kim, SC & Moon, H 2018, 'Nanostructured Biomass Based Carbon Materials from Beer Lees for Hydrogen Storage', Journal of Nanoscience and Nanotechnology, vol. 18, no. 3, pp. 2196-2199.
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The present work describes the preparation of carbon materials from beer lees and their hydrogen adsorption abilities. Activated carbons (ACs) from beer lees were prepared through chemical activation using potassium hydroxide as an activating agent. The low temperature nitrogen adsorption isotherm studies on prepared ACs were conducted at 77 K to determine their physical properties and adsorption energy distribution. The beer lees based carbons have energetically heterogeneous surfaces and high surface area ranging from 1927–2408 m2/g. ACs prepared in this study show the gravimetric hydrogen adsorption capacity of 2.43–2.92 wt% depending on their physical properties

Bano, M, Zowghi, D & Rimini, FD 2018, 'User Involvement in Software Development: The Good, the Bad, and the Ugly.', IEEE Softw., vol. 35, no. 6, pp. 8-11.
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© 2018 IEEE. Merely involving the users in software development won't guarantee system success. User involvement is a complex, multifaceted phenomenon with a good side, a bad side, and an ugly side. A better, deeper understanding of those sides can help project managers develop responsive strategies for increasing user involvement's effectiveness.

Bano, M, Zowghi, D, Kearney, M, Schuck, S & Aubusson, P 2018, 'Mobile learning for science and mathematics school education: A systematic review of empirical evidence.', Comput. Educ., vol. 121, pp. 30-58.
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© 2018 Elsevier Ltd The ubiquity, flexibility, ease of access and diverse capabilities of mobile technologies make them valuable and a necessity in current times. However, they are under-utilized assets in mathematics and science school education. This article analyses the high quality empirical evidence on mobile learning in secondary school science and mathematics education. Our study employed a Systematic Literature Review (SLR) using well-accepted and robust guidelines. The SLR resulted in the detailed analysis of 49 studies (60 papers) published during 2003–2016. Content and thematic analyses were used to ascertain pedagogical approaches, methodological designs, foci, and intended and achieved outcomes of the studies. The apps and technologies used in these studies were further classified for domain, type and context of use. The review has highlighted gaps in existing literature on the topic and has provided insights that have implications for future research.

Bao, L, Li, Q, Lu, P, Lu, J, Ruan, T & Zhang, K 2018, 'Execution anomaly detection in large-scale systems through console log analysis', Journal of Systems and Software, vol. 143, pp. 172-186.
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Baral, P, Rujikiatkamjorn, C, Indraratna, B & Kelly, R 2018, 'Radial consolidation characteristics of soft undisturbed clay based on large specimens', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1037-1045.
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Bargi, A, Xu, RYD & Piccardi, M 2018, 'AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 9, pp. 3953-3968.
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© 2012 IEEE. Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive 'learning rate' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.

Barker, RA, Eager, D & Sharwood, LN 2018, 'Ensuring safety in public playgrounds is everybody's business.', Med J Aust, vol. 210, no. 1, pp. 9-11.
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When an injury occurs in a children’s playground, who is responsible? Media headlines1,2 have highlighted risks associated with a recently opened playground in north-western Sydney. The playground’s giant tube slide was closed following a spate of injuries to both adult and child patrons. With injuries described as “horrific”, the media questioned “how the 30 m long, 14 m tall slide passed safety rules”.1 While playground injuries are fairly common,3 there are specific multilevel responsibilities required to balance the importance of play and physical activity with mitigation of injury risk. In this article, we review the role of standards in industry governance and injury prevention.

Barnet, MB, Blinman, P, Cooper, W, Boyer, MJ, Kao, S & Goodnow, CC 2018, 'Understanding Immune Tolerance of Cancer: Re‐Purposing Insights from Fetal Allografts and Microbes', BioEssays, vol. 40, no. 8.
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Cancer cells seem to exploit mechanisms that evolve as part of physiological tolerance, which is a complementary and often beneficial form of defense. The study of physiological systems of tolerance can therefore provide insights into the development of a state of host tolerance of cancer, and how to break it. Analysis of these models has the potential to improve our understanding of existing immunological therapeutic targets, and help to identify future targets and rational therapeutic combinations. The treatment of cancer with immune checkpoint inhibitors aims to reverse the progression to tolerance of cancer, and achieve an immunogenic, rather than tolerogenic, homeostasis. Broadening the efficacy and durability of checkpoint inhibitors focuses on reversing tolerance and stimulating immunogenicity in the cancer, host, and environment. Two examples of important physiological states of tolerance that may inform tolerance of cancer are microbial infection and placental reproduction. These states of tolerance result from bilateral shaping of host and non‐self, akin to immunoediting in cancer, and offer reliable models to study the immune tolerance paradigm.

Barnet, MB, Zielinski, RR, Warby, A, Lewis, CR & Kao, S 2018, 'Pseudoprogression Associated with Clinical Deterioration and Worsening Quality of Life in Malignant Pleural Mesothelioma', Journal of Thoracic Oncology, vol. 13, no. 1, pp. e1-e2.
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Basack, S & Nimbalkar, S 2018, 'Measured and Predicted Response of Pile Groups in Soft Clay Subjected to Cyclic Lateral Loading', International Journal of Geomechanics, vol. 18, no. 7, pp. 04018073-04018073.
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© 2018 American Society of Civil Engineers. Major offshore and onshore structures, including transport corridors and high-rise buildings, resting on soft compressible clays are often supported by pile foundations. Apart from the usual vertical loading from the superstructures, these piles are usually subjected to large cyclic loads arising from the actions of waves, ship impacts, or moving vehicles. Under such circumstances, vertical and lateral modes of cyclic loading are predominant and affect overall stability. Such repetitive loading on piles leads to reversal of axial stresses in the adjacent soft clay, initiating progressive degradation in soil strength and stiffness that deteriorates the pile capacity with unacceptable displacements. Although several studies have been carried out to investigate the response of a single pile, a detailed investigation on a pile group in soft soil subjected to cyclic lateral loading, which is of immense practical interest to field engineers, had yet to be conducted. In this paper, extensive laboratory model tests with steel-pipe-pile groups in soft cohesive soil were conducted followed by the development of a numerical model that was based on a two-dimensional (2D) dynamic finite-element (FE) approach. The degradation of both axial and lateral capacities of the pile group and the pattern of the degradation with variations in the cyclic-loading parameters were studied. Comparisons of the experimental data with the computed results validated the numerical analysis. The study indicates that both the axial and lateral pile capacities and displacements were significantly influenced by the cyclic-loading parameters (number of cycles, frequency, and amplitude). Relevant design recommendations are presented.

Basack, S, Indraratna, B & Rujikiatkamjorn, C 2018, 'Effectiveness of stone column reinforcement for stabilizing soft ground with reference to transport infrastructure', Geotechnical Engineering, vol. 49, no. 1, pp. 8-14.
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The use of stone columns for soft soil stabilization has numerous advantages compared to other methods. There are many factors controlling performance of stone columns including column geometry and particle morphology. The reinforced soft ground supporting transport infrastructure like the railways and highways is subjected to cyclic loading, usually initiating a partially drained condition. The study reveals that the stone columns are more effective in mitigating the built up of cyclic excess pore water pressure compared to conventional vertical drains. This paper presents a brief overview on the rigorous theoretical and experimental studies carried out by the Authors to investigate the effectiveness of stone column reinforcement for stabilizing soft ground with particular reference to transport infrastructure.

Basack, S, Indraratna, B, Rujikiatkamjorn, C & Siahaan, F 2018, 'Closure to “Modeling the Stone Column Behavior in Soft Ground with Special Emphasis on Lateral Deformation” by Sudip Basack, Buddhima Indraratna, Cholachat Rujikiatkamjorn, and Firman Siahaan', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 5, pp. 07018008-07018008.
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Basack, S, Siahaan, F, Indraratna, B & Rujikiatkamjorn, C 2018, 'Stone Column–Stabilized Soft-Soil Performance Influenced by Clogging and Lateral Deformation: Laboratory and Numerical Evaluation', International Journal of Geomechanics, vol. 18, no. 6, pp. 04018058-04018058.
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Bayuaji, R, Sigit Darmawan, M, Husin, NA, Anugraha, RB, Budipriyanto, A & Stewart, MG 2018, 'Corrosion damage assessment of a reinforced concrete canal structure of power plant after 20 years of exposure in a marine environment: A case study', Engineering Failure Analysis, vol. 84, pp. 287-299.
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Chloride attack is the primary cause of corrosion problem of concrete structures operate in marine environment. Therefore, concrete structures operate in such environment cannot escape from this corrosion related problem. This paper describes assessment of a reinforced concrete canal structure of power plant after 20 years of exposure in a marine environment. The work covers visual inspection of the structure, on-site and laboratory tests of the structure, analyses the current structural strength based on the tests, and proposing repair and/or strengthening for weak elements. Strength prediction is carried out using average and worst case scenarios. The strength calculations assuming average case scenario shows that by 2025 all the canal have no strength reduction due to corrosion. Calculation using the worst case scenario shows that all the canal by 2025 still comply with the limits specified in Indonesian Concrete Code, even though their strength has been reduced due to corrosion of the reinforcement.

Bazaz, SR, Mehrizi, AA, Ghorbani, S, Vasilescu, S, Asadnia, M & Warkiani, ME 2018, 'A hybrid micromixer with planar mixing units', RSC Advances, vol. 8, no. 58, pp. 33103-33120.
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Taguchi-optimized “hybrid micromixer” has been proposed which can be utilized in a wide range of chemical and biological applications.

Beck, D, Thoms, JAI, Palu, C, Herold, T, Shah, A, Olivier, J, Boelen, L, Huang, Y, Chacon, D, Brown, A, Babic, M, Hahn, C, Perugini, M, Zhou, X, Huntly, BJ, Schwarzer, A, Klusmann, J-H, Berdel, WE, Wörmann, B, Büchner, T, Hiddemann, W, Bohlander, SK, To, LB, Scott, HS, Lewis, ID, D'Andrea, RJ, Wong, JWH & Pimanda, JE 2018, 'A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients', Leukemia, vol. 32, no. 2, pp. 263-272.
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© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Prognostic gene expression signatures have been proposed as clinical tools to clarify therapeutic options in acute myeloid leukemia (AML). However, these signatures rely on measuring large numbers of genes and often perform poorly when applied to independent cohorts or those with older patients. Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulators of cell identity and oncogenesis, but knowledge of their utility as prognostic markers in AML is limited. Here we analyze transcriptomic data from multiple cohorts of clinically annotated AML patients and report that (i) microarrays designed for coding gene expression can be repurposed to yield robust lincRNA expression data, (ii) some lincRNA genes are located in close proximity to hematopoietic coding genes and show strong expression correlations in AML, (iii) lincRNA gene expression patterns distinguish cytogenetic and molecular subtypes of AML, (iv) lincRNA signatures composed of three or four genes are independent predictors of clinical outcome and further dichotomize survival in European Leukemia Net (ELN) risk groups and (v) an analytical tool based on logistic regression analysis of quantitative PCR measurement of four lincRNA genes (LINC4) can be used to determine risk in AML.

Belhaj, D, Athmouni, K, Ahmed, MB, Aoiadni, N, El Feki, A, Zhou, JL & Ayadi, H 2018, 'Polysaccharides from Phormidium versicolor (NCC466) protecting HepG2 human hepatocellular carcinoma cells and rat liver tissues from cadmium toxicity: Evidence from in vitro and in vivo tests', International Journal of Biological Macromolecules, vol. 113, pp. 813-820.
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© 2018 Elsevier B.V. The in vitro antioxidant, cytotoxic and cytoprotective properties and in vivo hepatoprotective activities of crude polysaccharides extracted from cyanobacteria Phormidim versicolor NCC466 (CFv-PS) were investigated. The CFv-PS, identified as heteropolysaccharides with molecular weight of 63.79 kDa, exhibited relatively strong antioxidant activity, in a concentration-depended manner, in vitro assays. Additionally, CFv-PS did not induce cytotoxic effect on HepG2 human hepatocellular carcinoma cells within the range of tested concentrations (25–150 μg·mL−1) while preventing them against Cd. Moreover, in rats subjected to Cd-induced hepatotoxicity, CFv-PS pretreatment significantly (P < 0.05) reduced the level of ALAT, ASAT, biliburin, MDA, protein carbonyl and DNA damage, and markedly increased enzyme activities in liver tissues. These findings suggest that the cyanobacteria Phormidium versicolor is a potential source of natural products possessing antioxidant, cytoprotective and hepatoprotective properties.

Bellezoni, RA, Sharma, D, Villela, AA & Pereira Junior, AO 2018, 'Water-energy-food nexus of sugarcane ethanol production in the state of Goiás, Brazil: An analysis with regional input-output matrix', Biomass and Bioenergy, vol. 115, pp. 108-119.
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© 2018 Elsevier Ltd Concerns about impacts of biomass growth for biofuel production emphasize the importance of planning energy crops expansion considering land, water, food and biodiversity. Brazil is the second largest ethanol producer worldwide and sugarcane is cultivated in many regions, including the Brazilian Cerrado (a Savannah-type biome). This paper analyses the impacts of first-generation sugarcane expansion in the Paranaíba basin (Goiás State), focusing on how future demand for ethanol could affect local resources availability. The study area is a sugarcane expansion frontier in Brazil, thus, the Cerrado biome should be focus of research considering competition for land and water uses. An economic-ecologic Input-Output (IO) framework was applied to develop a water-energy-food (WEF) nexus analysis. The Goiás’ IO table was expanded to assess water, energy and land uses, GHG emissions and employment levels through six different ethanol supply scenarios. Results show that if sugarcane expansion projected to 2030 considers the Goiás’ extended IO structure for the year 2008, it should cause little impact on land and water availability in the state, due to both the ample availability of suitable pasturelands for sugarcane expansion as well as water in most of the Paranaíba basin. The WEF nexus analysis is a valuable tool on guiding the sustainable management of natural resources considering water, energy, land use and GHG emissions as goals to the same policy. In particular, the hybrid extended IO-WEF nexus framework is useful to design effective biofuel policies, collectively addressing impacts on environmental, social and economic spheres, in a local or broader context.

Bengua, JA, Tuan, HD, Duong, TQ & Poor, HV 2018, 'Joint Sensor and Relay Power Control in Tracking Gaussian Mixture Targets by Wireless Sensor Networks', IEEE Transactions on Signal Processing, vol. 66, no. 2, pp. 492-506.
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© 2017 IEEE. This paper considers a wireless sensor network for locating a static target or tracking a dynamic target, which is characterized a priori by a Gaussian mixture distribution. An amplify- and-forward relay node acts as a wireless bridge in relaying the sensor’s independent observations of the target to a fusion center (FC). Joint power allocation is considered for the sensors and relay to optimize a Bayesian filter, which is deployed at the FC for a global estimate of the target. The mean squared error of the Bayesian filter is already computationally intractable for fixed sensor and relay transmitter power, so power allocation to minimize its mean squared error is a very challenging problem. In this paper, the problem is addressed by an iterative procedure of very low computational complexity. Simulations are provided to support the efficiency of our proposed power allocation.

Berry, DW, Kieferová, M, Scherer, A, Sanders, YR, Low, GH, Wiebe, N, Gidney, C & Babbush, R 2018, 'Improved techniques for preparing eigenstates of fermionic Hamiltonians', npj Quantum Information, vol. 4, no. 1.
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AbstractModeling low energy eigenstates of fermionic systems can provide insight into chemical reactions and material properties and is one of the most anticipated applications of quantum computing. We present three techniques for reducing the cost of preparing fermionic Hamiltonian eigenstates using phase estimation. First, we report a polylogarithmic-depth quantum algorithm for antisymmetrizing the initial states required for simulation of fermions in first quantization. This is an exponential improvement over the previous state-of-the-art. Next, we show how to reduce the overhead due to repeated state preparation in phase estimation when the goal is to prepare the ground state to high precision and one has knowledge of an upper bound on the ground state energy that is less than the excited state energy (often the case in quantum chemistry). Finally, we explain how one can perform the time evolution necessary for the phase estimation based preparation of Hamiltonian eigenstates with exactly zero error by using the recently introduced qubitization procedure.

Besa, C, Wagner, M, Lo, G, Gordic, S, Chatterji, M, Kennedy, P, Stueck, A, Thung, S, Babb, J, Smith, A & Taouli, B 2018, 'Detection of liver fibrosis using qualitative and quantitative MR elastography compared to liver surface nodularity measurement, gadoxetic acid uptake, and serum markers', Journal of Magnetic Resonance Imaging, vol. 47, no. 6, pp. 1552-1561.
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BackgroundMultiparametric magnetic resonance imaging (mpMRI) combining different techniques such as MR elastography (MRE) has emerged as a noninvasive approach to diagnose and stage liver fibrosis with high accuracy allowing for anatomical and functional information.PurposeTo assess the diagnostic performance of mpMRI including qualitative and quantitative assessment of MRE, liver surface nodularity (LSN) measurement, hepatic enhancement ratios postgadoxetic acid, and serum markers (APRI, FIB‐4) for the detection of liver fibrosis.Study TypeIRB‐approved retrospective.SubjectsEighty‐three adult patients.Field Strength/Sequence1.5T and 3.0T MR systems. MRE and T1‐weighted postgadoxetic acid sequences.AssessmentTwo independent observers analyzed qualitative color‐coded MRE maps on a scale of 0–3. Regions of interest were drawn to measure liver stiffness on MRE stiffness maps and on pre‐ and postcontrast T1‐weighted images to measure hepatic enhancement ratios. Software was used to generate LSN measurements. Histopathology was used as the reference standard for diagnosis of liver fibrosis in all patients.Statistical TestsA multivariable logistic analysis was performed to identify independent predictors of liver fibrosis. Receiver operating characteristic (ROC) analysis evaluated the performance of each imaging technique for detection of fibrosis, in comparison with serum markers.ResultsLiver stiffness measured with MRE provided the strongest...

Best, G, Faigl, J & Fitch, R 2018, 'Online planning for multi-robot active perception with self-organising maps', Autonomous Robots, vol. 42, no. 4, pp. 715-738.
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© 2017, Springer Science+Business Media, LLC, part of Springer Nature. We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting associated viewpoint regions defined by a sensor model. The key problem characteristics are that the viewpoint regions are overlapping polygonal continuous regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes to the robots and finds favourable sequences of sensing locations. The algorithm has a runtime complexity that is polynomial in the number of nodes to be observed and the magnitude of the relative weighting of rewards. We show empirically the runtime is sublinear in the number of robots. We demonstrate feasibility for the active perception task of observing a set of 3D objects. The viewpoint regions consider sensing ranges and self-occlusions, and the rewards are measured as discriminability in the ensemble of shape functions feature space. Exploration objectives for online tasks where the environment is only partially known in advance are modelled by introducing goal regions in unexplored space. Online replanning is performed efficiently by adapting previous solutions as new information becomes available. Simulations were performed using a 3D point-cloud dataset from a real robot in a large outdoor environment. Our results show the proposed methods enable multi-robot planning for online active perception tasks with continuous sets of candidate viewpoints and long planning horizons.

Beydoun, G, Dascalu, S, Dominey-Howes, D & Sheehan, A 2018, 'Disaster Management and Information Systems: Insights to Emerging Challenges.', Inf. Syst. Frontiers, vol. 20, no. 4, pp. 649-652.
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BEZDEK, J, KELLER, J, PAL, N, LIN, C-T & GARIBALDI, J 2018, 'Editorial Celebrating 25 Years of the IEEE Transactions on Fuzzy Systems', IEEE Transactions on Fuzzy Systems, vol. 26, no. 1, pp. 1-5.
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Bhandari, S, Bannister, KW, Murphy, T, Bell, M, Raja, W, Marvil, J, Hancock, PJ, Whiting, M, Flynn, CM, Collier, JD, Kaplan, DL, Allison, JR, Anderson, C, Heywood, I, Hotan, A, Hunstead, R, Lee-Waddell, K, Madrid, JP, McConnell, D, Popping, A, Rhee, J, Sadler, E & Voronkov, MA 2018, 'A pilot survey for transients and variables with the Australian Square Kilometre Array Pathfinder', Monthly Notices of the Royal Astronomical Society, vol. 478, no. 2, pp. 1784-1794.
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© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. We present a pilot search for variable and transient sources at 1.4 GHz with the Australian Square Kilometre Array Pathfinder (ASKAP). The search was performed in a 30 deg2 area centred on the NGC 7232 galaxy group over eight epochs and observed with a near-daily cadence. The search yielded nine potential variable sources, rejecting the null hypothesis that the flux densities of these sources do not change with 99.9 per cent confidence. These nine sources displayed flux density variations with modulation indices m ≥ 0.1 above our flux density limit of ~1.5mJy. They are identified to be compact active galactic nucleus (AGN)/quasars or galaxies hosting an AGN, whose variability is consistent with refractive interstellar scintillation.We also detect a highly variable source with modulation index m > 0.5 over a time interval of a decade between the SydneyUniversity Molonglo Sky Survey (SUMSS) and our latest ASKAP observations. We find the source to be consistent with the properties of long-term variability of a quasar. No transients were detected on time-scales of days and we place an upper limit ρt < 0.01 deg-2 with 95 per cent confidence for non-detections on near-daily time-scales. The future VAST-Wide survey with 36-ASKAP dishes will probe the transient phase space with similar cadence to our pilot survey, but better sensitivity, and will detect and monitor rarer brighter events.

Bian, X, Jin, W, Gu, Q, Zhou, X, Xi, Y, Tu, R, Han, S-F, Xie, G-J, Gao, S-H & Wang, Q 2018, 'Subcritical n-hexane/isopropanol extraction of lipid from wet microalgal pastes of Scenedesmus obliquus', World Journal of Microbiology and Biotechnology, vol. 34, no. 3, pp. 39-39.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. Abstract: Subcritical co-solvents of n-hexane/isopropanol were primarily utilized to extract lipid from wet microalgal pastes of Scenedesmus obliquus. The effects of key operational parameters were investigated, and the optimal parameters were obtained: solvent ratio of n-hexane to isopropanol was 3:2 (V:V), phase ratio of co-solvents to microalgal biomass was 35:1 (mL:g), reactor stirring speed was 900 rpm, extraction time was 60 min. Additional pretreatment with acid, ultrasonic and microwave as well as enhanced subcritical pressure/heating treatments were also applied to further study their effects on lipid extraction. The results showed that the lipid recovery rate with acid pretreatment was 8.6 and 6.2% higher than ultrasonic and microwave pretreatment; the optimum enhanced subcritical condition was 55 °C with atmospheric pressure. Under optimal operating conditions, the lipid and FAME yield were 13.5 and 7.2%, which was 82.6 and 135.1% higher than the traditional method. The results indicated that the subcritical n-hexane/isopropanol extraction process had promising application potential. Graphical Abstract: [Figure not available: see fulltext.].

Bickel, B, Cignoni, P, Malomo, L & Pietroni, N 2018, 'State of the Art on Stylized Fabrication.', Comput. Graph. Forum, vol. 37, pp. 325-342.
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Bjarnadottir, S, Li, Y, Reynisson, O & Stewart, MG 2018, 'Reliability-based assessment of climatic adaptation for the increased resiliency of power distribution systems subjected to hurricanes', Sustainable and Resilient Infrastructure, vol. 3, no. 1, pp. 36-48.
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Power distribution systems are vulnerable to hurricanes as has been documented in recent years. Hurricane intensity or/and frequency may change as a result of increased CO2 emissions. This paper proposes six climatic adaptation strategies for timber distribution poles that may aid in mitigating the hurricane damage costs that may be expected to increase because of global climate change. The effectiveness of adaptation is assessed through a life-cycle cost analysis, which includes direct cost (e.g. cost of pole replacement, maintenance, and adaptation) and indirect cost (e.g. cost of power outage to customers). The viability of the adaptation strategies is examined considering three CO2 emission scenarios. Furthermore, the scenario of no climate change is considered in this paper to show the applicability the proposed framework for hurricane risk mitigation under current conditions (i.e. wind speeds remain stationary). This paper finds that certain adaptation measures can effectively reduce costs, resulting in more resilient power distribution systems.

Błachnio, A, Przepiórka, A, Wołońciej, M, Bassam Mahmoud, A, Holdoš, J & Yafi, E 2018, 'Loneliness, Friendship, and Facebook Intrusion. A Study in Poland, Slovakia, Syria, Malaysia, and Ecuador', Studia Psychologica, vol. 60, no. 3, pp. 183-194.
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Blanco-Mesa, F, Gil-Lafuente, AM & Merigo, JM 2018, 'Dynamics of stakeholder relations with multi-person aggregation', Kybernetes, vol. 47, no. 9, pp. 1801-1820.
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PurposeThe purpose of this paper is to develop a novel method to analyse dynamic interactions of stakeholders to explain how a set of agents can act by considering the power/influence positions.Design/methodology/approachA novel mathematical application uses the importance of characteristics algorithm in combination with composition max-min to compare, group and order information according to the importance of its characteristics. The mathematical application is focused on a strategic analysis, evaluating stakeholder dynamics through power relationships.FindingsThe results show a comparison of the relationships among each of the stakeholders to obtain the relative intensity and importance of relationships between them, given by the fuzzy matrix FRInM and the fuzzy matrix FRIM, respectively. This application provides a useful tool for a dynamic analysis of stakeholders in a complex environment, where the best approach to performing a strategic analysis process is sought.Research limitations/implicationsThe main implication of the proposed approach is taking into account the importance of information to establish the boundaries and relationships of each characteristic according to its intensity. However, limitations are due to the nature of this research, based on theoretical assumptions regarding stakeholders and the use of a hypothetical example to show the operation of algorithms.Originality/valueThe primary advantage of this proposition is that it takes into account the im...

BLANCO-MESA, F, GIL-LAFUENTE, AM & MERIGÓ, JM 2018, 'NEW AGGREGATION OPERATORS FOR DECISION-MAKING UNDER UNCERTAINTY: AN APPLICATIONS IN SELECTION OF ENTREPRENEURIAL OPPORTUNITIES', Technological and Economic Development of Economy, vol. 24, no. 2, pp. 335-357.
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The main aim of this paper is to study how economic environment and logic reasoning guidance the decision-making process to start-up a new business by potential entrepreneurs. The study proposes a new method using the family of selection indices with OWA operator, which allows aggregating information according to the level of importance and their level of objectivity and subjectivity in the same formulation within the decision-making process. To develop case study, we have taken into account some industries of the sports sector and some critical environmental factors that influence the competitiveness and entrepreneurship in Colombia to start a new business. The results show in an orderly way all information aggregated, which can help potential investors and entrepreneurs to make a decision based on their preferences. Finally, the applicability of this method in real case can be given in aggregation different sources of information to help at dealing decision-making processes.

Blanco-Mesa, F, Gil-Lafuente, AM & Merigó, JM 2018, 'Subjective stakeholder dynamics relationships treatment: a methodological approach using fuzzy decision-making', Computational and Mathematical Organization Theory, vol. 24, no. 4, pp. 441-472.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Since the stakeholder theory was proposed to explain the interaction among its agents, extensive approaches have been developed. However, the literature continues to suggest the development of new methodologies that allow an analysis of the dynamics and uncertainty of the relationships between each agent. In this sense, this research proposes a novel methodology for the treatment of subjective stakeholder dynamics using fuzzy decision-making. The study proposes a mathematical methodological perspective for the treatment of subjective relationships among stakeholders, which allows a predictive simulation tool to be developed for attitude and personal preferences to analyze the links among all stakeholders. A mathematical application is developed to help the decision-making process in uncertainty concerning the ordering-according-to-their-importance and linking-of-relation algorithms, which are based on notions of relation, gathering and ordering. A numerical example is proposed to understand the method’s usefulness and feasibility. The results approximate how stakeholder ambiguity and fuzziness can be managed considering the decision-maker’s preference subjectivity. In addition, these results highlight the different relationships among each stakeholder, their intensity levels, the incidence linkage loops and the incidence relative on stakeholder behaviors. The main implication of this proposition is to deal with the subjective preferences provide by decision-maker to better interpret environmental and subjective factors. Furthermore, this study contributes to the strategic planning and decision-making processes for operative units within uncertain environment in the short term.

Blanco-Mesa, F, León-Castro, E & Merigó, JM 2018, 'Bonferroni induced heavy operators in ERM decision-making: A case on large companies in Colombia', Applied Soft Computing, vol. 72, pp. 371-391.
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© 2018 Elsevier B.V. Averaging aggregation operators analyse a set of data providing a summary of the results. This study focuses on the Bonferroni mean and the induced and heavy aggregation operators. The aim of the work is to present new aggregation operators that combine these concepts forming the Bonferroni induced heavy ordered weighted average and several particular formulations. This approach represents Bonferroni means with order inducing variables and with weighting vectors that can be higher than one. The paper also develops some extensions by using distance measures forming the Bonferroni induced heavy ordered weighted average distance and several particular cases. The study ends with an application in a large companies risk management problem in Colombia. The main advantage of this approach is that it provides a more general framework for analysing the data in scenarios where the numerical values may have some complexities that should be assessed with complex attitudinal characters.

Bluff, A, Johnston, A & Clarkson, D 2018, 'Interaction, Narrative and Animation in Live Theatre', IEEE Computer Graphics and Applications, vol. 38, no. 2, pp. 8-14.
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© 1981-2012 IEEE. Before embarking on their most ambitious project to date, a cosmically-themed participatory theatre event with interactive 3D visuals housed inside a bespoke dome structure, the interactive artists Andrew Johnston and Andrew Bluff joined the director of Stalker Theatre, David Clarkson in a round-table discussion. They reflected on what it was like to combine physical performance with interactive graphics in a childrens theatre show and discussed how the 360° format might be used to explore the cosmos in their upcoming Big Skies production.

Boostani, AF, Yazdani, S, Khosroshahi, RA, Jiang, ZY & Wei, D 2018, 'A novel graphene-stimulated semi-solid processing to fabricate advanced aluminium matrix nanocomposites', Materials Science and Engineering: A, vol. 736, pp. 316-322.
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© 2018 Elsevier B.V. This study reveals an unprecedented capacity of flake graphene sheets in manipulating semi-solid deformation of aluminium matrix nanocomposites by restricting the grain growth of the nanograins during the reheating process to significantly enhance (173%) the yield strength of the fabricated composites. The graphene sheets with onion shape have also shown the unique capability in alleviating the agglomeration of SiC nanoparticles, attributed to the manipulated Hamaker constant of these particles as a result of wrapping graphene sheets. A devised mathematical approach has authenticated, for the first time, the effect of wrapping graphene sheets on subtle adjusting the Hamaker constant of SiC nanoparticles to stimulate engulfment of these nanoparticles within solidifying matrix rather than agglomeration at grain boundaries. This, therefore, has resulted in diminishing the porosity and stimulating multi-scaled micro/nano grains, thereby significantly enhancing the tensile properties of the fabricated composites.

Booth, E & Narayan, B 2018, '‘Don’t talk about the gay character’: Barriers to queer young adult fiction and authors in schools and libraries', English in Australia, vol. 53, no. 2, pp. 40-48.
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This article explores findings from an investigation into the publishing experiences of Australian authors of inclusive Young Adult (YA) fiction. A total of seven authors, each publicly identifying as part of a marginalised community in Australia, were interviewed. This paper concentrates on the findings of semi-structured interviews with two authors of Lesbian, Gay, Bisexual, Transgender, Intersex, Asexual, Pansexual, and Other (LGBTQIAP+) fiction, and their experience of promoting their books in school and library environments. Findings were analysed using Critical Discourse Analysis to understand their interactions with publishers, audiences, and school staff. The research was carried out in 2016 but highlights longstanding issues regarding the inclusion of queer literature for young people in educational spaces, including school libraries and high school English curriculums. More broadly, it contributes to the understanding of how diversity and inclusion within YA Fiction is viewed in Australia, and the role of gatekeepers in providing or denying access.

Booth, E & Narayan, B 2018, 'Towards diversity in young adult fiction: Australian YA authors’ publishing experiences and its implications for YA librarians and readers’ advisory services', Journal of the Australian Library and Information Association, vol. 67, no. 3, pp. 195-211.
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© 2018, © 2018 Australian Library & Information Association. Based on a study of Australian young adult (YA) fiction authors, this paper argues that it is necessary for publishers, booksellers, and YA librarians to pay attention to the global movement towards diversity: diversity within their own organisations, diversity among authors they publish, stock, or collect, and representations of diversity within YA fiction. The mainstream attention to diversity has particularly focused on media for young people, with advocates stating that children and teenagers from traditionally marginalised communities deserve to see their own experiences reflected and validated in the media they consume. This paper looks at diversity in writing and traditional publishing through interviews with Australian YA authors (conducted in 2016) from traditionally marginalised or unacknowledged communities, especially as it relates to their transition from reader to writer, and their experience of the publishing journey. A critical discourse analysis of the interviews point to a need for more diversity representations in YA fiction, and also the need for a change in industry practices to enable this, including publishing, bookselling, and library practices. Abbreviations: YA - Young Adult Fiction WNDB - We Need Diverse Books CDA - Critical Discourse Analysis.

Borkert, M, Fisher, KE & Yafi, E 2018, 'The Best, the Worst, and the Hardest to Find: How People, Mobiles, and Social Media Connect Migrants In(to) Europe', Social Media + Society, vol. 4, no. 1, pp. 205630511876442-205630511876442.
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For displaced people, migrating into Europe has highly complex information needs about the journey and destination. Each new need presents problems of where to seek information, how to trust or distrust information, and financial and other costs. The outcomes of receiving poor or false information can cause bodily harm or death, loss of family, or financial ruin. We aim to make two major contributions: First, provide rich insights into digital literacy, information needs, and strategies among Syrian and Iraqi refugees who entered Europe in 2015, a topic rarely dealt with in the literature. Second, we seek to change the dominant perspective on migrants and refugees as passive victims of international events and policies by showing their capacities and skills to navigate the complex landscape of information and border regimes en route to Europe. Building on research at Za’atari refugee camp (Jordan), we surveyed 83 Arab refugees in two centers in Berlin. Analyses address refugees’ temporal information worlds, focusing on the importance and difficulty in finding specific information, how migrants identify mis- and disinformation, and the roles of information and technology mediaries. Findings illustrate the digital capacities refugees employ during and after their journey to Europe; they show social support via social media and highlight the need for a radical shift in thinking about and researching migration in the digital age.

Bowden, R & Veitch, D 2018, 'Finding the Right Tree: Topology Inference Despite Spatial Dependences', IEEE Transactions on Information Theory, vol. 64, no. 6, pp. 4594-4609.
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© 1963-2012 IEEE. Network tomographic techniques have almost exclusively been built on a strong assumption of mutual independence of link processes. We introduce model classes for link loss processes with non-Trivial spatial dependencies, for which the tree topology is nonetheless identifiable from leaf measurements using multicast probing. We show that these classes are large in a well-defined sense, and we provide an algorithm, SLTD, capable of returning the correct topology with certainty in the limit of infinite data.

Bown, O & Ferguson, S 2018, 'Creative Media + the Internet of Things = Media Multiplicities', Leonardo, vol. 51, no. 1, pp. 53-54.
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This paper proposes the term “media multiplicities” to describe contemporary media artworks that create multiples of “internet of things” devices. It discusses the properties that distinguish media multiplicities from other forms of media artwork, provides parameters for categorizing media multiplicities, and discusses aesthetic and creative factors in the production of media multiplicities.

Bown, O & Ferguson, S 2018, 'Understanding media multiplicities', Entertainment Computing, vol. 25, pp. 62-70.
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Internet of Things (IoT) technologies enable new forms of media artworks. ‘Media multiplicities’ are defined here as creative media experiences made up of multiples of interacting and coordinated devices. In this paper, we review the state of the art of multiplicitous media artworks and provide a systematic analysis of the novel affordances and different forms such artworks can take, specifically that they are spatial, scalable, scatterable and sensing. We consider the analysis of media multiplicities from the point of view of both user experience and creative production. We offer three primary axes through which a categorisation of multiplicitous media forms can be framed: substrate versus object; composed versus self-organised, and homogeneous versus heterogeneous. We also analyse how the number of elements in the multiplicities (from tens to tens of thousands and beyond) affects the qualities of the experience.

Bracci, M, Tarini, M, Pietroni, N, Livesu, M & Cignoni, P 2018, 'HexaLab.net: an online viewer for hexahedral meshes.', CoRR, vol. abs/1806.06639, pp. 24-36.
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© 2018 Elsevier Ltd We introduce HexaLab: a WebGL application for real time visualization, exploration and assessment of hexahedral meshes. HexaLab can be used by simply opening www.hexalab.net. Our visualization tool targets both users and scholars. Practitioners who employ hexmeshes for Finite Element Analysis, can readily check mesh quality and assess its usability for simulation. Researchers involved in mesh generation may use HexaLab to perform a detailed analysis of the mesh structure, isolating weak points and testing new solutions to improve on the state of the art and generate high quality images. To this end, we support a wide variety of visualization and volume inspection tools. Our system offers also immediate access to a repository containing all the publicly available meshes produced with the most recent techniques for hexmesh generation. We believe HexaLab, providing a common tool for visualizing, assessing and distributing results, will push forward the recent strive for replicability in our scientific community.

Bray, K, Regan, B, Trycz, A, Previdi, R, Seniutinas, G, Ganesan, K, Kianinia, M, Kim, S & Aharonovich, I 2018, 'Single Crystal Diamond Membranes and Photonic Resonators Containing Germanium Vacancy Color Centers', ACS Photonics, vol. 5, no. 12, pp. 4817-4822.
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Copyright © 2018 American Chemical Society. Single crystal diamond membranes that host optically active emitters are highly attractive components for integrated quantum nanophotonics. In this work we demonstrate bottom-up synthesis of single crystal diamond membranes containing germanium vacancy (GeV) color centers. We employ a lift-off technique to generate the membranes and perform chemical vapor deposition in the presence of a germanium source to realize the in situ doping. Finally, we show that these membranes are suitable for engineering of photonic resonators such as microdisk cavities with quality factors of ∼1500. The robust and scalable approach to engineer single crystal diamond membranes containing emerging color centers is a promising pathway for the realization of diamond integrated quantum nanophotonic circuits on a chip.

Brennan, MJ, Karimi, M, Muggleton, JM, Almeida, FCL, Kroll de Lima, F, Ayala, PC, Obata, D, Paschoalini, AT & Kessissoglou, N 2018, 'On the effects of soil properties on leak noise propagation in plastic water distribution pipes', Journal of Sound and Vibration, vol. 427, pp. 120-133.
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Brereton, M, Soro, A, Sitbon, L, Roe, P, Wyeth, P, Ploderer, B, Vyas, D, Zhang, J, Ambe, A, Wilson, C, Dema, T, Taylor, J, Oliver, J, Munoz, D, Bayor, A, Bircanin, F, Anggarendra, R, Capel, T, Kapuire, G & Wheeler, H 2018, 'Design participation lab', Interactions, vol. 25, no. 2, pp. 14-17.
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Broderick, JW, Fender, RP, Miller-Jones, JCA, Trushkin, SA, Stewart, AJ, Anderson, GE, Staley, TD, Blundell, KM, Pietka, M, Markoff, S, Rowlinson, A, Swinbank, JD, van der Horst, AJ, Bell, ME, Breton, RP, Carbone, D, Corbel, S, Eislöffel, J, Falcke, H, Grießmeier, J-M, Hessels, JWT, Kondratiev, VI, Law, CJ, Molenaar, GJ, Serylak, M, Stappers, BW, van Leeuwen, J, Wijers, RAMJ, Wijnands, R, Wise, MW & Zarka, P 2018, 'LOFAR 150-MHz observations of SS 433 and W 50', Monthly Notices of the Royal Astronomical Society, vol. 475, no. 4, pp. 5360-5377.
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© 2017 The Author(s). We present Low-Frequency Array (LOFAR) high-band data over the frequency range 115-189 MHz for the X-ray binary SS 433, obtained in an observing campaign from 2013 February to 2014 May. Our results include a deep, wide-field map, allowing a detailed view of the surrounding supernova remnant W50 at low radio frequencies, as well as a light curve for SS 433 determined from shorter monitoring runs. The complex morphology of W50 is in excellent agreement with previously published higher frequency maps; we find additional evidence for a spectral turnover in the eastern wing, potentially due to foreground free-free absorption. Furthermore, SS 433 is tentatively variable at 150 MHz, with both a debiased modulation index of 11 per cent and a Χ2 probability of a flat light curve of 8.2 × 10-3. By comparing the LOFAR flux densities with contemporaneous observations carried out at 4800 MHz with the RATAN-600 telescope, we suggest that an observed ~0.5-1 Jy rise in the 150-MHz flux density may correspond to sustained flaring activity over a period of approximately 6 months at 4800 MHz. However, the increase is too large to be explained with a standard synchrotron bubble model. We also detect a wealth of structure along the nearby Galactic plane, including the most complete detection to date of the radio shell of the candidate supernova remnant G38.7-1.4. This further demonstrates the potential of supernova remnant studies with the current generation of low-frequency radio telescopes.

Bunawan, AR, Momeni, E, Armaghani, DJ, Nissa binti Mat Said, K & Rashid, ASA 2018, 'Experimental and intelligent techniques to estimate bearing capacity of cohesive soft soils reinforced with soil-cement columns', Measurement, vol. 124, pp. 529-538.
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Burdon, S, Mooney, G & Kang, K 2018, 'Where Everybody Knows Your Name: Lessons in Innovation from the High-Tech Sector', Journal of Innovation and Business Best Practice, vol. 2018, no. 2018, pp. 1-16.
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This paper examines the major priorities and prevailing values of firms highly regarded for innovation success within the Australian high-tech sector. In conjunction with the Information Industry Association of Australia (AIIA), a survey was undertaken regarding member perceptions of peer enterprises most admired for innovation origination and delivery. 244 responses from 102 organisations were received, analysed and compared. Direct follow-up with selected enterprises then more closely examined factors deemed key to sustaining a cycle of innovation leadership. Findings suggest that firms most esteemed by peers also prioritise the realisation of innovation over simply making money - yet both high growth and cash flows are still habitually generated .Results also show that having a strong reputation for innovation is a competitive advantage in its own right as they attract invitation to cross-enterprise ecosystems and beneficial partner alliances. Interestingly however, topics linked to outsider/peer perceptions of rival enterprises seem to collect comparatively limited precedence within innovation debates. What our study shows is that balancing an internal reality of innovation with the external perception for innovation can lead firms to significant improvements in overall commercial performance.

Cagno, E, Neri, A & Trianni, A 2018, 'Broadening to sustainability the perspective of industrial decision-makers on the energy efficiency measures adoption: some empirical evidence', Energy Efficiency, vol. 11, no. 5, pp. 1193-1210.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. The industry should take further efforts towards increased energy efficiency, that is a major contributor to improve industrial sustainability performance, by implementing energy efficiency measures (EEMs). However, the rate of adoption of these measures is still quite low. Hitherto, EEMs and barriers to their adoption have been evaluated almost exclusively from the viewpoint of energy efficiency decision-makers, not accounting for the broader sustainability perspective. This work aims at understanding whether an industrial sustainability perspective can better address issues related to EEMs adoption, analyzing the question through different viewpoints and insights offered by industrial decision-makers of different industrial sustainability areas within a firm. By doing this, we aim at offering a contribution in the understanding of the low rate of adoption of EEMs. As case studies, we investigated 12 firms from Northern Italy. In comparison to previous literature, results show that an industrial sustainability perspective can better explain the real decision-making process of adopting an EEM. Indeed, people knowledgeable about different industrial sustainability areas may perceive different barriers about the same EEM. EEMs may be negatively affected by reasons related to other areas of industrial sustainability, while positive reciprocal impacts may exist among areas of industrial sustainability; thus, EEMs may have effects on areas other than energy efficiency, and these effects may be perceived only by such areas. The study concludes with some remarks for policy and industrial decision-makers and advice for further research.

Cai, C, Hu, S, Chen, X, Ni, B-J, Pu, J & Yuan, Z 2018, 'Effect of methane partial pressure on the performance of a membrane biofilm reactor coupling methane-dependent denitrification and anammox', Science of The Total Environment, vol. 639, pp. 278-285.
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© 2018 Complete nitrogen removal has recently been demonstrated by integrating anaerobic ammonium oxidation (anammox) and denitrifying anaerobic methane oxidation (DAMO) processes. In this work, the effect of methane partial pressure on the performance of a membrane biofilm reactor (MBfR) consisting of DAMO and anammox microorganisms was evaluated. The activities of DAMO archaea and DAMO bacteria in the biofilm increased significantly with increased methane partial pressure, from 367 ± 9 and 58 ± 22 mg-N L−1d−1 to 580 ± 12 and 222 ± 22 mg-N L−1d−1, respectively, while the activity of anammox bacteria only increased slightly, when the methane partial pressure was elevated from 0.24 to 1.39 atm in the short-term batch tests. The results were supported by a long-term (seven weeks) continuous test, when the methane partial pressure was dropped from 1.39 to 0.78 atm. The methane utilization efficiency was always above 96% during both short-term and long-term tests. Taken together, nitrogen removal rate (especially the nitrate reduction rate by DAMO archaea) and methane utilization efficiency could be maintained at high levels in a broad range of methane partial pressure (0.24–1.39 atm in this study). In addition, a previously established DAMO/anammox biofilm model was used to analyze the experimental data. The observed impacts of methane partial pressure on biofilm activity were well explained by the modeling results. These results suggest that methane partial pressure can potentially be used as a manipulated variable to control reaction rates, ultimately to maintain high nitrogen removal efficiency, according to nitrogen loading rate.

Cai, Q, Turner, BD, Sheng, D & Sloan, S 2018, 'Application of kinetic models to the design of a calcite permeable reactive barrier (PRB) for fluoride remediation', Water Research, vol. 130, pp. 300-311.
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Cancino, CA, Merigo, JM, Torres, JP & Diaz, D 2018, 'A bibliometric analysis of venture capital research', Journal of Economics, Finance and Administrative Science, vol. 23, no. 45, pp. 182-195.
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PurposeThe purpose of this study is to present the evolution of academic research in venture capital (VC) research between 1990 and 2014.Design/methodology/approachThe study analyzes the most influential journals in VC research by analyzing papers, which were published on the Web of Science database.FindingsResults show a steady increasing rate of VC research during the past 25 years. The paper reports the 40 academic journals that permanently publish articles about VC research.Originality/valueThe main contribution of this work is to develop a general overview of the leading journals in VC research, which leads to the development of a future research agenda for bibliometric analysis, such as the review of the most productive and influential authors, universities and countries in VC research.

Cao, F & Li, K 2018, 'A new method for image super-resolution with multi-channel constraints', Knowledge-Based Systems, vol. 146, pp. 118-128.
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Cao, S, Su, A, Zhao, Y & Zhang, G 2018, 'Laparoscopic versus open splenectomy and esophagogastric devascularization for portal hypertension: a meta-analysis', INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL MEDICINE, vol. 11, no. 10, pp. 10244-10254.

Cao, Y, Cao, Y, Wen, S, Huang, T & Zeng, Z 2018, 'Passivity analysis of coupled neural networks with reaction–diffusion terms and mixed delays', Journal of the Franklin Institute, vol. 355, no. 17, pp. 8915-8933.
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In this paper, we intend to discuss the passivity of coupled neural networks (NNs) with reaction–diffusion terms and mixed delays. By constructing appropriate Lyapunov functional, and with the help of liner matrix inequalities, some inequality techniques, several sufficient conditions are derived to guarantee the output strictly passive, input strictly passive, passive of the proposed neural network model. Then, a stability criterion is presented according to the obtained passivity results. Moreover, the proposed neural network model herein is more general than some recent studies, which can improve and enrich the previous research results. Finally, a numerical example is presented to show the effectiveness of the theoretical criteria.

Cao, Y, Romero, J, Olson, JP, Degroote, M, Johnson, PD, Kieferová, M, Kivlichan, ID, Menke, T, Peropadre, B, Sawaya, NPD, Sim, S, Veis, L & Aspuru-Guzik, A 2018, 'Quantum Chemistry in the Age of Quantum Computing', Chemical Reviews, vol. 119, no. 19.
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Practical challenges in simulating quantum systems on classical computershave been widely recognized in the quantum physics and quantum chemistrycommunities over the past century. Although many approximation methods havebeen introduced, the complexity of quantum mechanics remains hard to appease.The advent of quantum computation brings new pathways to navigate thischallenging complexity landscape. By manipulating quantum states of matter andtaking advantage of their unique features such as superposition andentanglement, quantum computers promise to efficiently deliver accurate resultsfor many important problems in quantum chemistry such as the electronicstructure of molecules. In the past two decades significant advances have beenmade in developing algorithms and physical hardware for quantum computing,heralding a revolution in simulation of quantum systems. This article is anoverview of the algorithms and results that are relevant for quantum chemistry.The intended audience is both quantum chemists who seek to learn more aboutquantum computing, and quantum computing researchers who would like to exploreapplications in quantum chemistry.

Cao, Z & Lin, C-T 2018, 'Inherent Fuzzy Entropy for the Improvement of EEG Complexity Evaluation', IEEE Transactions on Fuzzy Systems, vol. 26, no. 2, pp. 1032-1035.
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© 2017 IEEE. In recent years, the concept of entropy has been widely used to measure the dynamic complexity of signals. Since the state of complexity of human beings is significantly affected by their health state, developing accurate complexity evaluation algorithms is a crucial and urgent area of study. This paper proposes using inherent fuzzy entropy (Inherent FuzzyEn) and its multiscale version, which employs empirical mode decomposition and fuzzy membership function (exponential function) to address the dynamic complexity in electroencephalogram (EEG) data. In the literature, the reliability of entropy-based complexity evaluations has been limited by superimposed trends in signals and a lack of multiple time scales. Our proposed method represents the first attempt to use the Inherent FuzzyEn algorithm to increase the reliability of complexity evaluation in realistic EEG applications. We recorded the EEG signals of several subjects under resting condition, and the EEG complexity was evaluated using approximate entropy, sample entropy, FuzzyEn, and Inherent FuzzyEn, respectively. The results indicate that Inherent FuzzyEn is superior to other competing models regardless of the use of fuzzy or nonfuzzy structures, and has the most stable complexity and smallest root mean square deviation.

Cao, Z, Adnan, NNM, Wang, G, Rawal, A, Shi, B, Liu, R, Liang, K, Zhao, L, Gooding, JJ, Boyer, C & Gu, Z 2018, 'Enhanced colloidal stability and protein resistance of layered double hydroxide nanoparticles with phosphonic acid-terminated PEG coating for drug delivery', Journal of Colloid and Interface Science, vol. 521, pp. 242-251.
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Cao, Z, Lai, K-L, Lin, C-T, Chuang, C-H, Chou, C-C & Wang, S-J 2018, 'Exploring resting-state EEG complexity before migraine attacks', Cephalalgia, vol. 38, no. 7, pp. 1296-1306.
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Objective Entropy-based approaches to understanding the temporal dynamics of complexity have revealed novel insights into various brain activities. Herein, electroencephalogram complexity before migraine attacks was examined using an inherent fuzzy entropy approach, allowing the development of an electroencephalogram-based classification model to recognize the difference between interictal and preictal phases. Methods Forty patients with migraine without aura and 40 age-matched normal control subjects were recruited, and the resting-state electroencephalogram signals of their prefrontal and occipital areas were prospectively collected. The migraine phases were defined based on the headache diary, and the preictal phase was defined as within 72 hours before a migraine attack. Results The electroencephalogram complexity of patients in the preictal phase, which resembled that of normal control subjects, was significantly higher than that of patients in the interictal phase in the prefrontal area (FDR-adjusted p < 0.05) but not in the occipital area. The measurement of test-retest reliability (n = 8) using the intra-class correlation coefficient was good with r1 = 0.73 ( p = 0.01). Furthermore, the classification model, support vector machine, showed the highest accuracy (76 ± 4%) for classifying interictal and preictal phases using the prefrontal electroencephalogram complexity. Conclusion Entropy-based analytical methods identified enhancement or “normalization” of frontal electroencephalogram complexity during the preictal phase compared with the interictal phase. This classification model, using this complexity feature, may have the potential to provide a preictal alert to migraine without aura patients.

CARLES, M-F, PATRICIA, H, ANTONIO, S & JOSÉ M., M 2018, 'The Forgotten Effects: An Application in the Social Economy of Companies of the Balearic Islands', ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, vol. 52, no. 3/2018, pp. 147-160.
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© 2018, Bucharest University of Economic Studies. All rights reserved. Few studies have analyzed how to improve the results and productivity of companies with very peculiar characteristics, such as social economy entities. This paper determines the principal worth-creating activities for this type of companies that dedicate their activities to the service sector of the Balearic Islands. In order to carry out this work, incidence matrixes and recovery of forgotten effects have been used. Both direct cause and second generation causes that arise in the majority of the socio-economic cases have been identified. In fact, determining the second generation effects, or forgotten effects, is one of the main contributions of this study as it shows that those causes that are usually not foreseen, at least in the first instance, affect notably in the generation of social economy companies value to the service sector of the Balearic Islands.

Castro, J, Lu, J, Zhang, G, Dong, Y & Martinez, L 2018, 'Opinion Dynamics-Based Group Recommender Systems', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 12, pp. 2394-2406.
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© 2013 IEEE. With the accessibility to information, users often face the problem of selecting one item (a product or a service) from a huge search space. This problem is known as information overload. Recommender systems (RSs) personalize content to a user's interests to help them select the right item in information overload scenarios. Group RSs (GRSs) recommend items to a group of users. In GRSs, a recommendation is usually computed by a simple aggregation method for individual information. However, the aggregations are rigid and overlook certain group features, such as the relationships between the group members' preferences. In this paper, it is proposed a GRS based on opinion dynamics that considers these relationships using a smart weights matrix to drive the process. In some groups, opinions do not agree, hence the weights matrix is modified to reach a consensus value. The impact of ensuring agreed recommendations is evaluated through a set of experiments. Additionally, a sensitivity analysis studies its behavior. Compared to existing group recommendation models and frameworks, the proposal based on opinion dynamics would have the following advantages: 1) flexible aggregation method; 2) member relationships; and 3) agreed recommendations.

Cendes, Y, Prasad, P, Rowlinson, A, Wijers, RAMJ, Swinbank, JD, Law, CJ, van der Horst, AJ, Carbone, D, Broderick, JW, Staley, TD, Stewart, AJ, Huizinga, F, Molenaar, G, Alexov, A, Bell, ME, Coenen, T, Corbel, S, Eislöffel, J, Fender, R, Grießmeier, J-M, Jonker, P, Kramer, M, Kuniyoshi, M, Pietka, M, Stappers, B, Wise, M & Zarka, P 2018, 'RFI flagging implications for short-duration transients', Astronomy and Computing, vol. 23, pp. 103-114.
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© 2018 The Authors With their wide fields of view and often relatively long coverage of any position in the sky in imaging survey mode, modern radio telescopes provide a data stream that is naturally suited to searching for rare transients. However, Radio Frequency Interference (RFI) can show up in the data stream in similar ways to such transients, and thus the normal pre-treatment of filtering RFI (flagging) may also remove astrophysical transients from the data stream before imaging. In this paper we investigate how standard flagging affects the detectability of such transients by examining the case of transient detection in an observing mode used for Low Frequency Array (LOFAR; van Haarlem et al., 2013) surveys. We quantify the fluence range of transients that would be detected, and the reduction of their SNR due to partial flagging. We find that transients with a duration close to the integration sampling time, as well as bright transients with durations on the order of tens of seconds, are completely flagged. For longer transients on the order of several tens of seconds to minutes, the flagging effects are not as severe, although part of the signal is lost. For these transients, we present a modified flagging strategy which mitigates the effect of flagging on transient signals. We also present a script which uses the differences between the two strategies, and known differences between transient RFI and astrophysical transients, to notify the observer when a potential transient is in the data stream.

Chaei, MG, Akbarnezhad, A, Castel, A, Lloyd, R, Keyte, L & Foster, S 2018, 'Precision of cement hydration heat models in capturing the effects of SCMs and retarders', Magazine of Concrete Research, vol. 70, no. 23, pp. 1217-1231.
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A major input to numerical simulation models used to predict the risk of early-age thermal cracking in concrete is the hydration heat estimation. The precision of hydration heat estimation models has been extensively verified for different cement compositions in previous studies. However, little has been done to investigate the accuracy of such models for concrete mixes containing supplementary cementitious materials and retarders. This paper presents the results of a series of isothermal calorimetry tests conducted first to investigate the effects of Class F fly ash, ground-granulated blast-furnace slag (GGBFS) and three commonly used retarders (namely, retarder N, sucrose and citrate) on the heat of hydration profile of Australian general-purpose cement under different curing temperatures of 10, 23 and 30°C, and second to evaluate the precision of the two most commonly used hydration heat models in capturing the effects of fly ash, GGBFS, retarders and curing temperature on the hydration profile. The results reveal the possibility of considerable errors in estimating the hydration heat of concrete mixes containing supplementary cementitious materials and retarders under different curing temperatures, highlighting the need for re-calibration of the existing models for locally used materials to avoid misleading errors in numerical simulation of early-age thermal cracking.

Chandra Saha, K 2018, 'Double Lid Driven Cavity with Different Moving Wall Directions for Low Reynolds Number Flow', International Journal of Applied Mathematics and Theoretical Physics, vol. 4, no. 3, pp. 67-67.
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Chang, X, Yan, Y & Nie, L 2018, 'Guest Editorial: Semantic Concept Discovery in MM Data', Multimedia Tools and Applications, vol. 77, no. 3, pp. 2945-2946.
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Chauhan, J, Seneviratne, S, Hu, Y, Misra, A, Seneviratne, A & Lee, Y 2018, 'Breathing-Based Authentication on Resource-Constrained IoT Devices using Recurrent Neural Networks', Computer, vol. 51, no. 5, pp. 60-67.
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Chekli, L, Pathak, N, Kim, Y, Phuntsho, S, Li, S, Ghaffour, N, Leiknes, T & Shon, HK 2018, 'Combining high performance fertiliser with surfactants to reduce the reverse solute flux in the fertiliser drawn forward osmosis process', Journal of Environmental Management, vol. 226, pp. 217-225.
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© 2018 Elsevier Ltd Solutions to mitigate the reverse diffusion of solutes are critical to the successful commercialisation of the fertiliser drawn forward osmosis process. In this study, we proposed to combine a high performance fertiliser (i.e., ammonium sulfate or SOA) with surfactants as additives as an approach to reduce the reverse diffusion of ammonium ions. Results showed that combining SOA with both anionic and non-ionic surfactants can help in reducing the reverse salt diffusion by up to 67%. We hypothesised that, hydrophobic interactions between the surfactant tails and the membrane surface likely constricted membrane pores resulting in increased rejection of ions with large hydrated radii such as SO42−. By electroneutrality, the rejection of the counter ions (i.e., NH4+) also therefore subsequently improved. Anionic surfactant was found to further decrease the reverse salt diffusion due to electrostatic repulsions between the surfactant negatively-charged heads and SO42−. However, when the feed solution contains cations with small hydrated radii (e.g., Na+); it was found that NH4+ ions can be substituted in the DS to maintain its electroneutrality and thus the diffusion of NH4+ to the feed solution was increased.

Chelgani, SC & Matin, SS 2018, 'Study the relationship between coal properties with Gieseler plasticity parameters by random forest', International Journal of Oil, Gas and Coal Technology, vol. 17, no. 1, pp. 113-113.
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Chen, C, Guo, WS, Ngo, HH, Chang, SW, Nguyen, DD, Zhang, J, Liang, S, Guo, JB & Zhang, XB 2018, 'Effects of C/N ratio on the performance of a hybrid sponge-assisted aerobic moving bed-anaerobic granular membrane bioreactor for municipal wastewater treatment', Bioresource Technology, vol. 247, pp. 340-346.
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This study aimed to evaluate the impact of C/N ratio on the performance of a hybrid sponge-assisted aerobic moving bed-anaerobic granular membrane bioreactor (SAAMB-AnGMBR) in municipal wastewater treatment. The results showed that organic removal efficiencies were above 94% at all C/N conditions. Nutrient removal was over 91% at C/N ratio of 100/5 but was negatively affected when decreasing C/N ratio to 100/10. At lower C/N ratio (100/10), more noticeable membrane fouling was caused by aggravated cake formation and pore clogging, and accumulation of extracellular polymeric substances (EPS) in the mixed liquor and sludge cake as a result of deteriorated granular quality. Foulant analysis suggested significant difference existed in the foulant organic compositions under different C/N ratios, and humic substances were dominant when the fastest fouling rate was observed. The performance of the hybrid system was found to recover when gradually increasing C/N ratio from 100/10 to 100/5.

Chen, C, Wang, F, Wen, S, Su, QP, Wu, MCL, Liu, Y, Wang, B, Li, D, Shan, X, Kianinia, M, Aharonovich, I, Toth, M, Jackson, SP, Xi, P & Jin, D 2018, 'Multi-photon near-infrared emission saturation nanoscopy using upconversion nanoparticles', Nature Communications, vol. 9, no. 1.
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AbstractMultiphoton fluorescence microscopy (MPM), using near infrared excitation light, provides increased penetration depth, decreased detection background, and reduced phototoxicity. Using stimulated emission depletion (STED) approach, MPM can bypass the diffraction limitation, but it requires both spatial alignment and temporal synchronization of high power (femtosecond) lasers, which is limited by the inefficiency of the probes. Here, we report that upconversion nanoparticles (UCNPs) can unlock a new mode of near-infrared emission saturation (NIRES) nanoscopy for deep tissue super-resolution imaging with excitation intensity several orders of magnitude lower than that required by conventional MPM dyes. Using a doughnut beam excitation from a 980 nm diode laser and detecting at 800 nm, we achieve a resolution of sub 50 nm, 1/20th of the excitation wavelength, in imaging of single UCNP through 93 μm thick liver tissue. This method offers a simple solution for deep tissue super resolution imaging and single molecule tracking.

Chen, Q, Zhou, Y & Nimbalkar, S 2018, 'Closure to “Estimation of Passive Earth Pressure against Rigid Retaining Wall Considering Arching Effect in Cohesive-Frictional Backfill under Translation Mode” by Yanyan Cai, Qingsheng Chen, Yitao Zhou, Sanjay Nimbalkar, and Jin Yu', International Journal of Geomechanics, vol. 18, no. 7, pp. 07018012-07018012.
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Chen, Q, Zhou, Y & Nimbalkar, S 2018, 'Closure to 'Estimation of passive earth pressure against rigid retaining wall considering arching effect in cohesive- frictional backfill under translation mode' by Yanyan Cai, Qingsheng Chen, Yitao Zhou, Sanjay Nimbalkar, and Jin Yu', International Journal of Geomechanics, vol. 18, no. 7.
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Chen, S, Wang, Z, Liang, J & Yuan, X 2018, 'Uncertainty-aware visual analytics for exploring human behaviors from heterogeneous spatial temporal data', Journal of Visual Languages & Computing, vol. 48, pp. 187-198.
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© 2018 Elsevier Ltd When analyzing human behaviors, we need to construct the human behaviors from multiple sources of data, e.g. trajectory data, transaction data, identity data, etc. The problems we're facing are the data conflicts, different resolution, missing and conflicting data, which together lead to the uncertainty in the spatial temporal data. Such uncertainty in data leads to difficulties and even failure in the visual analytics task for analyzing people behavior, pattern and outliers. However, traditional automatic methods can not solve the problems in such complex scenario, where the uncertain and conflicting patterns are not well-defined. To solve the problems, we proposed a semi-automatic approach, for users to solve the conflicts and identify the uncertainties. To be general, we summarized five types of uncertainties and solutions to conduct the tasks of behavior analysis. Combined with the uncertainty-aware methods, we proposed a visual analytics system to analyze human behaviors, detect patterns and find outliers. Case studies from the IEEE VAST Challenge 2014 dataset confirm the effectiveness of our approach.

Chen, S, Yu, H & Fang, J 2018, 'A novel multi-cell tubal structure with circular corners for crashworthiness', Thin-Walled Structures, vol. 122, pp. 329-343.
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© 2017 Elsevier Ltd Multi-cell structures have proven to own excellent energy absorbing capability and lightweight effect in the automotive and aerospace industries. The cross-sectional configuration of the multi-cell structure has a significant effect on crashworthiness. Unlike existing multi-cell tubes, a new type of five-cell profile with four circular elements at the corners (C5C) was proposed in this study. To investigate the crashworthiness of the new C5C tube, finite element (FE) models were first established by using the nonlinear finite element code LS-DYNA and validated with experimental results. Following that, the comparison of the C5C tube and other multi-cell tubes with the same mass was conducted to quantify the relative merits of the C5C tube. Then, a detailed study was performed to analyze the effect of the corner-cell size and wall thickness. Finally, the optimization design was carried out to seek the optimal structure. The results showed that the new multi-cell structure can absorb much more crash energy than other four types of tubes. Moreover, the energy absorption of this new multi-cell tube C5C was affected by the corner-cell size and wall thickness significantly. A proper corner-cell size and slightly thicker internal ribs were recommended. In addition, the multi-objective particle swarm optimization (MOPSO) algorithm and radial basis function (RBF) surrogate model can optimize the structure effectively. The outcomes of the present study will facilitate the design of multi-cell structures with better crashworthiness.

Chen, S-L, Qin, P-Y, Lin, W & Guo, YJ 2018, 'Pattern-Reconfigurable Antenna With Five Switchable Beams in Elevation Plane', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 3, pp. 454-457.
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© 2017 IEEE. Pattern-reconfigurable antennas with multiple switchable beams, especially with both boresight and endfire directions, are highly desired for wireless communications. In this letter, a novel pattern-reconfigurable antenna is proposed that provides an efficient solution. By reconfiguring parasitic striplines placed around a radiating dipole and reflecting metal pieces under the dipole using p-i-n diodes, the antenna main beam can be switched to five directions in the elevation plane, approximately from-90(left endfire),-45 , 0 (boresight),+45 to +90(right endfire). The proposed antenna operates at 2.45 GHz with dimensions of about 0.57λ× 0.45\lambda×, 0.28λ. An antenna prototype is fabricated and measured. For all five directional beams, the measured S-{11}| values are below 13 dB, and the measured realized gains range from 5.2 to 6.5 dBi. They agree reasonably well with the simulated ones.

Chen, W, Deng, W, Xu, X, Zhao, X, Vo, JN, Anwer, AG, Williams, TC, Cui, H & Goldys, EM 2018, 'Photoresponsive endosomal escape enhances gene delivery using liposome–polycation–DNA (LPD) nanovectors', Journal of Materials Chemistry B, vol. 6, no. 32, pp. 5269-5281.
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Light-triggered endolysosomal escape enhances gene delivery by photoresponsive LPD nanoparticles.

Chen, W, Peng, J, Hong, H, Shahabi, H, Pradhan, B, Liu, J, Zhu, A-X, Pei, X & Duan, Z 2018, 'Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China', Science of The Total Environment, vol. 626, pp. 1121-1135.
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© 2018 Elsevier B.V. The preparation of a landslide susceptibility map is considered to be the first step for landslide hazard mitigation and risk assessment. However, these maps are accepted as end products that can be used for land use planning. The main goal of this study is to assess and compare four advanced machine learning techniques, namely the Bayes’ net (BN), radical basis function (RBF) classifier, logistic model tree (LMT), and random forest (RF) models, for landslide susceptibility modelling in Chongren County, China. A total of 222 landslide locations were identified in the study area using historical reports, interpretation of aerial photographs, and extensive field surveys. The landslide inventory data was randomly split into two groups with a ratio of 70/30 for training and validation purposes. Fifteen landslide conditioning factors were prepared for landslide susceptibility modelling. The spatial correlation between landslides and conditioning factors was analyzed using the information gain (IG) method. The BN, RBF classifier, LMT, and RF models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) and statistical measures, including sensitivity, specificity, and accuracy, were employed to validate and compare the predictive capabilities of the models. Out of the tested models, the RF model had the highest sensitivity, specificity, and accuracy values of 0.787, 0.716, and 0.752, respectively, for the training dataset. Overall, the RF model produced an optimized balance for the training and validation datasets in terms of AUC values and statistical measures. The results of this study also demonstrate the benefit of selecting optimal machine learning techniques with proper conditioning selection methods for landslide susceptibility modelling.

Chen, W, Simpson, JM, March, LM, Blyth, FM, Bliuc, D, Tran, T, Nguyen, TV, Eisman, JA & Center, JR 2018, 'Comorbidities Only Account for a Small Proportion of Excess Mortality After Fracture: A Record Linkage Study of Individual Fracture Types', Journal of Bone and Mineral Research, vol. 33, no. 5, pp. 795-802.
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ABSTRACT   Nonhip, nonvertebral (NHNV) fractures constitute the majority of osteoporotic fractures, but few studies have examined the association between these fractures, comorbidity, and mortality. Our objective was to examine the relationship between individual nonhip, nonvertebral fractures, comorbidities, and mortality. The prospective population-based cohort of 267,043 subjects (45 and Up Study, Australia) had baseline questionnaires linked to hospital administrative and all-cause mortality data from 2006 to 2013. Associations between fracture and mortality were examined using multivariate, time-dependent Cox models, adjusted for age, prior fracture, body mass index, smoking, and comorbidities (cardiovascular disease, diabetes, stroke, thrombosis, and cancer), and survival function curves. Population attributable fraction was calculated for each level of risk exposure. During 1,490,651 person-years, women and men experienced 7571 and 4571 fractures and 7064 deaths and 11,078 deaths, respectively. In addition to hip and vertebral fractures, pelvis, humerus, clavicle, rib, proximal tibia/fibula, elbow and distal forearm fractures in both sexes, and ankle fractures in men were associated with increased multivariable-adjusted mortality hazard ratios ranging from 1.3 to 3.4. Comorbidity independently added to mortality such that a woman with a humeral fracture and 1 comorbidity had a similarly reduced 5-year survival as that of a woman with a hip fracture and no comorbidities. Population mortality attributable to any fracture without comorbidity was 9.2% in women and 5.3% in men. All proximal nonhip, nonvertebral fractures in women and men were associated with increased mortality risk. Coexistent comorbidities independently further increased mortality. Population attributable risk for mortality for fractures was similar to cardiovascul...

Chen, X, Li, Y, Li, J & Gu, X 2018, 'A dual-loop adaptive control for minimizing time response delay in real-time structural vibration control with magnetorheological (MR) devices', Smart Materials and Structures, vol. 27, no. 1, pp. 015005-015005.
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© 2017 IOP Publishing Ltd. Time delay is a challenge issue faced by the real-time control application of the magnetorheological (MR) devices. Not to deal with it properly may jeopardize the effectiveness of the control, even lead to instability of the control system or catastrophic failure. This paper proposes a dual-loop adaptive control to address the response time delay associated with MR devices. In the proposed dual-loop control, the inner loop is designed to compensate the time delay of MR device induced by the PWM current driver. While the outer loop control can be any structural control algorithm with aims to reducing structural responses of a building during extreme loadings. Here an adaptive control strategy is adopted. To verify the proposed dual-loop control, a smart base isolation system employing magnetorheological elastomer base isolators is used as an example to illustrate the control effect. Numerical study is then conducted using a 5 -storey shear building model equipped with smart base isolation system. The result shows that with the implementation of the inner loop, the control current can instantly follow the control command which reduce the possibility of instability caused by the time delay. Comparative studies are conducted between three control strategies, i.e. dual-loop control, Lyapunov's direct method based control and optimal passive base isolation control. The results of the study have demonstrated that the proposed dual-loop control strategy can achieve much better performance than the other two control strategies.

Chen, X, Porto, CL, Chen, Z, Merenda, A, Allioux, F-M, d'Agostino, R, Magniez, K, Dai, XJ, Palumbo, F & Dumée, LF 2018, 'Single step synthesis of Janus nano-composite membranes by atmospheric aerosol plasma polymerization for solvents separation', Science of The Total Environment, vol. 645, pp. 22-33.
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Solvent permeation across membranes is limited due to physical resistance to diffusion from the selective layer within the membrane and to plasticizing effects generated by the solvent molecules onto the polymeric macromolecular matrix. Nano-composite thin film membranes provide promising routes to generate controlled microstructural separation materials with higher selectivities and permeabilities. Here, the fabrication of nano-composite based on octamethyl-polyhedral oligomeric silsesquioxane - hexamethyldisiloxane thin film membranes is demonstrated by aerosol assisted atmospheric plasma deposition onto pre-formed nano-porous membrane supports for the first time. Stable, atomically smooth and continuous solid films with controllable thickness down to 50 nm were achieved. The deposition process allowed for the control of the wettability of the surfaces to water and organic solvents, leading to the generation of hydrophobic but alcohol-philic surfaces. The liquid entry pressure of the films to water was found to be 8 bar from plasma polymerization as oppose to 3 bar for the bare nano-porous support only. In addition, the ideal separation selectivity for ethanol to water, up to 6.5, highlight the impact of both the surface energy and level of cross-linking of the hexamethyldisiloxane nanostructures on the diffusion mechanisms. This new atmospheric plasma deposition strategy opens-up cost-effective and environmentally friendly routes for the design of the smart Janus membrane with customizable properties and performance.

Chen, X, Yuan, G, Wang, W, Nie, F, Chang, X & Huang, JZ 2018, 'Local Adaptive Projection Framework for Feature Selection of Labeled and Unlabeled Data', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6362-6373.
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Most feature selection methods first compute a similarity matrix by assigning a fixed value to pairs of objects in the whole data or to pairs of objects in a class or by computing the similarity between two objects from the original data. The similarity matrix is fixed as a constant in the subsequent feature selection process. However, the similarities computed from the original data may be unreliable, because they are affected by noise features. Moreover, the local structure within classes cannot be recovered if the similarities between the pairs of objects in a class are equal. In this paper, we propose a novel local adaptive projection (LAP) framework. Instead of computing fixed similarities before performing feature selection, LAP simultaneously learns an adaptive similarity matrix and a projection matrix with an iterative method. In each iteration, is computed from the projected distance with the learned and W is computed with the learned . Therefore, LAP can learn better projection matrix by weakening the effect of noise features with the adaptive similarity matrix. A supervised feature selection with LAP (SLAP) method and an unsupervised feature selection with LAP (ULAP) method are proposed. Experimental results on eight data sets show the superiority of SLAP compared with seven supervised feature selection methods and the superiority of ULAP compared with five unsupervised feature selection methods.

Chen, X, Yuan, Z & Ni, B-J 2018, 'Nitrite accumulation inside sludge flocs significantly influencing nitrous oxide production by ammonium-oxidizing bacteria', Water Research, vol. 143, pp. 99-108.
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© 2018 Elsevier Ltd This work aims to clarify the role of potential nitrite (NO2−) accumulation inside sludge flocs in N2O production by ammonium-oxidizing bacteria (AOB) at different dissolved oxygen (DO) levels with focus on the conditions of no significant bulk NO2− accumulation (<0.2 mg N/L). To this end, an augmented nitrifying sludge with much higher abundance of nitrite-oxidizing bacteria (NOB) than AOB was enriched and then used for systematically designed batch tests, which targeted a range of DO levels from 0 to 3.0 mg O2/L at a fixed ammonium concentration of 10 mg N/L. A two-pathway N2O model was applied to facilitate the interpretation of batch experimental data, thus shedding light on the relationships between N2O production pathways and key process parameters (i.e., DO and NO2− accumulation inside sludge flocs). The results demonstrated (i) the biomass specific N2O production rate firstly increased and then decreased with DO, with the maximum value of 3.03 ± 0.05 mg N/h/g VSS obtained at DO level of 0.75 mg O2/L, (ii) the AOB denitrification pathway for N2O production was dominant (98.0%) at all DO levels tested even without significant bulk NO2− accumulation (<0.2 mg N/L) observed in the system, but its contribution decreased with DO, (iii) DO had a positive impact on the hydroxylamine pathway for N2O production which therefore increased with DO, and (iv) the nitrite accumulation existed inside the sludge flocs and induced significant N2O production from the AOB denitrification pathway.

Chen, Y, Dong, Y, Sun, Y & Liang, J 2018, 'A Multi-comparable visual analytic approach for complex hierarchical data', Journal of Visual Languages & Computing, vol. 47, pp. 19-30.
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© 2018 Elsevier Ltd Maximum residue limit (MRL) standard which specifies the highest level of every pesticide residue in different agricultural products plays a critical role in food safety. However, such standards which related to the characteristics of pesticides and the classification of agricultural products which organized into a hierarchical structure are complex and vary widely across different regions or countries. So it is a big challenge to compare multi-regional MRL standard data comprehensively. In this paper, we present a multi-comparable visual analytic approach for complex hierarchical data and a visual analytics system (McVA) to support multiple comparison and evaluation of MRL standard. With a cooperative multi-view visual design, our proposed approach links the hierarchies of MRL datasets and provides the capacity for comparison at different levels and dimensions. We also introduce a metric model for evaluating the completeness and strictness of MRL standards quantitatively. The case study of real problems and the positive feedback from domain experts demonstrate the effectiveness of this approach.

Chen, Y, Su, QP, Sun, Y & Yu, L 2018, 'Visualizing Autophagic Lysosome Reformation in Cells Using In Vitro Reconstitution Systems', Current Protocols in Cell Biology, vol. 78, no. 1, pp. 11.24.1-11.24.15.
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AbstractAutophagy is a lysosome‐based degradation pathway. Autophagic lysosome reformation (ALR) is a lysosomal membrane recycling process that marks the terminal step of autophagy. During ALR, LAMP1‐positive tubules, named reformation tubules, are extruded from autolysosomes, and nascent lysosomes are generated from these tubules. By combining proteomic analysis of purified autolysosomes and RNA interference screening of identified candidates, we systematically elucidated the ALR pathway at the molecular level. Based on the key components clathrin, PtdIns(4,5)P2, and the motor protein KIF5B, among others, we reconstituted this process in vitro. This unit describes a detailed method for visualizing ALR in cells during the autophagy process. This unit also present a protocol for reconstituting the ALR tubular protrusion and elongation process in vitro and three methods for preparing materials for in vitro reconstitution: (1) autolysosome purification from cultured cells, (2) liposome preparation, and (3) KIF5B purification and quality testing. © 2018 by John Wiley & Sons, Inc.

Chen, Y, Wu, Y, Wang, D, Li, H, Wang, Q, Liu, Y, Peng, L, Yang, Q, Li, X, Zeng, G & Chen, Y 2018, 'Understanding the mechanisms of how poly aluminium chloride inhibits short-chain fatty acids production from anaerobic fermentation of waste activated sludge', Chemical Engineering Journal, vol. 334, pp. 1351-1360.
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© 2017 Elsevier B.V. Poly aluminum chloride (PAC) is accumulated in waste activated sludge at high levels. However, details of how PAC affects short-chain fatty acids (SCFA) production from anaerobic sludge fermentation has not been documented. This work therefore aims to fill this knowledge gap by analyzing the impact of PAC on the aggregate of sludge flocs, disruption of extracellular polymeric substances (EPS), and the bio-processes of hydrolysis, acidogenesis, and methanogenesis. The relationship between SCFA production and different aluminum species (i.e., Ala, Alb, and Alc) was also identified by controlling different OH/Al ratio and pH in different fermentation systems. Experimental results showed that with the increase of PAC addition from 0 to 40 mg Al per gram of total suspended solids, SCFA yield decreased from 212.2 to 138.4 mg COD/g volatile suspended solids. Mechanism exploration revealed that PAC benefited the aggregates of sludge flocs and caused more loosely- and tightly-bound extracellular polymeric substances remained in sludge cells. Besides, it was found that the hydrolysis, acidiogenesis, and methanogenesis processes were all inhibited by PAC. Although three types of Al species, i.e., Ala (Al monomers, dimer, and trimer), Alb (Al13(AlO4Al12(OH)24(H2O)7 + 12), and Alc (Al polymer molecular weight normally larger than 3000 Da), were co-existed in fermentation systems, their impacts on SCFA production were different. No correlation was found between SCFA and Ala, whereas SCFA production decreased with the contents of Alb and Alc. Compared with Alb, Alc was the major contributor to the decreased SCFA production (R2 = 0.5132 vs R2 = 0.98). This is the first report revealing the underlying mechanism of how PAC affects SCFA production and identifying the contribution of different Al species to SCFA inhibition.

Chen, Y, Yang, D & Yu, J 2018, 'Multi-UAV Task Assignment With Parameter and Time-Sensitive Uncertainties Using Modified Two-Part Wolf Pack Search Algorithm', IEEE Transactions on Aerospace and Electronic Systems, vol. 54, no. 6, pp. 2853-2872.
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Chen, Z, Wang, D, Sun, M, Hao Ngo, H, Guo, W, Wu, G, Jia, W, Shi, L, Wu, Q, Guo, F & Hu, H-Y 2018, 'Sustainability evaluation and implication of a large scale membrane bioreactor plant', Bioresource Technology, vol. 269, pp. 246-254.
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Membrane bioreactor (MBR) technology is receiving increasing attention in wastewater treatment and reuse. This study presents an integral sustainability evaluation of a full scale MBR plant. The plant is capable of achieving prominent technical performance in terms of high compliance rate, low variation in effluent quality and high removal efficiency during long term operation. It is also more responsive to the new local standard with rigorous limits. However, electricity consumption is found to be the dominant process resulting in elevated life cycle environmental impacts and costs, accounting for 51.6% of the costs. As such, it is suggested to optimize energy use in MBR unit and implement sludge treatment and management. The prolonged membrane life span could also contribute largely to reduced life cycle environmental concerns and expenses. This study is of great theoretical significance and applicable value in guaranteeing the performance and sustainability of large scale MBR schemes.

Chen, Z, Yu, T, Ngo, HH, Lu, Y, Li, G, Wu, Q, Li, K, Bai, Y, Liu, S & Hu, H-Y 2018, 'Assimilable organic carbon (AOC) variation in reclaimed water: Insight on biological stability evaluation and control for sustainable water reuse', Bioresource Technology, vol. 254, pp. 290-299.
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This review highlights the importance of conducting biological stability evaluation due to water reuse progression. Specifically, assimilable organic carbon (AOC) has been identified as a practical indicator for microbial occurrence and regrowth which ultimately influence biological stability. Newly modified AOC bioassays aimed for reclaimed water are introduced. Since elevated AOC levels are often detected after tertiary treatment, the review emphasizes that actions can be taken to either limit AOC levels prior to disinfection or conduct post-treatment (e.g. biological filtration) as a supplement to chemical oxidation based approaches (e.g. ozonation and chlorine disinfection). During subsequent distribution and storage, microbial community and possible microbial regrowth caused by complex interactions are discussed. It is suggested that microbial surveillance, AOC threshold values, real-time field applications and surrogate parameters could provide additional information. This review can be used to formulate regulatory plans and strategies, and to aid in deriving relevant control, management and operational guidance.

Chenari, RJ, Fatahi, B, Ghorbani, A & Alamoti, MN 2018, 'Evaluation of strength properties of cement stabilized sand mixed with EPS beads and fly ash', Geomechanics and Engineering, vol. 14, no. 6, pp. 533-544.
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The importance of using materials cost effectively to enhance the strength and reduce the cost, and weight of earth fill materials in geotechnical engineering led researchers to seek for modifying the soil properties by adding proper additives. Lightweight fill materials made of soil, binder, water, and Expanded polystyrene (EPS) beads are increasingly being used in geotechnical practices. This paper primarily investigates the behavior of sandy soil, modified by EPS particles. Besides, the mechanical properties of blending sand, EPS and the binder material such as fly ash and cement were examined in different mixing ratios using a number of various laboratory studies including the Modified Standard Proctor (MSP) test, the Unconfined Compressive Strength (UCS) test, the California Bearing Ratio (CBR) test and the Direct Shear test (DST). According to the results, an increase of 0.1% of EPS results in a reduction of the density of the mixture for 10%, as well as making the mixture more ductile rather than brittle. Moreover, the compressive strength, CBR value and shear strength parameters of the mixture decreases by an increase of the EPS beads, a trend on the contrary to the increase of cement and fly ash content.

Cheng, D, Gong, Y, Chang, X, Shi, W, Hauptmann, A & Zheng, N 2018, 'Deep feature learning via structured graph Laplacian embedding for person re-identification', Pattern Recognition, vol. 82, pp. 94-104.
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Learning the distance metric between pairs of examples is of great importance for visual recognition, especially for person re-identification (Re-Id). Recently, the contrastive and triplet loss are proposed to enhance the discriminative power of the deeply learned features, and have achieved remarkable success. As can be seen, either the contrastive or triplet loss is just one special case of the Euclidean distance relationships among these training samples. Therefore, we propose a structured graph Laplacian embedding algorithm, which can formulate all these structured distance relationships into the graph Laplacian form. The proposed method can take full advantages of the structured distance relationships among these training samples, with the constructed complete graph. Besides, this formulation makes our method easy-to-implement and super-effective. When embedding the proposed algorithm with the softmax loss for the CNN training, our method can obtain much more robust and discriminative deep features with inter-personal dispersion and intra-personal compactness, which is essential to person Re-Id. We did experiments on top of three popular networks, namely AlexNet [1], DGDNet [2] and ResNet50 [3], on recent four widely used Re-Id benchmark datasets, and it shows that the proposed structure graph Laplacian embedding is very effective.

Cheng, D, Ngo, HH, Guo, W, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD, Zhou, J & Ni, B 2018, 'Anaerobic membrane bioreactors for antibiotic wastewater treatment: Performance and membrane fouling issues', Bioresource Technology, vol. 267, pp. 714-724.
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© 2018 Elsevier Ltd Antibiotic wastewater has become a major concern due to the toxicity and recalcitrance of antibiotics. Anaerobic membrane bioreactors (AnMBRs) are considered alternative technology for treating antibiotic wastewater because of their advantages over the conventional anaerobic processes and aerobic MBRs. However, membrane fouling remains the most challenging issue in the AnMBRs’ operation and this limits their application. This review critically discusses: (i) antibiotics removal and antibiotic resistance genes (ARGs) in different types of AnMBRs and the impact of antibiotics on membrane fouling and (ii) the integrated AnMBRs systems for fouling control and removal of antibiotics. The presence of antibiotics in AnMBRs could aggravate membrane fouling by influencing fouling-related factors (i.e., sludge particle size, extracellular polymeric substances (EPS), soluble microbial products (SMP), and fouling-related microbial communities). Conclusively, integrated AnMBR systems can be a practical technology for antibiotic wastewater treatment.

Cheng, DL, Ngo, HH, Guo, WS, Chang, SW, Nguyen, DD, Kumar, SM, Du, B, Wei, Q & Wei, D 2018, 'Problematic effects of antibiotics on anaerobic treatment of swine wastewater', Bioresource Technology, vol. 263, pp. 642-653.
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Swine wastewaters with high levels of organic pollutants and antibiotics have become serious environmental concerns. Anaerobic technology is a feasible option for swine wastewater treatment due to its advantage in low costs and bioenergy production. However, antibiotics in swine wastewater have problematic effects on micro-organisms, and the stability and performance of anaerobic processes. Thus, this paper critically reviews impacts of antibiotics on pH, COD removal efficiencies, biogas and methane productions as well as the accumulation of volatile fatty acids (VFAs) in the anaerobic processes. Meanwhile, impacts on the structure of bacteria and methanogens in anaerobic processes are also discussed comprehensively. Furthermore, to better understand the effect of antibiotics on anaerobic processes, detailed information about antimicrobial mechanisms of antibiotics and microbial functions in anaerobic processes is also summarized. Future research on deeper knowledge of the effect of antibiotics on anaerobic processes are suggested to reduce their adverse environmental impacts.

Cheng, DL, Ngo, HH, Guo, WS, Liu, YW, Zhou, JL, Chang, SW, Nguyen, DD, Bui, XT & Zhang, XB 2018, 'Bioprocessing for elimination antibiotics and hormones from swine wastewater', Science of The Total Environment, vol. 621, pp. 1664-1682.
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© 2017 Elsevier B.V. Antibiotics and hormones in swine wastewater have become a critical concern worldwide due to the severe threats to human health and the eco-environment. Removal of most detectable antibiotics and hormones, such as sulfonamides (SAs), SMs, tetracyclines (TCs), macrolides, and estrogenic hormones from swine wastewater utilizing various biological processes were summarized and compared. In biological processes, biosorption and biodegradation are the two major removal mechanisms for antibiotics and hormones. The residuals in treated effluents and sludge of conventional activated sludge and anaerobic digestion processes can still pose risks to the surrounding environment, and the anaerobic processes’ removal efficiencies were inferior to those of aerobic processes. In contrast, membrane bioreactors (MBRs), constructed wetlands (CWs) and modified processes performed better because of their higher biodegradation of toxicants. Process modification on activated sludge, anaerobic digestion and conventional MBRs could also enhance the performance (e.g. removing up to 98% SMs, 88.9% TCs, and 99.6% hormones from wastewater). The hybrid process combining MBRs with biological or physical technology also led to better removal efficiency. As such, modified conventional biological processes, advanced biological technologies and MBR hybrid systems are considered as a promising technology for removing toxicants from swine wastewater.

Cheng, L, Acuna, P, Aguilera, RP, Jiang, J, Wei, S, Fletcher, JE & Lu, DDC 2018, 'Model Predictive Control for DC–DC Boost Converters With Reduced-Prediction Horizon and Constant Switching Frequency', IEEE Transactions on Power Electronics, vol. 33, no. 10, pp. 9064-9075.
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© 1986-2012 IEEE. The implementation of multistep direct model predictive control (MPC) for DC-DC boost converters overcomes the well-known issue of nonminimum phase behavior. However, it can lead to a high computational burden depending on the prediction horizon length. In this paper, a simple and computationally efficient MPC method for DC-DC boost converters is proposed. The key novelty of the presented control strategy lies in the way dynamic references are handled. The control strategy is capable of providing suitable references for the inductor current and the output voltage, without requiring additional control loops. Moreover, this reference design allows the predictive controller to be implemented with a single-step prediction horizon. Thus, a significant reduction in the required real-time calculations executed in the control hardware is achieved. To obtain constant switching frequency, the power switch commutation instants within a sampling period are considered as control inputs. Therefore, the predictive controller is formulated as a continuous control set MPC. Additionally, the proposed formulation is able to deal with different operation modes of the converter without changing the controller structure. Finally, an observer is used to dynamically modify the reference to provide robustness to system parameter uncertainties. Simulation and experimental results show an accurate tracking of dynamic inductor current and output voltage references, while respecting the restrictions on maximum inductor current levels of the converter.

Cheng, P, Chen, Z, Zhang, JA, Li, Y & Vucetic, B 2018, 'A Unified Precoding Scheme for Generalized Spatial Modulation', IEEE Transactions on Communications, vol. 66, no. 6, pp. 2502-2514.
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© 1972-2012 IEEE. Generalized spatial modulation (GSM) activates Nt (1 ≤ nt < Nt) available transmit antennas, and information is conveyed through nt modulated symbols as well as the index of the nt activated antennas. GSM strikes an attractive tradeoff between spectrum efficiency and energy efficiency. Linear precoding that exploits channel state information at the transmitter enhances the system error performance. For GSM with nt=1 (the traditional SM), the existing precoding methods suffer from high computational complexity. On the other hand, GSM precoding for nt ≥ 2 is not thoroughly investigated in the open literature. In this paper, we develop a unified precoding design for GSM systems, which universally works for all nt values. Based on the maximum minimum Euclidean distance criterion, we find that the precoding design can be formulated as a large-scale nonconvex quadratically constrained quadratic program problem. Then, we transform this challenging problem into a sequence of unconstrained subproblems by leveraging augmented Lagrangian and dual ascent techniques. These subproblems can be solved in an iterative manner efficiently. Numerical results show that the proposed method can substantially improve the system error performance relative to the GSM without precoding and features extremely fast convergence rate with a very low computational complexity.

Cheng, T, Lu, DD-C & Qin, L 2018, 'Non-Isolated Single-Inductor DC/DC Converter With Fully Reconfigurable Structure for Renewable Energy Applications.', IEEE Trans. Circuits Syst. II Express Briefs, vol. 65-II, no. 3, pp. 351-355.
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© 2017 IEEE. A novel non-isolated three-port converter (NITPC) is introduced in this brief. The purpose of this topology is to integrate a regenerative load such as DC bus and motor with dynamic braking, instead of the widely reported consuming load, with a photovoltaic (PV)-battery system. Conventional methods require either a separate DC-DC converter to process the reversible power flow or employing an isolated three-port converter (TPC), which allows bi-directional power flow between any two ports. However, these methods require many switches, which increases the converter size and control complexity. This brief hence presents a compact but fully functional design by combining and integrating basic converters to form a simplified single-inductor converter structure while keeping a minimum amount of switches. The resultant converter is fully reconfigurable that all possible power flow combinations among the sources and load are achieved through different switching patterns, while preserving the single power processing feature of TPC. This brief presents a design example of the proposed NITPC for a PV-battery powered DC microgrid. Detailed circuitry analysis, operation principles of both DC grid-connected and islanded modes, and experimental results of different modes in steady state and mode transitions are presented.

Cheng, X, Jiang, Z, Monaghan, BJ, Longbottom, RJ, Wei, D, Hee, AC & Jiang, L 2018, 'Degradation of ferritic stainless steels at 1200 °C in air', Materials and Corrosion, vol. 69, no. 1, pp. 63-75.
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Three commercial ferritic stainless steels were investigated at 1200 °C by a thermogravimetric analyser (TGA) in air. The oxidation kinetics of the ferritic stainless steels differed significantly. The adhesion of the Cr2O3 scale, the morphology of the SiO2, with or without (Cr, Mn)3O4 spinel on the top can greatly influence the oxidation and the degradation behaviour of the steels. Although the SUS430 steel had less Cr among the ferritic stainless steels (16.2 wt% Cr), it did not show more degradation behaviour than the B443NT steel (21.0 wt% Cr). The spallation of the protective oxide scale on the B443NT steel was caused by vacancy condensation at the scale/substrate interface where the SiO2 particles were and the developed compressive stresses within the oxide scale during oxidation. (Cr, Mn)3O4 spinel on the top of the Cr2O3 scale on the B445J1M steel influenced its evaporation rate. The thermodynamic aspect of the chemical composition and oxidation atmosphere of the Fe–Cr–O system was also discussed.

Cheng, Z, Zhang, X, Shen, S, Yu, S, Ren, J & Lin, R 2018, 'T-Trail: Link Failure Monitoring in Software-Defined Optical Networks', Journal of Optical Communications and Networking, vol. 10, no. 4, pp. 344-344.
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Monitoring trail (m-trail) provides a striking mechanism for fast and unambiguous link failure localization in all-optical networks. However, allocating dedicated supervisory lightpaths (m-trail) undoubtedly increases total network cost. Accordingly, how to maximally reduce monitoring cost in an optical network is an important issue. To this end, we propose a concept of traffic trail (t-trail) that uses traffic lightpaths, instead of dedicated supervisory lightpaths, to localize a single link failure in the context of a software-defined optical network (SDON). The central controller of an SDON collects routing information of all t-trails in the network. Thus, any link failure can be localized according to the ON-OFF status of the traversing t-trails. We first formulate the problem as an integer linear programming (ILP) model. Since the ILP is not feasible for solving the problem in large-size networks, an efficient heuristic algorithm t-trail allocation (TTA) is proposed to address it. We conduct extensive simulations to evaluate the performance of TTA. The results show that compared with the existing m-trail schemes, TTA can reduce total costs by 20.91% on average.

Chi, L, Li, B, Zhu, X, Pan, S & Chen, L 2018, 'Hashing for Adaptive Real-Time Graph Stream Classification With Concept Drifts', IEEE Transactions on Cybernetics, vol. 48, no. 5, pp. 1591-1604.
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Many applications involve processing networked streaming data in a timely manner. Graph stream classification aims to learn a classification model from a stream of graphs with only one-pass of data, requiring real-time processing in training and prediction. This is a nontrivial task, as many existing methods require multipass of the graph stream to extract subgraph structures as features for graph classification which does not simultaneously satisfy "one-pass" and "real-time" requirements. In this paper, we propose an adaptive real-time graph stream classification method to address this challenge. We partition the unbounded graph stream data into consecutive graph chunks, each consisting of a fixed number of graphs and delivering a corresponding chunk-level classifier. We employ a random hashing function to compress the original node set of graphs in each chunk for fast feature detection when training chunk-level classifiers. Furthermore, a differential hashing strategy is applied to map unlimited increasing features (i.e., cliques) into a fixed-size feature space which is then used as a feature vector for stochastic learning. Finally, the chunk-level classifiers are weighted in an ensemble learning model for graph classification. The proposed method substantially speeds up the graph feature extraction and avoids unbounded graph feature growth. Moreover, it effectively offsets concept drifts in graph stream classification. Experiments on real-world and synthetic graph streams demonstrate that our method significantly outperforms existing methods in both classification accuracy and learning efficiency.

Chia, SR, Chew, KW, Show, PL, Yap, YJ, Ong, HC, Ling, TC & Chang, J-S 2018, 'Analysis of Economic and Environmental Aspects of Microalgae Biorefinery for Biofuels Production: A Review', Biotechnology Journal, vol. 13, no. 6, pp. 1700618-1700618.
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Chia, SR, Ong, HC, Chew, KW, Show, PL, Phang, S-M, Ling, TC, Nagarajan, D, Lee, D-J & Chang, J-S 2018, 'Sustainable approaches for algae utilisation in bioenergy production', Renewable Energy, vol. 129, pp. 838-852.
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Chia, SR, Show, PL, Phang, S-M, Ling, TC & Ong, HC 2018, 'Sustainable approach in phlorotannin recovery from macroalgae', Journal of Bioscience and Bioengineering, vol. 126, no. 2, pp. 220-225.
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Chikara, RK, Chang, EC, Lu, Y-C, Lin, D-S, Lin, C-T & Ko, L-W 2018, 'Monetary Reward and Punishment to Response Inhibition Modulate Activation and Synchronization Within the Inhibitory Brain Network', Frontiers in Human Neuroscience, vol. 12.
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© 2018 Chikara, Chang, Lu, Lin, Lin and Ko. A reward or punishment can modulate motivation and emotions, which in turn affect cognitive processing. The present simultaneous functional magnetic resonance imaging-electroencephalography study examines neural mechanisms of response inhibition under the influence of a monetary reward or punishment by implementing a modified stop-signal task in a virtual battlefield scenario. The participants were instructed to play as snipers who open fire at a terrorist target but withhold shooting in the presence of a hostage. The participants performed the task under three different feedback conditions in counterbalanced order: a reward condition where each successfully withheld response added a bonus (i.e., positive feedback) to the startup credit, a punishment condition where each failure in stopping deduced a penalty (i.e., negative feedback), and a no-feedback condition where response outcome had no consequences and served as a control setting. Behaviorally both reward and punishment conditions led to significantly down-regulated inhibitory function in terms of the critical stop-signal delay. As for the neuroimaging results, increased activities were found for the no-feedback condition in regions previously reported to be associated with response inhibition, including the right inferior frontal gyrus and the pre-supplementary motor area. Moreover, higher activation of the lingual gyrus, posterior cingulate gyrus (PCG) and inferior parietal lobule were found in the reward condition, while stronger activation of the precuneus gyrus was found in the punishment condition. The positive feedback was also associated with stronger changes of delta, theta, and alpha synchronization in the PCG than were the negative or no-feedback conditions. These findings depicted the intertwining relationship between response inhibition and motivation networks.

Chiu, SK, Saw, J, Huang, Y, Sonderegger, SE, Wong, NC, Powell, DR, Beck, D, Pimanda, JE, Tremblay, CS & Curtis, DJ 2018, 'A novel role for Lyl1 in primitive erythropoiesis', Development, vol. 145, no. 19.
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Stem Cell Leukemia (Scl or Tal1) and Lymphoblastic Leukemia 1 (Lyl1) are highly related members of the basic helix-loop-helix (bHLH) family of transcription factors that are co- expressed in the erythroid lineage. Previous studies suggest that Scl is essential for primitive erythropoiesis. However, analysis of single-cell RNA-sequencing data of early embryos showed that primitive erythroid cells express both Scl and Lyl1. Therefore, to determine whether Lyl1 can function in primitive erythropoiesis, we crossed conditional Scl knockout mice with mice expressing a Cre recombinase under the control of the Epo receptor, active in erythroid progenitors. Embryos with 20% expression of Scl from E9.5 survived to adulthood. However, mice with reduced expression of Scl and absence of Lyl1 (double knockout; DKO) died at E10.5 due to progressive loss of erythropoiesis. Gene expression profiling of DKO yolk sacs revealed loss of Gata1 and many of the known target genes of the SCL-GATA1 complex. ChIP-seq analyses showed that LYL1 exclusively bound a small subset of SCL targets including GATA1. Together, these data show for the first time that Lyl1 can maintain primitive erythropoiesis.

Choi, I, Milne, DN, Deady, M, Calvo, RA, Harvey, SB & Glozier, N 2018, 'Impact of Mental Health Screening on Promoting Immediate Online Help-Seeking: Randomized Trial Comparing Normative Versus Humor-Driven Feedback', JMIR Mental Health, vol. 5, no. 2, pp. e26-e26.
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Background Given the widespread availability of mental health screening apps, providing personalized feedback may encourage people at high risk to seek help to manage their symptoms. While apps typically provide personal score feedback only, feedback types that are user-friendly and increase personal relevance may encourage further help-seeking. Objective The aim of this study was to compare the effects of providing normative and humor-driven feedback on immediate online help-seeking, defined as clicking on a link to an external resource, and to explore demographic predictors that encourage help-seeking. Methods An online sample of 549 adults were recruited using social media advertisements. Participants downloaded a smartphone app known as “Mindgauge” which allowed them to screen their mental wellbeing by completing standardized measures on Symptoms (Kessler 6-item Scale), Wellbeing (World Health Organization [Five] Wellbeing Index), and Resilience (Brief Resilience Scale). Participants were randomized to receive normative feedback that compared their scores to a reference group or humor-driven feedback that presented their scores in a relaxed manner. Those who scored in the moderate or poor ranges in any measure were encouraged to seek help by clicking on a link to an external online resource. Results A total of 318 participants scored poorly on one or more measures and were provided with an external link after being randomized to receive normative or humor-driven feedback. There was no significant difference of feedback type on clicking on the external link acros...

Choi, I, Milne, DN, Deady, M, Calvo, RA, Harvey, SB & Glozier, N 2018, 'Impact of mental health screening on promoting immediate online help-seeking: Randomized trial comparing normative versus humor-driven feedback', Journal of Medical Internet Research, vol. 20, no. 4.
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Background: Given the widespread availability of mental health screening apps, providing personalized feedback may encourage people at high risk to seek help to manage their symptoms. While apps typically provide personal score feedback only, feedback types that are user-friendly and increase personal relevance may encourage further help-seeking. Objective: The aim of this study was to compare the effects of providing normative and humor-driven feedback on immediate online help-seeking, defined as clicking on a link to an external resource, and to explore demographic predictors that encourage help-seeking. Methods: An online sample of 549 adults were recruited using social media advertisements. Participants downloaded a smartphone app known as “Mindgauge” which allowed them to screen their mental wellbeing by completing standardized measures on Symptoms (Kessler 6-item Scale), Wellbeing (World Health Organization [Five] Wellbeing Index), and Resilience (Brief Resilience Scale). Participants were randomized to receive normative feedback that compared their scores to a reference group or humor-driven feedback that presented their scores in a relaxed manner. Those who scored in the moderate or poor ranges in any measure were encouraged to seek help by clicking on a link to an external online resource. Results: A total of 318 participants scored poorly on one or more measures and were provided with an external link after being randomized to receive normative or humor-driven feedback. There was no significant difference of feedback type on clicking on the external link across all measures. A larger proportion of participants from the Wellbeing measure (170/274, 62.0%) clicked on the links than the Resilience (47/179, 26.3%) or Symptoms (26/75, 34.7%) measures (? =60.35, P<.001). There were no significant demographic factors associated with help-seeking for the Resilience or Wellbeing measures. Participants with a previous episode of poor mental health were l...

Choi, Y, Naidu, G, Jeong, S, Lee, S & Vigneswaran, S 2018, 'Effect of chemical and physical factors on the crystallization of calcium sulfate in seawater reverse osmosis brine', Desalination, vol. 426, pp. 78-87.
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© 2017 Elsevier B.V. A major challenge of seawater reverse osmosis (SWRO) desalination process corresponds to the management of concentrated brine waste because discharging the brine back into the sea influences the marine ecosystem and incurs additional costs to plants. A membrane distillation crystallizer (MDC) can further produce clean water and simultaneously recover valuable resources from the concentrated brine; this is more environmentally and economically optimal. SWRO brine contains salts, which contribute to scaling development during the MDC operation. Hence, the main goals of this study was to observe the crystallization tendency of calcium sulfate (CaSO4) under high salinity and, to examine other inorganic and organic compounds and operational conditions that affect the CaSO4 crystallization. The crystallization tendency of CaSO4 in SWRO brine was examined with respect to different temperatures; changes in pH values; and in the presence of co-existing ions, chemical agents, and organic matters as well as physical factors. The results showed that the size and quantity of crystals formed increased at higher temperatures. Furthermore, an increase in the pH values increased the crystal size. At higher pH, the complexion of NaCl along with CaSO4 was created. Moreover, stirring enhanced CaSO4 crystal formation due to the kinetic mechanism.

Choi, Y, Naidu, G, Jeong, S, Lee, S & Vigneswaran, S 2018, 'Fractional-submerged membrane distillation crystallizer (F-SMDC) for treatment of high salinity solution', Desalination, vol. 440, pp. 59-67.
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© 2018 Elsevier B.V. Membrane distillation with crystallization (MDC) is an attractive process for high saline seawater reverse osmosis (SWRO) brine treatment. MDC produces additional fresh water while simultaneously recovering valuable resources. This study developed a novel approach of fractional-submerged MDC (F-SMDC) process, in which MD and crystallizer are integrated in a feed tank with a submerged membrane. F-SMDC principle is based on the presence of temperature/concentration gradient (TG/CG) in the feed reactor. The operational conditions at the top portion of the feed reactor (higher temperature and lower feed concentration) was well suited for MD operation, while the bottom portion of the reactor (lower temperature and higher concentration) was favourable for crystal growth. F-SMDC performance with direct contact MD to treat brine and produce sodium sulfate (Na2SO4) crystals using TG/CG showed positive results. The TG/CG approach in F-SMDC enabled to achieve higher water recovery for brine treatment with a volume concentration factor (VCF) of over 3.5 compared to VCF of 2.9 with a conventional S-MDC set-up. Further, the high feed concentration and low temperature at the reactor bottom in F-SMDC enabled the formation of Na2SO4 crystals with narrow crystal size distribution.

Chou, K-P, Prasad, M, Wu, D, Sharma, N, Li, D-L, Lin, Y-F, Blumenstein, M, Lin, W-C & Lin, C-T 2018, 'Robust Feature-Based Automated Multi-View Human Action Recognition System', IEEE Access, vol. 6, pp. 15283-15296.
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© 2013 IEEE. Automated human action recognition has the potential to play an important role in public security, for example, in relation to the multiview surveillance videos taken in public places, such as train stations or airports. This paper compares three practical, reliable, and generic systems for multiview video-based human action recognition, namely, the nearest neighbor classifier, Gaussian mixture model classifier, and the nearest mean classifier. To describe the different actions performed in different views, view-invariant features are proposed to address multiview action recognition. These features are obtained by extracting the holistic features from different temporal scales which are modeled as points of interest which represent the global spatial-temporal distribution. Experiments and cross-data testing are conducted on the KTH, WEIZMANN, and MuHAVi datasets. The system does not need to be retrained when scenarios are changed which means the trained database can be applied in a wide variety of environments, such as view angle or background changes. The experiment results show that the proposed approach outperforms the existing methods on the KTH and WEIZMANN datasets.

Chu Van, T, Ristovski, Z, Surawski, N, Bodisco, TA, Rahman, SMA, Alroe, J, Miljevic, B, Hossain, FM, Suara, K, Rainey, T & Brown, RJ 2018, 'Effect of sulphur and vanadium spiked fuels on particle characteristics and engine performance of auxiliary diesel engines', Environmental Pollution, vol. 243, no. Pt B, pp. 1943-1951.
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© 2018 Elsevier Ltd Particle emission characteristics and engine performance were investigated from an auxiliary, heavy duty, six-cylinder, turbocharged and after-cooled diesel engine with a common rail injection system using spiked fuels with different combinations of sulphur (S) and vanadium (V) spiking. The effect of fuel S content on both particle number (PN) and mass (PM) was clearly observed in this study. Higher PN and PM were observed for fuels with higher S contents at all engine load conditions. This study also found a correlation between fuel S content and nucleation mode particle number concentration which have more harmful impact on human health than larger particles. The highest PN and PM were observed at partial load conditions. In addition, S in fuel resulted in higher viscosity of spiked fuels, which led to lower engine blow-by. Fuel V content was observed in this study, evidencing that it had no clear effect on engine performance and emissions. Increased engine load also resulted in higher engine blow-by. The lower peak of in-cylinder pressure observed at both pre-mixed and diffusion combustion phases with the spiked fuels may be associated with the lower energy content in the fuel blends compared to diesel fuel.

Chu, S, Gao, L, Xiao, M, Luo, Z & Li, H 2018, 'Stress‐based multi‐material topology optimization of compliant mechanisms', International Journal for Numerical Methods in Engineering, vol. 113, no. 7, pp. 1021-1044.
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AbstractIn this paper, a level‐set‐based method is presented to deal with the multi‐material topology optimization of compliant mechanisms with stress constraints. A novel stress‐based multi‐material topology optimization model of compliant mechanisms is proposed. In this model, the multi‐material level set topology description model and the separable stress interpolation scheme are adopted. The weighted sum method is used to deal with the multi‐objective optimization of the output displacement and compliance of compliant mechanisms. The penalty of stresses is also considered in the objective function to control the local stress level in different materials. To solve the optimization problem, the parametric level set method is employed, and the sensitivity analysis is conducted. Application of the method is demonstrated by 2 numerical examples. Results show that the multi‐material structures without undesirable de facto hinges can be obtained. The output displacement and compliance of the compliant mechanisms are optimized, and stress constraints in different materials are simultaneously satisfied.

Chu, S, Gao, L, Xiao, M, Luo, Z, Li, H & Gui, X 2018, 'A new method based on adaptive volume constraint and stress penalty for stress-constrained topology optimization', Structural and Multidisciplinary Optimization, vol. 57, no. 3, pp. 1163-1185.
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© 2017, Springer-Verlag GmbH Germany. This paper focuses on the stress-constrained topology optimization of minimizing the structural volume and compliance. A new method based on adaptive volume constraint and stress penalty is proposed. According to this method, the stress-constrained volume and compliance minimization topology optimization problem is transformed into two simple and related problems: a stress-penalty-based compliance minimization problem and a volume-decision problem. In the former problem, stress penalty is conducted and used to control the local stress level of the structure. To solve this problem, the parametric level set method with the compactly supported radial basis functions is adopted. Meanwhile, an adaptive adjusting scheme of the stress penalty factor is used to improve the control of the local stress level. To solve the volume-decision problem, a combination scheme of the interval search and local search is proposed. Numerical examples are used to test the proposed method. Results show the lightweight design, which meets the stress constraint and whose compliance is simultaneously optimized, can be obtained by the proposed method.

Chuah, C, Wang, J, Tavakoli, J & Tang, Y 2018, 'Novel Bacterial Cellulose-Poly (Acrylic Acid) Hybrid Hydrogels with Controllable Antimicrobial Ability as Dressings for Chronic Wounds', Polymers, vol. 10, no. 12, pp. 1323-1323.
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This investigation examines the combination of poly (acrylic acid) (PAA) and bacterial cellulose (BC) nanofibers to synthesize hydrogel hybrid composites used for wound dressing application. Amoxicillin (AM) was also grafted onto the composites for drug release. Fourier transform infrared analysis and scanning electron microscopy conducted revealed the structure and porosity of the composite being developed, as well as the successful fabrication of BC-PAA composites. The results of mechanical testing and hygroscopicity revealed that the composite shows higher stability than hydrogels which are currently used worldwide, albeit with a slight reduction in swelling capabilities. However, the composite was revealed to be responsive to a rise in pH values with an increase in composite swelling and drug release. These results together with their morphological characteristics suggest that BC-PAA hydrogel hybrid composite is a promising candidate for wound dressing application.

Chuang, C-H, Cao, Z, King, J-T, Wu, B-S, Wang, Y-K & Lin, C-T 2018, 'Brain Electrodynamic and Hemodynamic Signatures Against Fatigue During Driving', Frontiers in Neuroscience, vol. 12, no. MAR, pp. 1-12.
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© 2018 Chuang, Cao, King, Wu, Wang and Lin. Fatigue is likely to be gradually cumulated in a prolonged and attention-demanding task that may adversely affect task performance. To address the brain dynamics during a driving task, this study recruited 16 subjects to participate in an event-related lane-departure driving experiment. Each subject was instructed to maintain attention and task performance throughout an hour-long driving experiment. The subjects' brain electrodynamics and hemodynamics were simultaneously recorded via 32-channel electroencephalography (EEG) and 8-source/16-detector functional near-infrared spectroscopy (fNIRS). The behavior performance demonstrated that all subjects were able to promptly respond to lane-deviation events, even if the sign of fatigue arose in the brain, which suggests that the subjects were fighting fatigue during the driving experiment. The EEG event-related analysis showed strengthening alpha suppression in the occipital cortex, a common brain region of fatigue. Furthermore, we noted increasing oxygenated hemoglobin (HbO) of the brain to fight driving fatigue in the frontal cortex, primary motor cortex, parieto-occipital cortex and supplementary motor area. In conclusion, the increasing neural activity and cortical activations were aimed at maintaining driving performance when fatigue emerged. The electrodynamic and hemodynamic signatures of fatigue fighting contribute to our understanding of the brain dynamics of driving fatigue and address driving safety issues through the maintenance of attention and behavioral performance.

Clarke, C, Liu, D, Wang, F, Liu, Y, Chen, C, Ton-That, C, Xu, X & Jin, D 2018, 'Large-scale dewetting assembly of gold nanoparticles for plasmonic enhanced upconversion nanoparticles', Nanoscale, vol. 10, no. 14, pp. 6270-6276.
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The integrated methods of core shell upconversion nanoparticle synthesis, thermal annealing and gold dewetting produce gold-decorated upconversion nanoparticles with enhanced emission.

Clement, S, Chen, W, Deng, W & Goldys, EM 2018, 'X-ray radiation-induced and targeted photodynamic therapy with folic acid-conjugated biodegradable nanoconstructs', International Journal of Nanomedicine, vol. Volume 13, pp. 3553-3570.
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Clemon, LM & Zohdi, TI 2018, 'On the tolerable limits of granulated recycled material additives to maintain structural integrity', Construction and Building Materials, vol. 167, pp. 846-852.
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© 2018 Elsevier Ltd Production and maker spaces are increasingly generating mixed plastic material waste of varying quality from 3-D printers. Industrial interest is growing in embedding granulated recycled particulate material additives into a virgin binding matrix. Examples include the introduction of granulated mixed recycled materials into 3-D printer material, concrete, and pavement. The stress load-sharing between the particulate additive and the binding matrix is an important factor in design and development of these composite materials. With mixed material additives, a designer is interested in the variation of such predicted load-sharing. However, experimental development is costly and time-consuming, thus analytical and semi-analytical estimates are desired for accelerated development. In this work, we expand on previous analytically correlated phase-averaged micro- and macrostructural loading to include variational effects present in mixed recycled material. In addition, model trade-offs are provided to aid designers in quickly selecting application specific mixtures. This framework identifies the stress contributions, and their variation, to reduce product development time and costs, which could greatly accelerate material recycling and reuse for improved infrastructure materials, low-cost 3-D printer filament, and reduced waste towards a more circular economy.

Cliff, O, Prokopenko, M & Fitch, R 2018, 'Minimising the Kullback–Leibler Divergence for Model Selection in Distributed Nonlinear Systems', Entropy, vol. 20, no. 2, pp. 51-51.
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The Kullback–Leibler (KL) divergence is a fundamental measure of information geometry that is used in a variety of contexts in artificial intelligence. We show that, when system dynamics are given by distributed nonlinear systems, this measure can be decomposed as a function of two information-theoretic measures, transfer entropy and stochastic interaction. More specifically, these measures are applicable when selecting a candidate model for a distributed system, where individual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed acyclic graph (DAG) that characterises the unidirectional coupling between subsystems. Standard approaches to structure learning are not applicable in this framework due to the hidden variables; however, we can exploit the properties of certain dynamical systems to formulate exact methods based on differential topology. We approach the problem by using reconstruction theorems to derive an analytical expression for the KL divergence of a candidate DAG from the observed dataset. Using this result, we present a scoring function based on transfer entropy to be used as a subroutine in a structure learning algorithm. We then demonstrate its use in recovering the structure of coupled Lorenz and Rössler systems.

Cliff, OM, Saunders, DL & Fitch, R 2018, 'Robotic ecology: Tracking small dynamic animals with an autonomous aerial vehicle', Science Robotics, vol. 3, no. 23.
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Estimation algorithms for wildlife tracking with an autonomous aerial robot are supported by field validation with wild swift parrots.

Coglitore, D, Merenda, A, Giamblanco, N, Dumée, LF, Janot, J-M & Balme, S 2018, 'Metal alloy solid-state nanopores for single nanoparticle detection', Physical Chemistry Chemical Physics, vol. 20, no. 18, pp. 12799-12807.
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We design metal alloy nanopore to detect nanoparticle and propose an original model to estimate the relative current blockade.

Coiera, E, Kocaballi, B, Halamka, J & Laranjo, L 2018, 'Author Correction: The digital scribe', npj Digital Medicine, vol. 1, no. 1.
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The original version of the published Article contained an error in the spelling of the third Author’s name. “John Halamaka” has been changed to “John Halamka”. This has been corrected in the HTML and PDF version of the Article.

Coiera, E, Kocaballi, B, Halamka, J & Laranjo, L 2018, 'The digital scribe', npj Digital Medicine, vol. 1, no. 1.
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AbstractCurrent generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans. Whilst in their infancy, digital scribes are likely to evolve through three broad stages. Human led systems task clinicians with creating documentation, but provide tools to make the task simpler and more effective, for example with dictation support, semantic checking and templates. Mixed-initiative systems are delegated part of the documentation task, converting the conversations in a clinical encounter into summaries suitable for the electronic record. Computer-led systems are delegated full control of documentation and only request human interaction when exceptions are encountered. Intelligent clinical environments permit such augmented clinical encounters to occur in a fully digitised space where the environment becomes the computer. Data from clinical instruments can be automatically transmitted, interpreted using AI and entered directly into the record. Digital scribes raise many issues for clinical practice, including new patient safety risks. Automation bias may see clinicians automatically accept scribe documents without checking. The electronic record also shifts from a human created summary of events to potentially a full audio, video and sensor record of the clinical encounter. Digital scribes promisingly offer a gateway into the clinical workflow for more advanced support for diagnostic, prognostic and therapeutic tasks.

Collier, JD, Tingay, SJ, Callingham, JR, Norris, RP, Filipović, MD, Galvin, TJ, Huynh, MT, Intema, HT, Marvil, J, O’Brien, AN, Roper, Q, Sirothia, S, Tothill, NFH, Bell, ME, For, B-Q, Gaensler, BM, Hancock, PJ, Hindson, L, Hurley-Walker, N, Johnston-Hollitt, M, Kapińska, AD, Lenc, E, Morgan, J, Procopio, P, Staveley-Smith, L, Wayth, RB, Wu, C, Zheng, Q, Heywood, I & Popping, A 2018, 'High-resolution Observations of Low-luminosity Gigahertz-Peaked Spectrum and Compact Steep Spectrum Sources', Monthly Notices of the Royal Astronomical Society, vol. 477, no. 1, pp. 78-592.
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© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. We present very long baseline interferometry observations of a faint and low-luminosity (L1.4 GHz < 1027 W Hz-1) gigahertz-peaked spectrum (GPS) and compact steep-spectrum (CSS) sample. We select eight sources from deep radio observations that have radio spectra characteristic of a GPS or CSS source and an angular size of θ ≲ 2 arcsec, and detect six of them with the Australian Long Baseline Array. We determine their linear sizes, and model their radio spectra using synchrotron self-absorption (SSA) and free-free absorption (FFA) models. We derive statistical model ages, based on a fitted scaling relation, and spectral ages, based on the radio spectrum, which are generally consistent with the hypothesis that GPS and CSS sources are young and evolving. We resolve the morphology of one CSS source with a radio luminosity of 1025WHz-1, and find what appear to be two hotspots spanning 1.7 kpc. We find that our sources follow the turnover-linear size relation, and that both homogeneous SSA and an inhomogeneous FFA model can account for the spectra with observable turnovers. All but one of the FFA models do not require a spectral break to account for the radio spectrum, while all but one of the alternative SSA and power-law models do require a spectral break to account for the radio spectrum. We conclude that our low-luminosity sample is similar to brighter samples in terms of their spectral shape, turnover frequencies, linear sizes, and ages, but cannot test for a difference in morphology.

Combes, J, Ferrie, C, Leifer, MS & Pusey, MF 2018, 'Why protective measurement does not establish the reality of the quantum state', Quantum Studies: Mathematics and Foundations, vol. 5, no. 2, pp. 189-211.
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Cook, AJ, Ng, B, Gargiulo, GD, Hindmarsh, D, Pitney, M, Lehmann, T & Hamilton, TJ 2018, 'Instantaneous VO2 from a wearable device', Medical Engineering & Physics, vol. 52, pp. 41-48.
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© 2018 IPEM We present a method for calculating instantaneous oxygen uptake (VO2) through the use of a non-invasive and non-obtrusive (i.e. without a face mask) wearable device, together with its clinical evaluation against a standard technique based upon expired gas calorimetry. This method can be integrated with existing wearable devices, we implemented it in the “Device for Reliable Energy Expenditure Monitoring” (DREEM). The DREEM comprises a single lead electrocardiogram (ECG) device combined with a tri-axial accelerometer and is worn around the waist. Our clinical evaluation tests the developed method against a gold standard for VO2, expired gas calorimetry, using an ethically approved protocol comprising active exercise and sedentary periods. The study was performed on 42 participants from a wide sample population including healthy people, athletes and an at-risk health group including persons affected by obesity. We developed an algorithm combining heart rate (HR) and the integral of absolute acceleration (IAA), with results showing a correlation of r = 0.93 for instantaneous VO2, and r = 0.97 for 3 min mean VO2, this is a considerably improved estimation of VO2 in comparison to methods utilising HR and IAA independently.

Cooper, WA, Barnet, MB, Kao, SC & Scolyer, RA 2018, 'Biomarkers that predict response to immunotherapy-no magic bullet', Cancer Forum, vol. 42, no. 1.
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Immunotherapeutic agents have shown impressive clinical efficacy in a broad range of tumour types, particularly in non-small cell lung cancer and melanoma. An effective predictive biomarker is needed to provide patients with the most effective available treatments, avoid unnecessary toxicity and improve cost effectiveness. While it has been an area of very active research in recent years, the ideal biomarker for predicting response to immune check point inhibitor therapy has not yet been universally agreed upon. Approaches to date have focussed on assessment of tumour related factors such as immunohistochemical expression of programmed death ligand-1 (PD-L1), mutational load and DNA mismatch repair gene or protein status. Alternatively, assessment of the immune microenvironment by techniques such as gene expression profiling or measurement of tumour infiltrating lymphocytes can also be informative. Identifying and validating effective biomarkers is particularly challenging for immunotherapy because the dynamic and multifactorial nature of the interaction between tumours and host immunity. In this review, we discuss the relative advantages and disadvantages of different biomarker approaches in the quest to identify a clinically effective predictive biomarker that can improve the overall utility for immune checkpoint inhibitors.

Corsetti, S, Rabl, T, McGloin, D & Nabi, G 2018, 'Raman spectroscopy for accurately characterizing biomolecular changes in androgen‐independent prostate cancer cells', Journal of Biophotonics, vol. 11, no. 3, pp. e201700166-e201700166.
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Metastatic prostate cancer resistant to hormonal manipulation is considered the advanced stage of the disease and leads to most cancer‐related mortality. With new research focusing on modulating cancer growth, it is essential to understand the biochemical changes in cells that can then be exploited for drug discovery and for improving responsiveness to treatment. Raman spectroscopy has a high chemical specificity and can be used to detect and quantify molecular changes at the cellular level. Collection of large data sets generated from biological samples can be employed to form discriminatory algorithms for detection of subtle and early changes in cancer cells. The present study describes Raman finger printing of normal and metastatic hormone‐resistant prostate cancer cells including analyses with principal component analysis and linear discrimination. Amino acid‐specific signals were identified, especially loss of arginine band. Androgen‐resistant prostate cancer cells presented a higher content of phenylalanine, tyrosine, DNA and Amide III in comparison to PNT2 cells, which possessed greater amounts of L‐arginine and had a B conformation of DNA. The analysis utilized in this study could reliably differentiate the 2 cell lines (sensitivity 95%; specificity 88%).

Cui, H, Wang, X, Zhou, J, Gong, G, Eberl, S, Yin, Y, Wang, L, Feng, D & Fulham, M 2018, 'A topo-graph model for indistinct target boundary definition from anatomical images', Computer Methods and Programs in Biomedicine, vol. 159, pp. 211-222.
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BACKGROUND AND OBJECTIVE:It can be challenging to delineate the target object in anatomical imaging when the object boundaries are difficult to discern due to the low contrast or overlapping intensity distributions from adjacent tissues. METHODS:We propose a topo-graph model to address this issue. The first step is to extract a topographic representation that reflects multiple levels of topographic information in an input image. We then define two types of node connections - nesting branches (NBs) and geodesic edges (GEs). NBs connect nodes corresponding to initial topographic regions and GEs link the nodes at a detailed level. The weights for NBs are defined to measure the similarity of regional appearance, and weights for GEs are defined with geodesic and local constraints. NBs contribute to the separation of topographic regions and the GEs assist the delineation of uncertain boundaries. Final segmentation is achieved by calculating the relevance of the unlabeled nodes to the labels by the optimization of a graph-based energy function. We test our model on 47 low contrast CT studies of patients with non-small cell lung cancer (NSCLC), 10 contrast-enhanced CT liver cases and 50 breast and abdominal ultrasound images. The validation criteria are the Dice's similarity coefficient and the Hausdorff distance. RESULTS:Student's t-test show that our model outperformed the graph models with pixel-only, pixel and regional, neighboring and radial connections (p-values <0.05). CONCLUSIONS:Our findings show that the topographic representation and topo-graph model provides improved delineation and separation of objects from adjacent tissues compared to the tested models.

Cui, L, Hu, H, Yu, S, Yan, Q, Ming, Z, Wen, Z & Lu, N 2018, 'DDSE: A novel evolutionary algorithm based on degree-descending search strategy for influence maximization in social networks', Journal of Network and Computer Applications, vol. 103, pp. 119-130.
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Influence maximization (IM) is the problem of finding a small subset of nodes in a social network so that the number of nodes influenced by this subset can be maximized. Influence maximization problem plays an important role in viral marketing and information diffusions. The existing solutions to influence maximization perform badly in either efficiency or accuracy. In this study, we analyze the causes for the low efficiency of the greedy approaches and propose a more efficient algorithm called degree-descending search evolution (DDSE). Firstly, we propose a degree-descending search strategy (DDS). DDS is capable of generating a node set whose influence spread is comparable to the degree centrality. Based on DDS, we develop an evolutionary algorithm that is capable of improving the efficiency significantly by eliminating the time-consuming simulations of the greedy algorithms. Experimental results on real-world social networks demonstrate that DDSE is about five orders of magnitude faster than the state-of-art greedy method while keeping competitive accuracy, which can verify the high effectiveness and efficiency of our proposed algorithm for influence maximization.

Cui, L, Yue, L, Wen, D & Qin, L 2018, 'K-Connected Cores Computation in Large Dual Networks.', Data Sci. Eng., vol. 3, no. 4, pp. 293-306.
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© 2018, The Author(s). Computing k- cores is a fundamental and important graph problem, which can be applied in many areas, such as community detection, network visualization, and network topology analysis. Due to the complex relationship between different entities, dual graph widely exists in the applications. A dual graph contains a physical graph and a conceptual graph, both of which have the same vertex set. Given that there exist no previous studies on the k- core in dual graphs, we formulate a k-connected core (k- CCO) model in dual graphs. A k- CCO is a k- core in the conceptual graph, and also connected in the physical graph. Given a dual graph and an integer k, we propose a polynomial time algorithm for computing all k- CCOs. We also propose three algorithms for computing all maximum-connected cores (MCCO), which are the existing k- CCOs such that a (k+ 1) -CCO does not exist. We further study a subgraph search problem, which is computing a k- CCO that contains a set of query vertices. We propose an index-based approach to efficiently answer the query for any given parameter k. We conduct extensive experiments on six real-world datasets and four synthetic datasets. The experimental results demonstrate the effectiveness and efficiency of our proposed algorithms.

Cui, Q, Gu, Y, Ni, W, Zhang, X, Tao, X, Zhang, P & Liu, RP 2018, 'Preserving Reliability of Heterogeneous Ultra-Dense Distributed Networks in Unlicensed Spectrum', IEEE Communications Magazine, vol. 56, no. 6, pp. 72-78.
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© 1979-2012 IEEE. This article investigates the prominent dilemma between capacity and reliability in heterogeneous ultra-dense distributed networks, and advocates a new measure of effective capacity to quantify the maximum sustainable data rate of a link while preserving the quality of service of the link in such networks. Recent breakthroughs are brought forth in developing the theory of the effective capacity in heterogeneous ultra-dense distributed networks. Potential applications of the effective capacity are demonstrated on the admission control, power control, and resource allocation of such networks, with substantial gains revealed over existing technologies. This new measure is of particular interest to ultra-dense deployment of the emerging 5G wireless networks in the unlicensed spectrum, leveraging the capacity gain brought by the use of the unlicensed band and the stringent reliability sustained by 5G in future heterogeneous network environments.

Cui, Z, Wang, J, Zhang, H, Ngo, HH, Jia, H, Guo, W, Gao, F, Yang, G & Kang, D 2018, 'Investigation of backwashing effectiveness in membrane bioreactor (MBR) based on different membrane fouling stages', Bioresource Technology, vol. 269, pp. 355-362.
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In this study the effect of different fouling stages of hollow fiber membranes on effective backwashing length in MBR has been investigated. Computational fluid dynamics (CFD) is imported to simulate backwashing process. A multi-physics coupling model for free porous media flow, convective mass transfer and diluted species transport was established. The laser bijection sensors (LBS) were imported to monitor the backwashing solution position inside fiber lumen. Simulation results indicated that membrane fouling degree could change the velocity of backwash solution inside fiber lumen and make a further effect on effective backwash length. The signal variations of LBS are in accordance with the simulation results. The backwashing process can only play an active role when the filtration pressure is below the critical TMP. It can be concluded that backwash duration in industrial applications need to be set based on changes in TMP.

D’Urso, G, Smith, SL, Mettu, R, Oksanen, T & Fitch, R 2018, 'Multi-vehicle refill scheduling with queueing', Computers and Electronics in Agriculture, vol. 144, pp. 44-57.
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© 2017 We consider the problem of refill scheduling for a team of vehicles or robots that must contend for access to a single physical location for refilling. The objective is to minimise time spent in travelling to/from the refill station, and also time lost to queuing (waiting for access). In this paper, we present principled results for this problem in the context of agricultural operations. We first establish that the problem is NP-hard and prove that the maximum number of vehicles that can usefully work together is bounded. We then focus on the design of practical algorithms and present two solutions. The first is an exact algorithm based on dynamic programming that is suitable for small problem instances. The second is an approximate anytime algorithm based on the branch and bound approach that is suitable for large problem instances with many robots. We present simulated results of our algorithms for three classes of agricultural work that cover a range of operations: spot spraying, broadcast spraying and slurry application. We show that the algorithm is reasonably robust to inaccurate prediction of resource utilisation rate, which is difficult to estimate in cases such as spot application of herbicide for weed control, and validate its performance in simulation using realistic scenarios with up to 30 robots.

da Rocha, CG & Kemmer, S 2018, 'Integrating product and process design in construction', Construction Management and Economics, vol. 36, no. 9, pp. 535-543.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Product modularity namely the notion that products can be decomposed into parts (or modules) has been widely applied in manufacturing but not in construction, precluding this industry to also benefit from it. The narrow definition of a module, which is often simplistically equated to a sub-assembly produced off-site, and the lack of integration between product and process design, which is typical in construction, are argued to be two root causes of such problem. This paper starts by discussing the operational implications of misaligned decisions in these two domains in an empirical study addressing a high-rise apartments building project. Seven guidelines are then devised using a Design Science Research (DSR) approach for integrating product (product modularity and modules) and process (work structure and work packages) design. The results indicate that product modularity can be applied for improving operations regardless of the construction method(s) used. Yet, a revised understanding of modules (as a material, a component, a non-volumetric or a volumetric sub-assembly) is needed in addition to a coordinated product and process design, particularly for traditional construction.

da Rocha, CG & Miron, LIG 2018, 'The House Factory: A Simulation Game for Understanding Mass Customization in House Building', Journal of Professional Issues in Engineering Education and Practice, vol. 144, no. 1, pp. 05017007-05017007.
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Dadzie, J, Runeson, G & Ding, G 2018, 'Determinants of sustainable upgrade for energy efficiency – the case of existing buildings in Australia', Energy Procedia, vol. 153, pp. 284-289.
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© 2018 The Authors. Published by Elsevier Ltd. The impact of existing buildings on the environment is on the rise; thus to achieve environmental sustainability requires sustainable upgrade (SU) of existing built facilities. Over the years, SU has focused on technologies with little attention given to the nature and conditions of existing buildings. The purpose of this paper is to identify existing building characteristics that impact SU. A detailed literature review on the nature and characteristics of existing buildings, as well as energy and environmental performance was undertaken. A survey questionnaire with all the determinants of existing buildings was administered to sustainability and construction professionals in Australia. The results show that size of building, age of building, U-value of wall, U-value of ceiling, area of external wall, thickness of insulation materials, occupancy, size of window opening, life span of sustainable technologies, and the type of building impact sustainable upgrade of existing buildings for energy efficiency.

Dadzie, J, Runeson, G, Ding, G & Bondinuba, F 2018, 'Barriers to Adoption of Sustainable Technologies for Energy-Efficient Building Upgrade—Semi-Structured Interviews', Buildings, vol. 8, no. 4, pp. 57-57.
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Globally, only 2% of existing building stock is built yearly; the remaining 98% already exist. Energy consumption and indoor thermal comfort of the existing building stock are not encouraging. This is due to many challenges associated with existing buildings; the challenges range from cracks, leakages, poor insulation, heat losses and high rate of unsustainable technologies. This paper investigates possible barriers facing the adoption and application of sustainable technologies (STs) for sustainable or energy-efficient upgrade of existing buildings. New STs are manufactured on a regular basis to meet improved energy efficiency standards, yet there are minimal actions/attempts to adopt and apply improved technologies in existing buildings for energy efficiency. Indeed, there are limited studies focused on the use of qualitative approaches to identify barriers to adoption and use of STs. Thus, a semi-structured interview approach was adopted and applied using sustainability/energy efficiency professionals, building services engineers, project managers, architects, and facility managers in Australia. The results indicate that barriers to the adoption and application of sustainable technologies are perceived benefits in demolish-and-build, age of building, cost of STs, perceived poor payback time, unreliable energy-savings projections, existing design, hidden and overall cost of renovation, and cost of STs.

Dai, S, Tymchenko, M, Xu, Z-Q, Tran, TT, Yang, Y, Ma, Q, Watanabe, K, Taniguchi, T, Jarillo-Herrero, P, Aharonovich, I, Basov, DN, Tao, TH & Alù, A 2018, 'Internal Nanostructure Diagnosis with Hyperbolic Phonon Polaritons in Hexagonal Boron Nitride', Nano Letters, vol. 18, no. 8, pp. 5205-5210.
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Copyright © 2018 American Chemical Society. Imaging materials and inner structures with resolution below the diffraction limit has become of fundamental importance in recent years for a wide variety of applications. We report subdiffractive internal structure diagnosis of hexagonal boron nitride by exciting and imaging hyperbolic phonon polaritons. On the basis of their unique propagation properties, we are able to accurately locate defects in the crystal interior with nanometer resolution. The precise location, size, and geometry of the concealed defects are reconstructed by analyzing the polariton wavelength, reflection coefficient, and their dispersion. We have also studied the evolution of polariton reflection, transmission, and scattering as a function of defect size and photon frequency. The nondestructive high-precision polaritonic structure diagnosis technique introduced here can be also applied to other hyperbolic or waveguide systems and may be deployed in the next-generation biomedical imaging, sensing, and fine structure analysis.

Damanik, N, Ong, HC, Tong, CW, Mahlia, TMI & Silitonga, AS 2018, 'A review on the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends', Environmental Science and Pollution Research, vol. 25, no. 16, pp. 15307-15325.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Biodiesels have gained much popularity because they are cleaner alternative fuels and they can be used directly in diesel engines without modifications. In this paper, a brief review of the key studies pertaining to the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends, exhaust aftertreatment systems, and low-temperature combustion technology is presented. In general, most biodiesel blends result in a significant decrease in carbon monoxide and total unburned hydrocarbon emissions. There is also a decrease in carbon monoxide, nitrogen oxide, and total unburned hydrocarbon emissions while the engine performance increases for diesel engines fueled with biodiesels blended with nano-additives. The development of automotive technologies, such as exhaust gas recirculation systems and low-temperature combustion technology, also improves the thermal efficiency of diesel engines and reduces nitrogen oxide and particulate matter emissions.

De Medeiros, JF, Da Rocha, CG & Ribeiro, JLD 2018, 'Design for sustainable behavior (DfSB): Analysis of existing frameworks of behavior change strategies, experts' assessment and proposal for a decision support diagram', Journal of Cleaner Production, vol. 188, pp. 402-415.
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Deady, M, Johnston, D, Milne, D, Glozier, N, Peters, D, Calvo, R & Harvey, S 2018, 'Preliminary Effectiveness of a Smartphone App to Reduce Depressive Symptoms in the Workplace: Feasibility and Acceptability Study', JMIR mHealth and uHealth, vol. 6, no. 12, pp. e11661-e11661.
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© Mark Deady, David Johnston, David Milne, Nick Glozier, Dorian Peters, Rafael Calvo, Samuel Harvey. Background: The workplace represents a unique setting for mental health interventions. Due to range of job-related factors, employees in male-dominated industries are at an elevated risk. However, these at-risk groups are often overlooked. HeadGear is a smartphone app–based intervention designed to reduce depressive symptoms and increase well-being in these populations. Objective: This paper presents the development and pilot testing of the app’s usability, acceptability, feasibility, and preliminary effectiveness. Methods: The development process took place from January 2016 to August 2017. Participants for prototype testing (n=21; stage 1) were recruited from industry partner organizations to assess acceptability and utility. A 5-week effectiveness and feasibility pilot study (n=84; stage 2) was then undertaken, utilizing social media recruitment. Demographic data, acceptability and utility questionnaires, depression (Patient Health Questionnaire-9), and other mental health measures were collected. Results: The majority of respondents felt HeadGear was easy to use (92%), easily understood (92%), were satisfied with the app (67%), and would recommend it to a friend (75%; stage 1). Stage 2 found that compared with baseline, depression and anxiety symptoms were significantly lower at follow-up (t30=2.53; P=.02 and t30=2.18; P=.04, respectively), days of sick leave in past month (t28=2.38; P=.02), and higher self-reported job performance (t28=−2.09; P=.046; stage 2). Over 90% of respondents claimed it helped improve their mental fitness, and user feedback was again positive. Attrition was high across the stages. Conclusions: Overall, HeadGear was well received, and preliminary findings indicate it may provide an innovative new platform for improving mental health outcomes. Unfortunately, attrition was a significant issue, and findings should be interpreted...

Deady, M, Johnston, D, Milne, D, Glozier, N, Peters, D, Calvo, R & Harvey, S 2018, 'Preliminary effectiveness of a smartphone app to reduce depressive symptoms in the workplace: Feasibility and acceptability study', Journal of Medical Internet Research, vol. 20, no. 12.
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© Mark Deady, David Johnston, David Milne, Nick Glozier, Dorian Peters, Rafael Calvo, Samuel Harvey. Background: The workplace represents a unique setting for mental health interventions. Due to range of job-related factors, employees in male-dominated industries are at an elevated risk. However, these at-risk groups are often overlooked. HeadGear is a smartphone app–based intervention designed to reduce depressive symptoms and increase well-being in these populations. Objective: This paper presents the development and pilot testing of the app’s usability, acceptability, feasibility, and preliminary effectiveness. Methods: The development process took place from January 2016 to August 2017. Participants for prototype testing (n=21; stage 1) were recruited from industry partner organizations to assess acceptability and utility. A 5-week effectiveness and feasibility pilot study (n=84; stage 2) was then undertaken, utilizing social media recruitment. Demographic data, acceptability and utility questionnaires, depression (Patient Health Questionnaire-9), and other mental health measures were collected. Results: The majority of respondents felt HeadGear was easy to use (92%), easily understood (92%), were satisfied with the app (67%), and would recommend it to a friend (75%; stage 1). Stage 2 found that compared with baseline, depression and anxiety symptoms were significantly lower at follow-up (t30=2.53; P=.02 and t30=2.18; P=.04, respectively), days of sick leave in past month (t28=2.38; P=.02), and higher self-reported job performance (t28=−2.09; P=.046; stage 2). Over 90% of respondents claimed it helped improve their mental fitness, and user feedback was again positive. Attrition was high across the stages. Conclusions: Overall, HeadGear was well received, and preliminary findings indicate it may provide an innovative new platform for improving mental health outcomes. Unfortunately, attrition was a significant issue, and findings should be interpreted...

Deady, M, Johnston, DA, Glozier, N, Milne, D, Choi, I, Mackinnon, A, Mykletun, A, Calvo, RA, Gayed, A, Bryant, R, Christensen, H & Harvey, SB 2018, 'A smartphone application for treating depressive symptoms: study protocol for a randomised controlled trial', BMC Psychiatry, vol. 18, no. 1, pp. 1-9.
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© 2018 The Author(s). Background: Depression is a commonly occurring disorder linked to diminished role functioning and quality of life. The development of treatments that overcome barriers to accessing treatment remains an important area of clinical research as most people delay or do not receive treatment at an appropriate time. The workplace is an ideal setting to roll-out an intervention, particularly given the substantial psychological benefits associated with remaining in the workforce. Mobile health (mhealth) interventions utilising smartphone applications (apps) offer novel solutions to disseminating evidence based programs, however few apps have undergone rigorous testing. The present study aims to evaluate the effectiveness of a smartphone app designed to treat depressive symptoms in workers. Methods: The present study is a multicentre randomised controlled trial (RCT), comparing the effectiveness of the intervention to that of an attention control. The primary outcome measured will be reduced depressive symptoms at 3 months. Secondary outcomes such as wellbeing and work performance will also be measured. Employees from a range of industries will be recruited via a mixture of targeted social media advertising and Industry partners. Participants will be included if they present with likely current depression at baseline. Following baseline assessment (administered within the app), participants will be randomised to receive one of two versions of the Headgear application: 1) Intervention (a 30-day mental health intervention focusing on behavioural activation and mindfulness), or 2) attention control app (mood monitoring for 30 days). Participants will be blinded to their allocation. Analyses will be conducted within an intention to treat framework using mixed modelling. Discussion: The results of this trial will provide valuable information about the effectiveness of mhealth interventions in the treatment of depressive symptoms in a workplace context.

Deady, M, Johnston, DA, Glozier, N, Milne, D, Choi, I, Mackinnon, A, Mykletun, A, Calvo, RA, Gayed, A, Bryant, R, Christensen, H & Harvey, SB 2018, 'Smartphone application for preventing depression: study protocol for a workplace randomised controlled trial', BMJ Open, vol. 8, no. 7, pp. e020510-e020510.
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IntroductionDepression is the leading cause of life years lost due to disability. Appropriate prevention has the potential to reduce the incidence of new cases of depression, however, traditional prevention approaches face significant scalability issues. Prevention programmes delivered by via smartphone applications provide a potential solution. The workplace is an ideal setting to roll out this form of intervention, particularly among industries that are unlikely to access traditional health initiatives and whose workplace characteristics create accessibility and portability issues. The study aims to evaluate the effectiveness of a smartphone application designed to prevent depression and improve well-being. The effectiveness of the app as a universal, selective and indicated prevention tool will also be evaluated.Methods and analysisA multicentre randomised controlled trial, to determine the effectiveness of the intervention compared with an active mood monitoring control in reducing depressive symptoms (primary outcome) and the prevalence of depression at 3 months, with secondary outcomes assessing well-being and work performance. Employees from a range of industries will be invited to participate. Participants with likely current depression at baseline will be excluded. Following baseline assessment, participants, blinded to their allocation, will be randomised to receive one of two versions of the application: headgear (a 30-day mental health intervention) or a control application (mood monitoring for 30 days). Both versions of the app contain a risk calculator to provide a measure of future risk. Analyses will be conducted within an intention-to-treat framework using mixed modelling, with additional analyses conducted to compare the moderating effect of baseline risk level and depression symptom severity on the intervention’s effectiveness.

Deng, L, Ngo, H-H, Guo, W, Wang, J & Zhang, H 2018, 'Evaluation of a new sponge addition-microbial fuel cell system for removing nutrient from low C/N ratio wastewater', Chemical Engineering Journal, vol. 338, pp. 166-175.
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© 2018 This study developed a new microbial fuel cell (MFC) system (Sponge-MFC), which consisted of a cathodic chamber with an added sponge and two anodic chambers, for low carbon/nitrogen (C/N) wastewater treatment. When operating in the closed-circuit state, the Sponge-MFC(C) demonstrated its superior electrochemical performance compared to the closed-circuit MFC. This superiority took the form of higher coulombic efficiencies, voltage outputs, current densities and power densities. Adding a sponge could reduce the cathode's charge transfer resistance and solution resistance, and improve its capacitance, thus increasing cathodic reaction rate and power outputs. Simultaneous nitrification denitrification (SND) and bioelectrochemical denitrification processes on the cathode coupled with the sponge's SND process were responsible for efficient removal of nitrogen from the Sponge-MFC(C). Fluorescent in situ hybridization (FISH) analysis revealed that nitrifying bacteria and highly diversified denitrifying bacteria were distributed at the cathode's outer layer and inner layer, respectively. Higher phosphorus removal efficiencies (82.06 ± 1.21%) in the Sponge-MFC(C) than that in the MFC(C) (53.97 ± 2.32%) could be ascribed to biological phosphorus removal and precipitation of phosphate salts on the cathode. These results suggested the Sponge-MFC(C) could accomplish better electrochemical behaviors and nutrient removal due to sponge addition when treating wastewater with low C/N ratio.

Deng, W, Chen, W, Clement, S, Guller, A, Zhao, Z, Engel, A & Goldys, EM 2018, 'Controlled gene and drug release from a liposomal delivery platform triggered by X-ray radiation', Nature Communications, vol. 9, no. 1, p. 2713.
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AbstractLiposomes have been well established as an effective drug delivery system, due to simplicity of their preparation and unique characteristics. However conventional liposomes are unsuitable for the on-demand content release, which limits their therapeutic utility. Here we report X-ray-triggerable liposomes incorporating gold nanoparticles and photosensitizer verteporfin. The 6 MeV X-ray radiation induces verteporfin to produce singlet oxygen, which destabilises the liposomal membrane and causes the release of cargos from the liposomal cavity. This triggering strategy is demonstrated by the efficiency of gene silencing in vitro and increased effectiveness of chemotherapy in vivo. Our work indicates the feasibility of a combinatorial treatment and possible synergistic effects in the course of standard radiotherapy combined with chemotherapy delivered via X-ray-triggered liposomes. Importantly, our X-ray-mediated liposome release strategy offers prospects for deep tissue photodynamic therapy, by removing its depth limitation.

Deng, W, Goldys, EM & Zhao, Z 2018, 'Release of doxorubicin from liposomes by x-ray radiation', Nanomedicine: Nanotechnology, Biology and Medicine, vol. 14, no. 5, pp. 1753-1753.
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Deng, Z, Chen, J, Zhang, T, Cao, L & Wang, S 2018, 'Generalized Hidden-Mapping Minimax Probability Machine for the training and reliability learning of several classical intelligent models', Information Sciences, vol. 436-437, pp. 302-319.
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© 2018 Elsevier Inc. Minimax Probability Machine (MPM) is a binary classifier that optimizes the upper bound of the misclassification probability. This upper bound of the misclassification probability can be used as an explicit indicator to characterize the reliability of the classification model and thus makes the classification model more transparent. However, the existing related work is constrained to linear models or the corresponding nonlinear models by applying the kernel trick. To relax such constraints, we propose the Generalized Hidden-Mapping Minimax Probability Machine (GHM-MPM). GHM-MPM is a generalized MPM. It is capable of training many classical intelligent models, such as feedforward neural networks, fuzzy logic systems, and linear and kernelized linear models for classification tasks, and realizing the reliability learning of these models simultaneously. Since the GHM-MPM, similarly to the classical MPM, was originally developed only for binary classification, it is further extended to multi-class classification by using the obtained reliability indices of the binary classifiers of two arbitrary classes. The experimental results show that GHM-MPM makes the trained models more transparent and reliable than those trained by classical methods.

Depczynski, B, Young, T & White, C 2018, 'A high ankle-brachial index is associated with obesity and low serum 25-hydroxyvitamin D in patients with diabetes', Journal of Clinical & Translational Endocrinology, vol. 11, pp. 7-10.
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Deveci, Ö & Shannon, AG 2018, 'The quaternion-Pell sequence', Communications in Algebra, vol. 46, no. 12, pp. 5403-5409.
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© 2018, © 2018 Taylor & Francis. In this paper, we define the quaternion-Pell sequence and derive the generating matrix of the sequence. Then we produce the semigroups using the multiplicative orders of the generating matrix of the quaternion-Pell sequence when read modulo α. We also study the quaternion-Pell sequence modulo α and then we give the relationship among the periods of the quaternion-Pell sequence modulo α and the orders of the semigroups obtained. In addition, we extend the quaternion-Pell sequence to groups. Finally, we obtain the periods of the quaternion-Pell sequences in dihedral groups D 2m as applications of the results obtained.

Dickson-Deane, C, Bradshaw, AC & Asino, TI 2018, 'Recognizing the Inseparability of Culture, Learning, and Technology', TechTrends, vol. 62, no. 4, pp. 310-311.
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Dietrich, A, Bürk, M, Steiger, ES, Antoniuk, L, Tran, TT, Nguyen, M, Aharonovich, I, Jelezko, F & Kubanek, A 2018, 'Observation of Fourier transform limited lines in hexagonal boron nitride', Physical Review B, vol. 98, no. 8.
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© 2018 American Physical Society. Single defect centers in layered hexagonal boron nitride are promising candidates as single-photon sources for quantum optics and nanophotonics applications. However, spectral instability hinders many applications. Here, we perform resonant excitation measurements and observe Fourier transform limited linewidths down to ≈50 MHz. We investigated the optical properties of more than 600 single-photon emitters (SPEs) in hBN. The SPEs exhibit narrow zero-phonon lines distributed over a spectral range from 580 to 800 nm and with dipolelike emission with a high polarization contrast. Finally, the emitters withstand transfer to a foreign photonic platform, namely, a silver mirror, which makes them compatible with photonic devices such as optical resonators and paves the way to quantum photonics applications.

Ding, C, Sun, H-H, Ziolkowski, RW & Jay Guo, Y 2018, 'A Dual Layered Loop Array Antenna for Base Stations With Enhanced Cross-Polarization Discrimination', IEEE Transactions on Antennas and Propagation, vol. 66, no. 12, pp. 6975-6985.
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© 1963-2012 IEEE. This paper presents a novel dual-loop array antenna targeted at current and future base station applications. The antenna has four rectangular loops and four trapezoidal loops printed on the front and back sides, respectively, of a substrate placed above a flat square reflector. All eight loop radiators are excited simultaneously with properly designed feed networks to achieve its ±45° polarization states. The trapezoidal loops act like folded (electric) dipoles; the rectangular loops act primarily as magnetic dipoles. The combination of these two loop arrays leads to a type of magnetoelectric loop antenna that has stable directivity patterns with high cross-polarization discrimination (XPD) values across a 45.5% operational fractional bandwidth from 1.7 to 2.7 GHz. A fabricated and measured prototype confirms the simulation results and demonstrates that the half-power beamwidths in the horizontal plane vary between 63° and 70°, the XPD values are >20 dB in the boresight direction, and are >10 dB within the entire cellular coverage angular range:-60 θ 60°.

Ding, KC, Xiaoyu, Y, Xin, R & Qi, K 2018, 'Design analysis of high-rise buildings in the view of wind environment——A case study of four seasons green block in Hangzhou Qianjiang new city', Xi'an Jianzhu Keji Daxue Xuebao/Journal of Xi'an University of Architecture & Technology, vol. 50, no. 6, pp. 884-900.
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Due to the trend of high-rise and densification of urban buildings, high-rise buildings have a significant impact on the wind environment in their plots, and further affect the comfort of outdoor pedestrians to improve the wind environment around high-rise buildings, which is an urgent problem to be solved. First of all, in this paper, six high-rise buildings in Qianjiang New Town, Hangzhou City, were measured and the location of the building group towards the outdoor wind environment was selected and the points were determined. Then, by constantly changing the orientation of the building blocks, eight typical layouts were obtained. Finally, the CFD fluid dynamics simulation software phoenics was used to analyze the distribution of the wind speed ratio at the height (1.5 m). It is found that the change of the building orientation can achieve the optimization of the surrounding wind environment of the high-rise buildings. This paper, by exploring the relationship between wind environment and building orientation, provides a reference for the design of high-rise building groups in the region.

Ding, W, Lin, C-T & Prasad, M 2018, 'Hierarchical co-evolutionary clustering tree-based rough feature game equilibrium selection and its application in neonatal cerebral cortex MRI', Expert Systems with Applications, vol. 101, pp. 243-257.
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© 2018 Elsevier Ltd A wide variety of feature selection methods have been developed as promising solutions to find the classification pattern inside increasing applications. But the exploring efficient, flexible and robust feature selection method to handle the rising big data is still an exciting challenge. This paper presents a novel hierarchical co-evolutionary clustering tree-based rough feature game equilibrium selection algorithm (CTFGES). It aims to select out the high-quality feature subsets, which can enrich the research of feature selection and classification in the heterogeneous big data. Firstly, we construct a flexible hierarchical co-evolutionary clustering tree model to speed up the process of feature selection, which can effectively extract the features from the parent and children branches of four-layer co-evolutionary clustering tree. Secondly, we design a mixed co-evolutionary game equilibrium scheme with adaptive dynamics to guide parent and children branch subtrees to approach the optimal equilibrium regions, and enable their feature sets to converge stably to the Nash equilibrium. So both noisy heterogeneous features and non-identified redundant ones can be further eliminated. Finally, the extensive experiments on various big datasets are conducted to demonstrate the more excellent performance of CTFGES, in terms of accuracy, efficiency and robustness, compared with the representative feature selection algorithms. In addition, the proposed CTFGES algorithm has been successfully applied into the feature segmentation of large-scale neonatal cerebral cortex MRI with varying noise ratios and intensity non-uniformity levels. The results indicate that it can be adaptive to derive from the cortical folding surfaces and achieves the satisfying consistency with medical experts, which will be potential significance for successfully assessing the impact of aberrant brain growth on the neurodevelopment of neonatal cerebrum.

Ding, Z, Dong, Y, Kou, G, Palomares, I & Yu, S 2018, 'Consensus formation in opinion dynamics with online and offline interactions at complex networks', International Journal of Modern Physics C, vol. 29, no. 07, pp. 1850046-1850046.
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Nowadays, with the development of information communication technology and Internet, more and more people receive information and exchange their opinions with others via online environments (e.g. Twitter, Facebook, Weibo, and WeChat). According to eMarketer Report [Worldwide Internet and Mobile Users: eMarketer’s Updated Estimates and Forecast for 2015–2020 (eMarketer Report). Published October 11, 2016, https://www.emarketer.com/Report/Worldwide-Internet-Mobile-Users-eMarketers-Updated-Estimates-Forecast-20152020/2001897 ).], by the end of 2016, more than 3.2 billion individuals worldwide will use the Internet regularly, accounting for nearly 45% of the world population. By contrast, the other half of the global population still obtain information and regularly exchange their opinions in a more traditional way (e.g. face to face). Generally, the speed at which information spreads and opinions are exchanged and updated in an online environment is much faster than in an offline environment. This paper focuses on jointly investigating the challenge of consensus formation in opinion dynamics with online and offline interactions. Without loss of generality, we assume the speed at which information spreads and opinions are exchanged and updated in an online environment is [Formula: see text] times as fast as in an offline environment. We demonstrate that the update speed ratio in mixed online and offline environments (i.e. [Formula: see text]) strongly impacts the consensus formation at complex networks: a large update speed ratio of online and offline environments (i.e. [Formula: see text]) makes it difficult for all agents to reach consensus in opinion dynamics. Furthermore, these effects are often further intensified as the number of online participating agents increases.

Do, MH, Ngo, HH, Guo, WS, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD & Ni, BJ 2018, 'Challenges in the application of microbial fuel cells to wastewater treatment and energy production: A mini review', Science of The Total Environment, vol. 639, pp. 910-920.
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© 2018 Wastewater is now considered to be a vital reusable source of water reuse and saving energy. However, current wastewater has multiple limitations such as high energy costs, large quantities of residuals being generated and lacking in potential resources. Recently, great attention has been paid to microbial fuel cells (MFCs) due to their mild operating conditions where a variety of biodegradable substrates can serve as fuel. MFCs can be used in wastewater treatment facilities to break down organic matter, and they have also been analysed for application as a biosensor such as a sensor for biological oxygen which demands monitoring. MFCs represent an innovation technology solution that is simple and rapid. Despite the advantages of this technology, there are still practical barriers to consider including low electricity production, current instability, high internal resistance and costly materials used. Thus, many problems must be overcome and doing this requires a more detailed analysis of energy production, consumption, and application. Currently, real-world applications of MFCs are limited due to their low power density level of only several thousand mW/m2. Efforts are being made to improve the performance and reduce the construction and operating costs of MFCs. This paper explores several aspects of MFCs such as anode, cathode and membrane, and in an effort to overcome the practical challenges of this system.

Dong, F, Lu, J, Zhang, G & Li, K 2018, 'Active Fuzzy Weighting Ensemble for Dealing with Concept Drift', International Journal of Computational Intelligence Systems, vol. 11, no. 1, pp. 438-438.
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© 2018, the Authors. The concept drift problem is a pervasive phenomenon in real-world data stream applications. It makes well-trained static learning models lose accuracy and become outdated as time goes by. The existence of different types of concept drift makes it more difficult for learning algorithms to track. This paper proposes a novel adaptive ensemble algorithm, the Active Fuzzy Weighting Ensemble, to handle data streams involving concept drift. During the processing of data instances in the data streams, our algorithm first identifies whether or not a drift occurs. Once a drift is confirmed, it uses data instances accumulated by the drift detection method to create a new base classifier. Then, it applies fuzzy instance weighting and a dynamic voting strategy to organize all the existing base classifiers to construct an ensemble learning model. Experimental evaluations on seven datasets show that our proposed algorithm can shorten the recovery time of accuracy drop when concept drift occurs, adapt to different types of concept drift, and obtain better performance with less computation costs than the other adaptive ensembles.

Dong, F, Zhang, G, Lu, J & Li, K 2018, 'Fuzzy competence model drift detection for data-driven decision support systems', Knowledge-Based Systems, vol. 143, pp. 284-294.
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© 2017 Elsevier B.V. This paper focuses on concept drift in business intelligence and data-driven decision support systems (DSSs). The assumption of a fixed distribution in the data renders conventional static DSSs inaccurate and unable to make correct decisions when concept drift occurs. However, it is important to know when, how, and where concept drift occurs so a DSS can adjust its decision processing knowledge to adapt to an ever-changing environment at the appropriate time. This paper presents a data distribution-based concept drift detection method called fuzzy competence model drift detection (FCM-DD). By introducing fuzzy sets theory and replacing crisp boundaries with fuzzy ones, we have improved the competence model to provide a better, more refined empirical distribution of the data stream. FCM-DD requires no prior knowledge of the underlying distribution and provides statistical guarantee of the reliability of the detected drift, based on the theory of bootstrapping. A series of experiments show that our proposed FCM-DD method can detect drift more accurately, has good sensitivity, and is robust.

Dong, X, Gong, Y & Cao, L 2018, 'F-NSP+: A fast negative sequential patterns mining method with self-adaptive data storage', Pattern Recognition, vol. 84, pp. 13-27.
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© 2018 Elsevier Ltd Mining negative sequential patterns (NSP) is an important tool for nonoccurring behavior analysis, and it is much more challenging than mining positive sequential patterns (PSPs) due to the high computational complexity and huge search space when obtaining the support of negative sequential candidates (NSCs). Very few NSP mining algorithms are available and most of them are very inefficient since they obtain the support of NSC by scanning the database repeatedly. Instead, the state-of-the-art NSP mining algorithm e-NSP only uses the PSP's information stored in an array structure to ‘calculate' the support of NSC by equations, without database re-scanning. This makes e-NSP highly efficient, particularly on sparse datasets. However, when datasets become dense, the key process to obtain the support of NSC in e-NSP becomes very time-consuming and needs to be improved. In this paper, we propose a novel and efficient data structure, a bitmap, to obtain the support of NSC. We correspondingly propose a fast NSP mining algorithm, f-NSP, which uses a bitmap to store the PSP's information and then obtain the support of NSC only by bitwise operations, which is much faster than the hash method in e-NSP. Experimental results on real-world and synthetic datasets show that f-NSP is not only tens to hundreds of times faster than e-NSP, but also saves more than ten-fold the storage spaces of e-NSP, particularly on dense datasets with a large number of elements in a sequence or a small number of itemsets. Further, we find that f-NSP consumes more storage space than e-NSP when PSP's support is less than a support threshold sdsup, a value obtained through our theoretical analysis of storage space. Accordingly, we propose a self-adaptive storage strategy and a corresponding algorithm f-NSP+ to overcome this deficiency. f-NSP+ can automatically choose a bitmap or an array structure to store PSP information according to PSP support. Experimental results sho...

Dong, Y, Fatahi, B, Khabbaz, H & Zhang, H 2018, 'Influence of particle contact models on soil response of poorly graded sand during cavity expansion in discrete element simulation', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1154-1170.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences The discrete element method (DEM) has been extensively adopted to investigate many complex geotechnical related problems due to its capability to incorporate the discontinuous nature of granular materials. In particular, when simulating large deformations or distortion of soil (e.g. cavity expansion), DEM can be very effective as other numerical solutions may experience convergence problems. Cavity expansion theory has widespread applications in geotechnical engineering, particularly to the problems concerning in situ testing, pile installation and so forth. In addition, the behaviour of geomaterials in a macro-level is utterly determined by microscopic properties, highlighting the importance of contact models. Despite the fact that there are numerous contact models proposed to mimic the realistic behaviour of granular materials, there are lack of studies on the effects of these contact models on the soil response. Hence, in this study, a series of three-dimensional numerical simulations with different contact constitutive models was conducted to simulate the response of sandy soils during cylindrical cavity expansion. In this numerical investigation, three contact models, i.e. linear contact model, rolling resistance contact model, and Hertz contact model, are considered. It should be noted that the former two models are linear based models, providing linearly elastic and frictional plasticity behaviours, whereas the latter one consists of nonlinear formulation based on an approximation of the theory of Mindlin and Deresiewicz. To examine the effects of these contact models, several cylindrical cavities were created and expanded gradually from an initial radius of 0.055 m to a final radius of 0.1 m. The numerical predictions confirm that the calibrated contact models produced similar results regarding the variations of cavity pressure, radial stress, deviatoric stress, volumetric ...

Dorji, P, Choi, J, Kim, DI, Phuntsho, S, Hong, S & Shon, HK 2018, 'Membrane capacitive deionisation as an alternative to the 2nd pass for seawater reverse osmosis desalination plant for bromide removal', Desalination, vol. 433, pp. 113-119.
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© 2018 Elsevier B.V. Most Australian surface and ground waters have relatively high concentration of bromide between 400 and 8000 μg/L and even higher concentration in seawater between 60,000–78,000 μg/L. Although bromide is not regulated, even at low concentrations of 50–100 μg/L, it can lead to the formation of several types of harmful disinfection by-products (DBPs) during the disinfection process. One of the major concerns with brominated DBPs is the formation of bromate (BrO3−), a serious carcinogen that is formed when water containing a high concentration of bromide is disinfected. As a result, bromate is highly regulated in Australian water standards with the maximum concentration of 20 μg/L in the drinking water. Since seawater reverse osmosis (SWRO) desalination plays an important role in augmenting fresh water supplies in Australia, SWRO plants in Australia usually adopt 2nd pass brackish water reverse osmosis (BWRO) for effective bromide removal, which is not only energy-intensive to operate but also has higher capital cost. In this study, we evaluated the feasibility of membrane capacitive deionisation (MCDI) as one of the alternatives to the 2nd pass BWRO for effective bromide removal in a more energy efficient way.

Dorneburg, C, Fischer, M, Barth, TFE, Mueller-Klieser, W, Hero, B, Gecht, J, Carter, DR, de Preter, K, Mayer, B, Christner, L, Speleman, F, Marshall, GM, Debatin, K-M & Beltinger, C 2018, 'LDHA in Neuroblastoma Is Associated with Poor Outcome and Its Depletion Decreases Neuroblastoma Growth Independent of Aerobic Glycolysis', Clinical Cancer Research, vol. 24, no. 22, pp. 5772-5783.
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Abstract Purpose: To investigate whether lactate dehydrogenase A (LDHA), an important component of the LDH tetramer crucial for aerobic glycolysis, is associated with patient outcome and constitutes a therapeutic target in neuroblastoma (NB). Experimental Design: Expression of LDHA mRNA and protein was determined in 709 and 110 NB patient samples, respectively, and correlated with survival and risk factors. LDHA and LDHB were depleted in human NB cell lines by CRISPR/Cas9 and shRNA, respectively, and aerobic glycolysis, clonogenicity, and tumorigenicity were determined. Expression of LDHA in relation to MYCN was measured in NB cell lines and in the TH-MYCN NB mouse model. Results: Expression of LDHA, both on the mRNA and the protein level, was significantly and independently associated with decreased patient survival. Predominant cytoplasmic localization of LDHA protein was associated with poor outcome. Amplification and expression of MYCN did not correlate with expression of LDHA in NB cell lines or TH-MYCN mice, respectively. Knockout of LDHA inhibited clonogenicity, tumorigenicity, and tumor growth without abolishing LDH activity or significantly decreasing aerobic glycolysis. Concomitant depletion of LDHA and the isoform LDHB ablated clonogenicity while not abrogating LDH activity or decreasing aerobic glycolysis. The isoform LDHC was not expressed. Conclusions: High expression of LDHA is independently associated with outcome of NB, and NB cells can be inhibited by depletion of LDHA or LDHB. This inhibition appears to be unrelated to LDH activity and aerobic glycolysis. Thus, investigations of inhibitory mechanisms beyond attenuation of aerobic glycolysis are warranted, both in NB and normal cells. Clin Cancer Res; 24(22); 5772–83. ©2018 AACR.

Douglas, A, Torpy, F, Surawski, N & Irga, P 2018, 'Mapping Urban Aerosolized Fungi: Predicting Spatial and Temporal Indoor Concentrations', Human Ecology Review, vol. 24, no. 2, pp. 81-103.
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DU, Y 2018, 'Topology Optimization of Multiple Materials Compliant Mechanisms Based on Sequence Interpolation Model and Multigrid Method', Journal of Mechanical Engineering, vol. 54, no. 13, pp. 47-47.
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Multi-material flexible mechanism topology optimization based on Solid isotropic material with penalization (SIMP) is to decompose the original problem into several sub-problems for layer optimization, which increases the number of design variables exponentially. The method utilizes the traditional finite element discretization. In order to obtain a clear topology, the number of meshes is inevitably huge. These two factors cause the computational efficiency of the method to be low. Therefore, based on the power function polynomial, the sequence interpolation model is proposed, and the multi-material layout iteration is used to make the different materials gather in the design domain to a plurality of predefined material points. It can be completed under a single optimization framework without decomposing into sub-problems. Topology optimization of materials without increasing the number of design variables. Aiming at the maximum geometric gain of the mechanism, a multi-material flexible mechanism topology optimization model is established. In the process of solving the governing equations by using finite element method, the multi-grid method is introduced. The meshing granularity progressively moves the displacement field of the coarse mesh horizontally as the initial field quantity on the fine mesh, avoiding directly using the fine mesh to design the domain. The high computational cost problem caused by the overall dispersion improves the calculation efficiency. The improved optimization criterion method is used to solve the model, and the multi-material flexible mechanism with optimal sequence layout is obtained. The effectiveness of the proposed method is verified by a typical example and the corresponding results of SIMP-based methods.

Dua, K, Rapalli, VK, Shukla, SD, Singhvi, G, Shastri, MD, Chellappan, DK, Satija, S, Mehta, M, Gulati, M, Pinto, TDJA, Gupta, G & Hansbro, PM 2018, 'Multi-drug resistant Mycobacterium tuberculosis & oxidative stress complexity: Emerging need for novel drug delivery approaches', Biomedicine & Pharmacotherapy, vol. 107, pp. 1218-1229.
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© 2018 Elsevier Masson SAS Tuberculosis (caused by Mycobacterium tuberculosis, Mtb) treatment involves multiple drug regimens for a prolonged period. However, the therapeutic benefit is often limited by poor patient compliance, subsequently leading to treatment failure and development of antibiotic resistance. Notably, oxidative stress is a crucial underlying factor that adversely influences the various treatment regimens in tuberculosis. Little information is available with advanced drug delivery systems that could be effectively utilized, in particular, for targeting the oxidative stress in tuberculosis. Thus, this presents an opportunity to review the utility of various available, controlled-release drug delivery systems (e.g., microspheres, liposomes, niosomes, solid lipid nanoparticles, dendrimers) that could be beneficial in tuberculosis treatments. This will help the biological and formulation scientists to pave a new path in formulating a treatment regimen for multi-drug resistant Mtb.

Duan, H, Wang, Q, Erler, DV, Ye, L & Yuan, Z 2018, 'Effects of free nitrous acid treatment conditions on the nitrite pathway performance in mainstream wastewater treatment', Science of The Total Environment, vol. 644, pp. 360-370.
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© 2018 Elsevier B.V. Inline sludge treatment using free nitrous acid (FNA) was recently shown to be effective in establishing the nitrite pathway in a biological nitrogen removal system. However, the effects of FNA treatment conditions on the nitrite pathway performance remained to be investigated. In this study, three different FNA treatment frequencies (daily sludge treatment ratios of 0.22, 0.31 and 0.38, respectively), two FNA concentrations (1.35 mgN/L and 4.23 mgN/L, respectively) and two influent feeding regimes (one- and two-step feeding) were investigated in four laboratory-scale sequencing batch reactors. The nitrite accumulation ratio was positively correlated to the FNA treatment frequency. However, when a high treatment frequency was used e.g., daily sludge treatment ratio of 0.38, a significant reduction in ammonia oxidizing bacteria (AOB) activity occurred, leading to poor ammonium oxidation. AOB were able to acclimatise to FNA concentrations up to of 4.23 mgN/L, whereas nitrite oxidizing bacteria (NOB) were limited by an FNA concentration of 1.35 mgN/L over the duration of the study (up to 120 days). This difference in sensitivity to FNA could be used to further enhance nitrite accumulation, with 90% accumulation achieved at an FNA concentration of 4.23 mgN/L and a daily sludge treatment ratio of 0.31 in this study. However, this high level of nitrite accumulation led to increased N2O emission, with emission factors of up to 3.9% observed. The N2O emission was mitigated (reduced to 1.3%) by applying two-step feeding resulting in a nitrite accumulation ratio of 45.1%. Economic analysis showed that choosing the optimal FNA treatment conditions depends on a combination of the wastewater characteristics, the nitrogen discharge standards, and the operational costs. This study provides important information for the optimisation and practical application of FNA-based sludge treatment technology for achieving the mainstream stable nitrite pathway.

Duong, HC, Álvarez, IRC, Nguyen, TV & Nghiem, LD 2018, 'Membrane distillation to regenerate different liquid desiccant solutions for air conditioning', Desalination, vol. 443, pp. 137-142.
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© 2018 The capacity of membrane distillation (MD) to regenerate three commonly used liquid desiccant solutions (i.e. CaCl2, LiCl, and a mixture of CaCl2/LiCl) for liquid desiccant air-conditioners (LDAC) was evaluated. The results demonstrate considerable impact of the concentration polarisation effect on the process water flux during MD regeneration of these three desiccant solutions. For each of these liquid desiccant solutions, the experimentally measured water flux of the MD process was about half of the calculated value using the process mass transfer coefficient (Km) obtained during the process characterisation without taking into account the concentration polarisation effect. The observed deviation between the experimentally measured and calculated process water flux indicates the need to include the concentration polarisation effect in the model for calculating water flux. Although Ca2+ concentration in the CaCl2 and CaCl2/LiCl liquid desiccant solutions exceeded the solubility limit for CaCO3, membrane scaling was not observed. Nevertheless, there was evidence that membrane fouling might occur during extended MD regeneration of liquid desiccant solutions containing CaCl2.

Duong, HC, Ansari, AJ, Nghiem, LD, Pham, TM & Pham, TD 2018, 'Low Carbon Desalination by Innovative Membrane Materials and Processes', Current Pollution Reports, vol. 4, no. 4, pp. 251-264.
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Duong, HC, Chuai, D, Woo, YC, Shon, HK, Nghiem, LD & Sencadas, V 2018, 'A novel electrospun, hydrophobic, and elastomeric styrene-butadiene-styrene membrane for membrane distillation applications', Journal of Membrane Science, vol. 549, pp. 420-427.
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© 2017 In this study, a novel hydrophobic, microporous membrane was fabricated from styrene-butadiene-styrene (SBS) polymer using electrospinning and evaluated for membrane distillation applications. Compared to a commercially available polytetrafluoroethylene (PTFE) membrane, the SBS membrane had larger membrane pore size and fiber diameter and comparable membrane porosity. The fabricated SBS showed slightly lower water flux than the PTFE membrane because it was two times thicker. However, the SBS membrane had better salt rejection and most importantly could be fabricated via a simple process. The SBS membrane was also more hydrophobic than the reference PTFE membrane. In particular, as temperature of the reference water liquid increased to 60 °C, the SBS membrane remained hydrophobic with a contact angle of 100° whereas the PTFE became hydrophilic with a contact angle of less than 90°. The hydrophobic membrane surface prevented the intrusion of liquid into the membrane pores, thus improving the salt rejection of the SBS membrane. In addition, the SBS membrane had superior mechanical strength over the PTFE membrane. Using the SBS membrane, stable water flux was achieved throughout an extended MD operation period of 120 h to produce excellent quality distillate (over 99.7% salt rejection) from seawater.

Duong, NMH, Xu, Z-Q, Kianinia, M, Su, R, Liu, Z, Kim, S, Bradac, C, Li, L-J, Solntsev, A, Liu, J & Aharonovich, I 2018, 'Enhanced Emission from WSe2 Monolayers Coupled to Circular Bragg Gratings', ACS Photonics, vol. 5, no. 10, pp. 3950-3955.
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Two-dimensional transition-metal dichalcogenides (TMDC) are of great interestfor on-chip nanophotonics due to their unique optoelectronic properties. Here,we propose and realize coupling of tungsten diselenide (WSe2) monolayers tocircular Bragg grating structures to achieve enhanced emission. The interactionbetween WSe2 and the resonant mode of the structure results in Purcell-enhancedemission, while the symmetric geometrical structure improves the directionalityof the out-coupling stream of emitted photons. Furthermore, this hybridstructure produces a record high contrast of the spin valley readout (> 40%)revealed by the polarization resolved photoluminescence (PL) measurements. Ourresults are promising for on-chip integration of TMDC monolayers with opticalresonators for nanophotonic circuits.

Durán Santomil, P, Otero González, L, Martorell Cunill, O & Merigó Lindahl, JM 2018, 'Backtesting an equity risk model under Solvency II', Journal of Business Research, vol. 89, pp. 216-222.
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© 2018 Elsevier Inc. Backtesting is a technique for validating internal models under Solvency II, which allows for evaluating the discrepancies between the results provided by a model and real observations. This paper aims to establish various backtesting tests and to show their applications to equity risk in Solvency II. Normal and empirical models with a rolling window are used to determine VaR at the 99.5% confidence level over a one-year time horizon. The proposed methodology performs the backtesting of annualized returns arising from the accumulation of daily returns. The results show that even if a model is conservative when tested out of a sample, it may be inadequate when evaluated in a sample, thereby highlighting the problems inherent in the out-of-sample backtesting proposed by the regulator.

Dyson, LE & Frawley, JK 2018, 'A Student-Generated Video Careers Project', International Journal of Mobile and Blended Learning, vol. 10, no. 4, pp. 32-51.
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This article describes how in recent years, the multimedia recording capabilities of mobile devices have been used increasingly to create a more active, learner-centred educational experience. Despite the proven value of student-generated multimedia projects, there are still gaps in our understanding of how students learn during them. This article reports on a project in which first-year information technology students interviewed IT professionals in their workplace and video-recorded the interview to enable sharing with their peers. In order to understand the statistically significant increases found in students' learning, student diaries and reflections were analyzed qualitatively. Factors found to contribute to learning included: the iterative nature of student activities; the multiple, evolving representations of knowledge as students proceeded through the project; the importance of the workplace context in engaging students and enhancing learning; the affordance of mobile technology for capturing and sharing this context; and the collaborative and metacognitive processes fostered by the project.

Ebrahimi, M, ShafieiBavani, E, Wong, R & Chen, F 2018, 'Twitter user geolocation by filtering of highly mentioned users', Journal of the Association for Information Science and Technology, vol. 69, no. 7, pp. 879-889.
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Geolocated social media data provide a powerful source of information about places and regional human behavior. Because only a small amount of social media data have been geolocation‐annotated, inference techniques play a substantial role to increase the volume of annotated data. Conventional research in this area has been based on the text content of posts from a given user or the social network of the user, with some recent crossovers between the text‐ and network‐based approaches. This paper proposes a novel approach to categorize highly‐mentioned users (celebrities) into Local and Global types, and consequently use Local celebrities as location indicators. A label propagation algorithm is then used over the refined social network for geolocation inference. Finally, we propose a hybrid approach by merging a text‐based method as a back‐off strategy into our network‐based approach. Empirical experiments over three standard Twitter benchmark data sets demonstrate that our approach outperforms state‐of‐the‐art user geolocation methods.

Eeshwarasinghe, D, Loganathan, P, Kalaruban, M, Sounthararajah, DP, Kandasamy, J & Vigneswaran, S 2018, 'Removing polycyclic aromatic hydrocarbons from water using granular activated carbon: kinetic and equilibrium adsorption studies', Environmental Science and Pollution Research, vol. 25, no. 14, pp. 13511-13524.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Polycyclic aromatic hydrocarbons (PAHs) constitute a group of highly persistent, toxic and widespread environmental micropollutants that are increasingly found in water. A study was conducted in removing five PAHs, specifically naphthalene, acenaphthylene, acenaphthene, fluorene and phenanthrene, from water by adsorption onto granular activated carbon (GAC). The pseudo-first-order (PFO) model satisfactorily described the kinetics of adsorption of the PAHs. The Weber and Morris diffusion model’s fit to the data showed that there were faster and slower rates of intra-particle diffusion probably into the mesopores and micropores of the GAC, respectively. These rates were negatively related to the molar volumes of the PAHs. Batch equilibrium adsorption data fitted well to the Langmuir, Freundlich and Dubinin–Radushkevich models, of which the Freundlich model exhibited the best fit. The adsorption affinities were related to the hydrophobicity of the PAHs as determined by the log Kow values. Free energies of adsorption calculated from the Dubinin–Radushkevich model and the satisfactory kinetic data fitting to the PFO model suggested physical adsorption of the PAHs. Adsorption of naphthalene, acenaphthylene and acenaphthene in fixed-bed columns containing a mixture of GAC (0.5 g) + sand (24.5 g) was satisfactorily simulated by the Thomas model.

El-Sayed, H, Sankar, S, Daraghmi, Y-A, Tiwari, P, Rattagan, E, Mohanty, M, Puthal, D & Prasad, M 2018, 'Accurate Traffic Flow Prediction in Heterogeneous Vehicular Networks in an Intelligent Transport System Using a Supervised Non-Parametric Classifier', Sensors, vol. 18, no. 6, pp. 1696-1696.
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Heterogeneous vehicular networks (HETVNETs) evolve from vehicular ad hoc networks (VANETs), which allow vehicles to always be connected so as to obtain safety services within intelligent transportation systems (ITSs). The services and data provided by HETVNETs should be neither interrupted nor delayed. Therefore, Quality of Service (QoS) improvement of HETVNETs is one of the topics attracting the attention of researchers and the manufacturing community. Several methodologies and frameworks have been devised by researchers to address QoS-prediction service issues. In this paper, to improve QoS, we evaluate various traffic characteristics of HETVNETs and propose a new supervised learning model to capture knowledge on all possible traffic patterns. This model is a refinement of support vector machine (SVM) kernels with a radial basis function (RBF). The proposed model produces better results than SVMs, and outperforms other prediction methods used in a traffic context, as it has lower computational complexity and higher prediction accuracy.

El-Sayed, H, Sankar, S, Prasad, M, Puthal, D, Gupta, A, Mohanty, M & Lin, C-T 2018, 'Edge of Things: The Big Picture on the Integration of Edge, IoT and the Cloud in a Distributed Computing Environment', IEEE Access, vol. 6, pp. 1706-1717.
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© 2013 IEEE. A centralized infrastructure system carries out existing data analytics and decision-making processes from our current highly virtualized platform of wireless networks and the Internet of Things (IoT) applications. There is a high possibility that these existing methods will encounter more challenges and issues in relation to network dynamics, resulting in a high overhead in the network response time, leading to latency and traffic. In order to avoid these problems in the network and achieve an optimum level of resource utilization, a new paradigm called edge computing (EC) is proposed to pave the way for the evolution of new age applications and services. With the integration of EC, the processing capabilities are pushed to the edge of network devices such as smart phones, sensor nodes, wearables, and on-board units, where data analytics and knowledge generation are performed which removes the necessity for a centralized system. Many IoT applications, such as smart cities, the smart grid, smart traffic lights, and smart vehicles, are rapidly upgrading their applications with EC, significantly improving response time as well as conserving network resources. Irrespective of the fact that EC shifts the workload from a centralized cloud to the edge, the analogy between EC and the cloud pertaining to factors such as resource management and computation optimization are still open to research studies. Hence, this paper aims to validate the efficiency and resourcefulness of EC. We extensively survey the edge systems and present a comparative study of cloud computing systems. After analyzing the different network properties in the system, the results show that EC systems perform better than cloud computing systems. Finally, the research challenges in implementing an EC system and future research directions are discussed.

Erfani, SS & Abedin, B 2018, 'Impacts of the use of social network sites on users' psychological well‐being: A systematic review', Journal of the Association for Information Science and Technology, vol. 69, no. 7, pp. 900-912.
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As Social Network Sites (SNSs) are increasingly becoming part of people's everyday lives, the implications of their use need to be investigated and understood. We conducted a systematic literature review to lay the groundwork for understanding the relationship between SNS use and users' psychological well‐being and for devising strategies for taking advantage of this relationship. The review included articles published between 2003 and 2016, extracted from major academic databases. Findings revealed that the use of SNSs is both positively and negatively related to users' psychological well‐being. We discuss the factors that moderate this relationship and their implications on users' psychological well‐being. Many of the studies we reviewed lacked a sound theoretical justification for their findings and most involved young and healthy students, leaving other cohorts of SNS users neglected. The paper concludes with the presentation of a platform for future investigation.

Erwin, E, Surjosatyo, A, Sulistyo, N, Meurahindra, M & Soemardi, T 2018, 'The effect of hybrid savonius and darrieus turbine on the change of wake recovery and improvement of wind energy harvesting', Journal of Applied Engineering Science, vol. 16, no. 3, pp. 416-423.
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© 2018 Institut za Istrazivanja. All rights reserved. The energy crisis encourages the development of renewable energy; one of the potential renewable energy is wind. In the field of wind turbine there is a two-way development of the utilization of wind energy, first by making a large wind turbine, the second by making a wind farm energy with a relatively small wind turbine.This hybrid VAWT wind turbine (Sultan Wind Turbine) is designed to work optimally on a farm array, on a wind turbine farm array will always cause a wake effect that will reduce overall wind turbine and farm array performance, an investigation with a CFD simulation is required to predict how far the wake effect will be before farm array build.The use of simulation software has been widely used to predict the effects of this wake, and experiments in the laboratory have also been done to predict the effects of a wake as well.This study'spurpose is to predict the distance area of the recovery wake behindthe wind turbine, this distance which will be the reference distance between wind turbine units and determining the density of the turbine in a farm. Simulation using Computational Fluid Dynamics (CFD), with a method of Multi Frame Reference (MRF). Analysis using descriptive and inferential method in statistics such as mean, Kolmogorov-Smirnov Z and KruskalWalis test.From the analysis of simulation results and data processing descriptively and analytic statistic, it can be concluded from the data given, the distance of x/D=4, wind speed has recovery to the value near the input speed and no significant change to x/D= 9. Then it can be concluded that the distance between two windturbines that can be used is a distance of 3.6 meters.These data suggest that the hybrid farm array VAWT savonius and darrieus have a higher power density compared to HAWT. From this power density calculation the hybrid VAWT has a greater electrical potential up to 300 percent compared to the HAWT farm array.

Eskandari, M, Li, L & Moradi, MH 2018, 'Decentralized Optimal Servo Control System for Implementing Instantaneous Reactive Power Sharing in Microgrids', IEEE Transactions on Sustainable Energy, vol. 9, no. 2, pp. 525-537.
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© 2010-2012 IEEE. Active power is dispatched among distributed generation (DG) units in microgrids (MG) by means of f/P droop control loop, which controls the frequency set-point of voltage source converter (VSI). Since the frequency is a global variable, active power sharing is implemented well proportional to droop coefficients. However, the reactive power is not shared accurately, through V/Q control loop and according to the droop gains, as the voltage is a local variable. Furthermore, considering the small scale of DG units, reactive power sharing should be implemented instantaneously to prevent DG units from overcurrent or even blackout of the MG. This paper deals with reactive power sharing issue in droop control-based MGs as well as stability and dynamic performance concerns of V/Q control loop. A servo control system is designed to control power converters in MGs, by which droop-based VSIs are converted to servo VSIs (S-VSIs). A novel decentralized method is proposed to obtain the reactive power set-points of S-VSIs according to their droop coefficients, and fuzzy particle swarm optimization method is used to optimize the S-VSI's parameters, so that, in addition to securing stability of the V/Q loop, the desired (fast) response in reference tracking is achieved. The simulation results show that the proposed strategy is effective and its performance is not affected by delay or interruption of the existing low bandwidth communication link.

Eskandari, M, Li, L & Moradi, MH 2018, 'Improving power sharing in islanded networked microgrids using fuzzy-based consensus control', Sustainable Energy, Grids and Networks, vol. 16, pp. 259-269.
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© 2018 Elsevier Ltd The rising world-wide trend toward developing clean energy resources has caused dispersed installation of renewable energy resources (RESs) in distribution grids. Microgrid (MG) concept is proposed as a key factor in optimal and secure integration of, mostly converter-based, RESs into power systems. One of the major challenges related to MG control is ineffectiveness of droop control in accurate power sharing which is affected by the feeder impedance. In this paper, a fuzzy-based consensus control protocol is developed to address this issue in multi-bus MGs (MBMGs). Consensus signals are inserted into the conventional droop controller as complementary part to overcome the drawback of the droop control in power sharing in MBMGs. Dynamic fuzzy coefficients of consensus signals are designed to model X/R ratio of the grid impedance in the control system. In addition, a novel small signal model of MBMG is developed, by considering the conventional droop control, MBMG power network and power lines impedance to design and assess performance of the control system. Consensus control is also incorporated into the proposed control system of MBMG to analyze the stability. Simulation results are presented to assess effectiveness of the control strategy in MATLAB\Simulink.

Esmaili, N, Piccardi, M, Kruger, B & Girosi, F 2018, 'Analysis of healthcare service utilization after transport-related injuries by a mixture of hidden Markov models', PLOS ONE, vol. 13, no. 11, pp. e0206274-e0206274.
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© 2018 Esmaili et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background Transport injuries commonly result in significant disease burden, leading to physical disability, mental health deterioration and reduced quality of life. Analyzing the patterns of healthcare service utilization after transport injuries can provide an insight into the health of the affected parties, allow improved health system resource planning, and provide a baseline against which any future system-level interventions can be evaluated. Therefore, this research aims to use time series of service utilization provided by a compensation agency to identify groups of claimants with similar utilization patterns, describe such patterns, and characterize the groups in terms of demographic, accident type and injury type. Methods To achieve this aim, we have proposed an analytical framework that utilizes latent variables to describe the utilization patterns over time and group the claimants into clusters based on their service utilization time series. To perform the clustering without dismissing the temporal dimension of the time series, we have used a well-established statistical approach known as the mixture of hidden Markov models (MHMM). Ensuing the clustering, we have applied multinomial logistic regression to provide a description of the clusters against demographic, injury and accident covariates. Results We have tested our model with data on psychology service utilization from one of the main compensation agencies for transport accidents in Australia, and found that three clear clusters of service utilization can be evinced from the data. These three clusters correspond to claimants who have tended to use the services 1) only briefly after the accident; 2) for an intermediate period of time...

Fahmideh, M & Beydoun, G 2018, 'Reusing empirical knowledge during cloud computing adoption.', J. Syst. Softw., vol. 138, pp. 124-157.
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Fan, X, He, X, Xiang, C, Puthal, D, Gong, L, Nanda, P & Fang, G 2018, 'Towards System Implementation and Data Analysis for Crowdsensing Based Outdoor RSS Maps', IEEE Access, vol. 6, pp. 47535-47545.
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© 2013 IEEE. With the explosive usage of smart mobile devices, sustainable access to wireless networks (e.g., Wi-Fi) has become a pervasive demand. Most mobile users expect seamless network connection with low cost. Indeed, this can be achieved by using an accurate received signal strength (RSS) map of wireless access points. While existing methods are either costly or unscalable, the recently emerged mobile crowdsensing (MCS) paradigm is a promising technique for building RSS maps. MCS applications leverage pervasive mobile devices to collaboratively collect data. However, the heterogeneity of devices and the mobility of users could cause inherent noises and blank spots in collected data set. In this paper, we study how to: 1) tame the sensing noises from heterogenous mobile devices and 2) construct accurate and complete RSS maps with random mobility of crowdsensing participants. First, we build a mobile crowdsensing system called i Map to collect RSS measurements with heterogeneous mobile devices. Second, through observing experimental results, we build statistical models of sensing noises and derive different parameters for each kind of mobile device. Third, we present the signal transmission model with measurement error model, and we propose a novel signal recovery scheme to construct accurate and complete RSS maps. The evaluation results show that the proposed method can achieve 90% and 95% recovery rate in geographic coordinate system and polar coordinate system, respectively.

Fan, X, Zhao, J, Ren, F, Wang, Y, Feng, Y, Ding, L, Zhao, L, Shang, Y, Li, J, Ni, J, Jia, B, Liu, Y & Chang, Z 2018, 'Dimerization of p15RS mediated by a leucine zipper–like motif is critical for its inhibitory role on Wnt signaling', Journal of Biological Chemistry, vol. 293, no. 20, pp. 7618-7628.
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© 2018 Fan et al. We previously demonstrated that p15RS, a newly discovered tumor suppressor, inhibits Wnt/-catenin signaling by interrupting the formation of -cateninTCF4 complex. However, it remains unclear how p15RS helps exert such an inhibitory effect on Wnt signaling based on its molecular structure. In this study, we reported that dimerization of p15RS is required for its inhibition on the transcription regulation of Wnt-targeted genes. We found that p15RS forms a dimer through a highly conserved leucine zipper–like motif in the coiled-coil terminus domain. In particular, residues Leu-248 and Leu-255 were identified as being responsible for p15RS dimerization, as mutation of these two leucines into prolines disrupted the homodimer formation of p15RS and weakened its suppression of Wnt signaling. Functional studies further confirmed that mutations of p15RS at these residues results in diminishment of its inhibition on cell proliferation and tumor formation. We therefore concluded that dimerization of p15RS governed by the leucine zipper–like motif is critical for its inhibition of Wnt/-catenin signaling and tumorigenesis.

Fang, J, Sun, G, Qiu, N, Pang, T, Li, S & Li, Q 2018, 'On hierarchical honeycombs under out-of-plane crushing', International Journal of Solids and Structures, vol. 135, pp. 1-13.
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© 2017 Hierarchy has been introduced to honeycomb structures in pursuing ultralight materials with outstanding mechanical properties. Nevertheless, the hierarchical honeycombs under the out-of-plane loads have not been well studied experimentally and analytically for energy absorption to date. This study aimed to apply a special structural hierarchy to the honeycomb by replacing the sides of hexagons with smaller hexagons. The quasi-static test of the hierarchical honeycomb specimen was first conducted experimentally to investigate the crushing behaviours; and then the corresponding finite element (FE) analyses were performed. Finally, the analytical solutions to the mean crushing force and plateau stress were derived based on the simplified super folding element (SSFE) method. It was shown that the experimental data and numerical results agreed well in terms of crushing force versus displacement relation and energy absorption characteristics; and the analytical results were validated by the experimental test. Importantly, the hierarchy could improve the energy absorption; and the increase in the order and number of replacement hexagons could excavate the advantage even further. Specifically, the second order honeycomb characterized by five smaller replacement hexagons at each order can yield a plateau stress 2.63 and 4.16 times higher than the regular honeycomb and the aluminium foam, respectively. While it might lead to global bending, structural hierarchy provides new architectural configurations for developing novel ultralight materials with exceptional energy absorption capacity under out-of-plane loads.

Fanos, AM & Pradhan, B 2018, 'Laser Scanning Systems and Techniques in Rockfall Source Identification and Risk Assessment: A Critical Review', Earth Systems and Environment, vol. 2, no. 2, pp. 163-182.
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Rockfall poses risk to people, their properties and to transportation ways in mountainous and hilly regions. This catastrophe shows various characteristics such as vast distribution, sudden occurrence, variable magnitude, strong fatalness and randomicity. Therefore, prediction of rockfall phenomenon both spatially and temporally is a challenging task. Digital Terrain model (DTM) is one of the most significant elements in rockfall source identification and risk assessment. Light detection and ranging (LiDAR) is the most advanced effective technique to derive high-resolution and accurate DTM. This paper presents a critical overview of rockfall phenomenon (definition, triggering factors, motion modes and modeling) and LiDAR technique in terms of data pre-processing, DTM generation and the factors that can be obtained from this technique for rockfall source identification and risk assessment. It also reviews the existing methods that are utilized for the evaluation of the rockfall trajectories and their characteristics (frequency, velocity, bouncing height and kinetic energy), probability, susceptibility, hazard and risk. Detail consideration is given on quantitative methodologies in addition to the qualitative ones. Various methods are demonstrated with respect to their application scales (local and regional). Additionally, attention is given to the latest improvement, particularly including the consideration of the intensity of the phenomena and the magnitude of the events at chosen sites.

Fanos, AM, Pradhan, B, Mansor, S, Yusoff, ZM & Abdullah, AFB 2018, 'A hybrid model using machine learning methods and GIS for potential rockfall source identification from airborne laser scanning data', Landslides, vol. 15, no. 9, pp. 1833-1850.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. The main objectives of this paper are to design and evaluate a hybrid approach based on Gaussian mixture model (GMM) and random forest (RF) for detecting rockfall source areas using airborne laser scanning data. The former model was used to calculate automatically slope angle thresholds for different type of landslides such as shallow, translational, rotational, rotational-translational, complex, debris flow, and rockfalls. After calculating the slope angle thresholds, a homogenous morphometric land use area (HMLA) was constructed to improve the performance of the model computations and reduce the sensitivity of the model to the variations in different conditioning factors. After that, the support vector machine (SVM) was applied in addition to backward elimination (BE) to select and rank the conditioning factors considering the type of landslides. Then, different machine learning methods [artificial neural network (ANN), logistic regression (LR), and random forest (RF) were trained with the selected best factors and previously prepared inventory datasets. The best fit method (RF) was then used to generate the probability maps and then the source areas were detected by combining the slope raster (reclassified according to the thresholds found by the GMM model) and the probability maps. The accuracy assessment shows that the proposed hybrid model could detect the potential rockfalls with an accuracy of 0.92 based on training data and 0.96 on validation data. Overall, the proposed model is an efficient model for identifying rockfall source areas in the presence of other types of landslides with an accepted generalization performance.

Faradonbeh, RS, Armaghani, DJ, Amnieh, HB & Mohamad, ET 2018, 'Prediction and minimization of blast-induced flyrock using gene expression programming and firefly algorithm', Neural Computing and Applications, vol. 29, no. 6, pp. 269-281.
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Faradonbeh, RS, Hasanipanah, M, Amnieh, HB, Armaghani, DJ & Monjezi, M 2018, 'Development of GP and GEP models to estimate an environmental issue induced by blasting operation', Environmental Monitoring and Assessment, vol. 190, no. 6.
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Farizal, F, Aji, R, Rachman, A, Nasruddin, N & Mahlia, TMI 2018, 'Indonesia’s Municipal Solid Waste 3R and Waste to Energy Programs', Makara Journal of Technology, vol. 21, no. 3, pp. 153-153.
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Fatahi, B, Van Nguyen, Q, Xu, R & Sun, W-J 2018, 'Three-Dimensional Response of Neighboring Buildings Sitting on Pile Foundations to Seismic Pounding', International Journal of Geomechanics, vol. 18, no. 4, pp. 04018007-04018007.
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© 2018 American Society of Civil Engineers. Seismic pounding occurs when the separation gap between buildings and structures is not wide enough, particularly during major earthquake events; this can cause them to collide, causing local damage or, in extreme cases, collapse. This study investigated the impact that this separation gap has on the seismic response of midrise buildings supported on piles while considering seismic soil-pile-structure interaction (SSPSI). To achieve this aim, three 15-story reinforced concrete buildings sitting on pile foundations and with five different separation gaps under excitations from the 1994 Northridge and 1995 Kobe earthquakes were numerically simulated. This study used three-dimensional numerical modeling to simultaneously capture the effects of seismic pounding and SSPSI. Because the considered structure, pile foundation, and soil deposit are three-dimensional in nature, the adopted three-dimensional numerical modeling can provide a more realistic simulation to capture the seismic behavior of the system. The nonlinear behavior of structural elements was included, and the dynamic soil properties were obtained from field data and backbone curves. A contact pair interface with small-sliding surface-to-surface formulation between buildings was used to capture possible seismic pounding, and contact interfaces with a finite-sliding formulation were used to simulate the interaction between the piles and the soil. The results, including lateral building deflections, interstory drifts, structural shear forces, foundation rocking, lateral pile deflections, and the distributions of bending moments and shear forces of the piles, are presented and discussed. The findings of this study will give engineers a better insight into the possible effects of seismic pounding on the seismic performance of buildings, and the response of endbearing piles in soft soils.

Fattah, IMR, Ming, C, Chan, QN, Wehrfritz, A, Pham, PX, Yang, W, Kook, S, Medwell, PR, Yeoh, GH, Hawkes, ER & Masri, AR 2018, 'Spray and Combustion Investigation of Post Injections under Low-Temperature Combustion Conditions with Biodiesel', Energy & Fuels, vol. 32, no. 8, pp. 8727-8742.
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Post injection is a multiple-injection strategy that is commonly used as a particulate matter control measure to reduce soot emissions, yet the mechanisms and the interactions between the main and post injections are only vaguely understood. For this work, experiments were performed to assess the effects of varying dwell time between the main and post injections in a compression-ignition (CI) engine environment simulated using a constant-volume combustion chamber. The ambient density, bulk temperature, and oxygen concentration used for this work were controlled at 19.4 kg/m3, 900 K, and 15 vol % O2, respectively. A canola oil-based biodiesel was tested and injected at a fixed injection pressure of 100 MPa into the simulated CI engine environment. A mass ratio of 80%-20% was maintained between the main and post injections, with the dwell time between the injections varied from 1.5 to 2.5 ms. Comparative measurements were performed using the same fuel and injection schedules, but at a higher ambient gas temperature condition of 1100 K. Optical diagnostics methods, including diffused-back illumination and high-speed flame luminosity imaging, were used to assess the spray and combustion processes of the post injection test case. Under the conditions of this work, it was found that the ignition delays, ignition locations, and flame lift-off lengths of the post injection flames are consistently shorter than those of the main injections, with the variations influenced by the extent of the interaction of the post injection with the combustion products from the main injection. A two-color pyrometry technique was also used to measure the soot temperature and soot concentration factor information on the main-post injection cases. The data revealed a greater interaction between the main and post injections resulted in a more rapid development of the soot zone of the post injection with higher temperature after ignition. The distribution of the most probable soot co...

Faunce, TA, Prest, J, Su, D, Hearne, SJ & Iacopi, F 2018, 'On-grid batteries for large-scale energy storage: Challenges and opportunities for policy and technology', MRS Energy & Sustainability, vol. 5, no. 1.
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ABSTRACT

Feng, J, Wu, D, Gao, W & Li, G 2018, 'Hybrid uncertain natural frequency analysis for structures with random and interval fields', Computer Methods in Applied Mechanics and Engineering, vol. 328, pp. 365-389.
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This paper presents a robust non-deterministic free vibration analysis for engineering structures involving hybrid, yet spatially dependent, uncertain system parameters. Distinguished from the conventional hybrid uncertain eigenvalue problem, the concept of interval field is enclosed with random field model such that, both the stochastic and non-stochastic representations of the spatial dependency of the uncertainties are simultaneously incorporated within a unified non-deterministic free vibration analysis. In order to determine the probabilistic characteristics (i.e., means and standard deviations) of the extremities of structural natural frequencies, an extended unified interval stochastic sampling (X-UISS) method is implemented for the purpose of effective hybrid uncertain free vibration analysis. By meticulously blending sharpness-promised interval eigenvalue analysis with stochastic sampling techniques, the stochastic profiles (i.e., probability density functions (PDFs) and the cumulative distribution functions (CDFs)) of the extreme bounds of the structural natural frequencies can be rigorously established by utilizing the adequate statistical inference methods. The applicability and effectiveness of the proposed computational framework are evidently demonstrated through the numerical investigations on various practically motivated engineering structures.

Feng, X, Chang, L, Lin, X, Qin, L, Zhang, W & Yuan, L 2018, 'Distributed computing connected components with linear communication cost.', Distributed Parallel Databases, vol. 36, no. 3, pp. 555-592.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The paper studies three fundamental problems in graph analytics, computing connected components (CCs), biconnected components (BCCs), and 2-edge-connected components (ECCs) of a graph. With the recent advent of big data, developing efficient distributed algorithms for computing CCs, BCCs and ECCs of a big graph has received increasing interests. As with the existing research efforts, we focus on the Pregel programming model, while the techniques may be extended to other programming models including MapReduce and Spark. The state-of-the-art techniques for computing CCs and BCCs in Pregel incur O(m× # supersteps) total costs for both data communication and computation, where m is the number of edges in a graph and #supersteps is the number of supersteps. Since the network communication speed is usually much slower than the computation speed, communication costs are the dominant costs of the total running time in the existing techniques. In this paper, we propose a new paradigm based on graph decomposition to compute CCs and BCCs with O(m) total communication cost. The total computation costs of our techniques are also smaller than that of the existing techniques in practice, though theoretically almost the same. Moreover, we also study distributed computing ECCs. We are the first to study this problem and an approach with O(m) total communication cost is proposed. Comprehensive empirical studies demonstrate that our approaches can outperform the existing techniques by one order of magnitude regarding the total running time.

Feng, X, Wan, W, Xu, RYD, Chen, H, Li, P & Sánchez, JA 2018, 'A perceptual quality metric for 3D triangle meshes based on spatial pooling', Frontiers of Computer Science, vol. 12, no. 4, pp. 798-812.
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Feng, X, Wan, W, Xu, RYD, Perry, S, Zhu, S & Liu, Z 2018, 'A new mesh visual quality metric using saliency weighting-based pooling strategy', Graphical Models, vol. 99, pp. 1-12.
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© 2018 Elsevier Inc. Several metrics have been proposed to assess the visual quality of 3D triangular meshes during the last decade. In this paper, we propose a mesh visual quality metric by integrating mesh saliency into mesh visual quality assessment. We use the Tensor-based Perceptual Distance Measure metric to estimate the local distortions for the mesh, and pool local distortions into a quality score using a saliency weighting-based pooling strategy. Three well-known mesh saliency detection methods are used to demonstrate the superiority and effectiveness of our metric. Experimental results show that our metric with any of three saliency maps performs better than state-of-the-art metrics on the LIRIS/EPFL general-purpose database. We generate a synthetic saliency map by assembling salient regions from individual saliency maps. Experimental results reveal that the synthetic saliency map achieves better performance than individual saliency maps, and the performance gain is closely correlated with the similarity between the individual saliency maps.

Feng, X, Wan, W, Yi Da Xu, R, Perry, S, Li, P & Zhu, S 2018, 'A novel spatial pooling method for 3D mesh quality assessment based on percentile weighting strategy', Computers & Graphics, vol. 74, pp. 12-22.
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Fernandez, E, Hossain, MJ & Nizami, MSH 2018, 'Game-theoretic approach to demand-side energy management for a smart neighbourhood in Sydney incorporating renewable resources', Applied Energy, vol. 232, pp. 245-257.
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Fernández-Barrera, J, Bernabé-Rubio, M, Casares-Arias, J, Rangel, L, Fernández-Martín, L, Correas, I & Alonso, MA 2018, 'The actin-MRTF-SRF transcriptional circuit controls tubulin acetylation via α-TAT1 gene expression', The Journal of Cell Biology, vol. 217, no. 3, pp. 929-944.
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The role of formins in microtubules is not well understood. In this study, we have investigated the mechanism by which INF2, a formin mutated in degenerative renal and neurological hereditary disorders, controls microtubule acetylation. We found that silencing of INF2 in epithelial RPE-1 cells produced a dramatic drop in tubulin acetylation, increased the G-actin/F-actin ratio, and impaired myocardin-related transcription factor (MRTF)/serum response factor (SRF)–dependent transcription, which is known to be repressed by increased levels of G-actin. The effect on tubulin acetylation was caused by the almost complete absence of α-tubulin acetyltransferase 1 (α-TAT1) messenger RNA (mRNA). Activation of the MRTF-SRF transcriptional complex restored α-TAT1 mRNA levels and tubulin acetylation. Several functional MRTF-SRF–responsive elements were consistently identified in the α-TAT1 gene. The effect of INF2 silencing on microtubule acetylation was also observed in epithelial ECV304 cells, but not in Jurkat T cells. Therefore, the actin-MRTF-SRF circuit controls α-TAT1 transcription. INF2 regulates the circuit, and hence microtubule acetylation, in cell types where it has a prominent role in actin polymerization.

Fitch, R, Isler, V, Tokekar, P & Scaramuzza, D 2018, 'Guest editorial: Special issue on active perception', Autonomous Robots, vol. 42, no. 2, pp. 175-176.
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Fonseca, A, Kerick, S, King, J-T, Lin, C-T & Jung, T-P 2018, 'Brain Network Changes in Fatigued Drivers: A Longitudinal Study in a Real-World Environment Based on the Effective Connectivity Analysis and Actigraphy Data', Frontiers in Human Neuroscience, vol. 12.
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© 2018 Fonseca, Kerick, King, Lin and Jung. The analysis of neurophysiological changes during driving can clarify the mechanisms of fatigue, considered an important cause of vehicle accidents. The fluctuations in alertness can be investigated as changes in the brain network connections, reflected in the direction and magnitude of the information transferred. Those changes are induced not only by the time on task but also by the quality of sleep. In an unprecedented 5-month longitudinal study, daily sampling actigraphy and EEG data were collected during a sustained-attention driving task within a near-real-world environment. Using a performance index associated with the subjects' reaction times and a predictive score related to the sleep quality, we identify fatigue levels in drivers and investigate the shifts in their effective connectivity in different frequency bands, through the analysis of the dynamical coupling between brain areas. Study results support the hypothesis that combining EEG, behavioral and actigraphy data can reveal new features of the decline in alertness. In addition, the use of directed measures such as the Convergent Cross Mapping can contribute to the development of fatigue countermeasure devices.

For, B-Q, Staveley-Smith, L, Hurley-Walker, N, Franzen, T, Kapińska, AD, Filipović, MD, Collier, JD, Wu, C, Grieve, K, Callingham, JR, Bell, ME, Bernardi, G, Bowman, JD, Briggs, F, Cappallo, RJ, Deshpande, AA, Dwarakanath, KS, Gaensler, BM, Greenhill, LJ, Hancock, P, Hazelton, BJ, Hindson, L, Johnston-Hollitt, M, Kaplan, DL, Lenc, E, Lonsdale, CJ, McKinley, B, McWhirter, SR, Mitchell, DA, Morales, MF, Morgan, E, Morgan, J, Oberoi, D, Offringa, A, Ord, SM, Prabu, T, Procopio, P, Shankar, NU, Srivani, KS, Subrahmanyan, R, Tingay, SJ, Wayth, RB, Webster, RL, Williams, A, Williams, CL & Zheng, Q 2018, 'A multifrequency radio continuum study of the Magellanic Clouds – I. Overall structure and star formation rates', Monthly Notices of the Royal Astronomical Society, vol. 480, no. 2, pp. 2743-2756.
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© 2018 The Author(s). We present the first low-frequency Murchison Widefield Array (MWA) radio continuum maps of the Magellanic Clouds (MCs), usingmosaics from the GaLactic Extragalactic All-SkyMWA (GLEAM) survey. In this paper, we discuss the overall radio continuum morphology between 76 and 227 MHz and compare them with neutral hydrogen maps, 1.4 GHz continuum maps and optical images. Variation of diffuse emission is noticeable across the Large Magellanic Cloud (LMC) but absent across the bar of the Small Magellanic Cloud (SMC). We also measure the integrated flux densities and derive the spectral indices for the MCs. A double power-law model with fixed α1 = -0.1 fit between 19.7 MHz and 8.55 GHz yields α0 = -0.66 ± 0.08 for the LMC. A power-law model yields α8.55GHz85.5MHz = -0.82 ± 0.03 for the SMC. The radio spectral index maps reveal distinctive flat and steep spectral indices for the HII regions and supernova remnants, respectively. We find strong correlation between HII regions and Ha emission. Using a new 150 MHz-Hα relation as a star formation rate indicator, we estimate global star formation rates of 0.068-0.161 M⊙ yr-1 and 0.021-0.050 M⊙ yr-1 for the LMC and SMC, respectively. Images in 20 frequency bands, and wideband averages are made available via the GLEAM virtual observatory server.

Forouzesh, M, Shen, Y, Yari, K, Siwakoti, YP & Blaabjerg, F 2018, 'High-Efficiency High Step-Up DC–DC Converter With Dual Coupled Inductors for Grid-Connected Photovoltaic Systems', IEEE Transactions on Power Electronics, vol. 33, no. 7, pp. 5967-5982.
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© 1986-2012 IEEE. This paper introduces a non-isolated high step-up DC-DC converter with dual coupled inductors suitable for distributed generation applications. By implementing an input parallel connection, the proposed DC-DC structure inherits shared input current with low ripple, which also requires small capacitive filter at its input. Moreover, this topology can reach high voltage gain by using dual coupled inductors in series connection at the output stage. The proposed converter uses active clamp circuits with a shared clamp capacitor for the main switches. In addition to the active clamp circuit, the leakage energy is recycled to the output by using an integrated regenerative snubber. Indeed, these circuits allow soft-switching conditions, i.e., zero voltage switching and zero current switching for active and passive switching devices, respectively. The mentioned features along with a common ground connection of the input and output make the proposed topology a proper candidate for transformer-less grid-connected photovoltaic systems. The operating performance, analysis and mathematical derivations of the proposed DC-DC converter have been demonstrated in the paper. Moreover, the main features of the proposed converter have been verified through experimental results of a 1-kW laboratory prototype.

Fortunato, L, Pathak, N, Ur Rehman, Z, Shon, H & Leiknes, T 2018, 'Real-time monitoring of membrane fouling development during early stages of activated sludge membrane bioreactor operation', Process Safety and Environmental Protection, vol. 120, pp. 313-320.
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© 2018 Institution of Chemical Engineers Non-invasive analysis and a final destructive analysis were employed to study the fouling formation during the initial days of AS-MBR operation. The fouling layer development was quantified in-situ non-invasively with Optical Coherence Tomography (OCT). The increase in biomass thickness was related to the transmembrane pressure (TMP) and to the increase in concentration of soluble microbial products (SMP) in the reactor The OCT non-destructive analysis allowed normalizing the final autopsy values for the amount of biomass deposited on the membrane. After 8 days of operation, the cake layer presented a biomass activity of 400 pg/mm3 of intra-ATP and EPS concentration of 9.8 mg/ mm3. The microbial community analysis of sludge and biofouling on the membrane surface revealed the abundance of Proteobacteria.

Frawley, JK & Dyson, LE 2018, 'Literacies and Learning in Motion', International Journal of Mobile and Blended Learning, vol. 10, no. 4, pp. 52-72.
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Mobile and participatory cultures have led to widespread change in the way we communicate; emphasizing user generated content and digital multimedia. In this environment, informal learning may occur through digital and networked activities, with literacy no longer limited to alphabetic and character-based texts. This article explores adult learners' new literacies within the context of a digital mobile storytelling project. A qualitative approach is used to explore the artifacts and practices of nine adult participants who comprise the study. Participants created a range of fiction, non-fiction, poetry and diary-style content in a variety of modes and media. Outcomes from content analysis, interview and survey methods depict mobile digital literacies as characteristically situated, experiential and multimodal. The mobile and participatory nature of this project was catalytic to participants' imaginative re-interpretation of the world around them as sources for meaning making and transformation. This paper contributes a case example of mobile learning with adults in a community setting.

Fu, A, Li, S, Yu, S, Zhang, Y & Sun, Y 2018, 'Privacy-preserving composite modular exponentiation outsourcing with optimal checkability in single untrusted cloud server', Journal of Network and Computer Applications, vol. 118, pp. 102-112.
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© 2018 Elsevier Ltd Outsourcing computing allows users with resource-constrained devices to outsource their complex computation workloads to cloud servers, which is more economical for cloud customers. However, since users lose direct control of the computation task, possible threats need to be addressed, such as data privacy and the correctness of results. Modular exponentiation is one of the most basic and time-consuming operations but widely applied in the field of cryptography. In this paper, we propose two new and efficient algorithms for secure outsourcing of single and multiple composite modular exponentiations. Unlike the algorithms based on two untrusted servers, we outsource modular exponentiation operation to only a single server, eliminating the possible collusion attack with two servers. Moreover, we put forward a new mathematical division method, which hides the base and exponent of the outsourced data, without exposing sensitive information to the cloud server. In addition, compared with other state-of-the-art algorithms, our scheme shows a remarkable improvement in checkability, enabling the user to detect any misbehavior with the optimal probability close to 1. Finally, we use our proposed algorithms as a subroutine to realize Shamir's Identity-Based Signature Scheme and Identity-Based Multi-Signatures Scheme.

Fu, A, Li, Y, Yu, S, Yu, Y & Zhang, G 2018, 'DIPOR: An IDA-based dynamic proof of retrievability scheme for cloud storage systems', Journal of Network and Computer Applications, vol. 104, pp. 97-106.
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As cloud storage has become more and more ubiquitous, there are a large number of consumers renting cloud storage services. However, as users lose direct control over the data, the integrity and availability of the outsourced data become a big concern for users. Accordingly, how to verify the integrity of stored data and retrieve the availability of the corrupted data has become an urgent problem. Moreover, in most cases, users' data is not always static, but needs to be updated. In this paper, we propose a dynamic proof of retrievability scheme for cloud storage system, named as DIPOR. The DIPOR not only can retrieve the original data of corrupted blocks by using partial healthy data stored in healthy servers, but also support for updating operations of data. Furthermore, the number of forks in our scheme is not fixed, which means we can always look for the optimal forks based on the number of data blocks. In addition, the security analysis indicates that our scheme is provably secure and the performance evaluations show the efficiency of the proposed scheme.

Fu, A, Zhu, Y, Yang, G, Yu, S & Yu, Y 2018, 'Secure outsourcing algorithms of modular exponentiations with optimal checkability based on a single untrusted cloud server', Cluster Computing, vol. 21, no. 4, pp. 1933-1947.
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Fu, Q, Ranji-Burachaloo, H, Liu, M, McKenzie, TG, Tan, S, Reyhani, A, Nothling, MD, Dunstan, DE & Qiao, GG 2018, 'Controlled RAFT polymerization facilitated by a nanostructured enzyme mimic', Polymer Chemistry, vol. 9, no. 35, pp. 4448-4454.
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A nanostructured MOF composite was utilized as an enzyme mimic for the generation of hydroxyl radicals from hydrogen peroxide, which can subsequently initiate RAFT polymerizations in aqueous or organic media.

Fujioka, T, Hoang, AT, Okuda, T, Takeuchi, H, Tanaka, H & Nghiem, LD 2018, 'Water Reclamation Using a Ceramic Nanofiltration Membrane and Surface Flushing with Ozonated Water', International Journal of Environmental Research and Public Health, vol. 15, no. 4, pp. 799-799.
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A new membrane fouling control technique using ozonated water flushing was evaluated for direct nanofiltration (NF) of secondary wastewater effluent using a ceramic NF membrane. Experiments were conducted at a permeate flux of 44 L/m2h to evaluate the ozonated water flushing technique for fouling mitigation. Surface flushing with clean water did not effectively remove foulants from the NF membrane. In contrast, surface flushing with ozonated water (4 mg/L dissolved ozone) could effectively remove most foulants to restore the membrane permeability. This surface flushing technique using ozonated water was able to limit the progression of fouling to 35% in transmembrane pressure increase over five filtration cycles. Results from this study also heighten the need for further development of ceramic NF membrane to ensure adequate removal of pharmaceuticals and personal care products (PPCPs) for water recycling applications. The ceramic NF membrane used in this study showed approximately 40% TOC rejection, and the rejection of PPCPs was generally low and highly variable. It is expected that the fouling mitigation technique developed here is even more important for ceramic NF membranes with smaller pore size and thus better PPCP rejection.

Fujioka, T, Kodamatani, H, Takeuchi, H, Tanaka, H & Nghiem, LD 2018, 'Online monitoring of N-nitrosodimethylamine for the removal assurance of 1,4-dioxane and other trace organic compounds by reverse osmosis', Environmental Science: Water Research & Technology, vol. 4, no. 12, pp. 2021-2028.
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Online monitoring of N-nitrosodimethylamine (NDMA) during reverse osmosis (RO) treatment was effective in ensuring the removal of trace organic chemicals, particularly 1,4-dioxane.

Fujioka, T, Nguyen, KH, Hoang, AT, Ueyama, T, Yasui, H, Terashima, M & Nghiem, LD 2018, 'Biofouling Mitigation by Chloramination during Forward Osmosis Filtration of Wastewater', International Journal of Environmental Research and Public Health, vol. 15, no. 10, pp. 2124-2124.
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Pre-concentration is essential for energy and resource recovery from municipal wastewater. The potential of forward osmosis (FO) membranes to pre-concentrate wastewater for subsequent biogas production has been demonstrated, although biofouling has also emerged as a prominent challenge. This study, using a cellulose triacetate FO membrane, shows that chloramination of wastewater in the feed solution at 3–8 mg/L residual monochloramine significantly reduces membrane biofouling. During a 96-h pre-concentration, flux in the chloraminated FO system decreased by only 6% and this flux decline is mostly attributed to the increase in salinity (or osmotic pressure) of the feed due to pre-concentration. In contrast, flux in the non-chloraminated FO system dropped by 35% under the same experimental conditions. When the feed was chloraminated, the number of bacterial particles deposited on the membrane surface was significantly lower compared to a non-chloraminated wastewater feed. This study demonstrated, for the first time, the potential of chloramination to inhibit bacteria growth and consequently biofouling during pre-concentration of wastewater using a FO membrane.

Fujioka, T, O'Rourke, BE, Michishio, K, Kobayashi, Y, Oshima, N, Kodamatani, H, Shintani, T & Nghiem, LD 2018, 'Transport of small and neutral solutes through reverse osmosis membranes: Role of skin layer conformation of the polyamide film', Journal of Membrane Science, vol. 554, pp. 301-308.
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© 2018 Elsevier B.V. The polyamide skin layer of reverse osmosis (RO) membranes was characterised using advanced and complementary analytical techniques to investigate the mechanisms underlying the permeation of contaminants of emerging concern in potable water reuse – N-nitrosodimethylamine (NDMA) and N-nitrosomethylethylamine (NMEA). This study used five RO membrane samples with similar membrane properties. The five RO membrane samples spanned over a large range of water permeance (0.9–5.8 L/m2 h bar) as well as permeation of NDMA (9–66%) and NMEA (3–29%). Despite these differences among the five RO membranes, characterisations of the skin layer using positron annihilation lifetime spectroscopy, atomic force microscopy and field emission scanning electron microscopy revealed almost no variation in their free-volume hole-radius (0.270–0.275 nm), effective surface area (198–212%) and thickness (30–35 nm) of the skin layer. The results suggest that there could be other RO skin layer properties, such as the interconnectivity of the protuberances within the polyamide skin layer additional to the free-volume hole-size and thickness of the skin layer, which can also govern water and solute permeation.

Galvin, TJ, Seymour, N, Marvil, J, Filipović, MD, Tothill, NFH, McDermid, RM, Hurley-Walker, N, Hancock, PJ, Callingham, JR, Cook, RH, Norris, RP, Bell, ME, Dwarakanath, KS, For, B, Gaensler, BM, Hindson, L, Johnston-Hollitt, M, Kapińska, AD, Lenc, E, McKinley, B, Morgan, J, Offringa, AR, Procopio, P, Staveley-Smith, L, Wayth, RB, Wu, C & Zheng, Q 2018, 'The spectral energy distribution of powerful starburst galaxies – I. Modelling the radio continuum', Monthly Notices of the Royal Astronomical Society, vol. 474, no. 1, pp. 779-799.
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© 2018 The Author(s). We have acquired radio-continuum data between 70MHz and 48 GHz for a sample of 19 southern starburst galaxies at moderate redshifts (0.067 < z < 0.227) with the aim of separating synchrotron and free-free emission components. Using a Bayesian framework, we find the radio continuum is rarely characterized well by a single power law, instead often exhibiting lowfrequency turnovers below 500 MHz, steepening at mid to high frequencies, and a flattening at high frequencies where free-free emission begins to dominate over the synchrotron emission. These higher order curvature components may be attributed to free-free absorption across multiple regions of star formation with varying optical depths. The decomposed synchrotron and free-free emission components in our sample of galaxies form strong correlations with the total-infrared bolometric luminosities. Finally, we find that without accounting for free-free absorption with turnovers between 90 and 500MHz the radio continuum at low frequency (v < 200 MHz) could be overestimated by upwards of a factor of 12 if a simple power-law extrapolation is used from higher frequencies. The mean synchrotron spectral index of our sample is constrained to be α = -1.06, which is steeper than the canonical value of -0.8 for normal galaxies. We suggest this may be caused by an intrinsically steeper cosmic ray distribution.

Gan, YY, Ong, HC, Ling, TC, Zulkifli, NWM, Wang, C-T & Yang, Y-C 2018, 'Thermal conductivity optimization and entropy generation analysis of titanium dioxide nanofluid in evacuated tube solar collector', Applied Thermal Engineering, vol. 145, pp. 155-164.
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Gan, YY, Ong, HC, Show, PL, Ling, TC, Chen, W-H, Yu, KL & Abdullah, R 2018, 'Torrefaction of microalgal biochar as potential coal fuel and application as bio-adsorbent', Energy Conversion and Management, vol. 165, pp. 152-162.
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Gandomi, AH & Alavi, AH 2018, 'Metaheuristics in Reliability and Risk Analysis', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, vol. 4, no. 3, pp. 02018001-02018001.
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Gandomi, AH & Goldman, BW 2018, 'Parameter-less population pyramid for large-scale tower optimization', Expert Systems with Applications, vol. 96, pp. 175-184.
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The parameter-less population pyramid (P3) is a recent evolutionary computation algorithm proposed for black box optimization. Shown to be efficient for a variety of benchmark problems, P3 replaces the conventional constant population model with expanding sets of expanding populations. We investigated how this new metaheuristic optimization algorithm would transfer to optimize large-scale tower structure problems involving different constraints: geometric and mechanical. P3 is examined by optimizing two discrete tower design problems, 26-story and 35- story tower structures. The performance of P3 is compared with other well-known evolutionary algorithms for black-box optimization including random restart hill climbing, parameter-less hierarchical Bayesian optimization algorithm, differential evolution, and a modified genetic algorithm. The results show that does P3 not only finds the best final solutions, but it also reaches high quality solutions much faster than the other algorithms This fast optimization is vital for the tedious and large-scale structural engineering problems. Finally, the unique search features used in the P3 and the implications for future studies are discussed.

Gandomi, AH & Kashani, AR 2018, 'Automating pseudo-static analysis of concrete cantilever retaining wall using evolutionary algorithms', Measurement, vol. 115, pp. 104-124.
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Evolutionary optimization algorithms by imitating survival of the best features and transmutation of the creatures within their generation, approach complicated engineering problems very well. Similar to many other field of research, civil engineering problems have benefited from this capacity. In the current study, optimum design of retaining walls under seismic loading case is analyzed by three evolutionary algorithms, differential evolution (DE), evolutionary strategy (ES), and biogeography-based optimization algorithms (BBO). All the results are benchmarked with the classical evolutionary algorithm, genetic algorithm (GA). To this end, two different measures, minimum-cost and minimum-weight, are considered based on ACI 318-05 requirements coupled with geotechnical considerations for retaining walls. Numerical simulations on three case studies revealed that BBO reached the best results over all the case studies decisively.

Gandomi, AH & Kashani, AR 2018, 'Construction Cost Minimization of Shallow Foundation Using Recent Swarm Intelligence Techniques', IEEE Transactions on Industrial Informatics, vol. 14, no. 3, pp. 1099-1106.
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In this study, the performances of eight recent swarm intelligence techniques, accelerated particle swarm optimization (APSO), firefly algorithm, levy-flight krill herd, whale optimization algorithm (WOA), ant lion optimizer, grey wolf optimizer, moth-flame optimization algorithm and teaching-learning-based optimization algorithm (TLBO), are explored. Particle swarm optimization algorithm is also considered to benchmark the efficiencies. A final cost is considered as an objective function which deals with shallow footing optimization with two attitudes: routine optimization, and sensitivity analysis. Moreover, as a further study, the effect of the location of the column at the top of the foundation is examined by adding two spare design variables. To this end, three numerical case studies are simulated. Based on the final results TLBO showed an acceptable performance because of the lowest mean values and WOA demonstrated the weakest efficiency among the algorithms in this study.

Gandomi, AH & Kashani, AR 2018, 'Probabilistic evolutionary bound constraint handling for particle swarm optimization', Operational Research, vol. 18, no. 3, pp. 801-823.
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Keeping the search space between the valid domains is one of the most important necessities for most of the optimization problems. Among the optimization algorithms, particle swarm optimization (PSO) is highly likely to violate boundary limitations easily because of its oscillating behavior. Therefore, PSO is led to be sensitive to bound constraint handling (BCH) method. This matter has not been taken to account very much until now. This study attempt to apply and explore the efficiency of one of the most recent BCH schemes called evolutionary boundary constraint handling (EBCH) on PSO. In addition, probabilistic evolutionary boundary constraint handling (PEBCH) is also introduced in this study as an update on EBCH approach. As a complementary step of previous efforts, in the current document, PSO with both EBCH and PEBCH are utilized to solve several benchmark functions and the results are compared to other approaches in the literature. The results reveal that, in most cases, the EBCH and PEBCH can considerably improve the performance of the PSO algorithm in comparison with other BCH methods.

Gao, J, Li, H, Luo, Z, Gao, L & Li, P 2018, 'Topology optimization of micro-structured materials featured with the specific mechanical properties', International Journal of Computational Methods, vol. 17, no. 3.
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Micro-structured materials consisting of an array of microstructures areengineered to provide the specific material properties. This present workinvestigates the design of cellular materials under the framework of level set,so as to optimize the topologies and shapes of these porous materialmicrostructures. Firstly, the energy-based homogenization method (EBHM) isapplied to evaluate the material effective properties based on the topology ofthe material cell, where the effective elasticity property is evaluated by theaverage stress and strain theorems. Secondly, a parametric level set method(PLSM) is employed to optimize the microstructural topology until the specificmechanical properties can be achieved, including the maximum bulk modulus, themaximum shear modulus and their combinations, as well as the negative Poisson'sratio (NPR). The complicated topological shape optimization of the materialmicrostructure has been equivalent to evolve the sizes of the expansioncoefficients in the interpolation of the level set function. Finally, severalnumerical examples are fully discussed to demonstrate the effectiveness of thedeveloped method. A series of new and interesting material cells with thespecific mechanical properties can be found.

Gao, K, Gao, W, Wu, B, Wu, D & Song, C 2018, 'Nonlinear primary resonance of functionally graded porous cylindrical shells using the method of multiple scales', Thin-Walled Structures, vol. 125, pp. 281-293.
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An analytical method is proposed for the nonlinear primary resonance analysis of cylindrical shells made of functionally graded (FG) porous materials subjected to a uniformly distributed harmonic load including the damping effect. The Young's modulus, shear modulus and density of porous materials are assumed to vary through the thickness direction based on the assumption of a common mechanical feature of the open-cell foam. Three types of FG porous distributions, namely symmetric porosity distribution, non-symmetric porosity stiff or soft distribution and uniform porosity distribution are considered in this paper. Theoretical formulations are derived based on Donnell shell theory (DST) and accounting for von-Kármán strain-displacement relation and damping effect. The first mode of deflection function that satisfies the boundary conditions is introduced into this nonlinear governing partial differential equation and then a Galerkin-based procedure is utilized to obtain a Duffing-type nonlinear ordinary differential equation with a cubic nonlinear term. Finally, the governing equation is solved analytically by conducting the method of multiple scales (MMS) which results in frequency-response curves of FG porous cylindrical shells in the presence of damping effect. The detailed parametric studies on porosity distribution, porosity coefficient, damping ratio, amplitude and frequency of the external harmonic excitation, aspect ratio and thickness ratio, shown that the distribution type of FG porous cylindrical shells significantly affects primary resonance behavior and the response presents a hardening-type nonlinearity, which provides a useful help for the design and optimize of FG porous shell-type devices working under external harmonic excitation.

Gao, K, Gao, W, Wu, D & Song, C 2018, 'Nonlinear dynamic buckling of the imperfect orthotropic E-FGM circular cylindrical shells subjected to the longitudinal constant velocity', International Journal of Mechanical Sciences, vol. 138-139, pp. 199-209.
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In this study, an analytical approach on the nonlinear dynamic buckling of the orthotropic circular cylindrical shells made of exponential law functionally graded material (E-FGM) subjected to the longitudinal constant velocity is investigated with the incorporation of mercurial damping effect. The material properties are assumed to vary gradually in the thickness direction according to an exponential distribution function of the volume fraction of constituent materials. Theoretical formulations are derived based on improved Donnell shell theory (DST) and accounting for von-Kármán strain–displacement relation, initial imperfection and damping effect. By applying Galerkin method and Airy's stress function, the obtained nonlinear differential equations are solved numerically by the fourth-order Runge–Kutta method. The nonlinear dynamic stability of the orthotropic FG cylindrical shell is assessed based on Budiansky–Roth criterion. Additionally, a parametric study is conducted to demonstrate the effects of various velocities, initial imperfections, damping ratios, inhomogeneous parameters on nonlinear dynamic buckling behavior of an imperfect orthotropic FG cylindrical shell. Comparing results with those in other publications validates the proposed method.

Gao, K, Gao, W, Wu, D & Song, C 2018, 'Nonlinear dynamic stability of the orthotropic functionally graded cylindrical shell surrounded by Winkler-Pasternak elastic foundation subjected to a linearly increasing load', Journal of Sound and Vibration, vol. 415, pp. 147-168.
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This paper focuses on the dynamic stability behaviors of the functionally graded (FG) orthotropic circular cylindrical shell surrounded by the two-parameter (Winkler-Pasternak) elastic foundation subjected to a linearly increasing load with the consideration of damping effect. The material properties are assumed to vary gradually in the thickness direction based on an exponential distribution function of the volume fraction of constituent materials. Equations of motion are derived from Hamilton's principle and the nonlinear compatibility equation is considered by the means of modified Donnell shell theory including large deflection. Then the nonlinear dynamic buckling equation is solved by a hybrid analytical-numerical method (combined Galerkin method and fourth-order Runge-Kutta method). The nonlinear dynamic stability of the FG orthotropic cylindrical shell is assessed based on Budiansky-Roth criterion. Additionally, effects of different parameters such as various inhomogeneous parameters, loading speeds, damping ratios and aspect ratios and thickness ratios of the structure on dynamic buckling are discussed in details. Finally, the proposed method is validated with published literature.

Gao, L, Chen, J, Liu, Y, Yamauchi, Y, Huang, Z & Kong, X 2018, 'Revealing the chemistry of an anode-passivating electrolyte salt for high rate and stable sodium metal batteries', Journal of Materials Chemistry A, vol. 6, no. 25, pp. 12012-12017.
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A compact and conductive solid-electrolyte interphase formed by NaDFOB enables high performance of sodium metal batteries.

Gao, W, Wu, D, Gao, K, Chen, X & Tin-Loi, F 2018, 'Structural reliability analysis with imprecise random and interval fields', Applied Mathematical Modelling, vol. 55, pp. 49-67.
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This paper investigates the issue of reliability assessment for engineering structures involving mixture of stochastic and non-stochastic uncertain parameters through the Finite Element Method (FEM). Non-deterministic system inputs modelled by both imprecise random and interval fields have been incorporated, so the applicability of the structural reliability analysis scheme can be further promoted to satisfy the intricate demand of modern engineering application. The concept of robust structural reliability profile for systems involving hybrid uncertainties is discussed, and then a new computational scheme, namely the unified interval stochastic reliability sampling (UISRS) approach, is proposed for assessing the safety of engineering structures. The proposed method provides a robust semi-sampling scheme for assessing the safety of engineering structures involving multiple imprecise random fields with various distribution types and interval fields simultaneously. Various aspects of structural reliability analysis with multiple imprecise random and interval fields are explored, and some theoretically instructive remarks are also reported herein.

Gao, X, Zhang, T, Du, J & Guo, YJ 2018, 'Design, modelling and simulation of a monolithic high-T _c superconducting terahertz mixer', Superconductor Science and Technology, vol. 31, no. 11, pp. 115010-115010.
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© 2018 IOP Publishing Ltd. This paper presents a novel concept and design of a full monolithic integrated high-T c superconducting (HTS) Josephson junction terahertz (THz) harmonic mixer coupled with a circularly polarized (CP) antenna. The fully on-chip mixer device is very compact in size and utilizes the CP antenna to enhance the polarization orientation flexibility in coupling THz radiation. Electromagnetic simulations are carried out to optimize the coupling efficiency and axial ratio of the THz CP antenna, and the signal transmission and isolation characteristics of the monolithic circuit. An equivalent circuit model of the HTS THz mixer is then established and simulation is performed based on our previously measured step-edge Josephson junction characteristics to evaluate the device performance and validate the concept of design. The results show that a superior performance could be achieved from such a monolithic HTS mixer device, which is significantly better than any HTS THz harmonic mixers reported to date.

Gardner, A & Willey, K 2018, 'Academic identity reconstruction: the transition of engineering academics to engineering education researchers', Studies in Higher Education, vol. 43, no. 2, pp. 234-250.
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The field of research (FoR) that an academic participates in is both a manifestation of, and a contributor to the development of their identity. When an academic changes that FoR the question then arises as to how they reconcile this change with their identity. This paper uses the identity-trajectory framework to analyse the discourse of 19 engineering academics in relation to their educational research. The findings reveal insights into the identity changes experienced in the transition from typical engineering academic to engineering education researcher. Participants’ responses illustrate how various aspects of their research activities contribute to the development of the networking and intellectual strands of their academic identity as engineering education researchers, and the effect of their university environment on this development. Conference participation was found to be an important contributor to progression of the intellectual and networking strands of identity-trajectory for researchers at all stages of development, although for different reasons.

Gaviria-Marin, M, Merigo, JM & Popa, S 2018, 'Twenty years of theJournal of Knowledge Management: a bibliometric analysis', Journal of Knowledge Management, vol. 22, no. 8, pp. 1655-1687.
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PurposeIn 2017, theJournal of Knowledge Management(JKM) celebrates its 20th anniversary. This study aims to show an updated analysis of their publications to provide a general overview of the journal, focusing on a bibliometric analysis of its publications between 1997 and 2016.Design/methodology/approachThe methodology involves two procedures: a performance analysis and a science mapping analysis of JKM. The performance analysis uses a series of bibliometric indicators such ash-index, productivity and citations. This analysis considers different dimensions, including papers, authors, universities and countries. VOSviewer software is used to carry out the mapping of science of JKM, which, based on the concurrence of key words and co-citation points of view, seeks to graphically analyze the structure of the references of this journal.FindingsThere is a positive evolution in the number of publications (although with certain oscillations), which shows a growing interest in publishing in JKM. The USA and the UK lead the publications in this journal, although at a regional level, Europe is the most productive. The low participation of emerging economies in JKM is also observed.Practical implicationsThe paper will identify the leading trends in the journal in terms of papers, authors, institutions, countries, journals and keywords. This study is useful for obtaining a quick snapshot of what is happening in the journal.Originality/valueFrom the h...

George, L, Lehmann, T & Hamilton, TJ 2018, 'A reconfigurable dual-output buck-boost switched-capacitor converter using adaptive gain and discrete frequency scaling control', Microelectronics Journal, vol. 73, pp. 59-74.
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Ghabrial, A, Franklin, D & Zaidi, H 2018, 'A Monte Carlo simulation study of the impact of novel scintillation crystals on performance characteristics of PET scanners', Physica Medica, vol. 50, pp. 37-45.
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The purpose of this study is to validate a Monte Carlo simulation model for the clinical Siemens Biograph mCT PET scanner using the GATE simulation toolkit, and to evaluate the performance of six different scintillation materials in this model using the National Electrical Manufactures Association (NEMA) NU 2-2007 protocol.A model of the Biograph mCT PET detection system and its geometry was developed. NEMA NU 2-2007 phantoms were also modelled. The accuracy of the developed scanner model was validated through a comparison of the simulation results from GATE, SimSET and PeneloPET toolkits, and experimental data obtained using the NEMA NU 2-2007 protocols. The evaluated performance metrics included count rate performance, spatial resolution, sensitivity, and scatter fraction (SF). Thereafter, the mCT PET scanner was simulated with six different candidate high-performance scintillation materials, including LSO, LaBr3, CeBr3, LuAP, GLuGAG and LFS-3, and its performance evaluated according to the NEMA NU 2-2007 specifications.The Monte Carlo simulation model demonstrates good agreement with the experimental data and results from other simulation packages. For instance, the scatter fraction calculated using GATE simulation is 34.35% while the experimentally measured value is 33.2%, 38.48% for the SimSET, and 34.8% for the PeneloPET toolkit. The best-performing scintillation materials were found to be LuAP, LSO and LFS-3, while GLuGAG offers acceptable performance if cost is the dominant concern.The main performance characteristics of the Biograph mCT PET scanner can be simulated accurately using GATE with a good agreement with other Monte Carlo simulation packages and experimental measurements. Newly developed scintillators show promise and offer alternative options for the design of novel generation PET scanners.

Ghaffari Jadidi, M, Valls Miro, J & Dissanayake, G 2018, 'Gaussian processes autonomous mapping and exploration for range-sensing mobile robots', Autonomous Robots, vol. 42, no. 2, pp. 273-290.
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© 2017, Springer Science+Business Media, LLC. Most of the existing robotic exploration schemes use occupancy grid representations and geometric targets known as frontiers. The occupancy grid representation relies on the assumption of independence between grid cells and ignores structural correlations present in the environment. We develop a Gaussian processes (GPs) occupancy mapping technique that is computationally tractable for online map building due to its incremental formulation and provides a continuous model of uncertainty over the map spatial coordinates. The standard way to represent geometric frontiers extracted from occupancy maps is to assign binary values to each grid cell. We extend this notion to novel probabilistic frontier maps computed efficiently using the gradient of the GP occupancy map. We also propose a mutual information-based greedy exploration technique built on that representation that takes into account all possible future observations. A major advantage of high-dimensional map inference is the fact that such techniques require fewer observations, leading to a faster map entropy reduction during exploration for map building scenarios. Evaluations using the publicly available datasets show the effectiveness of the proposed framework for robotic mapping and exploration tasks.

Ghanbarikarekani, M, Qu, X, Zeibots, M & Qi, W 2018, 'Minimizing the Average Delay at Intersections via Presignals and Speed Control', Journal of Advanced Transportation, vol. 2018, pp. 1-8.
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Urban intersections have been well recognized as bottlenecks of urban transport systems. It is thus important to propose and implement strategies for increasing the efficiency of public and private transportation systems as a whole. In order to achieve this goal, an additional signal could be set up near the intersection to give priority to buses through stopping vehicles in advance of the main intersection as a presignal. It has been increasingly popular in urban cities. While presignals indeed reduce the average delay per traveler, they cause extra stops of private vehicles, which might compromise the overall efficiency, safety, and sustainability. This paper aims to propose a model to improve presignals by reducing the vehicles’ number of stops behind the presignals. By applying the method, vehicles would be able to adjust their speed based on traffic conditions as well as buses’ speed and approach. Numerical analyses have been conducted to determine the conditions required for implementing this method.

Gharehbaghi, S, Gandomi, AH, Achakpour, S & Omidvar, MN 2018, 'A hybrid computational approach for seismic energy demand prediction', Expert Systems with Applications, vol. 110, pp. 335-351.
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In this paper, a hybrid genetic programming (GP) with multiple genes is implemented for developing prediction models of spectral energy demands. A multi-objective strategy is used for maximizing the accuracy and minimizing the complexity of the models. Both structural properties and earthquake characteristics are considered in prediction models of four demand parameters. Here, the earthquake records are classified based on soil type assuming that different soil classes have linear relationships in terms of GP genes. Therefore, linear regression analysis is used to connect genes for different soil types, which results in a total of sixteen prediction models. The accuracy and effectiveness of these models were assessed using different performance metrics and their performance was compared with several other models. The results indicate that not only the proposed models are simple, but also they outperform other spectral energy demand models proposed in the literature.

Ghasemi, K, Pradhan, B & Jena, R 2018, 'Spatial Identification of Key Alteration Minerals Using ASTER and Landsat 8 Data in a Heavily Vegetated Tropical Area', Journal of the Indian Society of Remote Sensing, vol. 46, no. 7, pp. 1061-1073.
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© 2018, Indian Society of Remote Sensing. The Central Gold Belt (CGB) of Malaysia is a major host to gold deposits. Penjom, Raub, Selising and Buffalo reef are major gold mines in CGB. The study area, Selinsing gold mine, is located at the northwest of Pahang province on the lineament known as the Raub Bentong Suture. Presence of dense vegetation and cloud cover in tropical regions are main obstacles in alteration mapping using satellite imageries. In this study, Landsat 8 and ASTER level 1B images were used to map clay minerals and quartz rich zones at Selinsing gold mine and surrounding areas. Direct principal component analysis (DPCA), matched filtering (MF) and band ratio were the effective methods used in this study. High concentration of clay minerals was detected using band ratio 6/7, DPC2 and MF and ratio 14/12 was carried out to highlight quartz rich zones. The results of image processing methods were verified by in situ inspection and X-ray diffraction analyses. The results show that, in spite of limited bedrock exposure, the known gold prospects and potential areas of mineralization can be recognized by the methods employed in this study.

Ghasemi, M, Ghavidel, S, Aghaei, J, Akbari, E & Li, L 2018, 'CFA optimizer: A new and powerful algorithm inspired by Franklin's and Coulomb's laws theory for solving the economic load dispatch problems', International Transactions on Electrical Energy Systems, vol. 28, no. 5, pp. e2536-e2536.
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Copyright © 2018 John Wiley & Sons, Ltd. This paper presents a new efficient algorithm inspired by Franklin's and Coulomb's laws theory that is referred to as CFA algorithm, for finding the global solutions of optimal economic load dispatch problems in power systems. CFA is based on the impact of electrically charged particles on each other due to electrical attraction and repulsion forces. The effectiveness of the CFA in different terms is tested on basic benchmark problems. Then, the quality of the CFA to achieve accurate results in different aspects is examined and proven on economic load dispatch problems including 4 different size cases, 6, 10, 15, and 110-unit test systems. Finally, the results are compared with other inspired algorithms as well as results reported in the literature. The simulation results provide evidence for the well-organized and efficient performance of the CFA algorithm in solving great diversity of nonlinear optimization problems.

Ghavidel, S, Azizivahed, A & Li, L 2018, 'A hybrid Jaya algorithm for reliability–redundancy allocation problems', Engineering Optimization, vol. 50, no. 4, pp. 698-715.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group. This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching–learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability–redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series–parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30–100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

Gheisari, S, Catchpoole, DR, Charlton, A & Kennedy, PJ 2018, 'Convolutional Deep Belief Network with Feature Encoding for Classification of Neuroblastoma Histological Images', Journal of Pathology Informatics, vol. 9, no. 1, pp. 17-17.
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© 2018 Journal of Pathology Informatics. Background: Neuroblastoma is the most common extracranial solid tumor in children younger than 5 years old. Optimal management of neuroblastic tumors depends on many factors including histopathological classification. The gold standard for classification of neuroblastoma histological images is visual microscopic assessment. In this study, we propose and evaluate a deep learning approach to classify high-resolution digital images of neuroblastoma histology into five different classes determined by the Shimada classification. Subjects and Methods: We apply a combination of convolutional deep belief network (CDBN) with feature encoding algorithm that automatically classifies digital images of neuroblastoma histology into five different classes. We design a three-layer CDBN to extract high-level features from neuroblastoma histological images and combine with a feature encoding model to extract features that are highly discriminative in the classification task. The extracted features are classified into five different classes using a support vector machine classifier. Data: We constructed a dataset of 1043 neuroblastoma histological images derived from Aperio scanner from 125 patients representing different classes of neuroblastoma tumors. Results: The weighted average F-measure of 86.01% was obtained from the selected high-level features, outperforming state-of-the-art methods. Conclusion: The proposed computer-aided classification system, which uses the combination of deep architecture and feature encoding to learn high-level features, is highly effective in the classification of neuroblastoma histological images.

Gheisari, S, Catchpoole, DR, Charlton, A, Melegh, Z, Gradhand, E & Kennedy, PJ 2018, 'Computer Aided Classification of Neuroblastoma Histological Images Using Scale Invariant Feature Transform with Feature Encoding', Diagnostics, vol. 8, no. 3, pp. 56-56.
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Neuroblastoma is the most common extracranial solid malignancy in early childhood. Optimal management of neuroblastoma depends on many factors, including histopathological classification. Although histopathology study is considered the gold standard for classification of neuroblastoma histological images, computers can help to extract many more features some of which may not be recognizable by human eyes. This paper, proposes a combination of Scale Invariant Feature Transform with feature encoding algorithm to extract highly discriminative features. Then, distinctive image features are classified by Support Vector Machine classifier into five clinically relevant classes. The advantage of our model is extracting features which are more robust to scale variation compared to the Patched Completed Local Binary Pattern and Completed Local Binary Pattern methods. We gathered a database of 1043 histologic images of neuroblastic tumours classified into five subtypes. Our approach identified features that outperformed the state-of-the-art on both our neuroblastoma dataset and a benchmark breast cancer dataset. Our method shows promise for classification of neuroblastoma histological images.

Ghorbani, S, Eyni, H, Tiraihi, T, Salari Asl, L, Soleimani, M, Atashi, A, Pour Beiranvand, S & Ebrahimi Warkiani, M 2018, 'Combined effects of 3D bone marrow stem cell-seeded wet-electrospun poly lactic acid scaffolds on full-thickness skin wound healing', International Journal of Polymeric Materials and Polymeric Biomaterials, vol. 67, no. 15, pp. 905-912.
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© 2017 Taylor & Francis. Tissue engineering has emerged as an alternative treatment to traditional grafts for skin wound healing. Three-dimensional nanofibers have been used extensively for this purpose due to their excellent biomedical-related properties. In this study, high porous 3D poly lactic acid nanofibrous scaffolds (PLA-S) were prepared by wet-electrospinning technique and seeded with rat bone-marrow stem cells (BMSCs) to characterize the biocompatibility and therapeutic efficacy of these fibers on the treating full-thickness dermal wounds. The results of in vitro andin vivo studies indicate that the 3D fibrous PLA-S can be a potential wound dressing for wound repair, particularly when seeded with BMSCs. GRAPHICAL ABSTRACT.

Ghosh, S & Lee, JE-Y 2018, 'Extended Bandwidth Piezoelectric Lorentz Force Magnetometer Based on a Mechanically Coupled Beam Resonator Array', IEEE Transactions on Magnetics, vol. 54, no. 10, pp. 1-7.
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Ghosh, S & Lee, JE-Y 2018, 'Piezoelectric-on-silicon Lorentz force magnetometers based on radial contour mode disk resonators', Sensors and Actuators A: Physical, vol. 281, pp. 185-195.
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Gill, AQ, Henderson-Sellers, B & Niazi, M 2018, 'Scaling for agility: A reference model for hybrid traditional-agile software development methodologies', Information Systems Frontiers, vol. 20, no. 2, pp. 315-341.
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© 2016, Springer Science+Business Media New York. The adoption of agility at a large scale often requires the integration of agile and non-agile development elements for architecting a hybrid adaptive methodology. The challenge is ”which elements or components (agile or non-agile) are relevant to develop the context-aware hybrid adaptive methodology reference architecture?” This paper addresses this important challenge and develops a hybrid adaptive methodology reference architecture model using a qualitative constructive empirical research approach. In this way, we have uncovered the agility, abstraction, business value, business policy, rules, legal, context and facility elements or components that have not been explicitly modelled or discussed in International Standards (IS) such as the ISO/IEC 24744 metamodel. It is anticipated that a context-aware hybrid adaptive methodology can be architected by using the proposed context-aware hybrid adaptive methodology reference architecture elements for a particular situation when using a situational method engineering approach.

Goldsmith, R & Willey, K 2018, 'The otherness of writing in the engineering curriculum: A practice architectures perspective', JOURNAL OF ACADEMIC LANGUAGE AND LEARNING, vol. 12, no. 1, pp. A97-A114.
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Engineering students are expected to graduate with high level written and oral communication, yet these expectations continue to fall short despite repeated calls by industry and by accrediting bodies such as Engineers Australia for engineering faculties to address this issue. One explanation for this ongoing challenge is that the prevailing practices of engineering education constrain rather than enable the development of writing practices in the engineering curriculum, in part because writing practices are viewed as ‘other’, and as not belonging to engineering knowledge. We argue that the reasons for the view of ‘otherness’ of writing practices in the engineering curriculum relate ontologically to the construction of engineering identities, and epistemologically to perspectives of engineering and writing as being different types of knowledge. Drawing on elements of identities of engineering educators and students, research on engineering knowledge and legitimation code theory, the authors explore these ideas through the lens of practice architectures theory. The analysis reveals that dominant practices in engineering education place writing practices outside what is seen to be engineering, although there are exceptions. The authors conclude that the practice architectures of the engineering curriculum which prefigure writing as being what engineers are not expected to be ‘good at’, and not as important as technical skills, are so much a part of the ‘unspoken narratives’ of engineering educators that writing practices are marginalised. When they become part of what engineers do, they are re-framed as ‘documentation’. This suggests that writing practices can be seen as intrinsic to engineering education and practice if or when they are re-framed as engineering practice.

Golhani, K, Balasundram, SK, Vadamalai, G & Pradhan, B 2018, 'A review of neural networks in plant disease detection using hyperspectral data', Information Processing in Agriculture, vol. 5, no. 3, pp. 354-371.
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© 2018 China Agricultural University This paper reviews advanced Neural Network (NN) techniques available to process hyperspectral data, with a special emphasis on plant disease detection. Firstly, we provide a review on NN mechanism, types, models, and classifiers that use different algorithms to process hyperspectral data. Then we highlight the current state of imaging and non-imaging hyperspectral data for early disease detection. The hybridization of NN-hyperspectral approach has emerged as a powerful tool for disease detection and diagnosis. Spectral Disease Index (SDI) is the ratio of different spectral bands of pure disease spectra. Subsequently, we introduce NN techniques for rapid development of SDI. We also highlight current challenges and future trends of hyperspectral data.

Golkarian, A, Naghibi, SA, Kalantar, B & Pradhan, B 2018, 'Groundwater potential mapping using C5.0, random forest, and multivariate adaptive regression spline models in GIS', Environmental Monitoring and Assessment, vol. 190, no. 3.
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© 2018, Springer International Publishing AG, part of Springer Nature. Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.

Gong, B, Wang, S, Sloan, SW, Sheng, D & Tang, C 2018, 'Modelling Coastal Cliff Recession Based on the GIM–DDD Method', Rock Mechanics and Rock Engineering, vol. 51, no. 4, pp. 1077-1095.
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Gong, C, Li, Z, Chang, X & Luo, Y 2018, 'Learning-Based Multimedia Analyses and Applications', Advances in Multimedia, vol. 2018, pp. 1-2.
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Gong, L, Heitor, A & Indraratna, B 2018, 'An approach to measure infill matric suction of irregular infilled rock joints under constant normal stiffness shearing', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 4, pp. 653-660.
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Gong, Y, Zhao, D & Wang, Q 2018, 'An overview of field-scale studies on remediation of soil contaminated with heavy metals and metalloids: Technical progress over the last decade', Water Research, vol. 147, pp. 440-460.
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© 2018 Elsevier Ltd Soil contamination by heavy metals and metalloids has been a major concern to human health and environmental quality. While many remediation technologies have been tested at the bench scale, there have been only limited reports at the field scale. This paper aimed to provide a comprehensive overview on the field applications of various soil remediation technologies performed over the last decade or so. Under the general categories of physical, chemical, and biological approaches, ten remediation techniques were critically reviewed. The technical feasibility and economic effectiveness were evaluated, and the pros and cons were appraised. In addition, attention was placed to the environmental impacts of the remediation practices and long-term stability of the contaminants, which should be taken into account in the establishment of remediation goals and environmental criteria. Moreover, key knowledge gaps and practical challenges are identified.

Gonzales, R, Park, M, Tijing, L, Han, D, Phuntsho, S & Shon, H 2018, 'Modification of Nanofiber Support Layer for Thin Film Composite Forward Osmosis Membranes via Layer-by-Layer Polyelectrolyte Deposition', Membranes, vol. 8, no. 3, pp. 70-70.
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Electrospun nanofiber-supported thin film composite membranes are among the most promising membranes for seawater desalination via forward osmosis. In this study, a high-performance electrospun polyvinylidenefluoride (PVDF) nanofiber-supported thin film composite (TFC) membrane was successfully fabricated after molecular layer-by-layer polyelectrolyte deposition. Negatively-charged electrospun polyacrylic acid (PAA) nanofibers were deposited on electrospun PVDF nanofibers to form a support layer consisted of PVDF and PAA nanofibers. This resulted to a more hydrophilic support compared to the plain PVDF nanofiber support. The PVDF-PAA nanofiber support then underwent a layer-by-layer deposition of polyethylenimine (PEI) and PAA to form a polyelectrolyte layer on the nanofiber surface prior to interfacial polymerization, which forms the selective polyamide layer of TFC membranes. The resultant PVDF-LbL TFC membrane exhibited enhanced hydrophilicity and porosity, without sacrificing mechanical strength. As a result, it showed high pure water permeability and low structural parameter values of 4.12 L m−2 h−1 bar−1 and 221 µm, respectively, significantly better compared to commercial FO membrane. Layer-by-layer deposition of polyelectrolyte is therefore a useful and practical modification method for fabrication of high performance nanofiber-supported TFC membrane.

Gonzalez Cruz, C, Naderpour, M & Ramezani, F 2018, 'Water resource selection and optimisation for shale gas developments in Australia: A combinatorial approach', Computers & Industrial Engineering, vol. 124, pp. 1-11.
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Goodswen, SJ, Kennedy, PJ & Ellis, JT 2018, 'A Gene-Based Positive Selection Detection Approach to Identify Vaccine Candidates Using Toxoplasma gondii as a Test Case Protozoan Pathogen', Frontiers in Genetics, vol. 9, no. AUG.
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© 2018 Goodswen, Kennedy and Ellis. Over the last two decades, various in silico approaches have been developed and refined that attempt to identify protein and/or peptide vaccines candidates from informative signals encoded in protein sequences of a target pathogen. As to date, no signal has been identified that clearly indicates a protein will effectively contribute to a protective immune response in a host. The premise for this study is that proteins under positive selection from the immune system are more likely suitable vaccine candidates than proteins exposed to other selection pressures. Furthermore, our expectation is that protein sequence regions encoding major histocompatibility complexes (MHC) binding peptides will contain consecutive positive selection sites. Using freely available data and bioinformatic tools, we present a high-throughput approach through a pipeline that predicts positive selection sites, protein subcellular locations, and sequence locations of medium to high T-Cell MHC class I binding peptides. Positive selection sites are estimated from a sequence alignment by comparing rates of synonymous (dS) and non-synonymous (dN) substitutions among protein coding sequences of orthologous genes in a phylogeny. The main pipeline output is a list of protein vaccine candidates predicted to be naturally exposed to the immune system and containing sites under positive selection. Candidates are ranked with respect to the number of consecutive sites located on protein sequence regions encoding MHCI-binding peptides. Results are constrained by the reliability of prediction programs and quality of input data. Protein sequences from Toxoplasma gondii ME49 strain (TGME49) were used as a case study. Surface antigen (SAG), dense granules (GRA), microneme (MIC), and rhoptry (ROP) proteins are considered worthy T. gondii candidates. Given 8263 TGME49 protein sequences processed anonymously, the top 10 predicted candidates were all worthy candidates...

Gracia, L, Perez-Vidal, C & Valls-Miro, J 2018, 'Advanced Mathematical Methods for Collaborative Robotics', Mathematical Problems in Engineering, vol. 2018, pp. 1-3.
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Gracia, L, Solanes, JE, Muñoz-Benavent, P, Esparza, A, Valls Miro, J & Tornero, J 2018, 'Cooperative transport tasks with robots using adaptive non-conventional sliding mode control', Control Engineering Practice, vol. 78, pp. 35-55.
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© 2018 Elsevier Ltd This work presents a hybrid position/force control of robots aimed at handling applications using multi-task and sliding mode ideas. The proposed robot control is based on a novel adaptive non-conventional sliding mode control used to robustly satisfy a set of inequality constraints defined to accomplish the cooperative transport task. In particular, these constraints are used to guarantee the reference parameters imposed by the task (e.g., keeping the load at a desired orientation) and to guide the robot using the human operator's forces detected by a force sensor located at the robot tool. Another feature of the proposal is the multi-layered nature of the strategy, where a set of four tasks are defined with different priorities. The effectiveness of the proposed adaptive non-conventional sliding mode control is illustrated by simulation results. Furthermore, the applicability and feasibility of the proposed robot control for transport tasks are substantiated by experimental results using a redundant 7R manipulator.

Gracia, L, Solanes, JE, Muñoz-Benavent, P, Valls Miro, J, Perez-Vidal, C & Tornero, J 2018, 'Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback', Mechatronics, vol. 52, pp. 102-118.
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© 2018 Elsevier Ltd This work presents a hybrid position-force control of robots in order to apply surface treatments such as polishing, grinding, finishing, deburring, etc. The robot force control is designed using sliding mode concepts to benefit from robustness. In particular, the sliding mode force task is defined using equality constraints to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. In order to deal with sudden changes in material stiffness, which are ultimately transferred to the polishing tool and can produce instability and compromise polishing performance, several adaptive switching gain laws are considered and compared. Moreover, a lower priority tracking controller is defined to follow the desired reference trajectory on the surface being polished. Hence, deviations from the reference trajectory are allowed if such deviations are required to satisfy the constraints mentioned above. Finally, a third-level task is also considered for the case of redundant robots in order to use the remaining degrees of freedom to keep the manipulator close to the home configuration with safety in mind. The main advantages of the method are increased robustness and low computational cost. The applicability and effectiveness of the proposed approach are substantiated by experimental results using a redundant 7R manipulator: the Rethink Robotics Sawyer collaborative robot.

Graham, C, Smith, W, Moncur, W & van den Hoven, E 2018, 'Introduction: Mortality in Design', Design Issues, vol. 34, no. 1, pp. 3-14.
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Gray, S, Voinov, A, Paolisso, M, Jordan, R, BenDor, T, Bommel, P, Glynn, P, Hedelin, B, Hubacek, K, Introne, J, Kolagani, N, Laursen, B, Prell, C, Schmitt Olabisi, L, Singer, A, Sterling, E & Zellner, M 2018, 'Purpose, processes, partnerships, and products: four Ps to advance participatory socio‐environmental modeling', Ecological Applications, vol. 28, no. 1, pp. 46-61.
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AbstractIncluding stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio‐environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four‐dimensional framework (4P) that includes reporting on dimensions of (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software‐based approaches (fuzzy cognitive mapping, agent‐based modeling, system dynamics, and participatory geospatial modeling) to understand human–environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model‐base...

Gu, Y, Cui, Q, Chen, Y, Ni, W, Tao, X & Zhang, P 2018, 'Effective Capacity Analysis in Ultra-Dense Wireless Networks With Random Interference', IEEE Access, vol. 6, pp. 19499-19508.
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© 2013 IEEE. Ultra-dense networks (UDNs) provide a promising paradigm to cope with exponentially increasing mobile traffic. However, a little work has to date considered unsaturated traffic with Quality-of-Service (QoS) requirements. This paper presents a new cross-layer analytical model to capture the unsaturated traffic of a UDN in the presence of QoS requirements. The effiective capacity (EC) of the UDN is derived, taking into account small-scale channel fading and possible interference. Key properties of the EC are revealed. The amount of traffic impacts EC of the UDN due to the sophisticated interactions among small base stations operating in the same frequency. The maximization of total EC is formulated as a non-cooperative game in this paper. The best-response function is derived, iteratively searching the Nash equilibrium point. System simulation results indicate that our proposed model is accurate. The simulations also show the maximum allowed arrival rate with the QoS guarantee, compared with the full interference model.

Gu, Y, Gu, M, Long, Y, Xu, G, Yang, Z, Zhou, J & Qu, W 2018, 'An enhanced short text categorization model with deep abundant representation', World Wide Web, vol. 21, no. 6, pp. 1705-1719.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Short text categorization is a crucial issue to many applications, e.g., Information Retrieval, Question-Answering System, MRI Database Construction and so forth. Many researches focus on data sparsity and ambiguity issues in short text categorization. To tackle these issues, we propose a novel short text categorization strategy based on abundant representation, which utilizes Bi-directional Recurrent Neural Network(Bi-RNN) with Long Short-Term Memory(LSTM) and topic model to catch more contextual and semantic information. Bi-RNN enriches contextual information, and topic model discovers more latent semantic information for abundant text representation of short text. Experimental results demonstrate that the proposed model is comparable to state-of-the-art neural network models and method proposed is effective.

Gulzar, M, Mahmood, K, Zahid, R, Alabdulkarem, A, Masjuki, HH, Kalam, MA, Varman, M, Zulkifli, NWM, Ahmad, P & Malik, MSS 2018, 'The effect of particle size on the dispersion and wear protection ability of MoS₂ particles in polyalphaolefin and trimethylolpropane ester', Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, vol. 232, no. 8, pp. 987-998.
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The effect of particle size and surfactant on dispersion stability and wear protection ability was experimentally evaluated for polyalphaolefin (PAO 10) and bio-based base oil (palm trimethylolpropane ester) added with molybdenum disulfide (MoS2) particles. Nanolubricants were developed by adding 1 wt% of MoS2 particles that varied in size. In addition to the variation in particle size, an anionic surfactant was also used to analyze its interaction with both types of nanoparticles for stable suspensions and for the related effects on the antiwear characteristics. The wear protection characteristics of the formulations were evaluated by four-ball extreme pressure tests and piston ring on cylinder sliding wear tests. The wear surfaces were analyzed by scanning electron microscopy along with an energy-dispersive X-ray and an atomic force microscopy. The MoS2 nanoparticles with a nominal size of 20 nm exhibited a better load-carrying capacity, while better sliding wear protection was provided by nanoparticles with a nominal size of 50 nm.

Gunawardane, K & Kularatna, N 2018, 'Supercapacitor‐assisted low dropout regulator technique: a new design approach to achieve high‐efficiency linear DC–DC converters', IET Power Electronics, vol. 11, no. 2, pp. 229-238.
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Approximate efficiency of a linear regulator is given by the ratio of regulated output voltage to input voltage. Higher voltage difference between the input and the output means a lower efficiency due to heavy losses in the series power semiconductor. Supercapacitor‐assisted low dropout regulator (SCALDO) is an emerging linear DC–DC converter technique, where a supercapacitor (SC) is used to reduce the voltage drop across the series transistor in a linear regulator where the SC acts as a lossless dropper. The circuit operates at a very low frequency decided by the size of the SC. An efficiency multiplication factor such as 1.33, 2, or 3 is achieved depending on the configuration. This study presents the essentials of its generalised theory, few prototype implementations, and a discussion on SCALDO properties. Typical efficiencies of 12–5 and 5–1.2 V linear regulators are around 42 and 24%, respectively. When SCALDO prototypes are built, the authors achieve respective end‐to‐end efficiencies of 79–81 and 58–73%. A loss analysis summary and further developments of the novel technique are also provided, in addition to a discussion to indicate that this is not a variation of the switched capacitor converters.

Guntuku, SC, Zhou, JT, Roy, S, Lin, W & Tsang, IW 2018, '‘Who Likes What and, Why?’ Insights into Modeling Users’ Personality Based on Image ‘Likes’', IEEE Transactions on Affective Computing, vol. 9, no. 1, pp. 130-143.
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© 2010-2012 IEEE. The increased proliferation of data production technologies (e.g., cameras) and consumption avenues (e.g., social media) has led to images and videos being utilized by users to convey innate preferences and tastes. This has opened up the possibility of using multimedia as a source for user-modeling. This work attempts to model personality traits (based on the Five Factor Theory) of users using a collection of images they tag as 'favorite' (or like) on Flickr. First, a set of semantic features are proposed to be used for representing different concepts in images which influence users to like them. The addition of the proposed features led to improvement over state-of-the-art by 12 percent. Second, a novel machine learning approach is developed to model users' personality based on the image features (resulting in upto 15 percent improvement). Third, efficacy of the semantic features and the modeling approach is shown in recommending images based on personality modeling. Using the modeling approach, recommendations are made regarding the factors that might influence users with different personality traits to like an image.

Guo, J, Yang, T, Yuan, J & Zhang, JA 2018, 'A Novel Linear Physical-Layer Network Coding Scheme for Y-Channel Without Transmitter CSI', IEEE Transactions on Vehicular Technology, vol. 67, no. 10, pp. 10049-10053.
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© 1967-2012 IEEE. We propose a novel linear physical-layer network coding (NC) scheme for a fading Y-channel without channel state information at transmitters. In this three-user scheme, each user intends to realize a full data exchange with the other two users via a relay. Instead of directly decoding the users' messages from the received signal, the relay determines NC generator matrices and reconstructs linear NC codewords from its received signals to facilitate the information exchange. We present an explicit solution for NC generator matrices that minimize the NC error probability at high SNRs. We also present and prove an approximation of the NC error probability of the proposed scheme at high SNRs. Numerical results show that the proposed scheme outperforms existing ones, and its performance can be well characterized by the approximation.

Guo, J, Yuan, J & Zhang, J 2018, 'An Achievable Throughput Scaling Law of Wireless Device-to-Device Caching Networks With Distributed MIMO and Hierarchical Cooperations', IEEE Transactions on Wireless Communications, vol. 17, no. 1, pp. 492-505.
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© 2002-2012 IEEE. In this paper, we propose a new caching scheme for a random wireless device-to-device (D2D) network of n nodes with local caches, where each node intends to download files from a prefixed library via D2D links. Our proposed caching delivery includes two stages, employing distributed MIMO and hierarchical cooperations, respectively. The distributed MIMO is applied to the first stage between source nodes and neighbors of the destination node. The induced multiplexing gain and diversity gain increase the number of simultaneous transmissions, improving the throughput of the network. The hierarchical cooperations are applied to the second stage to facilitate the transmissions between the destination node and its neighbors. The two stages together exploit spatial degrees of freedom as well as spatial reuse. We develop an uncoded random caching placement strategy to serve this cooperative caching delivery. Analytical results show that the average aggregate throughput of the network scales almost linearly with n, with a vanishing outage probability. Furthermore, we derive an explicit expression of the optimal throughput as a function of system parameters, such as pathloss factor under a target outage probability. Analytical and numerical results demonstrate that our proposed scheme outperforms existing ones when the local cache size is limited.

Guo, Q, Zhang, Y, Celler, BG & Su, SW 2018, 'State-Constrained Control of Single-Rod Electrohydraulic Actuator With Parametric Uncertainty and Load Disturbance', IEEE Transactions on Control Systems Technology, vol. 26, no. 6, pp. 2242-2249.
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IEEE The suppression of disturbances under parametric uncertainties is one of the most common control problems in electrohydraulic systems, as both disturbances and uncertainties often significantly degrade the tracking performance and bias the load pressure of the electrohydraulic actuator (EHA). This brief presents a state-constrained control of single-rod EHA to restrict the position tracking error to a prescribed accuracy and guarantee the load pressure in the maximal power boundary. Furthermore, a dynamic surface is designed to avoid the explosion of complexity due to the repeatedly calculated differentiations of the virtual control variables in the backstepping iteration. Integrating with a disturbance observer and the parametric estimation law, this state-constrained controller guarantees the asymptotic convergence of system state error under parametric uncertainties and large load disturbances. The effectiveness of the proposed controller has been demonstrated by a comparative experiment on the motion control of the two-degree-of-freedom robotic arm.

Guo, Y, Xie, H, Zhang, J, Wang, W, Ngo, HH, Guo, W, Kang, Y & Zhang, B 2018, 'Improving nutrient removal performance of surface flow constructed wetlands in winter using hardy submerged plant-benthic fauna systems', RSC Advances, vol. 8, no. 73, pp. 42179-42188.
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A novel hardy submerged plant-benthic fauna systems to enhance the performance of surface flow constructed wetlands in winter.

Guo, Z, Le, AN, Feng, X, Choo, Y, Liu, B, Wang, D, Wan, Z, Gu, Y, Zhao, J, Li, V, Osuji, CO, Johnson, JA & Zhong, M 2018, 'Janus Graft Block Copolymers: Design of a Polymer Architecture for Independently Tuned Nanostructures and Polymer Properties', Angewandte Chemie International Edition, vol. 57, no. 28, pp. 8493-8497.
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AbstractThe graft‐through synthesis of Janus graft block copolymers (GBCPs) from branched macromonomers composed of various combinations of homopolymers is presented. Self‐assembly of GBCPs resulted in ordered nanostructures with ultra‐small domain sizes down to 2.8 nm (half‐pitch). The grafted architecture introduces an additional parameter, the backbone length, which enables control over the thermomechanical properties and processability of the GBCPs independently of their self‐assembled nanostructures. The simple synthetic route to GBCPs and the possibility of using a variety of polymer combinations contribute to the universality of this technique.

Guo, Z, Le, AN, Feng, X, Choo, Y, Liu, B, Wang, D, Wan, Z, Gu, Y, Zhao, J, Li, V, Osuji, CO, Johnson, JA & Zhong, M 2018, 'Janus Graft Block Copolymers: Design of a Polymer Architecture for Independently Tuned Nanostructures and Polymer Properties', Angewandte Chemie, vol. 130, no. 28, pp. 8629-8633.
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AbstractThe graft‐through synthesis of Janus graft block copolymers (GBCPs) from branched macromonomers composed of various combinations of homopolymers is presented. Self‐assembly of GBCPs resulted in ordered nanostructures with ultra‐small domain sizes down to 2.8 nm (half‐pitch). The grafted architecture introduces an additional parameter, the backbone length, which enables control over the thermomechanical properties and processability of the GBCPs independently of their self‐assembled nanostructures. The simple synthetic route to GBCPs and the possibility of using a variety of polymer combinations contribute to the universality of this technique.

H. Almabrok, M, G. McLaughlan, R & Vessalas, K 2018, 'EFFECT OF SYNTHETIC DRILL CUTTINGS ON MORTAR PROPERTIES', Malaysian Journal of Civil Engineering, vol. 30, no. 3, pp. 405-414.
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Drill cuttings from oil exploration are recognised as a major environmental concern. Current cost-effective treatment technologies often involve sending treated products to landfill without any potential end-use thereby rendering these solutions unsustainable. There is potential for using drill cuttings comprising of oily, saline and clayey waste materials as fine aggregate replacements in structural concretes requiring characteristic compressive strength from 20-32 MPa. Research into the hydration process as well as evaluating the fresh and hardened properties of mortars incorporating synthetic drill cuttings were undertaken. Replacement of sand by synthetic drill cuttings (up to 25% by weight) produced mortar with accelerated hydration as well as reduced flow and density. In addition, the 28-day compressive strength of mortar incorporating synthetic drill cuttings decreased by up to 50%. Satisfactory strength for all sand replacement levels evaluated in mortars was still attainable for reuse of these synthetic of drill cuttings as fine aggregate replacements in structural concretes.

Ha, Q, Royel, S & Balaguer, C 2018, 'Low-energy structures embedded with smart dampers', Energy and Buildings, vol. 177, pp. 375-384.
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Building structures, subject to dynamic loadings or external disturbances, may undergo destructive vibrations and encounter different degrees of deformation. Modeling and control techniques can be applied to effectively damp out these vibrations and maintain structural health with a low energy cost. Smart structures embedded with semi-active control devices, offer a promising solution to the problem. The smart damping concept has been proven to be an effective approach for input energy shaping and sup- pressing unwanted vibrations in structural control for buildings embedded with magnetorheological fluid dampers (MRDs). In this paper, the dissipation energy in MRD is studied by using results from induced hysteretic effect of structural vibrations while the fluid is placed under a controlled magnetic field. Then, a frequency-shaped second-order sliding mode controller (FS2SMC) is designed along with a low-pass filter to implement the desired dynamic sliding surface, wherein the frequency responses of the hysteretic MRD is represented by its magnitude and phase describing functions. The proposed controller can thus shape the frequency characteristics of the equivalent dynamics for the MRD-embedded structure against induced vibrations, and hence, dissipate the energy flow within the smart devices to prevent structural damage. Simulation results for a 10-floor building model equipped with current-controlled MRDs, subject to horizontal seismic excitations validate the proposed technique for low-energy structures with smart devices. The closed-loop performance and comparison in terms of energy signals indicate that the pro- posed method allows not only to reduce induced vibrations and input energy, but also its spectrum can be adjusted to prevent natural modes of the structure under external excitations.

Haes Alhelou, H, Hamedani Golshan, ME & Hajiakbari Fini, M 2018, 'Wind Driven Optimization Algorithm Application to Load Frequency Control in Interconnected Power Systems Considering GRC and GDB Nonlinearities', Electric Power Components and Systems, vol. 46, no. 11-12, pp. 1223-1238.
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Hajihassani, M, Jahed Armaghani, D & Kalatehjari, R 2018, 'Applications of Particle Swarm Optimization in Geotechnical Engineering: A Comprehensive Review', Geotechnical and Geological Engineering, vol. 36, no. 2, pp. 705-722.
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Halliday, BJ, Fukuzawa, R, Markie, DM, Grundy, RG, Ludgate, JL, Black, MA, Skeen, JE, Weeks, RJ, Catchpoole, DR, Roberts, AGK, Reeve, AE & Morison, IM 2018, 'Germline mutations and somatic inactivation of TRIM28 in Wilms tumour', PLOS Genetics, vol. 14, no. 6, pp. e1007399-e1007399.
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© 2018 Halliday et al. http://creativecommons.org/licenses/by/4.0/ Wilms tumour is a childhood tumour that arises as a consequence of somatic and rare germline mutations, the characterisation of which has refined our understanding of nephrogenesis and carcinogenesis. Here we report that germline loss of function mutations in TRIM28 predispose children to Wilms tumour. Loss of function of this transcriptional co-repressor, which has a role in nephrogenesis, has not previously been associated with cancer. Inactivation of TRIM28, either germline or somatic, occurred through inactivating mutations, loss of heterozygosity or epigenetic silencing. TRIM28-mutated tumours had a monomorphic epithelial histology that is uncommon for Wilms tumour. Critically, these tumours were negative for TRIM28 immunohistochemical staining whereas the epithelial component in normal tissue and other Wilms tumours stained positively. These data, together with a characteristic gene expression profile, suggest that inactivation of TRIM28 provides the molecular basis for defining a previously described subtype of Wilms tumour, that has early age of onset and excellent prognosis.

Hamdani, Rizal, S, Riza, M & Mahlia, TMI 2018, 'Mechanical properties of concrete containing beeswax/dammar gum as phase change material for thermal energy storage', AIMS Energy, vol. 6, no. 3, pp. 521-529.
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© 2018 the Author(s). This study aims to investigate the mechanical properties of concrete containing phase change materials (PCM). This research begins with the investigation of melting temperature, enthalpy, the thermal conductivity of the phase change materials using the T-history method, followed by preparation of concrete containing PCM, and finally testing of mechanical properties of concrete through compressive strength test. This study used beeswax, tallow, and dammar gum as PCM mixture. From the results of the PCM properties test, shows that the latent heat energy content from beeswax and tallow exhibit an excellent potential to be used as PCM, while dammar gum is benefited in increasing the thermal conductivity of concrete containing PCM. From concrete specimen test containing 10%, 20% and 30% PCM with 7 days and 28 days aged, the results exhibit that the mechanical properties of the concrete decreased along with the increasing of PCM content. The same test also conducted at the PCM melting temperature. Therefore, the concrete compressive strength test conducted at 45 °C. From the test results, the concrete compressive strength decreased about 3-24% of PCM-0% concrete compressive strength. Drastic compressive strength reduction tends to occur in PCM-Tallow concrete mixture. This study concluded that the PCM is potentially useful as a heat energy absorber material in buildings and lightweight concrete rather than construction structures.

Han, B, Pan, Y & Tsang, IW 2018, 'Robust Plackett–Luce model for k-ary crowdsourced preferences', Machine Learning, vol. 107, no. 4, pp. 675-702.
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© 2017, The Author(s). The aggregation of k-ary preferences is an emerging ranking problem, which plays an important role in several aspects of our daily life, such as ordinal peer grading and online product recommendation. At the same time, crowdsourcing has become a trendy way to provide a plethora of k-ary preferences for this ranking problem, due to convenient platforms and low costs. However, k-ary preferences from crowdsourced workers are often noisy, which inevitably degenerates the performance of traditional aggregation models. To address this challenge, in this paper, we present a RObust PlAckett–Luce (ROPAL) model. Specifically, to ensure the robustness, ROPAL integrates the Plackett–Luce model with a denoising vector. Based on the Kendall-tau distance, this vector corrects k-ary crowdsourced preferences with a certain probability. In addition, we propose an online Bayesian inference to make ROPAL scalable to large-scale preferences. We conduct comprehensive experiments on simulated and real-world datasets. Empirical results on “massive synthetic” and “real-world” datasets show that ROPAL with online Bayesian inference achieves substantial improvements in robustness and noisy worker detection over current approaches.

Han, B, Tsang, IW, Chen, L, Yu, CP & Fung, S-F 2018, 'Progressive Stochastic Learning for Noisy Labels', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 10, pp. 5136-5148.
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© 2018 IEEE. Large-scale learning problems require a plethora of labels that can be efficiently collected from crowdsourcing services at low cost. However, labels annotated by crowdsourced workers are often noisy, which inevitably degrades the performance of large-scale optimizations including the prevalent stochastic gradient descent (SGD). Specifically, these noisy labels adversely affect updates of the primal variable in conventional SGD. To solve this challenge, we propose a robust SGD mechanism called progressive stochastic learning (POSTAL), which naturally integrates the learning regime of curriculum learning (CL) with the update process of vanilla SGD. Our inspiration comes from the progressive learning process of CL, namely learning from 'easy' tasks to 'complex' tasks. Through the robust learning process of CL, POSTAL aims to yield robust updates of the primal variable on an ordered label sequence, namely, from 'reliable' labels to 'noisy' labels. To realize POSTAL mechanism, we design a cluster of 'screening losses,' which sorts all labels from the reliable region to the noisy region. To sum up, POSTAL using screening losses ensures robust updates of the primal variable on reliable labels first, then on noisy labels incrementally until convergence. In theory, we derive the convergence rate of POSTAL realized by screening losses. Meanwhile, we provide the robustness analysis of representative screening losses. Experimental results on UCI1 simulated and Amazon Mechanical Turk crowdsourcing data sets show that the POSTAL using screening losses is more effective and robust than several existing baselines.1UCI is the abbreviation of University of California Irvine.

Han, F, Wei, D, Ngo, HH, Guo, W, Xu, W, Du, B & Wei, Q 2018, 'Performance, microbial community and fluorescent characteristic of microbial products in a solid-phase denitrification biofilm reactor for WWTP effluent treatment', Journal of Environmental Management, vol. 227, pp. 375-385.
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Microbial products, i.e. extracellular polymeric substance (EPS) and soluble microbial product (SMP), have a significant correlation with microbial activity of biologically based systems. In present study, the spectral characteristics of two kinds of microbial products were comprehensively evaluated in a solid-phase denitrification biofilm reactor for WWTP effluent treatment by using poly (butylene succinate) (PBS) as carbon source. After the achievement of PBS-biofilm, nitrate and total nitrogen removal efficiencies were high of 97.39 ± 1.24% and 96.38 ± 1.1%, respectively. The contents of protein and polysaccharide were changed different degrees in both LB-EPS and TB-EPS. Excitation-emission matrix (EEM) implied that protein-like substances played a significant role in the formation of PBS-biofilm. High-throughput sequencing result implied that the proportion of denitrifying bacteria, including Simplicispira, Dechloromonas, Diaphorobacter, Desulfovibrio, increased to 9.2%, 7.4%, 4.8% and 3.6% in PBS-biofilm system, respectively. According to EEM-PARAFAC, two components were identified from SMP samples, including protein-like substances for component 1 and humic-like and fulvic acid-like substances for component 2, respectively. Moreover, the fluorescent scores of two components expressed significant different trends to reaction time. Gas chromatography-mass spectrometer (GC-MS) implied that some new organic matters were produced in the effluent of SP-DBR due to biopolymer degradation and denitrification processes. The results could provide a new insight about the formation and stability of solid-phase denitrification PBS-biofilm via the point of microbial products.

Han, L, Liu, S, Han, S, Jia, W & Lei, J 2018, 'Owner based malware discrimination', Future Generation Computer Systems, vol. 80, pp. 496-504.
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© 2016 Elsevier B.V. A piece of malware code can be harmful in one's system but totally harmless in another's. In this paper, we point out that the detection of malicious code or software is actually a matter of discrimination which depends on the owners of the computer systems. We propose an owner based malicious software discrimination model, named as Unlimited Register Machine of Owners (URMO). First, we characterize and analyze the limitations of existing discrimination techniques in theory by using the discrimination model of Unlimited Register Machine (URM) and then move on to construct the URMO discrimination model by giving the two important elements of malicious behavior: an operation and the object of the operation. The relationship between an operation and the object of the operation is fundamental to solving the relativity of the discrimination problem about malice, which is also the advantage of the URMO model. Finally, by applying the model to discriminate real-world malware and comparing it with existing popular antivirus software, we demonstrate the effectiveness and superior performance of the URMO model.

Han, W, Zhang, H-P, Tavakoli, J, Campbell, J & Tang, Y 2018, 'Polydopamine as sizing on carbon fiber surfaces for enhancement of epoxy laminated composites', Composites Part A: Applied Science and Manufacturing, vol. 107, pp. 626-632.
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Carbon fiber reinforced polymer (CFRP) laminate normally has plastic dominant crack propagation behavior, inducing potential insecurity in the safety and reliability of structures in practical applications. In this study, we report a simple process to increase the stability of crack growth by using polydopamine (PDA) as sizing on the surface of carbon fiber (CF) fabric. The crack propagation behavior changes from a saw-tooth-shaped curve in neat CFRP laminate to a relatively smooth trending curve in PDA coated CFRP laminate with increased Mode I interlaminar fracture toughness. Enhanced impact strength and interlaminar shear strength of PDA coated CFRP laminates is also observed. A single fiber pull-out experiment and morphological study reveal that, with PDA coating on CF fabrics, cracks tend to fracture through the epoxy matrix rather than between fiber and matrix interfaces. The use of PDA as sizing on the CF contributes to improving the load transfer between the CF and the polymer matrix by enhancing the interfaces between the epoxy and the CF, increasing the friction of the fractured interface, reducing unstable crack growth, and thereby enhancing interfacial fracture toughness and impact performance.

Han, Z, Wu, M, Zhu, Q & Yang, J 2018, 'Two-dimensional multizone sound field reproduction using a wave-domain method', The Journal of the Acoustical Society of America, vol. 144, no. 3, pp. EL185-EL190.
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This paper addresses a two-dimensional multizone sound field reproduction approach using a wave-domain method. The desired sound fields in the bright and dark zones are described as orthogonal expansions of basis functions over the regions. The loudspeaker weights are obtained by maximizing the contrast among multiple zones in the wave domain. Simulation results demonstrate that compared with the conventional acoustic contrast control approach, the proposed method improves the level of acoustic contrast and array gain over the entire control region and is less sensitive to the selection of the regularization parameter.

Handojoseno A.M. Ardi, Naik Ganesh R., Gilat Moran, Shine James M., Nguyen Tuan N., Ly Quynh T., Lewis Simon J.G. & Nguyen Hung T. 2018, 'Prediction of Freezing of Gait in Patients with Parkinson's Disease Using EEG Signals', Stud Health Technol Inform, vol. 246, pp. 124-131.
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Freezing of gait (FOG) is an episodic gait disturbance affecting initiation and continuation of locomotion in many Parkinson's disease (PD) patients, causing falls and a poor quality of life. FOG can be experienced on turning and start hesitation, passing through doorways or crowded areas dual tasking, and in stressful situations. Electroencephalography (EEG) offers an innovative technique that may be able to effectively foresee an impending FOG. From data of 16 PD patients, using directed transfer function (DTF) and independent component analysis (ICA) as data pre-processing, and an optimal Bayesian neural network as a predictor of a transition of 5 seconds before the impending FOG occurs in 11 in-group PD patients, we achieved sensitivity and specificity of 85.86% and 80.25% respectively in the test set (5 out-group PD patients). This study therefore contributes to the development of a non-invasive device to prevent freezing of gait in PD.

Hanh, LTM, Binh, NT & Tung, KT 2018, 'Parallel Mutant Execution Techniques in Mutation Testing Process for Simulink Models', Journal of Telecommunications and Information Technology, vol. 4, no. 2017, pp. 90-100.
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Mutation testing – a fault-based technique for software testing – is a computationally expensive approach. One of the powerful methods to improve the performance of mutation without reducing effectiveness is to employ parallel processing, where mutants and tests are executed in parallel. This approach reduces the total time needed to accomplish the mutation analysis. This paper proposes three strategies for parallel execution of mutants on multicore machines using the Parallel Computing Toolbox (PCT) with the Matlab Distributed Computing Server. It aims to demonstrate that the computationally intensive software testing schemes, such as mutation, can be facilitated by using parallel processing. The experiments were carried out on eight different Simulink models. The results represented the efficiency of the proposed approaches in terms of execution time during the testing process.

Hannan, MA, Faisal, M, Ker, PJ, Mun, LH, Parvin, K, Mahlia, TMI & Blaabjerg, F 2018, 'A Review of Internet of Energy Based Building Energy Management Systems: Issues and Recommendations', IEEE Access, vol. 6, pp. 38997-39014.
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© 2013 IEEE. A building energy management system (BEMS) is a sophisticated method used for monitoring and controlling a building's energy requirements. A number of potential studies were conducted in nearly or net zero energy buildings (nZEBs) for the optimization of building energy consumption through efficient and sustainable ways. Moreover, policy makers are approving measures to improve building energy efficiency in order to foster sustainable energy usages. However, the intelligence of existing BEMSs or nZEBs is inadequate, because of the static set points for heating, cooling, and lighting, the complexity of large amounts of BEMS data, data loss, and network problems. To solve these issues, a BEMS or nZEB solution based on the Internet of energy (IoE) provides disruptive opportunities for revolutionizing sustainable building energy management. This paper presents a critical review of the potential of an IoE-based BEMS for enhancing the performance of future generation building energy utilization. The detailed studies of the IoE architecture, typical nZEB configuration, different generations of nZEB, and smart building energy systems for future BEMS are investigated. The operations, advantages, and limitations of the existing BEMSs or nZEBs are illustrated. A comprehensive review of the different types of IoE-based BEMS technologies, such as energy routers, storage systems and materials, renewable sources, and plug-and-play interfaces, is then presented. The rigorous review indicates that existing BEMSs require advanced controllers integrated with IoE-based technologies for sustainable building energy usage. The main objective of this review is to highlight several issues and challenges of the conventional controllers and IoE applications of BEMSs or nZEBs. Accordingly, the review provides several suggestions for the research and development of the advanced optimized controller and IoE of future BEMSs. All the highlighted insights and recommendatio...

Hao, S, Shi, C, Niu, Z & Cao, L 2018, 'Concept coupling learning for improving concept lattice-based document retrieval', Engineering Applications of Artificial Intelligence, vol. 69, pp. 65-75.
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© 2017 Elsevier Ltd The semantic information in any document collection is critical for query understanding in information retrieval. Existing concept lattice-based retrieval systems mainly rely on the partial order relation of formal concepts to index documents. However, the methods used by these systems often ignore the explicit semantic information between the formal concepts extracted from the collection. In this paper, a concept coupling relationship analysis model is proposed to learn and aggregate the intra- and inter-concept coupling relationships. The intra-concept coupling relationship employs the common terms of formal concepts to describe the explicit semantics of formal concepts. The inter-concept coupling relationship adopts the partial order relation of formal concepts to capture the implicit dependency of formal concepts. Based on the concept coupling relationship analysis model, we propose a concept lattice-based retrieval framework. This framework represents user queries and documents in a concept space based on fuzzy formal concept analysis, utilizes a concept lattice as a semantic index to organize documents, and ranks documents with respect to the learned concept coupling relationships. Experiments are performed on the text collections acquired from the SMART information retrieval system. Compared with classic concept lattice-based retrieval methods, our proposed method achieves at least 9%, 8% and 15% improvement in terms of average MAP, IAP@11 and P@10 respectively on all the collections.

Hasan, ASMM, Hoq, MT & Thollander, P 2018, 'Energy management practices in Bangladesh's iron and steel industries', Energy Strategy Reviews, vol. 22, pp. 230-236.
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The aim of this paper was to study energy management and improved energy efficiency among large iron and steel mills in Bangladesh. The results show that there are some barriers to energy management practices among large steel mills, the most important barriers being the perceived absence of cost-effective technical measures, high perceived risks due to uncertain future energy costs and poor information quality. However, this study has shown that the reduction in energy costs due to improved energy efficiency constitutes the most important driver for energy efficiency in the studied steel mills. The results also show that most of the steel mills have not had any technical energy efficiency improvement measures implemented in the production process. Moreover, the steel mills seem unfamiliar with the concept of including energy service companies, and the lack of information or awareness seems to be the main reason behind this. The paper also finds that energy efficiency is perceived to be able to be improved by 6%–8% through energy management practices.

Hasanipanah, M, Bakhshandeh Amnieh, H, Khamesi, H, Jahed Armaghani, D, Bagheri Golzar, S & Shahnazar, A 2018, 'Prediction of an environmental issue of mine blasting: an imperialistic competitive algorithm-based fuzzy system', International Journal of Environmental Science and Technology, vol. 15, no. 3, pp. 551-560.
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Hasanipanah, M, Jahed Armaghani, D, Bakhshandeh Amnieh, H, Koopialipoor, M & Arab, H 2018, 'A Risk-Based Technique to Analyze Flyrock Results Through Rock Engineering System', Geotechnical and Geological Engineering, vol. 36, no. 4, pp. 2247-2260.
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Hassan, M, Liu, D & Paul, G 2018, 'Collaboration of Multiple Autonomous Industrial Robots through Optimal Base Placements', Journal of Intelligent & Robotic Systems, vol. 90, no. 1-2, pp. 113-132.
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© 2017, Springer Science+Business Media B.V. Multiple autonomous industrial robots can be of great use in manufacturing applications, particularly if the environment is unstructured and custom manufacturing is required. Autonomous robots that are equipped with manipulators can collaborate to carry out manufacturing tasks such as surface preparation by means of grit-blasting, surface coating or spray painting, all of which require complete surface coverage. However, as part of the collaboration process, appropriate base placements relative to the environment and the target object need to be determined by the robots. The problem of finding appropriate base placements is further complicated when the object under consideration is large and has a complex geometric shape, and thus the robots need to operate from a number of base placements in order to obtain complete coverage of the entire object. To address this problem, an approach for Optimization of Multiple Base Placements (OMBP) for each robot is proposed in this paper. The approach aims to optimize base placements for multi-robot collaboration by taking into account task-specific objectives such as makespan, fair workload division amongst the robots, and coverage percentage; and manipulator-related objectives such as torque and manipulability measure. In addition, the constraint of robots maintaining an appropriate distance between each other and relative to the environment is taken into account. Simulated and real-world experiments are carried out to demonstrate the effectiveness of the approach and to verify that the simulated results are accurate and reliable.

Hassanzadeh-Barforoushi, A, Law, AMK, Hejri, A, Asadnia, M, Ormandy, CJ, Gallego-Ortega, D & Ebrahimi Warkiani, M 2018, 'Static droplet array for culturing single live adherent cells in an isolated chemical microenvironment', Lab on a Chip, vol. 18, no. 15, pp. 2156-2166.
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Rapid and reliable capture and analysis of single cells in a chemically isolated static droplet array for fast-tracking single cell discoveries.

Hawari, AH, Al-Qahoumi, A, Ltaief, A, Zaidi, S & Altaee, A 2018, 'Dilution of seawater using dewatered construction water in a hybrid forward osmosis system', Journal of Cleaner Production, vol. 195, pp. 365-373.
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© 2018 Elsevier Ltd In this study, dewatered construction water was used for the first time as the feed solution in a combined pretreatment-forward osmosis process to dilute seawater (i.e. draw solution) for further desalination. It was found that at a feed solution and a draw solution flow rate of 2.2 L min−1 gave the optimum membrane flux with minimal fouling effects. The addition of a spacer in the membrane feed side was effective at low flow rates (0.8 and 1.5 L min−1). The feed solution was then pretreated using two methods: settling and multimedia filtration and used in the forward osmosis unit at a low flow rate of 0.8 L min−1 using a spacer at the feed side. Results revealed a significant increase in the forward osmosis membrane flux by 64.3% when multimedia filtration was carried out with a flux reduction of 7.7%. While the settling method achieved only 13.5% increase in the permeate flux and 12.5% flux reduction. The multimedia filtration process removed most of the particles that would cause fouling which resulted in an elevated and more consistent membrane flux. Results also showed that the water flux was 1.3 times higher when the membrane's active layer was facing the draw solution than when it was facing the feed solution. Cost analysis showed that forward osmosis treatment of dewatered construction water was 7.88 $.day−1 and it was slightly cheaper when the forward osmosis operates in the pressure retarded osmosis mode.

Haydar, H, Far, H & Saleh, A 2018, 'Portal steel trusses vs. portal steel frames for long‐span industrial buildings', Steel Construction, vol. 11, no. 3, pp. 205-217.
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AbstractPortal frames and portal truss structures are two of the most cost‐effective and sustainable structural forms for the design and construction of long‐span industrial buildings. Although the use of both structure types as steel‐clad structures is widely accepted, due to frame complexity and variation of frame types for use in single‐storey buildings with spans > 30 m, literature providing a comprehensive investigation of the concepts of portal trusses and portal frames is scarce. This study compares the behaviour of a portal truss configuration with pitched portal frames for use in industrial buildings with spans > 30 m, focusing on weight, costs and construction time. Furthermore, this study entails a numerical investigation that utilizes the SAP2000 computer program to model and structurally optimize the member properties for both portal frame and portal truss configurations. Based on the results obtained from the investigation, it has become apparent that, due to the smaller sections used, the portal truss configurations are lighter and cheaper to fabricate and construct in comparison to the pitched portal frames, which, however, require a shorter construction time.

He, F, Jiang, F, Jiang, Y & Ling, SH 2018, 'New microscopic image sequence‐driven cell deformation model', The Journal of Engineering, vol. 2018, no. 16, pp. 1587-1589.
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It is of great significance that making quantitative description and analysis of the cell morphological change to explore physiological or pathological status of the life. To achieve the cells morphological changes of quantitative description, the authors constructed a cell deformation model based on microscopic image sequence here. Based on the graph regularisation and structured matrix decomposition, the high‐dimensional shape space is represented by the linear combination of the low‐dimension subshape space, so that the authors get a quantitative indicator which represents the degree of cell deformation–deformation factor. In order to verify the validity of the authors’ model, a deformation feature extraction experiment was performed on three groups of stem cell image sequence with different deformation degree. Compared with other three common quantitative methods of deformation, the authors’ model describes the cell morphological changes more comprehensively, and has better adaptability and stability for describing the diversity of cell movements.

He, Q, Wang, J & Lu, H 2018, 'A hybrid system for short-term wind speed forecasting', Applied Energy, vol. 226, pp. 756-771.
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© 2018 Elsevier Ltd Wind speed forecasting is important for high-efficiency utilization of wind energy. Correspondingly, numerous researchers have always focused on the development of reliable forecasting models of wind speed, which is often noisy, unstable and irregular. Current approaches could adapt to various wind speed data. However, many of these usually ignore the importance of the selection of the modeling sample, which often results in poor forecasting performance. In this study, a hybrid forecasting system is proposed that contains three modules: data preprocessing, data clustering, and forecasting modules. In this system, the decomposing technique is applied to reduce the influence of noise within the raw data series to obtain a more stable sequence that is conducive to extract traits from the original data. To extract the characteristic of similarity within wind speed data, a kernel-based fuzzy c-means clustering algorithm is used in data clustering module. In the forecasting module, a sample with a highly similar fluctuation pattern is selected as training dataset, and which could reduce the training requirement of model to improve the forecasting accuracy. The experimental results indicate that the developed system outperforms the discussed traditional forecasting models with respect to forecasting accuracy.

He, T, Lu, DD-C, Li, L, Zhang, J, Zheng, L & Zhu, J 2018, 'Model-Predictive Sliding-Mode Control for Three-Phase AC/DC Converters', IEEE Transactions on Power Electronics, vol. 33, no. 10, pp. 8982-8993.
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© 1986-2012 IEEE. This paper presents a model-predictive sliding-mode control (MPSMC) scheme for a three-phase ac/dc converter to achieve better stability and dynamic performances. In the conventional model-predictive control method, a proportional-integral (PI) controller is used to generate the active power reference. This traditional model-predictive PI control (MPPIC) scheme, however, produces a large overshoot/undershoot, a long settling time, and a large steady-state error under disturbances. To overcome these deficiencies, a sliding-mode controller is employed to replace the PI controller. Since the control law and the controller are designed based on the system model, the proposed MPSMC scheme can reduce the effects of unexpected disturbances, such as the output voltage demand and the resistance load variations. Both methods have been simulated in MATLAB/Simulink during various disturbances. Compared with the performances of MPPIC, the results obtained from MPSMC show that the settling time of the dc voltage can be minimized by about 91%, and the overshoot can be eliminated from 9.13% during the steady-state progress. The active and reactive power from MPSMC can also be controlled to the desired values, respectively, with a much smaller overshoot/undershoot and a faster response speed. Similar dynamic improvements can be achieved with MPSMC when the dc voltage demand varies. The simulation results are validated by experimental results.

He, X, Liang, D & Bolton, MD 2018, 'Run-out of cut-slope landslides: mesh-free simulations', Géotechnique, vol. 68, no. 1, pp. 50-63.
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This study uses an incompressible smoothed-particle hydrodynamics (ISPH) model to investigate the run-out and deposit morphology of granular materials flowing down cut slopes. The primary aim is to study the influence of various factors on the run-out and to summarise a quantitative relationship for direct use in landslide hazard management. In the model, the granular materials are modelled as a rigid perfectly plastic material with a Coulomb yield surface. The coupled continuity equation and momentum equation are solved by a semi-implicit algorithm. The model is first validated and its results are carefully compared with various controlled experiments regarding granular flows. The model reproduces the flows and correctly predicts the deposition profiles under various conditions. Then, the computational results are used to study the run-out and mobility of landslides. For granular columns collapsing onto a flat surface, a normalised run-out and a new scaling relationship are proposed, which are supported by numerous measured and numerical results. A similar relationship for the run-out of granular rectangles on steep slopes has also been explored. It is found that the normalised run-out is mainly determined by the slope angle and the normalised drop height. Furthermore, three types of idealised cut-slope landslides are simulated to study the influence of the initial landslide shape on the run-out. It is found that the normalised run-out of these idealised cut-slope landslides is smaller than that of granular rectangles on slopes of the same angles and drop heights. The difference between the run-outs is found to be mainly determined by the proportion of the whole mass that initially lies above a predictable discontinuity plane.

He, X, Liang, D, Wu, W, Cai, G, Zhao, C & Wang, S 2018, 'Study of the interaction between dry granular flows and rigid barriers with an SPH model', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 11, pp. 1217-1234.
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SummaryThis study uses an incompressible smoothed‐particle hydrodynamics model to investigate the interaction between dry granular material flows and rigid barriers. The primary aim is to summarise some practical guidelines for the design of debris‐resisting barriers. The granular materials are modelled as a rigid‐perfectly plastic material where the plastic flow corresponds to the critical state. The coupled continuity equation and momentum equation are solved by a semi‐implicit algorithm. Compared with flows in controlled flume experiments, the model adequately reproduces both the kinetic of the flows and the impact force under various conditions. Then the numerical simulations are used to study the detailed interaction process. It is illustrated quantitatively that the interaction force consists of two parts, ie, the earth pressure force caused by the weight of the soil and a dynamic force caused by the internal deformation (flowing mass on top of a dead zone). For the estimation of impact load, this study suggests that an increased earth pressure coefficient depending on the Froude number should be incorporated into the hydrostatic model.

He, X, Wang, K, Huang, H & Liu, B 2018, 'QoE-Driven Big Data Architecture for Smart City', IEEE Communications Magazine, vol. 56, no. 2, pp. 88-93.
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In the era of big data, the applications/services of the smart city are expected to offer end users better QoE than in a conventional smart city. Nevertheless, various types of sensors will produce an increasing volume of big data along with the implementation of a smart city, where we face redundant and diverse data. Therefore, providing satisfactory QoE will become the major challenge in the big-data-based smart city. In this article, to enhance the QoE, we propose a novel big data architecture consisting of three planes: The data storage plane, the data processing plane, and the data application plane. The data storage plane stores a wide variety of data collected by sensors and originating from different data sources. Then the data processing plane filters, analyzes, and processes the ocean of data to make decisions autonomously for extracting high-quality information. Finally, the application plane initiates the execution of the events corresponding to the decisions delivered from the data processing plane. Under this architecture, we particularly use machine learning techniques, trying to acquire accurate data and deliver precise information to end users. Simulation results indicate that our proposals could achieve high QoE performance for the smart city.

He, Y, Jayawickrama, BA, Dutkiewicz, E, Srikanteswara, S & Mueck, M 2018, 'Priority Access and General Authorized Access Interference Mitigation in the Spectrum Access System', IEEE Transactions on Vehicular Technology, vol. 67, no. 6, pp. 4969-4983.
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© 1967-2012 IEEE. To meet the capacity needs of next generation wireless communications, the U.S. Federal Communications Commission has recently introduced the spectrum access system. Spectrum is shared between three tiers - incumbents, priority access licensees (PAL), and general authorized access (GAA) licensees. When the incumbents are absent, PAL and GAA share the spectrum under the constraint that GAA ensure the interference to PAL is no more than $-$40 dBm with at least 99% confidence. We consider the scenario where locations are not shared between PAL and GAA. We propose a PAL-GAA cochannel interference mitigation technique that does not expose base station locations. Our approach relies on GAA sharing the distribution and maximum number of transmitters in a finite area. We show how PAL can derive the distribution of the aggregate interference using the probability density function and characteristic function, and notify GAA about the exclusion zones in space that will guarantee that the interference requirement is met. We also propose a numerical approximation using inverse fast Fourier and discrete Fourier transforms. Analytically calculated distribution aligns well with the numerical results. Additionally, we formulate an optimization problem for the optimal exclusion zone size. We analytically prove convexity of the problem. Our approach reduces the exclusion zone size by over 42%, which gives significantly more spectral opportunities to GAA in the spatial domain.

He, Z, Zhang, S, Teng, J, Yao, Y & Sheng, D 2018, 'A coupled model for liquid water-vapor-heat migration in freezing soils', Cold Regions Science and Technology, vol. 148, pp. 22-28.
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Herr, D, Paler, A, Devitt, SJ & Nori, F 2018, 'A local and scalable lattice renormalization method for ballistic quantum computation', npj Quantum Information, vol. 4, no. 1, pp. 1-8.
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AbstractA recent proposal has shown that it is possible to perform linear-optics quantum computation using a ballistic generation of the lattice. Yet, due to the probabilistic generation of its cluster state, it is not possible to use the fault-tolerant Raussendorf lattice, which requires a lower failure rate during the entanglement-generation process. Previous work in this area showed proof-of-principle linear-optics quantum computation, while this paper presents an approach to it which is more practical, satisfying several key constraints. We develop a classical measurement scheme that purifies a large faulty lattice to a smaller lattice with entanglement faults below threshold. A single application of this method can reduce the entanglement error rate to 7% for an input failure rate of 25%. Thus, we can show that it is possible to achieve fault tolerance for ballistic methods.

Herr, D, Paler, A, Devitt, SJ & Nori, F 2018, 'Lattice surgery on the Raussendorf lattice', Quantum Science and Technology, vol. 3, no. 3, pp. 035011-035011.
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© 2018 IOP Publishing Ltd. Lattice surgery is a method to perform quantum computation fault-tolerantly by using operations on boundary qubits between different patches of the planar code. This technique allows for universal planar code computation without eliminating the intrinsic two-dimensional nearest-neighbor properties of the surface code that eases physical hardware implementations. Lattice surgery approaches to algorithmic compilation and optimization have been demonstrated to be more resource efficient for resource-intensive components of a fault-tolerant algorithm, and consequently may be preferable over braid-based logic. Lattice surgery can be extended to the Raussendorf lattice, providing a measurement-based approach to the surface code. In this paper we describe how lattice surgery can be performed on the Raussendorf lattice and therefore give a viable alternative to computation using braiding in measurement-based implementations of topological codes.

Hill, M & Tran, N 2018, 'MicroRNAs Regulating MicroRNAs in Cancer', Trends in Cancer, vol. 4, no. 7, pp. 465-468.
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© 2018 MicroRNAs (miRNA) are capable of self-regulation, termed miRNA to miRNA interaction. Very little is known about these interactions and their impact on the cellular milieu. We discuss known miRNA to miRNA interactions, potential mechanisms, and their role in cancer.

Ho, L & Fatahi, B 2018, 'Analytical solution to axisymmetric consolidation of unsaturated soil stratum under equal strain condition incorporating smear effects', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 15, pp. 1890-1913.
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SummaryThis paper proposes closed‐form analytical solutions to the axisymmetric consolidation of an unsaturated soil stratum using the equal strain hypothesis. Following the 1‐dimensional (1D) consolidation theory for unsaturated soil mechanics, polar governing equations describing the air and water flows are first presented on the basis of Fick's law and Darcy's law, respectively. The current study takes into account the peripheral smear caused by an installation of vertical drain. Separation of variables and Laplace transformation are mainly adopted in the analytical derivation to obtain final solutions. Then, the hydraulic conductivity ratio, the radius of influence zone and smear parameters influencing time‐dependent excess pore pressures, and the average degree of consolidation are graphically interpreted. In this study, a comparison made between the proposed equal strain results and the existing free strain results suggests that both hypotheses would deliver similar predictions. Moreover, it is found that the smear zone resulting from vertical drain installations would hinder the consolidation rate considerably.

Ho, L, Fatahi, B & Khabbaz, H 2018, 'Analytical Solution to One-Dimensional Consolidation in Unsaturated Soil Deposit Incorporating Time-Dependent Diurnal Temperature Variation', International Journal of Geomechanics, vol. 18, no. 5, pp. 04018029-04018029.
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© 2018 American Society of Civil Engineers. Several experimental studies have demonstrated that temperature changes may significantly influence the deformation of unsaturated soils. Thus, there is an essential need to develop a predictive framework for unsaturated consolidation capturing the nonisothermal effect. This paper presents an analytical solution to the one-dimensional (1D) consolidation of unsaturated soil deposit in response to temperature variation. A set of governing equations of flow incorporating the nonisothermal condition were first obtained. Then, Fourier sine series and the Laplace transformation were used to derive solutions based on these governing equations. This study highlighted the effect of diurnal temperature variation on pore pressures and soil deformation at different depths while considering two conditions of interest: (1) no external applied load, and (2) application of step loading to the ground surface. In addition, the thermal diffusivity characterizing the consolidation behavior of unsaturated soils was also investigated and is discussed in this paper. It is predicted that a decrease in thermal diffusivity would attenuate the effects of diurnal temperature on the unsaturated consolidation.

Ho, N, Peng, H, Mayoh, C, Liu, PY, Atmadibrata, B, Marshall, GM, Li, J & Liu, T 2018, 'Delineation of the frequency and boundary of chromosomal copy number variations in paediatric neuroblastoma', Cell Cycle, vol. 17, no. 6, pp. 749-758.
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Ho, Y-J, Shih, C-P, Yeh, K-T, Shi, B, Gong, Z, Lin, Y-M & Lu, J-W 2018, 'Correlation between high expression levels of jumonji domain-containing 4 and short survival in cases of colon adenocarcinoma', Biochemical and Biophysical Research Communications, vol. 503, no. 3, pp. 1442-1449.
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Hoang, DT, Niyato, D, Nguyen, DN, Dutkiewicz, E, Wang, P & Han, Z 2018, 'A Dynamic Edge Caching Framework for Mobile 5G Networks', IEEE Wireless Communications, vol. 25, no. 5, pp. 95-103.
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© 2002-2012 IEEE. Mobile edge caching has emerged as a new paradigm to provide computing, networking resources, and storage for a variety of mobile applications. That helps achieve low latency, high reliability, and improve efficiency in handling a very large number of smart devices and emerging services (e.g., IoT, industry automation, virtual reality) in mobile 5G networks. Nonetheless, the development of mobile edge caching is challenged by the decentralized nature of edge nodes, their small coverage, limited computing, and storage resources. In this article, we first give an overview of mobile edge caching in 5G networks. After that, its key challenges and current approaches are discussed. We then propose a novel caching framework. Our framework allows an edge node to authorize the legitimate users and dynamically predicts and updates their content demands using the matrix factorization technique. Based on the prediction, the edge node can adopt advanced optimization methods to determine optimal content to store so as to maximize its revenue and minimize the average delay of its mobile users. Through numerical results, we demonstrate that our proposed framework provides not only an effective caching approach, but also an efficient economic solution for the mobile service provider.

Hoang, TM, Ngo, HQ, Duong, TQ, Tuan, HD & Marshall, A 2018, 'Cell-Free Massive MIMO Networks: Optimal Power Control Against Active Eavesdropping', IEEE Transactions on Communications, vol. 66, no. 10, pp. 4724-4737.
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© 1972-2012 IEEE. This paper studies the security aspect of a recently introduced 'cell-free massive MIMO' network under a pilot spoofing attack. First, a simple method to recognize the presence of this type of an active eavesdropping attack to a particular user is shown. In order to deal with this attack, we consider the problem of maximizing the achievable data rate of the attacked user or its achievable secrecy rate. The corresponding problems of minimizing the power consumption subject to security constraints are also considered in parallel. Path-following algorithms are developed to solve the posed optimization problems under different power allocation to access points (APs). Under equip-power allocation to APs, these optimization problems admit closed-form solutions. Numerical results show their efficiency.

Ho-Le, TP & Nguyen, TV 2018, 'Mathematics Research in Association of Southeast Asian Nations Countries: A Scientometric Analysis of Patterns and Impacts', Frontiers in Research Metrics and Analytics, vol. 3, p. 3.
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Ho-Le, TP, Pham, HM, Center, JR, Eisman, JA, Nguyen, HT & Nguyen, TV 2018, 'Prediction of changes in bone mineral density in the elderly: contribution of “osteogenomic profile”', Archives of Osteoporosis, vol. 13, no. 1.
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© 2018, International Osteoporosis Foundation and National Osteoporosis Foundation. Summary: The contribution of genetic variants to longitudinal bone loss has not been well documented. We constructed an “osteogenomic profile” based on 62 BMD-associated genetic variants and showed that the profile was significantly associated with bone loss, independently from baseline BMD and age. The osteogenomic profile can help predict bone loss in an individual. Introduction: The rate of longitudinal bone loss (ΔBMD) is a risk factor for fracture. The variation in ΔBMD is partly determined by genetic factors. This study sought to define the association between an osteogenomic profile and ΔBMD. Methods: The osteogenomic profile was created from 62 BMD-associated SNPs from genome-wide association studies (GWAS) that were genotyped in 1384 elderly men and women aged 60+ years. Weighted genetic risk scores (GRS) were constructed for each individual by summing the products of the number of risk alleles and the sex-specific regression coefficients [associated with BMD from GWAS]. ΔBMD, expressed as annual percent change-in-BMD, was determined by linear regression analysis for each individual who had had at least two femoral neck BMD measurements. Results: The mean ΔBMD was − 0.65% (SD 1.64%) for women and − 0.57% (SD 1.40%) for men, and this difference was not statistically significant (P = 0.32). In women, each unit increase in GRS was associated with 0.21% (SE 0.10) higher ΔBMD at the femoral neck (P = 0.036), and this association was independent of baseline BMD and age. In logistic regression analysis, each unit increase of GRS was associated with 41% odds (95%CI: 1.07–1.87) of rapid bone loss (ΔBMD ≤ − 1.2%/year; mean of rapid loss group = − 2.2%/year). There was no statistically significant association between ΔBMD and GRS in men. Conclusions: We conclude that the osteogenomic profile constructed from BMD-associated genetic variants is modestly associated with long-...

Hong, H, Liu, J, Bui, DT, Pradhan, B, Acharya, TD, Pham, BT, Zhu, A-X, Chen, W & Ahmad, BB 2018, 'Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)', CATENA, vol. 163, pp. 399-413.
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© 2018 Elsevier B.V. Landslides are a manifestation of slope instability causing different kinds of damage affecting life and property. Therefore, high-performance-based landslide prediction models are useful to government institutions for developing strategies for landslide hazard prevention and mitigation. Development of data mining based algorithms shows that high-performance models can be obtained using ensemble frameworks. The primary objective of this study is to investigate and compare the use of current state-of-the-art ensemble techniques, such as AdaBoost, Bagging, and Rotation Forest, for landslide susceptibility assessment with the base classifier of J48 Decision Tree (JDT). The Guangchang district (Jiangxi province, China) was selected as the case study. Firstly, a landslide inventory map with 237 landslide locations was constructed; the landslide locations were then randomly divided into a ratio of 70/30 for the training and validating models. Secondly, fifteen landslide conditioning factors were prepared, such as slope, aspect, altitude, topographic wetness index (TWI), stream power index (SPI), sediment transport index (STI), plan curvature, profile curvature, lithology, distance to faults, distance to rivers, distance to roads, land use, normalized difference vegetation index (NDVI), and rainfall. Relief-F with the 10-fold cross-validation method was applied to quantify the predictive ability of the conditioning factors and for feature selection. Using the JDT and its three ensemble techniques, a total of four landslide susceptibility models were constructed. Finally, the overall performance of the resulting models was assessed and compared using area under the receiver operating characteristic (ROC) curve (AUC) and statistical indexes. The result showed that all landslide models have high performance (AUC > 0.8). However, the JDT with the Rotation Forest model presents the highest prediction capability (AUC = 0.855), followed by the JD...

Hong, H, Pradhan, B, Sameen, MI, Kalantar, B, Zhu, A & Chen, W 2018, 'Improving the accuracy of landslide susceptibility model using a novel region-partitioning approach', Landslides, vol. 15, no. 4, pp. 753-772.
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© 2017, Springer-Verlag GmbH Germany. Landslide is a natural disaster that threatens human lives and properties worldwide. Numerous have been conducted on landslide susceptibility mapping (LSM), in which each has attempted to improve the accuracy of final outputs. This study presents a novel region-partitioning approach for LSM to understand the effects of partitioning a focused region into smaller areas on the prediction accuracy of common regression models. Results showed that the partitioning of the study area into two regions using the proposed method improved the prediction rate from 0.77 to 0.85 when support vector machine was used, and from 0.87 to 0.88 when logistic regression model was utilized. The spatial agreements of the models were also improved after partitioning the area into two regions based on Shannon entropy equations. Our comparative study indicated that the proposed method outperformed the geographically weighted regression model that considered the spatial variations in landslide samples. Overall, the main advantages of the proposed method are improved accuracy and the reduction of the effects of spatial variations exhibited in landslide-conditioning factors.

Ho-Pham, LT, Ho-Le, TP, Mai, LD, Do, TM, Doan, MC & Nguyen, TV 2018, 'Sex-difference in bone architecture and bone fragility in Vietnamese', Scientific Reports, vol. 8, no. 1.
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AbstractThis study sought to define the sex-difference in trabecular and cortical bone parameters in Vietnamese individuals. The study involved 1404 women and 864 men aged between 20 and 86 years who were recruited from Ho Chi Minh City, Vietnam. Trabecular and cortical volumetric BMD were measured at the proximal tibia and proximal radius at 4%, 38%, and 66% points, using a peripheral quantitative computed tomography XCT2000 (Stratec, Germany). Polar strength strain index was estimated from cortical bone parameters. Changes in bone parameters were assessed by the multiple linear regression model. Among individuals aged 20–39 years, women had significantly lower peak trabecular BMD at both the radius (40%) and tibia (16%) than men, but the age-related reduction in trabecular BMD were similar between two sexes. For cortical BMD, peak values in women and men were comparable, but the age-related diminution was greater in women than men. At any age, polar strength strain index in women was lower than men, and the difference was mainly attributable to cortical bone area and total bone mass. We conclude that in the elderly, sex-related difference in trabecular BMD is originated during growth, but sex-related difference in cortical BMD is determined by differential age-related bone loss.

Hoque, MA-A, Phinn, S, Roelfsema, C & Childs, I 2018, 'Assessing tropical cyclone risks using geospatial techniques', Applied Geography, vol. 98, pp. 22-33.
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Hoque, MA-A, Phinn, S, Roelfsema, C & Childs, I 2018, 'Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques', International Journal of Digital Earth, vol. 11, no. 3, pp. 246-263.
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Hossain, MA, Pota, HR, Hossain, MJ & Haruni, AMO 2018, 'Active power management in a low-voltage islanded microgrid', International Journal of Electrical Power & Energy Systems, vol. 98, pp. 36-47.
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Hossain, MJ, Rafi, FHM, Town, G & Lu, J 2018, 'Multifunctional Three-Phase Four-Leg PV-SVSI With Dynamic Capacity Distribution Method', IEEE Transactions on Industrial Informatics, vol. 14, no. 6, pp. 2507-2520.
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Hossain, N, Zaini, J, Jalil, R & Mahlia, TMI 2018, 'The Efficacy of the Period of Saccharification on Oil Palm (Elaeis guineensis) Trunk Sap Hydrolysis', International Journal of Technology, vol. 9, no. 4, pp. 652-652.
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© IJTech 2018. This study investigates the enzymatic hydrolysis rate of Oil Palm (Elaeis guineensis) Trunk (OPT) sap in terms of the length of saccharification process with the aim to elevate sugar production. Emphasis was placed on the reaction time and addition of supplements such epsom salt (MgSO4) and alanine amino acid (C3H7NO2) to accelerate the efficiency of Saccharomyces cerevisiae containing the enzyme invertase. A whole oil palm trunk was divided into four different sections, upper, middle-1, middle-2 and bottom with separate experiments over 10 days enzymatic reaction period. The highest saccharification rate was shown as 13.47% on the tenth day. This result indicates that the increase in the saccharification rate was positively correlated with the length of hydrolysis. Moreover, the sample with nutrients achieved the highest sugar output, 17.91% on the fourth day of hydrolysis which was 4.44% higher than the hydrolysis rate of the sample without nutrients. In the presence of complex OPT sugars, together with other essential elements, epsom salt and alanine amino acid, S.cerevisiae achieved a higher hydrolysis metabolism to simple sugars as the cells strived to produce energy and regenerated the invertase. Moreover, the upper part of the OPT rendered the highest potential for sugar production with levels of 21.2% with supplements and 15.6% without. From this experimental analysis, a conventional saccharification method was optimized through the addition of nutrients and a prolonged (10 days) hydrolysis process which yielded an increase in sugar production.

Hosseinzadeh, A, Najafpoor, AA, Jafari, AJ, Jazani, RK, Baziar, M, Bargozin, H & Piranloo, FG 2018, 'Application of response surface methodology and artificial neural network modeling to assess non-thermal plasma efficiency in simultaneous removal of BTEX from waste gases: Effect of operating parameters and prediction performance', Process Safety and Environmental Protection, vol. 119, pp. 261-270.
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Hou, Z, Wang, Y, Sui, Y, Gu, J, Zhao, T & Zhou, X 2018, 'Managing high-performance computing applications as an on-demand service on federated clouds', Computers & Electrical Engineering, vol. 67, pp. 579-595.
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© 2018 Elsevier Ltd There are several challenges (e.g., imbalance between supply and demand of hardware resources and software licenses, and usability) under modern High-Performance Computing (HPC) environment. As a means of providing an on-demand service for end users, we propose a Software-as-a-Service (SaaS) approach for managing commercial HPC applications as a Web-based service deployed on top of federated clouds. Some inter-trusted private or public clouds are federated to create a unified service platform with a large amount of hardware resources. In addition, an on-demand, pay-per-use model for Web-service-enabled HPC applications is proposed. Further, we provide an economic analysis of the proposed approach from the perspective of end users, cloud service providers, and Independent Software Vendors (ISVs). We conduct a simulation using two HPC application services on three federated clouds. A combined Quality of Service (QoS) and economic evaluation demonstrates a better effect of the proposed approach comparing with existing HPC platforms.

Hou, ZJ, Yang, Y, Chiu, L, Zhu, X & Xue, Q 2018, 'Wideband Millimeter-Wave On-Chip Quadrature Coupler With Improved In-Band Flatness in 0.13-<inline-formula> <tex-math notation='LaTeX'>$\mu$ </tex-math> </inline-formula>m SiGe Technology', IEEE Electron Device Letters, vol. 39, no. 5, pp. 652-655.
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© 1980-2012 IEEE. This letter proposes a compact and broadband quadrature coupler with a center frequency of 55 GHz, which consists of a 90° broadside coupled-line to support the differential signal propagation and two T-type L-C networks to support the common signal propagation. To analyze the proposed coupler, an equivalent circuit model is provided for estimation of the distributed and lumped component values. The measured results of the proposed on-chip quadrature coupler show that the return loss and isolation are greater than 20 dB with a bandwidth of 105%, while the insertion loss is about -0.85 dB. The magnitude imbalances are less than 1 dB within the bandwidth of 56% and the phase differences are with ±1° errors within the bandwidth of 96.9%. The chip size, excluding the test pads, is only 0.31 × 0.22 mm2.

Hou, ZJ, Yang, Y, Chiu, L, Zhu, X, Dutkiewicz, E, Vardaxoglou, JC & Xue, Q 2018, 'A W-Band Balanced Power Amplifier Using Broadside Coupled Strip-Line Coupler in SiGe BiCMOS 0.13-<inline-formula> <tex-math notation='LaTeX'>$\mu\text{m}$ </tex-math> </inline-formula> Technology', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 7, pp. 2139-2150.
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© 2004-2012 IEEE. Load-variation insensitivity, for impedance matching between power amplifiers (PAs) and transmitting antennas, contributes to challenging the design of millimeter-wave wireless systems. In this paper, a W -band two-way balanced PA based on a compact quadrature coupler with a broadside coupled strip-line (BCSL) as the core is presented to enhance the load-variation insensitivity and stability. The proposed coupler is truly broadband with low amplitude and phase imbalance. The proposed W -band balanced PA achieves higher power-added efficiency (PAE) and unsaturated output power {P} -{\mathrm{ sat}} over wide frequency bandwidth. The W -band balanced PA is implemented in a 0.13- \mu \text{m} SiGe BiCMOS process and achieves a measured {P} -{\mathrm{ sat}} of 16.3 dBm and a peak PAE of 14.1% at 100 GHz (with 1.6-V power supply). The measured {P} -{\mathrm{ sat}} with 1-dB bandwidth is from 91 to 102 GHz. The measured results present the feasibility of the compact quadrature coupler. The total chip surface area (with pads) is 0.64 mm2, where the size of the proposed quadrature coupler area is only 0.04 mm2.

Hou, ZJ, Yang, Y, Zhu, X, Li, YC, Dutkiewicz, E & Xue, Q 2018, 'A Compact and Low-Loss Bandpass Filter Using Self-Coupled Folded-Line Resonator With Capacitive Feeding Technique', IEEE Electron Device Letters, vol. 39, no. 10, pp. 1-1.
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© 1980-2012 IEEE. This letter proposes a compact and low-loss on-chip bandpass filter (BPF) design in (Bi)-CMOS technology. The proposed BPF consists of a self-coupled folded-line resonator and a pair of metal-insulator-metal capacitors. The proposed resonator has a property of flexible self-resonant frequency to form a transmission zero, which is analyzed in detail by a simplified LC equivalent circuit. Moreover, the parametric studies of the feeding capacitance for the proposed BPF design have been performed to demonstrate the tenability of the resonant frequency. For verification, the proposed BPF is fabricated in a standard 0.13-μ m (Bi)-CMOS technology. The measured results show that the proposed BPF has a notch with 25.4-dB suppression at 65 GHz and an insertion loss of 1.66 dB in the passband. The chip size of the device, excluding the test pads, is only 0.009 mm2 (0.11 × 0.086 mm2).

How, HG, Masjuki, HH, Kalam, MA & Teoh, YH 2018, 'Influence of injection timing and split injection strategies on performance, emissions, and combustion characteristics of diesel engine fueled with biodiesel blended fuels', Fuel, vol. 213, pp. 106-114.
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How, HG, Masjuki, HH, Kalam, MA, Teoh, YH & Chuah, HG 2018, 'Effect of Calophyllum Inophyllum biodiesel-diesel blends on combustion, performance, exhaust particulate matter and gaseous emissions in a multi-cylinder diesel engine', Fuel, vol. 227, pp. 154-164.
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Hu, C, Lu, J, Liu, X & Zhang, G 2018, 'Robust vehicle routing problem with hard time windows under demand and travel time uncertainty', Computers & Operations Research, vol. 94, pp. 139-153.
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© 2018 Elsevier Ltd Due to an increase in customer-oriented service strategies designed to meet more complex and exacting customer requirements, meeting a scheduled time window has become an important part of designing vehicle routes for logistics activities. However, practically, the uncertainty in travel times and customer demand often means vehicles miss these time windows, increasing service costs and decreasing customer satisfaction. In an effort to find a solution that meets the needs of real-world logistics, we examine the vehicle routing problem with hard time windows under demand and travel time uncertainty. To address the problem, we build a robust optimization model based on novel route-dependent uncertainty sets. However, due to the complex nature of the problem, the robust model is only able to tackle small-sized instances using standard solvers. Therefore, to tackle large instances, we design a two-stage algorithm based on a modified adaptive variable neighborhood search heuristic. The first stage of the algorithm minimizes the total number of vehicle routes, while the second stage minimizes the total travel distance. Extensive computational experiments are conducted with modified versions of Solomon's benchmark instances. The numerical results show that the proposed two-stage algorithm is able to find optimal solutions for small-sized instances and good-quality robust solutions for large-sized instances with little increase to the total travel distance and/or the number of vehicles used. A detailed analysis of the results also reveals several managerial insights for decision-makers in the logistics industry.

Hu, J, Zhang, Q, Lee, D-J & Ngo, HH 2018, 'Feasible use of microbial fuel cells for pollution treatment', Renewable Energy, vol. 129, pp. 824-829.
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© 2017 Elsevier Ltd. The microbial fuel cells (MFC) can directly transform chemical energy in feed substance to electricity by anodic aspiration pathways. This mini review provides an order-of-magnitude argument that MFC has much lower catalyst density at electrode surface and much higher diffusional resistance for substrates than the chemical fuel cell, the former should not be used as an energy generation unit; rather, it should be applied in low power density level applications such as biofilm wastewater treatment. The literature studies using MFC for pollution treatment are discussed.

Hu, L, Chen, Q, Zhao, H, Jian, S, Cao, L & Cao, J 2018, 'Neural Cross-Session Filtering: Next-Item Prediction Under Intra- and Inter-Session Context', IEEE Intelligent Systems, vol. 33, no. 6, pp. 57-67.
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© 2018 IEEE. Classic recommender systems (RSs) often repeatedly recommend similar items to user historical profiles or recent purchases. For this, session-based RSs (SBRSs) are extensively studied in recent years. Current SBRSs often assume a rigid-order sequence, which does not fit in many real-world cases. In fact, the next-item recommendation depends on not only current session context but also historical sessions which are often neglected by current SBRSs. Accordingly, an SBRS over relaxed-order sequences with both intra- and inter-context is more pragmatic. Inspired by the successful experience in modern language modeling, we design an efficient neural architecture to model both intra- and inter-context for next item prediction.

Hu, Y, Wang, XC, Ngo, HH, Sun, Q & Yang, Y 2018, 'Anaerobic dynamic membrane bioreactor (AnDMBR) for wastewater treatment: A review', Bioresource Technology, vol. 247, pp. 1107-1118.
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© 2017 Elsevier Ltd Recently, an increasing level of attention has focused on the emerging technology of anaerobic dynamic membrane bioreactors (AnDMBRs), owing to its merits such as low membrane module cost, easy control of membrane fouling, low energy consumption and sludge production, as well as biogas production. As research on AnDMBRs is still in the nascent stage, an introduction of bioreactor configurations, dynamic membrane (DM) module, and DM layer formation and cleaning is firstly presented. The process performance of the AnDMBR for wastewater treatment is then reviewed with regard to pollutant removal, DM filterability, biogas production, and potential advantages over the conventional anaerobic membrane bioreactor (AnMBR). In addition, the important parameters affecting process performance are briefly discussed. Lastly, the challenges encountered and perspectives regarding the future development of the AnDMBR process to promote its practical applications are presented.

Huang Weidong, Li Jane & Alem Leila 2018, 'Towards Preventative Healthcare: A Review of Wearable and Mobile Applications', Stud Health Technol Inform, vol. 251, pp. 11-14.
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Wearable and mobile devices are now commonly used in our daily activities, giving users instant access to various information. One the one hand, wearable and mobile technologies are developing at a fast rate and have been increasingly ubiquitous. On the other hand, the potential of their application in health is yet to be fully explored. This paper attempts to sketch an overview of wearable and mobile applications in the healthcare domain. We first review how various wearable and mobile applications are being used to monitor and manage health conditions. Then how connections between physiological factors and psychological factors can help with disease prevention is presented. Finally, challenges and future directions for further developments of these emerging technologies in health are discussed.

Huang, J, Duan, Q, Guo, S, Yan, Y & Yu, S 2018, 'Converged Network-Cloud Service Composition with End-to-End Performance Guarantee', IEEE Transactions on Cloud Computing, vol. 6, no. 2, pp. 545-557.
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The crucial role of networking in cloud computing calls for federated management of both computing and networking resources for end-to-end service provisioning. Application of the Service-Oriented Architecture (SOA) in both cloud computing and networking enables a convergence of network and cloud service provisioning. One of the key challenges to high performance converged network-cloud service provisioning lies in composition of network and cloud services with end-to-end performance guarantee. In this paper, we propose a QoS-aware service composition approach to tackling this challenging issue. We first present a system model for network-cloud service composition and formulate the service composition problem as a variant of Multi-Constrained Optimal Path (MCOP) problem. We then propose an approximation algorithm to solve the problem and give theoretical analysis on properties of the algorithm to show its effectiveness and efficiency for QoS-aware network-cloud service composition. Performance of the proposed algorithm is evaluated through extensive experiments and the obtained results indicate that the proposed method achieves better performance in service composition than the best current MCOP approaches.

Huang, L, Li, M, Ngo, HH, Guo, W, Xu, W, Du, B, Wei, Q & Wei, D 2018, 'Spectroscopic characteristics of dissolved organic matter from aquaculture wastewater and its interaction mechanism to chlorinated phenol compound', Journal of Molecular Liquids, vol. 263, pp. 422-427.
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© 2017 In present study, the characteristics of dissolved organic matter (DOM) from aquaculture wastewater and its interaction to 4-chlorophenol (4-CP) was evaluated via a spectroscopic approach. According to EEM-PARAFAC analysis, two components were derived from the interaction samples between DOM and 4-CP, including humic-like and fulvic-like substances for component 1 and protein-like substances for component 2, respectively. The fluorescence intensity scores of two PARAFAC-derived components decreased with increasing 4-CP concentration. Synchronous fluorescence coupled to two-dimensional correlation spectroscopy (2D-COS) implied that DOM fractions quenched different degrees and occurred in the order of fulvic-like and humic-like fractions > protein-like fraction. Moreover, the quenching mechanisms were mainly caused by static quenching process. It was also found from Fourier transform infrared spectroscopy that the main functional groups for interaction between 4-CP and DOM were O–H stretching and C[dbnd]O stretching vibration. The obtained results provided a spectroscopic approach for characterizing the interaction between organic pollutant and DOM from aquaculture wastewater.

Huang, L, Li, M, Si, G, Wei, J, Ngo, HH, Guo, W, Xu, W, Du, B, Wei, Q & Wei, D 2018, 'Assessment of microbial products in the biosorption process of Cu(II) onto aerobic granular sludge: Extracellular polymeric substances contribution and soluble microbial products release', Journal of Colloid and Interface Science, vol. 527, pp. 87-94.
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© 2018 In the present study, the responses of microbial products in the biosorption process of Cu(II) onto aerobic granular sludge were evaluated by using batch and spectroscopic approaches. Batch experimental data showed that extracellular polymeric substances (EPSs) contributed to Cu(II) removal from an aqueous solution, especially when treating low metal concentrations, whereas soluble microbial products (SMPs) were released under the metal stress during biosorption process. A three-dimensional excitation-emission matrix (3D-EEM) identified four main fluorescence peaks in the EPS, i.e., tryptophan protein-like, aromatic protein-like, humic-like and fulvic acid-like substances, and their fluorescence intensities decreased gradually in the presence of Cu(II) during the sorption process. Particularly, tryptophan protein-like substances quenched the Cu(II) binding to a much higher extent through a static quenching process with less than one class of binding sites. According to the synchronous fluorescence spectra, the whole fluorescence intensity of released SMP samples expressed an increased trend with different degrees along with contact time. Two-dimensional correlation spectroscopy (2D-COS) suggested that the fulvic-like fluorescence fraction might be more susceptible to metal exposure than other fractions. The result of molecular weight distribution demonstrated that the SMPs released from the biosorption process differed significantly according to contact time. The result obtained could provide new insights into the responses of microbial products from aerobic granular sludge with heavy metal treatment.

Huang, W, Alem, L, Tecchia, F & Duh, HB-L 2018, 'Augmented 3D hands: a gesture-based mixed reality system for distributed collaboration', Journal on Multimodal User Interfaces, vol. 12, no. 2, pp. 77-89.
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Huang, X, Zhang, J, Wu, Q, Fan, L & Yuan, C 2018, 'A Coarse-to-Fine Algorithm for Matching and Registration in 3D Cross-Source Point Clouds', IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 10, pp. 2965-2977.
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© 1991-2012 IEEE. We propose an efficient method to deal with the matching and registration problem found in cross-source point clouds captured by different types of sensors. This task is especially challenging due to the presence of density variation, scale difference, a large proportion of noise and outliers, missing data, and viewpoint variation. The proposed method has two stages: in the coarse matching stage, we use the ensemble of shape functions descriptor to select potential K regions from the candidate point clouds for the target. In the fine stage, we propose a scale embedded generative Gaussian mixture models registration method to refine the results from the coarse matching stage. Following the fine stage, both the best region and accurate camera pose relationships between the candidates and target are found. We conduct experiments in which we apply the method to two applications: one is 3D object detection and localization in street-view outdoor (LiDAR/VSFM) cross-source point clouds and the other is 3D scene matching and registration in indoor (KinectFusion/VSFM) cross-source point clouds. The experiment results show that the proposed method performs well when compared with the existing methods. It also shows that the proposed method is robust under various sensing techniques, such as LiDAR, Kinect, and RGB camera.

Huang, Y, Cao, L, Zhang, J, Pan, L & Liu, Y 2018, 'Exploring Feature Coupling and Model Coupling for Image Source Identification', IEEE Transactions on Information Forensics and Security, vol. 13, no. 12, pp. 3108-3121.
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© 2005-2012 IEEE. Recently, there has been great interest in feature-based image source identification. Previous statistical learning-based methods usually regarded the identification process as a classification problem. They assumed the dependence of features and the dependence of models. However, the two assumptions are usually problematic because of the genuine coupling of features and models. To address the issues, in this paper, we propose a novel image source identification scheme. For the feature coupling, a coupled feature representation is adopted to analyze the coupled interaction among features. The coupling relations among features and their powers are measured with Pearson's correlations and integrated in a Taylor-like expansion manner. Regarding model coupling, a new coupled probability representation is developed. The model coupling relationships are characterized with conditional probabilities induced by the confusion matrix and then combined with the law of total probability. The experiments carried out on the Dresden image collection confirm the effectiveness of the proposed scheme. Via mining the feature coupling and model coupling, the identification accuracy can be significantly improved.

Huang, Y, Ng, ECY, Zhou, JL, Surawski, NC, Chan, EFC & Hong, G 2018, 'Eco-driving technology for sustainable road transport: A review', Renewable and Sustainable Energy Reviews, vol. 93, pp. 596-609.
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© 2018 Elsevier Ltd Road transport consumes significant quantities of fossil fuel and accounts for a significant proportion of CO2 and pollutant emissions worldwide. The driver is a major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reviews the major factors, research methods and implementation of eco-driving technology. The major factors of eco-driving are acceleration/deceleration, driving speed, route choice and idling. Eco-driving training programs and in-vehicle feedback devices are commonly used to implement eco-driving skills. After training or using in-vehicle devices, immediate and significant reductions in fuel consumption and CO2 emissions have been observed with slightly increased travel time. However, the impacts of both methods attenuate over time due to the ingrained driving habits developed over the years. These findings imply the necessity of developing quantitative eco-driving patterns that could be integrated into vehicle hardware so as to generate more constant and uniform improvements, as well as developing more effective and lasting training programs and in-vehicle devices. Current eco-driving studies mainly focus on the fuel savings and CO2 reduction of individual vehicles, but ignore the pollutant emissions and the impacts at network levels. Finally, the challenges and future research directions of eco-driving technology are elaborated.

Huang, Y, Organ, B, Zhou, JL, Surawski, NC, Hong, G, Chan, EFC & Yam, YS 2018, 'Emission measurement of diesel vehicles in Hong Kong through on-road remote sensing: Performance review and identification of high-emitters', Environmental Pollution, vol. 237, pp. 133-142.
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© 2018 Elsevier Ltd A two-year remote sensing measurement program was carried out in Hong Kong to obtain a large dataset of on-road diesel vehicle emissions. Analysis was performed to evaluate the effect of vehicle manufacture year (1949–2015) and engine size (0.4–20 L) on the emission rates and high-emitters. The results showed that CO emission rates of larger engine size vehicles were higher than those of small vehicles during the study period, while HC and NO were higher before manufacture year 2006 and then became similar levels between manufacture years 2006 and 2015. CO, HC and NO of all vehicles showed an unexpectedly increasing trend during 1998–2004, in particular ≥6001 cc vehicles. However, they all decreased steadily in the last decade (2005–2015), except for NO of ≥6001 cc vehicles during 2013–2015. The distributions of CO and HC emission rates were highly skewed as the dirtiest 10% vehicles emitted much higher emissions than all the other vehicles. Moreover, this skewness became more significant for larger engine size or newer vehicles. The results indicated that remote sensing technology would be very effective to screen the CO and HC high-emitters and thus control the on-road vehicle emissions, but less effective for controlling NO emissions. No clear correlation was observed between the manufacture year and percentage of high-emitters for ≤3000 cc vehicles. However, the percentage of high-emitters decreased with newer manufacture year for larger vehicles. In addition, high-emitters of different pollutants were relatively independent, in particular NO emissions, indicating that high-emitter screening criteria should be defined on a CO-or-HC-or-NO basis, rather than a CO-and-HC-and-NO basis.

Huang, Y, Organ, B, Zhou, JL, Surawski, NC, Hong, G, Chan, EFC & Yam, YS 2018, 'Remote sensing of on-road vehicle emissions: Mechanism, applications and a case study from Hong Kong', Atmospheric Environment, vol. 182, pp. 58-74.
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© 2018 Elsevier Ltd Vehicle emissions are a major contributor to air pollution in cities and have serious health impacts to their inhabitants. On-road remote sensing is an effective and economic tool to monitor and control vehicle emissions. In this review, the mechanism, accuracy, advantages and limitations of remote sensing were introduced. Then the applications and major findings of remote sensing were critically reviewed. It was revealed that the emission distribution of on-road vehicles was highly skewed so that the dirtiest 10% vehicles accounted for over half of the total fleet emissions. Such findings highlighted the importance and effectiveness of using remote sensing for in situ identification of high-emitting vehicles for further inspection and maintenance programs. However, the accuracy and number of vehicles affected by screening programs were greatly dependent on the screening criteria. Remote sensing studies showed that the emissions of gasoline and diesel vehicles were significantly reduced in recent years, with the exception of NOx emissions of diesel vehicles in spite of greatly tightened automotive emission regulations. Thirdly, the experience and issues of using remote sensing for identifying high-emitting vehicles in Hong Kong (where remote sensing is a legislative instrument for enforcement purposes) were reported. That was followed by the first time ever identification and discussion of the issue of frequent false detection of diesel high-emitters using remote sensing. Finally, the challenges and future research directions of on-road remote sensing were elaborated.

Huang, Y, Yam, YS, Lee, CKC, Organ, B, Zhou, JL, Surawski, NC, Chan, EFC & Hong, G 2018, 'Tackling nitric oxide emissions from dominant diesel vehicle models using on-road remote sensing technology', Environmental Pollution, vol. 243, no. Pt B, pp. 1177-1185.
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© 2018 Elsevier Ltd Remote sensing provides a rapid detection of vehicle emissions under real driving condition. Remote sensing studies showed that diesel nitrogen oxides emissions changed little or were even increasing in recent years despite the tightened emission standards. To more accurately and fairly evaluate the emission trends, it is hypothesized that analysis should be detailed for individual vehicle models as each model adopted different emissions control technologies and retrofitted the engine/vehicle at different time. Therefore, this study was aimed to investigate the recent nitric oxide (NO) emission trends of the dominant diesel vehicle models using a large remote sensing dataset collected in Hong Kong. The results showed that the diesel vehicle fleet was dominated by only seven models, accounting for 78% of the total remote sensing records. Although each model had different emission levels and trends, generally all the dominant models showed a steady decrease or stable level in the fuel based NO emission factors (g/kg fuel) over the period studied except for BaM1 and BdM2. A significant increase was observed for the BaM1 2.49 L and early 2.98 L models during 2005–2011, which we attribute to the change in the diesel fuel injection technology. However, the overall mean NO emission factor of all the vehicles was stable during 1991–2006 and then decreased steadily during 2006–2016, in which the emission trends of individual models were averaged out and thus masked. Nevertheless, the latest small, medium and heavy diesel vehicles achieved similar NO emission factors due to the converging of operation windows of the engine and emission control devices. The findings suggested that the increasingly stringent European emission standards were not very effective in reducing the NO emissions of some diesel vehicle models in the real world. The European emission regulations were not very effective in reducing the NO emissions from some diesel vehicle...

Huber, S, Koenig, R & Tomamichel, M 2018, 'Jointly constrained semidefinite bilinear programming with an application to Dobrushin curves', IEEE Trans Inf Theory, vol. 56, no. 5, pp. 2934-2950.
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We propose a branch-and-bound algorithm for minimizing a bilinear functionalof the form \[ f(X,Y) = \mathrm{tr}((X\otimesY)Q)+\mathrm{tr}(AX)+\mathrm{tr}(BY) , \] of pairs of Hermitian matrices$(X,Y)$ restricted by joint semidefinite programming constraints. Thefunctional is parametrized by self-adjoint matrices $Q$, $A$ and $B$. Thisproblem generalizes that of a bilinear program, where $X$ and $Y$ belong topolyhedra. The algorithm converges to a global optimum and yields upper andlower bounds on its value in every step. Various problems in quantuminformation theory can be expressed in this form. As an example application, wecompute Dobrushin curves of quantum channels, giving upper bounds on classicalcoding with energy constraints.

Huitinga, I & Webster, MJ 2018, 'Preface', pp. ix-ix.
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Huo, S, Liu, M, Wu, L, Liu, M, Xu, M, Ni, W & Yan, Y-M 2018, 'Methanesulfonic acid-assisted synthesis of N/S co-doped hierarchically porous carbon for high performance supercapacitors', Journal of Power Sources, vol. 387, pp. 81-90.
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Husin, H, Solo, BB, Ibrahim, IM, Chyuan, OH & Roslan, A 2018, 'Weight loss effect and potentiodynamic polarization response of 1-butyl-3-methylimidazolium chloride ionic liquid in highly acidic medium', Journal of Engineering Science and Technology, vol. 13, no. 4, pp. 1005-1015.
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Ionic liquids are increasingly being used as corrosion inhibitors when oil and gas industries started to give focus on sustainability and green impact in their operations. In this study, 1-butyl-3-methylimidazolium chloride ionic liquid in 2M HCl medium has been investigated on mild steel, stainless steel and aluminium bars by using weight loss technique and potentiodynamic polarization measurement. Results showed that 1-butyl-3-methylimidazolium chloride is able to reduce the weight loss of aluminium metal under acidic corrosive surrounding up to 11% compared to that of without the presence of 1-butyl-3-methylimidazolium chloride. Based on potentiodynamic polarization response, percentage of corrosion inhibition efficiency is found to be up to 99.3%. In summary, 1-butyl-3-methylimidazolium chloride is highly potential to act as an anti-corrosion agent, even in a very low concentration.

Hussain, W, Hussain, FK, Hussain, O, Bagia, R & Chang, E 2018, 'Risk-based framework for SLA violation abatement from the cloud service provider’s perspective', The Computer Journal, vol. 61, no. 9, pp. 1306-1322.
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© The British Computer Society 2018. The constant increase in the growth of the cloud market creates new challenges for cloud service providers. One such challenge is the need to avoid possible service level agreement (SLA) violations and their consequences through good SLA management. Researchers have proposed various frameworks and have made significant advances in managing SLAs from the perspective of both cloud users and providers. However, none of these approaches guides the service provider on the necessary steps to take for SLA violation abatement; that is, the prediction of possible SLA violations, the process to follow when the system identifies the threat of SLA violation, and the recommended action to take to avoid SLA violation. In this paper, we approach this process of SLA violation detection and abatement from a risk management perspective. We propose a Risk Management-based Framework for SLA violation abatement (RMF-SLA) following the formation of an SLA which comprises SLA monitoring, violation prediction and decision recommendation. Through experiments, we validate and demonstrate the suitability of the proposed framework for assisting cloud providers to minimize possible service violations and penalties.

Hussain, W, Hussain, FK, Saberi, M, Hussain, OK & Chang, E 2018, 'Comparing time series with machine learning-based prediction approaches for violation management in cloud SLAs', Future Generation Computer Systems, vol. 89, pp. 464-477.
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© 2018 In cloud computing, service level agreements (SLAs) are legal agreements between a service provider and consumer that contain a list of obligations and commitments which need to be satisfied by both parties during the transaction. From a service provider's perspective, a violation of such a commitment leads to penalties in terms of money and reputation and thus has to be effectively managed. In the literature, this problem has been studied under the domain of cloud service management. One aspect required to manage cloud services after the formation of SLAs is to predict the future Quality of Service (QoS) of cloud parameters to ascertain if they lead to violations. Various approaches in the literature perform this task using different prediction approaches however none of them study the accuracy of each. However, it is important to do this as the results of each prediction approach vary according to the pattern of the input data and selecting an incorrect choice of a prediction algorithm could lead to service violation and penalties. In this paper, we test and report the accuracy of time series and machine learning-based prediction approaches. In each category, we test many different techniques and rank them according to their order of accuracy in predicting future QoS. Our analysis helps the cloud service provider to choose an appropriate prediction approach (whether time series or machine learning based) and further to utilize the best method depending on input data patterns to obtain an accurate prediction result and better manage their SLAs to avoid violation penalties.

Hussaini, SKK, Indraratna, B & Vinod, JS 2018, 'A critical review of the performance of geosynthetic-reinforced railroad ballast', Geotechnical Engineering, vol. 49, no. 4, pp. 31-41.
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In the recent times, railway organizations across the world have resorted to the use of geosynthetics as a low-cost solution to stabilize ballast. In this view, extensive studies have been conducted worldwide to assess the performance of geosynthetic-reinforced ballast under various loading conditions. This paper evaluates the various benefits the rail industry could attain because of the geosynthetic reinforcement. A review of literature reveals that geogrid arrests the lateral spreading of ballast, reduces the extent of permanent vertical settlement and minimizes the particle breakage. The geogrid was also found to reduce the extent of volumetric compressions in ballast. The overall performance improvement due to geogrid was observed to be a function of the interface efficiency factor (φ). Moreover, studies also established the additional role of geogrids in reducing the differential track settlements and diminishing the stresses at the subgrade level. The geosynthetics were found to be more beneficial in case of tracks resting on soft subgrades. Furthermore, the benefits of geosynthetics in stabilizing ballast were found to be significantly higher when placed within the ballast. The optimum placement location of geosynthetics has been reported by several researchers to be about 200-250 mm below the sleeper soffit for a conventional ballast depth of 300-350 mm. A number of field investigations and track rehabilitation schemes also confirmed the role of geosynthetics/geogrids in stabilizing the tracks thereby helping in removing the stringent speed restrictions that were imposed earlier, and enhancing the time interval between maintenance operations.

Huynh, NV, Hoang, DT, Nguyen, DN, Dutkiewicz, E, Niyato, D & Wang, P 2018, 'Optimal and Low-Complexity Dynamic Spectrum Access for RF-Powered Ambient Backscatter System with Online Reinforcement Learning', IEEE TRANSACTIONS ON COMMUNICATIONS, vol. 67, no. 8, pp. 5736-5752.
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Ambient backscatter has been introduced with a wide range of applications forlow power wireless communications. In this article, we propose an optimal andlow-complexity dynamic spectrum access framework for RF-powered ambientbackscatter system. In this system, the secondary transmitter not only harvestsenergy from ambient signals (from incumbent users), but also backscatters thesesignals to its receiver for data transmission. Under the dynamics of theambient signals, we first adopt the Markov decision process (MDP) framework toobtain the optimal policy for the secondary transmitter, aiming to maximize thesystem throughput. However, the MDP-based optimization requires completeknowledge of environment parameters, e.g., the probability of a channel to beidle and the probability of a successful packet transmission, that may not bepractical to obtain. To cope with such incomplete knowledge of the environment,we develop a low-complexity online reinforcement learning algorithm that allowsthe secondary transmitter to 'learn' from its decisions and then attain theoptimal policy. Simulation results show that the proposed learning algorithmnot only efficiently deals with the dynamics of the environment, but alsoimproves the average throughput up to 50% and reduces the blocking probabilityand delay up to 80% compared with conventional methods.

Huynh, NV, Hoang, DT, Niyato, D, Wang, P & Kim, DI 2018, 'Optimal Time Scheduling for Wireless-Powered Backscatter Communication Networks', IEEE Wireless Communications Letters, vol. 7, no. 5, pp. 820-823.
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This letter introduces a novel wireless-powered backscatter communicationsystem which allows sensors to utilize RF signals transmitted from a dedicatedRF energy source to transmit data. In the proposed system, when the RF energysource transmits RF signals, the sensors are able to backscatter the RF signalsto transmit date to the gateway and/or harvest energy from the RF signals fortheir operations. By integrating backscattering and energy harvestingtechniques, we can optimize the network throughput of the system. Inparticular, we first formulate the time scheduling problem for the system, andthen propose an optimal solution using convex optimization to maximize theoverall network throughput. Numerical results show a significant throughputgain achieved by our proposed design over two other baseline schemes.

Idrees, MO & Pradhan, B 2018, 'Geostructural stability assessment of cave using rock surface discontinuity extracted from terrestrial laser scanning point cloud', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 3, pp. 534-544.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences The use of terrestrial laser scanning (TLS) in the caves has been growing drastically over the last decade. However, TLS application to cave stability assessment has not received much attention of researchers. This study attempted to utilize rock surface orientations obtained from TLS point cloud collected along cave passages to (1) investigate the influence of rock geostructure on cave passage development, and (2) assess cave stability by determining areas susceptible to different failure types. The TLS point cloud was divided into six parts (Entry hall, Chamber, Main hall, Shaft 1, Shaft 2 and Shaft 3), each representing different segments of the cave passages. Furthermore, the surface orientation information was extracted and grouped into surface discontinuity joint sets. The computed global mean and best–fit planes of the entire cave show that the outcrop dips 290° with a major north-south strike. But at individual level, the passages with dip angle between 26° and 80° are featured with dip direction of 75°–322°. Kinematic tests reveal the potential for various failure modes of rock slope. Our findings show that toppling is the dominant failure type accounting for high-risk rockfall in the cave, with probabilities of 75.26%, 43.07% and 24.82% in the Entry hall, Main hall and Shaft 2, respectively. Unlike Shaft 2 characterized by high risk of the three failure types (32.49%, 24.82% and 50%), the chamber and Shaft 3 passages are not suffering from slope failure. The results also show that the characteristics of rock geostructure considerably influence the development of the cave passages, and four sections of the cave are susceptible to different slope failure types, at varying degrees of risk.

Imani, MH, Ghadi, MJ, Ghavidel, S & Li, L 2018, 'Demand Response Modeling in Microgrid Operation: a Review and Application for Incentive-Based and Time-Based Programs', Renewable and Sustainable Energy Reviews, vol. 94, pp. 486-499.
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© 2018 Elsevier Ltd During recent years, with the advent of restructuring in power systems as well as the increase of electricity demand and global fuel energy prices, challenges related to implementing demand response programs (DRPs) have gained remarkable attention of independent system operators (ISOs) and customers, aiming at the improvement of attributes of the load curve and reduction of energy consumption as well as benefiting customers. In this paper, different types of DRPs are modeled based on price elasticity of the demand and the concept of customer benefit. Besides, the impact of implementing DRPs on the operation of grid-connected microgrid (MG) is analyzed. Moreover, several scenarios are presented in order to model uncertainties interfering MG operations including failure of generation units and random outages of transmission lines and upstream line, error in load demand forecasting, uncertainty in production of renewable energies (wind and solar) based distributed generation units, and the possibility that customers do not respond to scheduled interruptions. Simulations are conducted for two principal categories of DRP including incentive-based programs and time-based programs on an 11-bus MG over a 24-h period and also a 14-bus MG over a period of 336 h (two weeks). Simulation results indicate the effects of DRPs on total operation costs, customer's benefit, and load curve as well as determining optimal use of energy resources in the MG operation. In this regard, prioritizing of DRPs on the MG operation is required.

Inan, DI, Beydoun, G & Opper, S 2018, 'Agent-Based Knowledge Analysis Framework in Disaster Management.', Inf. Syst. Frontiers, vol. 20, pp. 783-802.
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© 2017 Springer Science+Business Media, LLC Disaster Management (DM) is a complex set of interrelated activities. The activities are often knowledge-intensive and time sensitive. Timely sharing of the required knowledge is critical for DM. For recurring disasters (e.g. floods), developed countries tend to have dedicated document repositories of Disaster Management Plans (DISPLANs) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner, and sharing activities between plans, often requires significant domain knowledge and intimate understanding of the plans in the first place. This paper introduces an Agent-Based (AB) knowledge analysis method to convert DISPLANs into a collection of knowledge units that can be stored into a unified repository. The repository of DM actions then enables the mixing and matching of knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). We use the flood DISPLANs plans used by SES (State Emergency Service), an authoritative DM agency in New South Wales (NSW) State of Australia (hereinafter referred to as SES NSW) to illustrate and give a preliminary validation of the approach. It is illustrated by using displans along the flood-prone Murrumbidgee river in central NSW.

Inan, DI, Beydoun, G & Pradhan, B 2018, 'Developing a decision support system for Disaster Management: Case study of an Indonesia volcano eruption', International Journal of Disaster Risk Reduction, vol. 31, pp. 711-721.
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© 2018 Elsevier Ltd Disaster Management activities often focus on specific tasks (e.g. evacuation, logistic or coordination) and are confined to one specific DM phase (e.g. Preparedness or Response). New awareness about an external change, be it environmental or organisational, typically act as a trigger for such focussed activities. A variety of views or stakeholders are also involved in those activities, and their various concerns get often intertwined. This work advocates the use of a Decision Support System (DSS) that can be deployed as a single access point. Such a system requires a sufficient amount of representative knowledge, and facilities to avail the knowledge to the appropriate stakeholders in an appropriate form. With the multitude of stakeholders and their varying knowledge requirements, the system will need to present the knowledge differently according to the stakeholders needs in their decision making process. Such processes can vary, e.g. whether for policy making or for operational real time responses. This paper presents a hybrid of knowledge elicitation and retrieval mechanisms, some are top down and others are bottom up. The mechanisms make use of the Meta Object Facility (MOF) to structure and present the knowledge appropriately according to different interests and roles. A case study of the recent Mt. Agung volcano eruption in Bali Indonesia is successfully used to demonstrate the efficacy of the mechanisms proposed and the resultant DSS.

Indraratna, B, Baral, P, Rujikiatkamjorn, C & Perera, D 2018, 'Class A and C predictions for Ballina trial embankment with vertical drains using standard test data from industry and large diameter test specimens', Computers and Geotechnics, vol. 93, pp. 232-246.
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Indraratna, B, Ferreira, FB, Qi, Y & Ngo, TN 2018, 'Application of geoinclusions for sustainable rail infrastructure under increased axle loads and higher speeds', Innovative Infrastructure Solutions, vol. 3, no. 1, p. 69.
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Given the ongoing demand for faster trains for carrying heavier loads, conventional ballasted railroads require considerable upgrading in order to cope with the increasing traffic-induced stresses. During train operations, ballast deteriorates due to progressive breakage and fouling caused by the infiltration of fine particles from the surface or mud-pumping from the underneath layers (e.g. sub-ballast, sub-grade), which decreases the load bearing capacity, impedes drainage and increases the deformation of ballasted tracks. Suitable ground improvement techniques involving geosynthetics and resilient rubber sheets are commonly employed to enhance the stability and longevity of rail tracks. This keynote paper focuses mainly on research projects undertaken at the University of Wollongong to improve track performance by emphasising the main research outcomes and their practical implications. Results from laboratory tests, computational modelling and field trials have shown that track behaviour can be significantly improved by the use of geosynthetics, energy-absorbing rubber mats, rubber crumbs and infilled-recycled tyres. Full-scale monitoring of instrumented track sections supported by rail industry (ARTC) has been performed, and the obtained field data for in situ stresses and deformations could verify the track performance, apart from validating the numerical simulations. The research outcomes provide promising approaches that can be incorporated into current track design practices to cater for high-speed freight trains carrying heavier loads.

Indraratna, B, Israr, J & Li, M 2018, 'Inception of geohydraulic failures in granular soils – an experimental and theoretical treatment', Géotechnique, vol. 68, no. 3, pp. 233-248.
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This paper outlines an experimental investigation into seepage-induced failures in soils subjected to static and cyclic loading. Internally stable, marginal and unstable soils are characterised by heave, composite heave–piping and suffusion that develops immediately upon instability. In this study, the stable specimens exhibited heave at larger hydraulic gradients than the unstable specimens failing by suffusion at relatively smaller hydraulic gradients. Under no external load (i.e. self-weight only), the relative density (Rd) and particle size distribution (PSD) in tandem controlled the internal stability of soils, although the effective stress magnitude (σ′vt) also had a role to play under both static and cyclic loading conditions. Instability in soils was governed by specific combinations of their geo-hydro-mechanical characteristics such as PSD, Rd, stress reduction factor, critical hydraulic gradients and associated effective stress levels. These factors are combined to model the development and inception of instability, and the paper offers visual guides as a practical tool for practitioners. Each soil has a unique critical envelope related to its PSD and Rd, and a critical path with its inclination that depends on the hydro-mechanical conditions. The current results of internal erosion tests conducted by the authors plus those adopted from published literature are used to verify the proposed model.

Indraratna, B, Qi, Y & Heitor, A 2018, 'Evaluating the Properties of Mixtures of Steel Furnace Slag, Coal Wash, and Rubber Crumbs Used as Subballast', Journal of Materials in Civil Engineering, vol. 30, no. 1, pp. 04017251-04017251.
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Indraratna, B, Sun, Q, Heitor, A & Grant, J 2018, 'Performance of Rubber Tire-Confined Capping Layer under Cyclic Loading for Railroad Conditions', Journal of Materials in Civil Engineering, vol. 30, no. 3, pp. 06017021-06017021.
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Irga, PJ, Barker, K & Torpy, FR 2018, 'Conservation mycology in Australia and the potential role of citizen science', Conservation Biology, vol. 32, no. 5, pp. 1031-1037.
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AbstractFungi are undoubtedly important for ecosystem functioning; however, they have been omitted or given scant attention in most biodiversity policy documents, management plans, and formal conservation schedules throughout the world. This oversight may be due to a general lack of awareness in the scientific community and compounded by a scarcity of mycology‐associated curricula at the tertiary level and a lack of mycologists in research institutions. Although molecular techniques advance the systematic cataloging of fungi and facilitate insights into fungal communities, the scarcity of professional mycologists in the environmental sciences hampers conservation efforts. Conversely, citizen science initiatives are making significant contributions to the mycology discipline by increasing awareness and extending the scope of fungal surveys. Future research by professional and amateur mycologists into the distribution of fungi and their function in ecosystems will help identify wider and more effective conservation goals.

Irga, PJ, Pettit, TJ & Torpy, FR 2018, 'The phytoremediation of indoor air pollution: a review on the technology development from the potted plant through to functional green wall biofilters', Reviews in Environmental Science and Bio/Technology, vol. 17, no. 2, pp. 395-415.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. Poor indoor air quality is a health problem of escalating magnitude, as communities become increasingly urbanised and people’s behaviours change, lending to lives spent almost exclusively in indoor environments. The accumulation of, and continued exposure to, indoor air pollution has been shown to result in detrimental health outcomes. Particulate matter penetrating into the building, volatile organic compounds (VOCs) outgassing from synthetic materials and carbon dioxide from human respiration are the main contributors to these indoor air quality concerns. Whilst a range of physiochemical methods have been developed to remove contaminants from indoor air, all methods have high maintenance costs. Despite many years of study and substantial market demand, a well evidenced procedure for indoor air bioremediation for all applications is yet to be developed. This review presents the main aspects of using horticultural biotechnological tools for improving indoor air quality, and explores the history of the technology, from the humble potted plant through to active botanical biofiltration. Regarding the procedure of air purification by potted plants, many researchers and decades of work have confirmed that the plants remove CO2 through photosynthesis, degrade VOCs through the metabolic action of rhizospheric microbes, and can sequester particulate matter through a range of physical mechanisms. These benefits notwithstanding, there are practical barriers reducing the value of potted plants as standalone air cleaning devices. Recent technological advancements have led to the development of active botanical biofilters, or functional green walls, which are becoming increasingly efficient and have the potential for the functional mitigation of indoor air pollutant concentrations.

Ishac, K & Suzuki, K 2018, 'LifeChair: A Conductive Fabric Sensor-Based Smart Cushion for Actively Shaping Sitting Posture', Sensors, vol. 18, no. 7, pp. 2261-2261.
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The LifeChair is a smart cushion that provides vibrotactile feedback by actively sensing and classifying sitting postures to encourage upright posture and reduce slouching. The key component of the LifeChair is our novel conductive fabric pressure sensing array. Fabric sensors have been explored in the past, but a full sensing solution for embedded real world use has not been proposed. We have designed our system with commercial use in mind, and as a result, it has a high focus on manufacturability, cost-effectiveness and adaptiveness. We demonstrate the performance of our fabric sensing system by installing it into the LifeChair and comparing its posture detection accuracy with our previous study that implemented a conventional flexible printed PCB-sensing system. In this study, it is shown that the LifeChair can detect all 11 postures across 20 participants with an improved average accuracy of 98.1%, and it demonstrates significantly lower variance when interfacing with different users. We also conduct a performance study with 10 participants to evaluate the effectiveness of the LifeChair device in improving upright posture and reducing slouching. Our performance study demonstrates that the LifeChair is effective in encouraging users to sit upright with an increase of 68.1% in time spent seated upright when vibrotactile feedback is activated.

Islam, M, Mithulananthan, N & Hossain, MJ 2018, 'Dynamic Voltage Support by TL-PV Systems to Mitigate Short-Term Voltage Instability in Residential DN', IEEE Transactions on Power Systems, vol. 33, no. 4, pp. 4360-4370.
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Islam, MS, Saha, SC, Gemci, T, Yang, IA, Sauret, E & Gu, YT 2018, 'Polydisperse Microparticle Transport and Deposition to the Terminal Bronchioles in a Heterogeneous Vasculature Tree', Scientific Reports, vol. 8, no. 1.
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AbstractThe atmospheric particles from different sources, and the therapeutic particles from various drug delivery devices, exhibit a complex size distribution, and the particles are mostly polydisperse. The limited available in vitro, and the wide range of in silico models have improved understanding of the relationship between monodisperse particle deposition and therapeutic aerosol transport. However, comprehensive polydisperse transport and deposition (TD) data for the terminal airways is still unavailable. Therefore, to benefit future drug therapeutics, the present numerical model illustrates detailed polydisperse particle TD in the terminal bronchioles for the first time. Euler-Lagrange approach and Rosin-Rammler diameter distribution is used for polydisperse particles. The numerical results show higher deposition efficiency (DE) in the right lung. Specifically, the larger the particle diameter (dp > 5 μm), the higher the DE at the bifurcation area of the upper airways is, whereas for the smaller particle (dp < 5 μm), the DE is higher at the bifurcation wall. The overall deposition pattern shows a different deposition hot spot for different diameter particle. These comprehensive lobe-specific polydisperse particle deposition studies will increase understanding of actual inhalation for particle TD, which could potentially increase the efficiency of pharmaceutical aerosol delivery at the targeted position of the terminal airways.

Ismaiel, B, Abolhasan, M, Ni, W, Smith, DB, Franklin, DR & Jamalipour, A 2018, 'Analysis of Effective Capacity and Throughput of Polling-Based Device-To-Device Networks.', IEEE Trans. Veh. Technol., vol. 67, no. 9, pp. 8656-8666.
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© 1967-2012 IEEE. Next-generation wireless networks will give rise to heterogeneous networks by integrating multiple wireless access technologies to provide seamless mobility to mobile users with high-speed wireless connectivity. Device-to-device (D2D) communication has proven to be a promising technology that can increase the capacity and coverage of wireless networks. The D2D communication was first introduced in long-term evolution advanced (LTE-A) and has gained immense popularity for the offloading traffic using the licensed and unlicensed band. Challenges arise from resource allocation, provision of quality-of-service (QoS), and the quantification of capacity in an unlicensed band due to the distributed nature of Wi-Fi. In this paper, we propose an analytical performance model for the scalable MAC protocol (SC-MP) in which a resource allocation mechanism is based on the IEEE 802.11 point coordinated function to access the Wi-Fi channel for voice and video/multimedia traffic. In the SC-MP, D2D communication is applied to further offload the video/multimedia traffic. In particular, this paper establishes a three-state semi-Markovian model to derive a closed-form expression of effective capacity in terms of transmission rate and quality-of-service. Further, the SC-MP is analytically modeled using the four-state traditional Markov model to derive the saturation throughput. The analytical results are validated through simulations, hence, proving the appropriateness of the model.

Ismaiel, B, Abolhasan, M, Ni, W, Smith, DB, Franklin, DR, Dutkiewicz, E, Krunz, M & Jamalipour, A 2018, 'PCF-Based LTE Wi-Fi Aggregation for Coordinating and Offloading the Cellular Traffic to D2D Network.', IEEE Trans. Veh. Technol., vol. 67, no. 12, pp. 12193-12203.
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© 2018 IEEE. Device-to-device (D2D) communication is a promising technology towards 5G networks. D2D communication can offload traffic using licensed/unlicensed band by establishing a direct communication between two users without traversing the base station or core network. However, one of the major challenges of D2D communication is resource allocation and guaranteeing quality-of-service (QoS). In this paper, we establish an optimal queuing scheduling and resource allocation problem for three-tier heterogeneous network based on LTE Wi-Fi aggregation, to offload voice/multimedia traffic from licensed band to unlicensed band using scalable MAC protocol (SC-MP) under various static delay constraints. The access mechanism used for Wi-Fi in SC-MP is point coordination function, which further offloads the multimedia traffic using D2D communication in unlicensed band. Resource allocation and optimal joint queuing scheduling problems are formulated with diverse QoS guarantee between licensed and unlicensed band to minimize the bandwidth of licensed band. Furthermore, an iterative algorithm is proposed to express the nonconvex problem as a series of subproblems based on block coordinate descent and difference of two convex functions (D.C) program. We have simulated the proposed scheme using two scenarios: Voice traffic using licensed band and voice traffic using both licensed and unlicensed band, whereas multimedia traffic uses unlicensed band for both the scenarios. The simulation results show that both the schemes perform better than the existing scheme and scenario 2 outperforms scenario 1.

Israr, J & Indraratna, B 2018, 'Assessment of internal stability of filters under static and cyclic loading: An experimental and theoretical treatment', Australian Geomechanics Journal, vol. 53, no. 4, pp. 103-116.
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The occurrence of internal instability may significantly affect geo-mechanical characteristics of granular filters such as permeability and particle size distribution, consequently rendering them ineffective in retaining the protected base soils and thereby endangering the structural stability. This paper presents the results of 65 hydraulic tests performed on ten different granular soils compacted at varying relative densities between 0 and 100% and subjected to an upward hydraulic flow under both static and cyclic conditions. It was observed that the internal stability is a function of particle gradation and relative density in tandem, i.e. constriction size distribution, under static conditions. However, the agitation and pore pressure development under cyclic loading triggered excessively premature internal erosion in filters. Based on the analysis, new constriction-based criteria proposed for both static and cyclic conditions that showed remarkable accuracy in correctly assessing the potential of instability of filters compared to many existing criteria. Moreover, a new hydromechanical model is presented that could accurately capture the correct potential of instability of filters, thereby contributing toward increased confidence level for practical design of filters. Two practical design examples presented to demonstrate the implications of this research study in practice to conclude this paper.

Israr, J & Indraratna, B 2018, 'Mechanical response and pore pressure generation in granular filters subjected to uniaxial cyclic loading', Canadian Geotechnical Journal, vol. 55, no. 12, pp. 1756-1768.
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This paper presents results from a series of piping tests carried out on a selected range of granular filters under static and cyclic loading conditions. The mechanical response of filters subjected to cyclic loading could be characterized in three distinct phases; namely, (I) pre-shakedown, (II) post-shakedown, and (III) post-critical (i.e., the occurrence of internal erosion). All the permanent geomechanical changes such, as erosion, permeability variations, and axial strain developments, took place during phases I and III, while the specimen response remained purely elastic during phase II. The post-critical occurrence of erosion incurred significant settlement that may not be tolerable for high-speed railway substructures. The analysis revealed that a cyclic load would induce excess pore-water pressure, which, in corroboration with steady seepage forces and agitation due to dynamic loading, could then cause internal erosion of fines from the specimens. The resulting excess pore pressure is a direct function of the axial strain due to cyclic densification, as well as the loading frequency and reduction in permeability. A model based on strain energy is proposed to quantify the excess pore-water pressure, and subsequently validated using current and existing test results from published studies.

Ivanyos, G, Kulkarni, R, Qiao, Y, Santha, M & Sundaram, A 2018, 'On the complexity of trial and error for constraint satisfaction problems', Journal of Computer and System Sciences, vol. 92, pp. 48-64.
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© 2017 Elsevier Inc. In 2013 Bei, Chen and Zhang introduced a trial and error model of computing, and applied to some constraint satisfaction problems. In this model the input is hidden by an oracle which, for a candidate assignment, reveals some information about a violated constraint if the assignment is not satisfying. In this paper we initiate a systematic study of constraint satisfaction problems in the trial and error model, by adopting a formal framework for CSPs, and defining several types of revealing oracles. Our main contribution is to develop a transfer theorem for each type of the revealing oracle. To any hidden CSP with a specific type of revealing oracle, the transfer theorem associates another CSP in the normal setting, such that their complexities are polynomial-time equivalent. This in principle transfers the study of a large class of hidden CSPs to the study of normal CSPs. We apply the transfer theorems to get polynomial-time algorithms or hardness results for several families of concrete problems.

Ivanyos, G, Qiao, Y & Subrahmanyam, KV 2018, 'Constructive non-commutative rank computation is in deterministic polynomial time', computational complexity, vol. 27, no. 4, pp. 561-593.
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© 2018, Springer International Publishing AG, part of Springer Nature. We extend the techniques developed in Ivanyos et al. (Comput Complex 26(3):717–763, 2017) to obtain a deterministic polynomial-time algorithm for computing the non-commutative rank of linear spaces of matrices over any field. The key new idea that causes a reduction in the time complexity of the algorithm in Ivanyos et al. (2017) from exponential time to polynomial time is a reduction procedure that keeps the blow-up parameter small, and there are two methods to implement this idea: the first one is a greedy argument that removes certain rows and columns, and the second one is an efficient algorithmic version of a result of Derksen & Makam (Adv Math 310:44–63, 2017b), who were the first to observe that the blow-up parameter can be controlled. Both methods rely crucially on the regularity lemma from Ivanyos et al. (2017). In this note, we improve that lemma by removing a coprime condition there.

Jahed Armaghani, D, Faradonbeh, RS, Momeni, E, Fahimifar, A & Tahir, MM 2018, 'Performance prediction of tunnel boring machine through developing a gene expression programming equation', Engineering with Computers, vol. 34, no. 1, pp. 129-141.
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Jahed Armaghani, D, Hasanipanah, M, Mahdiyar, A, Abd Majid, MZ, Bakhshandeh Amnieh, H & Tahir, MMD 2018, 'Airblast prediction through a hybrid genetic algorithm-ANN model', Neural Computing and Applications, vol. 29, no. 9, pp. 619-629.
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Jahed Armaghani, D, Safari, V, Fahimifar, A, Mohd Amin, MF, Monjezi, M & Mohammadi, MA 2018, 'Uniaxial compressive strength prediction through a new technique based on gene expression programming', Neural Computing and Applications, vol. 30, no. 11, pp. 3523-3532.
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Jakowiecki, J, Sztyler, A, Filipek, S, Li, P, Raman, K, Barathiraja, N, Ramakrishna, S, Eswara, JR, Altaee, A, Sharif, AO, Ajayan, PM & Renugopalakrishnan, V 2018, 'Aquaporin–graphene interface: relevance to point-of-care device for renal cell carcinoma and desalination', Interface Focus, vol. 8, no. 3, pp. 20170066-20170066.
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The aquaporin superfamily of hydrophobic integral membrane proteins constitutes water channels essential to the movement of water across the cell membrane, maintaining homeostatic equilibrium. During the passage of water between the extracellular and intracellular sides of the cell, aquaporins act as ultra-sensitive filters. Owing to their hydrophobic nature, aquaporins self-assemble in phospholipids. If a proper choice of lipids is made then the aquaporin biomimetic membrane can be used in the design of an artificial kidney. In combination with graphene, the aquaporin biomimetic membrane finds practical application in desalination and water recycling using mostlyEscherichia coliAqpZ. Recently, human aquaporin 1 has emerged as an important biomarker in renal cell carcinoma. At present, the ultra-sensitive sensing of renal cell carcinoma is cumbersome. Hence, we discuss the use of epitopes from monoclonal antibodies as a probe for a point-of-care device for sensing renal cell carcinoma. This device works by immobilizing the antibody on the surface of a single-layer graphene, that is, as a microfluidic device for sensing renal cell carcinoma.

Jamil, S, Jeong, S & Vigneswaran, S 2018, 'Application of forward osmosis membrane in nanofiltration mode to treat reverse osmosis concentrate from wastewater reclamation plants', Water Science and Technology, vol. 77, no. 8, pp. 1990-1997.
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Abstract Reverse osmosis concentrate (ROC) from wastewater reclamation plants have high concentrations of organic and inorganic compounds, which have to be removed before its disposal. Forward osmosis (FO) and nanofiltration (NF) membranes were tested to treat the ROC for possible water reuse. This research investigated the combined and individual influence of organic and inorganic matter on the fouling of NF and FO membranes. The results revealed that the NF membrane removed most of the organic compounds and some inorganics. The study further highlighted that the FO membrane at NF mode removed the majority of the inorganic compounds and some organics from the ROC. A pretreatment of granulated activated carbon (GAC) adsorption removed 90% of the organic compounds from ROC. In addition, GAC adsorption and acid pretreatment of ROC improved the net water permeate flux by 17% when an FO membrane was used in the NF system. Acid treatment (by bringing the pH down to 5) helped to remove inorganic ions. Therefore, the resultant permeate can be recycled back to the RO water reclamation plant to improve its efficiency.

Jan, MA, Nanda, P, He, X & Liu, RP 2018, 'A Sybil attack detection scheme for a forest wildfire monitoring application', Future Generation Computer Systems, vol. 80, pp. 613-626.
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Wireless Sensor Networks (WSNs) have experienced phenomenal growth over the past decade. They are typically deployed in human-inaccessible terrains to monitor and collect time-critical and delay-sensitive events. There have been several studies on the use of WSN in different applications. All such studies have mainly focused on Quality of Service (QoS) parameters such as delay, loss, jitter, etc. of the sensed data. Security provisioning is also an important and challenging task lacking in all previous studies. In this paper, we propose a Sybil attack detection scheme for a cluster-based hierarchical network mainly deployed to monitor forest wildfire. We propose a two-tier detection scheme. Initially, Sybil nodes and their forged identities are detected by high-energy nodes. However, if one or more identities of a Sybil node sneak through the detection process, they are ultimately detected by the two base stations. After Sybil attack detection, an optimal percentage of cluster heads are elected and each one is informed using nomination packets. Each nomination packet contains the identity of an elected cluster head and an end user’s specific query for data collection within a cluster. These queries are user-centric, on-demand and adaptive to an end user requirement. The undetected identities of Sybil nodes reside in one or more clusters. Their goal is to transmit high false-negative alerts to an end user for diverting attention to those geographical regions which are less vulnerable to a wildfire. Our proposed approach has better network lifetime due to efficient sleep–awake scheduling, higher detection rate and low false-negative rate.

Jan, MA, Tan, Z, He, X & Ni, W 2018, 'Moving towards highly reliable and effective sensor networks', Ad-Hoc and Sensor Wireless Networks, vol. 40, no. 3-4, pp. 163-168.
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Wireless Sensor Networks (WSNs) have been the preferred choice for the design and deployment of next generation monitoring and control systems [1]. In these networks, the sensor nodes forward their sensed data towards a centralized base station. The neighboring nodes frequently sense correlated data and forward towards the base station, using disjoints multiple paths [2]. As a result, the area around the base station becomes congested with all the traffic converging towards it. Apart from packet lost due to congestion, a significant number of packets are lost due to interference, packet collision, node failure and transmission errors [3]. For a successful monitoring of the deployed environment, the critical data collected by the sensor nodes need to be reliably and effectively delivered to the base station. Given the error-prone nature of the wireless links, ensuring reliable transmission of data from resource-constrained sensor nodes towards the base station continues to be one of the major challenges in the field of WSNs [4]. Retransmission and redundancy are classified as the two main approaches to achieve data transmission reliability in WSNs. However, retransmission and redundancy techniques perform better when using hop-by-hop transmission approach as compared to end-to-end transmission. Using hop-by-hop approach introduces in-node processing overhead and incurs high overall latency in reporting data to the base station. As a result, hybrid approaches need to be adopted to ensure highly reliable and effective data transmission towards the base stations in WSNs. The specific objective of this special issue is to collect high quality research articles with solid background in both theoretical and practical aspects of reliability and effectiveness for WSNs. This special issue focuses on various topics pertaining to reliable and effective communication such as, fault-tolerance, energy-efficiency, topology control, load-balancing, propagation pathloss, co-channe...

Jayabarathi, T, Raghunathan, T & Gandomi, AH 2018, 'The Bat Algorithm, Variants and Some Practical Engineering Applications: A Review', vol. 744, pp. 313-330.
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The bat algorithm (BA), a metaheuristic algorithm developed by Xin-She Yang in 2010, has since been modified, and applied to numerous practical optimization problems in engineering. This chapter is a survey of the BA, its variants, some sample real-world optimization applications, and directions for future research.

Jayamali, KVSD, Nawagamuwa, UP & Indraratna, B 2018, 'Estimation of four-day soaked CBR using index properties', Australian Geomechanics Journal, vol. 53, no. 4, pp. 149-158.
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California Bearing Ratio (CBR) is an important parameter used to evaluate the strength of subgrade and sub-base soils for design of flexible pavements and hence it plays a significant role in road and highway constructions. Obtaining CBR is heavily time consuming and it is difficult to acquire a representative CBR value. Therefore, many correlations have been developed by various researchers worldwide to predict the CBR. Due to differences in soil formations in the tropical environment, these existing global correlations found to be not satisfactory with local soils in Sri Lanka. Hence, this study was carried out to develop empirical correlations between CBR and index properties those best suit for local soils, using the data obtained from Atterberg limits and sieve analysis tests together with compaction tests. The new correlations were established using the method of regression analysis in the form of empirical equations representing the role of index properties. Robust regression by the method of least absolute residuals using MATLAB was considered in the analysis to reduce the impact of outliers along with traditional multiple regression using Microsoft Excel. As a final verification, several laboratory tests were conducted to compare the results with proposed regression equations.

Jayawickrama, BA, He, Y, Dutkiewicz, E & Mueck, MD 2018, 'Scalable Spectrum Access System for Massive Machine Type Communication', IEEE Network, vol. 32, no. 3, pp. 154-160.
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© 1986-2012 IEEE. Future 5G networks aspire to enable new services with vastly different data rate, latency and scalability requirements. The consensus is that these new services will fall into three categories: eMBB, URLLC, and mMTC. Due to unique characteristics of these services and the limited availability of finite spectrum resources, 5G will need to carefully map appropriate bands and spectrum usage models for each service. The SAS is an emerging spectrum sharing model that is gaining momentum in the U.S. SAS presents an opportunity for operators to access the 3.5 GHz military radar band for commercial use. This article discusses the feasibility of the current SAS model in the context of mMTC. We propose a scalable SAS framework that can manage the mMTC uplink interference to the incumbent with less overhead. The simulation setup models the interference levels in New York City and its surrounding counties. The results show that mMTC uplink transmission can be enabled using our framework even on the coast of New York, where mMTC density is high, without causing a harmful level of interference to the incumbent.

Jhang, J-Y, Lin, C-J, Lin, C-T & Young, K-Y 2018, 'Navigation Control of Mobile Robots Using an Interval Type-2 Fuzzy Controller Based on Dynamic-group Particle Swarm Optimization', International Journal of Control, Automation and Systems, vol. 16, no. 5, pp. 2446-2457.
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© 2018, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature. This paper presents an effective navigation control method for mobile robots in an unknown environment. The proposed behavior manager (BM) switches between two behavioral control patterns, wall-following behavior (WFB) and toward-goal behavior (TGB), based on the relationship between the mobile robot and the unknown environment. An interval type-2 fuzzy neural controller with a dynamic-group particle swarm optimization (DGPSO) algorithm is proposed to provide WFB control and obstacle avoidance for mobile robots. In the WFB learning process, the input signal of a controller is the distance between the wall and the sonar sensors, and its output signal is the speed of two wheels of a mobile robot. A fitness function, which operates on the total distance traveled by the mobile robot, distance from the side wall, angle to the side wall, and moving speed, evaluates the WFB performance of the mobile robot. In addition, an escape mechanism is proposed to avoid a dead cycle. Experimental results reveal that the proposed DGPSO is superior to other methods in WFB and navigation control.

Ji, S, Yu, CP, Fung, S-F, Pan, S & Long, G 2018, 'Supervised Learning for Suicidal Ideation Detection in Online User Content', Complexity, vol. 2018, no. 1, pp. 1-10.
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Early detection and treatment are regarded as the most effective ways to prevent suicidal ideation and potential suicide attempts—two critical risk factors resulting in successful suicides. Online communication channels are becoming a new way for people to express their suicidal tendencies. This paper presents an approach to understand suicidal ideation through online user‐generated content with the goal of early detection via supervised learning. Analysing users’ language preferences and topic descriptions reveals rich knowledge that can be used as an early warning system for detecting suicidal tendencies. Suicidal individuals express strong negative feelings, anxiety, and hopelessness. Suicidal thoughts may involve family and friends. And topics they discuss cover both personal and social issues. To detect suicidal ideation, we extract several informative sets of features, including statistical, syntactic, linguistic, word embedding, and topic features, and we compare six classifiers, including four traditional supervised classifiers and two neural network models. An experimental study demonstrates the feasibility and practicability of the approach and provides benchmarks for the suicidal ideation detection on the active online platforms: Reddit SuicideWatch and Twitter.

Jia, H, Liu, W, Wang, J, Ngo, H-H, Guo, W & Zhang, H 2018, 'Optimization of sensing performance in an integrated dual sensors system combining microbial fuel cells and upflow anaerobic sludge bed reactor', Chemosphere, vol. 210, pp. 931-940.
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Jian, S, Cao, L, Lu, K & Gao, H 2018, 'Unsupervised Coupled Metric Similarity for Non-IID Categorical Data', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 9, pp. 1810-1823.
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© 1989-2012 IEEE. Appropriate similarity measures always play a critical role in data analytics, learning, and processing. Measuring the intrinsic similarity of categorical data for unsupervised learning has not been substantially addressed, and even less effort has been made for the similarity analysis of categorical data that is not independent and identically distributed (non-IID). In this work, a Coupled Metric Similarity (CMS) is defined for unsupervised learning which flexibly captures the value-to-attribute-to-object heterogeneous coupling relationships. CMS learns the similarities in terms of intrinsic heterogeneous intra-and inter-attribute couplings and attribute-to-object couplings in categorical data. The CMS validity is guaranteed by satisfying metric properties and conditions, and CMS can flexibly adapt to IID to non-IID data. CMS is incorporated into spectral clustering and k-modes clustering and compared with relevant state-of-the-art similarity measures that are not necessarily metrics. The experimental results and theoretical analysis show the CMS effectiveness of capturing independent and coupled data characteristics, which significantly outperforms other similarity measures on most datasets.

Jiang, J, Wen, S, Yu, S, Xiang, Y & Zhou, W 2018, 'Rumor Source Identification in Social Networks with Time-Varying Topology', IEEE Transactions on Dependable and Secure Computing, vol. 15, no. 1, pp. 166-179.
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© 2004-2012 IEEE. Identifying rumor sources in social networks plays a critical role in limiting the damage caused by them through the timely quarantine of the sources. However, the temporal variation in the topology of social networks and the ongoing dynamic processes challenge our traditional source identification techniques that are considered in static networks. In this paper, we borrow an idea from criminology and propose a novel method to overcome the challenges. First, we reduce the time-varying networks to a series of static networks by introducing a time-integrating window. Second, instead of inspecting every individual in traditional techniques, we adopt a reverse dissemination strategy to specify a set of suspects of the real rumor source. This process addresses the scalability issue of source identification problems, and therefore dramatically promotes the efficiency of rumor source identification. Third, to determine the real source from the suspects, we employ a novel microscopic rumor spreading model to calculate the maximum likelihood (ML) for each suspect. The one who can provide the largest ML estimate is considered as the real source. The evaluations are carried out on real social networks with time-varying topology. The experiment results show that our method can reduce 60 - 90 percent of the source seeking area in various time-varying social networks. The results further indicate that our method can accurately identify the real source, or an individual who is very close to the real source. To the best of our knowledge, the proposed method is the first that can be used to identify rumor sources in time-varying social networks.

Jiang, M, Qi, Y, Liu, H & Chen, Y 2018, 'The Role of Nanomaterials and Nanotechnologies in Wastewater Treatment: a Bibliometric Analysis', Nanoscale Research Letters, vol. 13, no. 1.
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Jiang, Q, Ngo, HH, Nghiem, LD, Hai, FI, Price, WE, Zhang, J, Liang, S, Deng, L & Guo, W 2018, 'Effect of hydraulic retention time on the performance of a hybrid moving bed biofilm reactor-membrane bioreactor system for micropollutants removal from municipal wastewater', Bioresource Technology, vol. 247, pp. 1228-1232.
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© 2017 Elsevier Ltd This study evaluated micropollutants removal and membrane fouling behaviour of a hybrid moving bed biofilm reactor-membrane bioreactor (MBBR-MBR) system at four different hydraulic retention times (HRTs) (24, 18, 12 and 6 h). The results revealed that HRT of 18 h was the optimal condition regarding the removal of most selected micropollutants. As the primary removal mechanism in the hybrid system was biodegradation, the attached growth pattern was desirable for enriching slow growing bacteria and developing a diversity of biocoenosis. Thus, the efficient removal of micropollutants was obtained. In terms of membrane fouling propensity analysis, a longer HRT (e.g. HRTs of 24 and 18 h) could significantly mitigate membrane fouling when compared with the shortest HRT of 6 h. Hence, enhanced system performance could be achieved when the MBBR-MBR system was operated at HRT of 18 h.

Jing, D, Huang, Y, Liu, X, Sia, KCS, Zhang, JC, Tai, X, Wang, M, Toscan, CE, McCalmont, H, Evans, K, Mayoh, C, Poulos, RC, Span, M, Mi, J, Zhang, C, Wong, JWH, Beck, D, Pimanda, JE & Lock, RB 2018, 'Lymphocyte-Specific Chromatin Accessibility Pre-determines Glucocorticoid Resistance in Acute Lymphoblastic Leukemia', Cancer Cell, vol. 34, no. 6, pp. 906-921.e8.
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© 2018 Elsevier Inc. Glucocorticoids play a critical role in the treatment of lymphoid malignancies. While glucocorticoid efficacy can be largely attributed to lymphocyte-specific apoptosis, its molecular basis remains elusive. Here, we studied genome-wide lymphocyte-specific open chromatin domains (LSOs), and integrated LSOs with glucocorticoid-induced RNA transcription and chromatin modulation using an in vivo patient-derived xenograft model of acute lymphoblastic leukemia (ALL). This led to the identification of LSOs critical for glucocorticoid-induced apoptosis. Glucocorticoid receptor cooperated with CTCF at these LSOs to mediate DNA looping, which was inhibited by increased DNA methylation in glucocorticoid-resistant ALL and non-lymphoid cell types. Our study demonstrates that lymphocyte-specific epigenetic modifications pre-determine glucocorticoid resistance in ALL and may account for the lack of glucocorticoid sensitivity in other cell types. Jing et al. identified lymphocyte-specific open chromatin domains (LSOs) critical for glucocorticoid (GC)-induced acute lymphoblastic leukemia (ALL) apoptosis. GC receptor cooperated with CTCF at these LSOs to mediate DNA looping, which was inhibited by DNA methylation in GC-resistant ALL and non-lymphoid cell types.

Jing, N, Jiang, T, Du, J & Sugumaran, V 2018, 'Personalized recommendation based on customer preference mining and sentiment assessment from a Chinese e-commerce website', Electronic Commerce Research, vol. 18, no. 1, pp. 159-179.
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Jonasson, OJ & Kandasamy, J 2018, 'Decentralised water reuse in Sydney, Australia: drivers for implementation and energy consumption', Journal of Environmental Engineering and Science, vol. 13, no. 1, pp. 2-7.
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Water recycling and reuse is becoming increasingly common throughout the world. The objective of this study was to compare five decentralised water recycling and reuse systems in Sydney, Australia, in terms of the drivers for their implementation and their ongoing energy consumption, allowing comparison to conventional water sources. The security of supply was found to be the main driver for four out of the five schemes. For the fifth scheme, the driver was to obtain a high environmental rating for the building it is located in. The analysis shows that water reuse can provide water at the same or less energy consumption compared to water supplied through the mains network. However, where the water recycling ethos of ‘fit for purpose’ is not considered, this can often lead to a significant overall increase in power consumption. This study highlights the need for regulatory bodies to consider a wider range of impacts when preparing guidelines and incentive schemes for water reuse. When the focus is too narrow, there is a risk that unintentional negative impacts such as increased power consumption and potential carbon dioxide emissions are the outcomes.

Jordaan, J, Punzet, S, Melnikov, A, Sanches, A, Oberst, S, Marburg, S & Powell, DA 2018, 'Measuring monopole and dipole polarizability of acoustic meta-atoms', Applied Physics Letters, vol. 113, no. 22, pp. 224102-224102.
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We present a method to extract monopole and dipole polarizability from experimental measurements of two-dimensional acoustic meta-atoms. In contrast to extraction from numerical results, this enables all second-order effects and uncertainties in material properties to be accounted for. We apply the technique to 3D-printed labyrinthine meta-atoms of a variety of geometries. We show that the polarizability of structures with a shorter acoustic path length agrees well with numerical results. However, those with longer path lengths suffer strong additional damping, which we attribute to the strong viscous and thermal losses in narrow channels.

Jordan, R, Gray, S, Zellner, M, Glynn, PD, Voinov, A, Hedelin, B, Sterling, EJ, Leong, K, Olabisi, LS, Hubacek, K, Bommel, P, BenDor, TK, Jetter, AJ, Laursen, B, Singer, A, Giabbanelli, PJ, Kolagani, N, Carrera, LB, Jenni, K & Prell, C 2018, 'Twelve Questions for the Participatory Modeling Community', Earth's Future, vol. 6, no. 8, pp. 1046-1057.
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AbstractParticipatory modeling engages the implicit and explicit knowledge of stakeholders to create formalized and shared representations of reality and has evolved into a field of study as well as a practice. Participatory modeling researchers and practitioners who focus specifically on environmental resources met at the National Socio‐Environmental Synthesis Center (SESYNC) in Annapolis, Maryland, over the course of 2 years to discuss the state of the field and future directions for participatory modeling. What follows is a description of 12 overarching groups of questions that could guide future inquiry.

Ju, M, Ding, C, Zhang, D & Guo, YJ 2018, 'Gamma-Correction-Based Visibility Restoration for Single Hazy Images', IEEE Signal Processing Letters, vol. 25, no. 7, pp. 1084-1088.
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© 1994-2012 IEEE. In this letter, a concise gamma-correction-based dehazing model (GDM) is proposed. This GDM explicitly describes the inner relationship between the gamma correction (GC) and the traditional scattering model. Combined with the existing priori constraints, GDM is further approximated into a one-dimensional (1-D) function to seek the only unknown constant that is used for haze removal. Using the determined constant, the scene albedo can be recovered, eliminating the haze from single hazy images. The proposed GDM is able to suppress the halo/blocking artifacts in the recovered results due to the scene albedo, which is less sensitive to the determined constant. Simulation results on different types of benchmark images verify that the proposed technique outperforms state-of-the-art methods in terms of both recovery, quality, and real-time performance.

Jumaah, HJ, Mansor, S, Pradhan, B & Adam, SN 2018, 'UAV-based PM2.5 monitoring for small-scale urban areas', International Journal of Geoinformatics, vol. 14, no. 4, pp. 61-69.
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Air quality data such as Particulate Matter PM2.5 collection near the ground is difficult, particularly in small complex regions. This study aims to introduce a PM2.5 prediction algorithm based on measurements from Unmanned Arial Vehicle (UAV)-based sensing system and validate the model at a specified low altitude. Observations were applied around 1.6 km2 area in University Putra Malaysia. This study uses an empirical method via applying amassed records of PM2.5 and meteorological parameters to produce a predictive Geographically Weighted Regression (GWR) model. An accuracy value is computed from the probability value given by the regression analysis model. To validate this approach, we have utilized training and testing data. To evaluate and validate the suggested model, we applied the model to the training set. The obtained result indicated that there is a good statistical correlation, and demonstrated that the characteristics obtained by analysis are able to predict the concentration of PM2.5.

Jupp, JR, Rivest, L, Forgues, D & Boton, C 2018, 'Comparison of shipbuilding and construction industries from the product structure standpoint', International Journal of Product Lifecycle Management, vol. 11, no. 3, pp. 191-191.
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Kaiwartya, O, Abdullah, AH, Cao, Y, Lloret, J, Kumar, S, Shah, RR, Prasad, M & Prakash, S 2018, 'Virtualization in Wireless Sensor Networks: Fault Tolerant Embedding for Internet of Things', IEEE Internet of Things Journal, vol. 5, no. 2, pp. 571-580.
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© 2017 IEEE. Recently, virtualization in wireless sensor networks (WSNs) has witnessed significant attention due to the growing service domain for Internet of Things (IoT). Related literature on virtualization in WSNs explored resource optimization without considering communication failure in WSNs environments. The failure of a communication link in WSNs impacts many virtual networks running IoT services. In this context, this paper proposes a framework for optimizing fault tolerance (FT) in virtualization in WSNs, focusing on heterogeneous networks for service-oriented IoT applications. An optimization problem is formulated considering FT and communication delay as two conflicting objectives. An adapted nondominated sorting-based genetic algorithm (A-NSGA) is developed to solve the optimization problem. The major components of A-NSGA include chromosome representation, FT and delay computation, crossover and mutation, and nondominance-based sorting. Analytical and simulation-based comparative performance evaluation has been carried out. From the analysis of results, it is evident that the framework effectively optimizes FT for virtualization in WSNs.

Kalantar, B, Pradhan, B, Naghibi, SA, Motevalli, A & Mansor, S 2018, 'Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 49-69.
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© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. All rights reserved. Landslide is a natural hazard that results in many economic damages and human losses every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each attempting to improve the accuracy of the final outputs. However, few studies have been published on the training data selection effects on the LSM. Thus, this study assesses the training landslides random selection effects on support vector machine (SVM) accuracy, logistic regression (LR) and artificial neural networks (ANN) models for LSM in a catchment at the Dodangeh watershed, Mazandaran province, Iran. A 160 landslide locations inventory was collected by Geological Survey of Iran for this investigation. Different methods were implemented to define the landslide locations, such as inventory reports, satellite images and field survey. Moreover, 14 landslide conditioning factors were considered in the analysis of landslide susceptibility. These factors include curvature, plan curvature, profile curvature, altitude, slope angle, slope aspect, distance to faults, distance to stream, topographic wetness index, stream power index, terrain roughness index, sediment transport index, lithology and land use. The results show that the random landslide training data selection affected the parameter estimations of the SVM, LR and ANN algorithms. The results also show that the training samples selection had an effect on the accuracy of the susceptibility model because landslide conditioning factors vary according to the geographic locations in the study area. The LR model was found to be less sensitive than the SVM and ANN models to the training samples selection. Validation results showed that SVM and LR models outperformed the ANN model for all scenarios. The average overall accuracy of LR, SVM and ANN models are 81.42%, 79.82% and 70.2%, respectively.

Kalaruban, M, Loganathan, P, Kandasamy, J & Vigneswaran, S 2018, 'Submerged membrane adsorption hybrid system using four adsorbents to remove nitrate from water', Environmental Science and Pollution Research, vol. 25, no. 21, pp. 20328-20335.
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© 2017, Springer-Verlag Berlin Heidelberg. Nitrate contamination of ground and surface waters causes environmental pollution and human health problems in many parts of the world. This study tests the nitrate removal efficiencies of two ion exchange resins (Dowex 21K XLT and iron-modified Dowex 21K XLT (Dowex-Fe)) and two chemically modified bio-adsorbents (amine-grafted corn cob (AG corn cob) and amine-grafted coconut copra (AG coconut copra)) using a dynamic adsorption treatment system. A submerged membrane (microfiltration) adsorption hybrid system (SMAHS) was used for the continuous removal of nitrate with a minimal amount of adsorbents. The efficiency of membrane filtration flux and replacement rate of adsorbent were studied to determine suitable operating conditions to maintain the effluent nitrate concentration below the WHO drinking standard limit of 11.3 mg N/L. The volume of water treated and the amount of nitrate adsorbed per gramme of adsorbent for all four flux tested were in the order Dowex-Fe > Dowex > AG coconut copra > AG corn cob. The volumes of water treated (L/g adsorbent) were 0.91 and 1.85, and the amount of nitrate removed (mg N/g adsorbent) were 9.8 and 22.2 for AG corn cob and Dowex-Fe, respectively, at a flux of 15 L/(m2/h).

Kalaruban, M, Loganathan, P, Shim, W, Kandasamy, J & Vigneswaran, S 2018, 'Mathematical Modelling of Nitrate Removal from Water Using a Submerged Membrane Adsorption Hybrid System with Four Adsorbents', Applied Sciences, vol. 8, no. 2, pp. 194-194.
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Excessive concentrations of nitrate in ground water are known to cause human health hazards. A submerged membrane adsorption hybrid system that includes a microfilter membrane and four different adsorbents (Dowex 21K XLT ion exchange resin (Dowex), Fe-coated Dowex, amine-grafted (AG) corn cob and AG coconut copra) operated at four different fluxes was used to continuously remove nitrate. The experimental data obtained in this study was simulated mathematically with a homogeneous surface diffusion model that incorporated membrane packing density and membrane correlation coefficient, and applied the concept of continuous flow stirred tank reactor. The model fit with experimental data was good. The surface diffusion coefficient was constant for all adsorbents and for all fluxes. The mass transfer coefficient increased with flux for all adsorbents and generally increased with the adsorption capacity of the adsorbents.

Kalhori, H, Alamdari, MM & Ye, L 2018, 'Automated algorithm for impact force identification using cosine similarity searching', Measurement, vol. 122, pp. 648-657.
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Kalhori, H, Makki Alamdari, M, Zhu, X & Samali, B 2018, 'Nothing-on-Road Axle Detection Strategies in Bridge-Weigh-in-Motion for a Cable-Stayed Bridge: Case Study', Journal of Bridge Engineering, vol. 23, no. 8, pp. 05018006-05018006.
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© 2018 American Society of Civil Engineers. This case-study article aims to share the field-test observations of a real-world cable-stayed bridge with the research community of bridge-weigh-in-motion to address the challenges of axle identification. Various structural members of the bridge, including cables, girders, and the deck, were instrumented with strain gauges at different locations to measure the axial, bending, or shear strain responses. Numerous field tests were conducted by running light and heavy vehicles traveling at different speeds, in different traffic directions, and in different lateral locations on the bridge. Because the identification of closely spaced axles is important to ensuring true classification of the vehicles, vehicles with tandem- and tridem-axle configurations were adopted in the field test. The study aimed to identify the sensor arrangement through which the closely spaced axles can be reliably detected regardless of the speed, traveling direction, and lateral location of the vehicle on the bridge. It was found that the axial strains on the cables and bending strains in the girders provided the global response of the structure; hence, they were unable to identify the closely spaced axles. In contrast, it was observed that the longitudinal strains under the deck were able to identify the closely spaced axles, provided they were positioned as closely as possible to the wheel path. Finally, the shear responses at the end of the span were able to identify the closely spaced axles irrespective of the traveling direction and lateral location of the vehicle. In this study, due to the testing limitations, including the short span of the bridge and the presence of a roundabout at one end of the bridge, it was not feasible to maintain a constant speed; therefore, identification of axle weight and axle spacing, which requires a constant-speed assumption, is not discussed.

Kamal, MS, Trivdedi, MC, Alam, JB, Dey, N, Ashour, AS, Shi, F & Tavares, JMRS 2018, 'Big DNA datasets analysis under push down automata', Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1555-1565.
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Kamal, S, Dey, N, Nimmy, SF, Ripon, SH, Ali, NY, Ashour, AS, Karaa, WBA, Nguyen, GN & Shi, F 2018, 'Evolutionary framework for coding area selection from cancer data', Neural Computing and Applications, vol. 29, no. 4, pp. 1015-1037.
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Kamyabniya, A, Lotfi, MM, Naderpour, M & Yih, Y 2018, 'Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach', Information Systems Frontiers, vol. 20, no. 4, pp. 759-782.
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© 2017, Springer Science+Business Media, LLC. Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation.

Kang, G, Li, J & Tao, D 2018, 'Shakeout: A New Approach to Regularized Deep Neural Network Training', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 5, pp. 1245-1258.
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© 1979-2012 IEEE. Recent years have witnessed the success of deep neural networks in dealing with a plenty of practical problems. Dropout has played an essential role in many successful deep neural networks, by inducing regularization in the model training. In this paper, we present a new regularized training approach: Shakeout. Instead of randomly discarding units as Dropout does at the training stage, Shakeout randomly chooses to enhance or reverse each unit's contribution to the next layer. This minor modification of Dropout has the statistical trait: the regularizer induced by Shakeout adaptively combines L-{0} , L-{1} and L-{2} regularization terms. Our classification experiments with representative deep architectures on image datasets MNIST, CIFAR-10 and ImageNet show that Shakeout deals with over-fitting effectively and outperforms Dropout. We empirically demonstrate that Shakeout leads to sparser weights under both unsupervised and supervised settings. Shakeout also leads to the grouping effect of the input units in a layer. Considering the weights in reflecting the importance of connections, Shakeout is superior to Dropout, which is valuable for the deep model compression. Moreover, we demonstrate that Shakeout can effectively reduce the instability of the training process of the deep architecture.

Kang, Y, Zhang, J, Li, B, Zhang, Y, Sun, H, Hao Ngo, H, Guo, W, Xie, H, Hu, Z & Zhao, C 2018, 'Improvement of bioavailable carbon source and microbial structure toward enhanced nitrate removal by Tubifex tubifex', Chemical Engineering Journal, vol. 353, pp. 699-707.
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Kani, K, Malgras, V, Jiang, B, Hossain, MSA, Alshehri, SM, Ahamad, T, Salunkhe, RR, Huang, Z & Yamauchi, Y 2018, 'Periodically Arranged Arrays of Dendritic Pt Nanospheres Using Cage‐Type Mesoporous Silica as a Hard Template', Chemistry – An Asian Journal, vol. 13, no. 1, pp. 106-110.
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AbstractDendritic Pt nanospheres of 20 nm diameter are synthesized by using a highly concentrated surfactant assembly within the large‐sized cage‐type mesopores of mesoporous silica (LP‐FDU‐12). After diluting the surfactant solution with ethanol, the lower viscosity leads to an improved penetration inside the mesopores. After Pt deposition followed by template removal, the arrangement of the Pt nanospheres is a replication from that of the mesopores in the original LP‐FDU‐12 template. Although it is well known that ordered LLCs can form on flat substrates, the confined space inside the mesopores hinders surfactant self‐organization. Therefore, the Pt nanospheres possess a dendritic porous structure over the entire area. The distortion observed in some nanospheres is attributed to the close proximity existing between neighboring cage‐type mesopores. This new type of nanoporous metal with a hierarchical architecture holds potential to enhance substance diffusivity/accessibility for further improvement of catalytic activity.

Kapeleris, J, Kulasinghe, A, Warkiani, ME, Vela, I, Kenny, L, O'Byrne, K & Punyadeera, C 2018, 'The Prognostic Role of Circulating Tumor Cells (CTCs) in Lung Cancer', Frontiers in Oncology, vol. 8, no. AUG.
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© 2018 Kapeleris, Kulasinghe, Warkiani, Vela, Kenny, O'Byrne and Punyadeera. Lung cancer affects over 1. 8 million people worldwide and is the leading cause of cancer related mortality globally. Currently, diagnosis of lung cancer involves a combination of imaging and invasive biopsies to confirm histopathology. Non-invasive diagnostic techniques under investigation include 'liquid biopsies' through a simple blood draw to develop predictive and prognostic biomarkers. A better understanding of circulating tumor cell (CTC) dissemination mechanisms offers promising potential for the development of techniques to assist in the diagnosis of lung cancer. Enumeration and characterization of CTCs has the potential to act as a prognostic biomarker and to identify novel drug targets for a precision medicine approach to lung cancer care. This review will focus on the current status of CTCs and their potential diagnostic and prognostic utility in this setting.

Karamanakos, P, Geyer, T & Aguilera, RP 2018, 'Long-Horizon Direct Model Predictive Control: Modified Sphere Decoding for Transient Operation', IEEE Transactions on Industry Applications, vol. 54, no. 6, pp. 6060-6070.
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© 1972-2012 IEEE. In this paper, we present modifications to the sphere decoder initially introduced in the work of Geyer and Quevedo and modified in the work of Karamanakos et al. that significantly reduce the computation times during transients. The relative position of the unconstrained solution of the integer quadratic program underlying model predictive control (MPC) with respect to the convex hull of the (truncated) lattice of integer points is examined. If it is found that the unconstrained solution does not lie within the convex hull - a phenomenon that is observed mostly during transients - then a projection is performed onto the convex hull. By doing so, a new sphere that guarantees feasibility and includes a significant smaller number of candidate solutions is computed. This reduces the computation time by up to three orders of magnitude when solving the optimization problem at hand. Nonetheless, the reduction of the computational burden comes at a cost of (mild) suboptimal results. The effectiveness of the proposed algorithm is tested with a variable speed drive system consisting of a three-level neutral point clamped voltage source inverter and a medium-voltage induction machine. Based on the presented results, the sphere decoding algorithm with the proposed refinements maintains the very fast transient responses inherent to direct MPC. Moreover, it is observed that the occasional implementation of suboptimal solutions does not lead to a deterioration of the system performance.

Karimi, F & Matous, P 2018, 'Mapping diversity and inclusion in student societies: A social network perspective', Computers in Human Behavior, vol. 88, pp. 184-194.
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Karmokar, DK, Guo, YJ, Qin, P-Y, Chen, S-L & Bird, TS 2018, 'Substrate Integrated Waveguide-Based Periodic Backward-to-Forward Scanning Leaky-Wave Antenna With Low Cross-Polarization', IEEE Transactions on Antennas and Propagation, vol. 66, no. 8, pp. 3846-3856.
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© 1963-2012 IEEE. For many leaky-wave antennas (LWAs), it is challenging to realize beam scanning through broadside. A problem is the presence of an open stopband (OSB), which restricts radiation in the broadside direction. In this paper, a novel substrate integrated waveguide (SIW)-based LWA is described to overcome the OSB problem and provide beam scanning continuously from the backward to the forward direction from a conventional periodic LWA. It is demonstrated that the n =-1 spatial harmonic can be excited efficiently from an SIW LWA and enables broadside radiation. However, it was found in our initial design that when the beam scans through the broadside, the cross-polarization level increases significantly compared to the beam close to the backfire direction. A technique is developed to reduce the cross-polarization level. As a result, a new antenna configuration is created. The antenna design has been realized and measured to validate the concept. The measured beam scanning range of the prototype is from -74° to +45° (119° of beam scanning) when the frequency sweeps from 7.625 to 11 GHz, and the measured cross-polarization level is 20.8 dB low at the main beam direction for the broadside beam.

Kashif, M, Hossain, MJ, Zhuo, F & Gautam, S 2018, 'Design and implementation of a three-level active power filter for harmonic and reactive power compensation', Electric Power Systems Research, vol. 165, pp. 144-156.
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Katalo, R, Okuda, T, Nghiem, LD & Fujioka, T 2018, 'Moringa oleifera coagulation as pretreatment prior to microfiltration for membrane fouling mitigation', Environmental Science: Water Research & Technology, vol. 4, no. 10, pp. 1604-1611.
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Coagulation pretreatment using Moringa oleifera in the microfiltration of river water achieved membrane fouling mitigation and filtered water quality improvement.

Ke, G, Li, W, Li, R, Li, Y & Wang, G 2018, 'Mitigation Effect of Waste Glass Powders on Alkali–Silica Reaction (ASR) Expansion in Cementitious Composite', International Journal of Concrete Structures and Materials, vol. 12, no. 1.
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© 2018, The Author(s). The effects of different contents and particle sizes of waste glass powder on alkali–silica reaction (ASR) expansion of cementitious composite bar were investigated in this study. Waste glass powder with particle size less than 300 μm exhibits an excellent mitigation effect on ASR expansion. With larger content and smaller particle size, the mitigation effect of waste glass powder on ASR expansion gradually increases. The mitigation effect of waste glass powder with particle size ranging from 38 to 53 μm and 20% by weight of cement seems relatively better than that of fly ash. When the waste glass powder content reaches 30%, the mitigation effect is still effective and almost the same as that of fly ash. However, the waste glass powder with particle size larger than 300 μm presents negative mitigation effect on ASR expansion when the replacement rate is larger than 30%. On the other hand, the waste glass powder and calcium hydroxide (CH) further react, and produce more calcium–silicate–hydrate gels, which apparently reduce the amount of CH. Moreover, the increasing content of waste glass powder results in a lower pH value in the pore solution of cementitious composite.

Keesstra, S, Nunes, JP, Saco, P, Parsons, T, Poeppl, R, Masselink, R & Cerdà, A 2018, 'The way forward: Can connectivity be useful to design better measuring and modelling schemes for water and sediment dynamics?', Science of The Total Environment, vol. 644, pp. 1557-1572.
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Kendrick, L, Musial, K & Gabrys, B 2018, 'Change point detection in social networks—Critical review with experiments', Computer Science Review, vol. 29, pp. 1-13.
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© 2018 Elsevier Inc. Change point detection in social networks is an important element in developing the understanding of dynamic systems. This complex and growing area of research has no clear guidelines on what methods to use or in which circumstances. This paper critically discusses several possible network metrics to be used for a change point detection problem and conducts an experimental, comparative analysis using the Enron and MIT networks. Bayesian change point detection analysis is conducted on different global graph metrics (Size, Density, Average Clustering Coefficient, Average Shortest Path) as well as metrics derived from the Hierarchical and Block models (Entropy, Edge Probability, No. of Communities, Hierarchy Level Membership). The results produced the posterior probability of a change point at weekly time intervals that were analysed against ground truth change points using precision and recall measures. Results suggest that computationally heavy generative models offer only slightly better results compared to some of the global graph metrics. The simplest metrics used in the experiments, i.e. nodes and links numbers, are the recommended choice for detecting overall structural changes.

Kennedy, P, Wagner, M, Castéra, L, Hong, CW, Johnson, CL, Sirlin, CB & Taouli, B 2018, 'Quantitative Elastography Methods in Liver Disease: Current Evidence and Future Directions', Radiology, vol. 286, no. 3, pp. 738-763.
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Keshavarzi, A, Shrestha, CK, Melville, B, Khabbaz, H, Ranjbar-Zahedani, M & Ball, J 2018, 'Estimation of maximum scour depths at upstream of front and rear piers for two in-line circular columns', Environmental Fluid Mechanics, vol. 18, no. 2, pp. 537-550.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. Previous investigations indicate that scour around bridge piers is one of the most important factors for the failure of waterway bridges. Hence, it is essential to determine the accurate scour depth around the bridge piers. Most of the previous studies were based on scour around a single pier; however, in practice, new bridges are usually wide and then piers comprise two circular piers aligned in the flow direction that together support the loading of the structure. In this study, the effect on maximum scour depth of the spacing between two piers aligned in the flow direction was investigated experimentally under clear water scour conditions. The results show that the maximum scour depth at upstream of the front pier occurs when the spacing between the two piers is 2.5 times the diameter of the pier. Two semi empirical equations have been developed to predict the maximum scour depth at upstream of both front and rear piers as a function of the spacing between the piers, in terms of a pier-spacing factor. If the new equations for the pier-spacing factor are used with some of the existing equations for scour at a single pier, the predicted scouring depths are in good agreement with observed results. The S/M equation exhibited the best performance among the various equations tested and was recommended for use in prediction of the equilibrium scour depth. The findings of this study can be used to facilitate the positioning of piers when scouring is a design concern.

Keshavarzi, A, Shrestha, CK, Zahedani, MR, Ball, J & Khabbaz, H 2018, 'Experimental study of flow structure around two in-line bridge piers', Proceedings of the Institution of Civil Engineers - Water Management, vol. 171, no. 6, pp. 311-327.
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Previous investigations indicate that local scouring is one of the most common causes of waterway bridge failure. The scour mechanism around bridge piers is complicated by the interaction of flow and structure. To explore the local scouring process, it is therefore essential to study the flow–structure interaction around bridge piers. Most previous studies have been based on this interaction around a single pier; however, in practice, many bridges are wide and comprise a number of piers aligned in the flow direction that together support the loading. In this study, a particle image velocimetry technique was used to investigate two-dimensional flow–structure interaction around two in-line bridge piers with different spacings. Various influencing flow characteristics including turbulence intensity, turbulent kinetic energy and Reynolds stresses were calculated in different vertical planes around the bridge piers. Results indicated that the flow characteristics around two in-line bridge piers are very different than for a single pier and the spacing between two in-line piers significantly influences the flow characteristics, particularly in the rear of the piers. Furthermore, for spacing in the range of 2 ≤ L/D ≤ 3, stronger turbulence structures occurred behind pier 1 and, as a result, a higher scour depth can be expected around pier 1.

Khalid, M, Aguilera, RP, Savkin, AV & Agelidis, VG 2018, 'A market‐oriented wind power dispatch strategy using adaptive price thresholds and battery energy storage', Wind Energy, vol. 21, no. 4, pp. 242-254.
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AbstractIn this paper, an adaptive dispatch strategy is presented to maximize the revenue for grid‐tied wind power plant coupled with a battery energy storage system (BESS). The proposed idea is mainly based on time‐varying market‐price thresholds, which are varied according to the proposed algorithm in an adaptive manner. The variable nature of wind power and market price signals leads to the idea of storing energy at low price periods and consequently selling it at high prices. In fact, the wind farm operators can take advantage of the price variability to earn additional income and to maximize the operational profit based on the choice of best price thresholds at each instant of time. This research study proposes an efficient strategy for intermittent power dispatch along with the optimal operation of a BESS in the presence of physical limits and constraints. The strategy is tested and validated with different BESSs, and the percentage improvement of income is calculated. The simulation results, based on actual wind farm and market‐price data, depict the proficiency of the proposed methodology over standard linear programming methods.

Khalid, M, Aguilera, RP, Savkin, AV & Agelidis, VG 2018, 'On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting', Applied Energy, vol. 211, pp. 764-773.
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© 2017 Elsevier Ltd This paper proposes a framework to develop an optimal power dispatch strategy for grid-connected wind power plants containing a Battery Energy Storage System (BESS). Considering the intermittent nature of wind power and rapidly varying electricity market price, short-term forecasting of these variables is used for efficient energy management. The predicted variability trends in market price assist in earning additional income which subsequently increase the operational profit. Then on the basis of income improvement, optimal capacity of the BESS can be determined. The proposed framework utilizes Dynamic Programming tool which can incorporate the predictions of both wind power and market price simultaneously as inputs in a receding horizon approach. The proposed strategy is validated using real electricity market price and wind power data in different scenarios of BESS power and capacity. The obtained results depict the effectiveness of the strategy to help power system operators in ensuring economically optimal energy dispatch. Moreover, the results can aid power system planners in the selection of optimal BESS capacity for given power ratings in order to maximize their operational profits.

Khalid, M, AlMuhaini, M, Aguilera, RP & Savkin, AV 2018, 'Method for planning a wind–solar–battery hybrid power plant with optimal generation‐demand matching', IET Renewable Power Generation, vol. 12, no. 15, pp. 1800-1806.
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This study aims to propose a methodology for a hybrid wind–solar power plant with the optimal contribution of renewable energy resources supported by battery energy storage technology. The motivating factor behind the hybrid solar–wind power system design is the fact that both solar and wind power exhibit complementary power profiles. Advantageous combination of wind and solar with optimal ratio will lead to clear benefits for hybrid wind–solar power plants such as smoothing of intermittent power, higher reliability, and availability. However, the potential challenges for its integration into electricity grids cannot be neglected. A potential solution is to utilise one of the energy storage technologies, though all of them are still very expensive for such applications, especially at large scale. Therefore, optimal capacity calculations for energy storage system are also vital to realise full benefits. Currently, battery energy storage technology is considered as one of the most promising choices for renewable power applications. This research targets at battery storage technology and proposes a generic methodology for optimal capacity calculations for the proposed hybrid wind–solar power system.

Khan, AA, Abolhasan, M & Ni, W 2018, 'An Evolutionary Game Theoretic Approach for Stable and Optimized Clustering in VANETs', IEEE Transactions on Vehicular Technology, vol. 67, no. 5, pp. 4501-4513.
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© 1967-2012 IEEE. Discovering and maintaining efficient routes for data dissemination in vehicular ad hoc networks (VANETs) has proven to be a very challenging problem. Clustering is one of the control protocols used to provide efficient and stable routes for data dissemination. However, the rapid changes in network topology in VANETs creates frequent cluster reformation, which can seriously affect route stability. We propose a novel evolutionary game theoretic (EGT) framework to automate the clustering of nodes and nominations of cluster heads, to achieve cluster stability in VANETs. The equilibrium point is proven analytically and the stability is also tested using Lyapunov function. The performance of the proposed evolutionary game is empirically investigated with different cost functions using static and mobile scenarios. The simulation results demonstrate the effectiveness and robustness of our proposed EGT approach for different populations and speeds, thus reducing the overhead of frequent cluster reformation in VANETs.

Khan, H, Razmjou, A, Ebrahimi Warkiani, M, Kottapalli, A & Asadnia, M 2018, 'Sensitive and Flexible Polymeric Strain Sensor for Accurate Human Motion Monitoring', Sensors, vol. 18, no. 2, pp. 418-418.
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Flexible electronic devices offer the capability to integrate and adapt with human body. These devices are mountable on surfaces with various shapes, which allow us to attach them to clothes or directly onto the body. This paper suggests a facile fabrication strategy via electrospinning to develop a stretchable, and sensitive poly (vinylidene fluoride) nanofibrous strain sensor for human motion monitoring. A complete characterization on the single PVDF nano fiber has been performed. The charge generated by PVDF electrospun strain sensor changes was employed as a parameter to control the finger motion of the robotic arm. As a proof of concept, we developed a smart glove with five sensors integrated into it to detect the fingers motion and transfer it to a robotic hand. Our results shows that the proposed strain sensors are able to detect tiny motion of fingers and successfully run the robotic hand.

Khan, HA, Khan, MSH, Castel, A & Sunarho, J 2018, 'Deterioration of alkali-activated mortars exposed to natural aggressive sewer environment', Construction and Building Materials, vol. 186, pp. 577-597.
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Khan, MA, Ngo, HH, Guo, W, Liu, Y, Chang, SW, Nguyen, DD, Nghiem, LD & Liang, H 2018, 'Can membrane bioreactor be a smart option for water treatment?', Bioresource Technology Reports, vol. 4, pp. 80-87.
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The gradual increase of organic and inorganic micropollutants in natural and drinking watercourses has posed a greater challenge for current water treatment technologies. Currently established water treatment processes such as activated sludge, microfiltration, reverse osmosis, adsorption, carbon nanotube etc. have a limited range of application, low energy recovery, and cost-intensive operation. Membrane bioreactor has already been utilized as a useful option to remove soluble organics, nutrients, and micropollutants from wastewater. Although currently established Membrane Bioreactors have few limitations, recent developments on this technology have improved its energy efficiency and reduced the operating and maintenance cost. Implementing these research findings in full-scale operation can make this process a favorable option in industrial wastewater treatment.

Khan, MA, Ngo, HH, Guo, W, Liu, Y, Zhang, X, Guo, J, Chang, SW, Nguyen, DD & Wang, J 2018, 'Biohydrogen production from anaerobic digestion and its potential as renewable energy', Renewable Energy, vol. 129, pp. 754-768.
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© 2017. The current demand-supply scenario for fossil fuels requires an alternative energy source with cleaner combustion products whilst production of hydrogen from anaerobic digestion involves the utilization of waste materials and zero emission of greenhouse gasses. However, large scale industrial application has yet not been implemented due to numerous challenges in its production, storage, and transportation. This review study demonstrates that production of hydrogen from anaerobic digestion is potentially a worthy alternative regarding energy density, environmental impact, and cost. Moreover, dependence on fossil fuel systems in the future could be minimized when biohydrogen production is feasible from renewable energy sources.

Khan, MA, Umer, T, Khan, SU, Yu, S & Rachedi, A 2018, 'IEEE Access Special Section Editorial: Green Cloud and Fog Computing: Energy Efficiency and Sustainability Aware Infrastructures, Protocols, and Applications', IEEE Access, vol. 6, pp. 12280-12283.
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Khan, MSH & Castel, A 2018, 'Effect of MgO and Na₂SiO₃ on the carbonation resistance of alkali activated slag concrete', Magazine of Concrete Research, vol. 70, no. 13, pp. 685-692.
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This paper investigates the effect of magnesium oxide (MgO) on the carbonation resistance of alkali-activated slag–fly ash blend containing 75% ground granulated blast furnace slag (GGBS) and 25% low-calcium fly ash. Two types of GGBS were used with different magnesium oxide content. Phenolphthalein indicator and pH profiles showed that the GGBS with higher levels of magnesium oxide offered no significant improvement in resistance against natural and 1% accelerated carbonation. X-ray diffraction confirmed no hydrotalcite formation, although the magnesium oxide content was 9·1%. A very small amount of free magnesium ions (Mg2+) was available in the pore solution, which was deemed insufficient to form hydrotalcite. Lack of its formation was the major reason for the lower carbonation resistance. Excessive silicate in the system reduces the calcium oxide/silicon dioxide ratio, which leads to the incorporation of magnesium ions in the calcium silicate hydrate structure. Hydrotalcite was observed when the activator concentration was reduced. The results suggest that in addition to magnesium and aluminium ion (Al3+) availability, silicate concentration also plays a strong role in deciding the hydrotalcite formation in alkali-activated GGBS concrete.

Khandelwal, M, Marto, A, Fatemi, SA, Ghoroqi, M, Armaghani, DJ, Singh, TN & Tabrizi, O 2018, 'Implementing an ANN model optimized by genetic algorithm for estimating cohesion of limestone samples', Engineering with Computers, vol. 34, no. 2, pp. 307-317.
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Khosrokhani, M, Khairunniza-Bejo, S & Pradhan, B 2018, 'Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques', Geocarto International, vol. 33, no. 3, pp. 260-276.
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Khuat, TT & Le, MH 2018, 'A Novel Hybrid ABC-PSO Algorithm for Effort Estimation of Software Projects Using Agile Methodologies', Journal of Intelligent Systems, vol. 27, no. 3, pp. 489-506.
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AbstractIn modern software development processes, software effort estimation plays a crucial role. The success or failure of projects depends greatly on the accuracy of effort estimation and schedule results. Many studies focused on proposing novel models to enhance the accuracy of predicted results; however, the question of accurate estimation of effort has been a challenging issue with regards to researchers and practitioners, especially when it comes to projects using agile methodologies. This study aims at introducing a novel formula based on team velocity and story point factors. The parameters of this formula are then optimized by employing swarm optimization algorithms. We also propose an improved algorithm combining the advantages of the artificial bee colony and particle swarm optimization algorithms. The experimental results indicated that our approaches outperformed methods in other studies in terms of the accuracy of predicted results.

Kieu, LM, Ou, Y & Cai, C 2018, 'Large-scale transit market segmentation with spatial-behavioural features', Transportation Research Part C: Emerging Technologies, vol. 90, pp. 97-113.
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Transit market segmentation enables transit providers to comprehend the commonalities and heterogeneities among different groups of passengers, so that they can cater for individual transit riders’ mobility needs. The problem has recently been attracting a great interest with the proliferation of automated data collection systems such as Smart Card Automated Fare Collection (AFC), which allow researchers to observe individual travel behaviours over a long time period. However, there is a need for an integrated market segmentation method that incorporating both spatial and behavioural features of individual transit passengers. This algorithm also needs to be efficient for large-scale implementation. This paper proposes a new algorithm named Spatial Affinity Propagation (SAP) based on the classical Affinity Propagation algorithm (AP) to enable large-scale spatial transit market segmentation with spatial-behavioural features. SAP segments transit passengers using spatial geodetic coordinates, where passengers from the same segment are located within immediate walking distance; and using behavioural features mined from AFC data. The comparison with AP and popular algorithms in literature shows that SAP provides nearly as good clustering performance as AP while being 52% more efficient in computation time. This efficient framework would enable transit operators to leverage the availability of AFC data to understand the commonalities and heterogeneities among different groups of passengers.

Kim, DI, Gwak, G, Dorji, P, He, D, Phuntsho, S, Hong, S & Shon, H 2018, 'Palladium Recovery through Membrane Capacitive Deionization from Metal Plating Wastewater', ACS Sustainable Chemistry & Engineering, vol. 6, no. 2, pp. 1692-1701.
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© 2017 American Chemical Society. The potential application of membrane capacitive deionization (MCDI) for recovery of palladium (Pd) ions from catalyst solution wastewater generated from the plating industry was investigated in this study. Several major issues were explored in this work to verify the suitability of MCDI for Pd recovery from a practical perspective: adsorption and desorption efficiencies, desorption mechanisms into high concentration of Pd concentrate, and its sustainability in long-term operation. The lab-scale MCDI operation achieved satisfactory and highly competitive Pd removal (99.07-99.94% removal with 1.42-1.52 of Pd selectivity over ammonium ions) showing that Pd can be effectively collected from plating industry wastewater. A high concentration of Pd concentrate (64.77 and 919.44 mg/L of Pd from the 10 and 100 mg/L Pd containing catalyst solution, respectively) was obtained through successive five operation cycles of adsorption/desorption phases. However, it is significant to note that the desorption efficiency was inversely proportional to the concentration of Pd concentrate which is likely due to the Pd ions discharged from carbon electrode toward Pd solution against the enhanced concentration gradient. The long-term operation results suggest that scaling could reduce the MCDI efficiency during Pd recovery (0.17% decrease in Pd removal for every cycle on average) and hence may require an adequate electrode cleaning regime.

Kim, J 2018, 'Robot Navigation and SLAM', Robots and Human: Special Issue on Robot Navigation and SLAM Technology, vol. 15.

Kim, JE, Phuntsho, S, Ali, SM, Choi, JY & Shon, HK 2018, 'Forward osmosis membrane modular configurations for osmotic dilution of seawater by forward osmosis and reverse osmosis hybrid system', Water Research, vol. 128, pp. 183-192.
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© 2017 Elsevier Ltd This study evaluates various options for full-scale modular configuration of forward osmosis (FO) process for osmotic dilution of seawater using wastewater for simultaneous desalination and water reuse through FO-reverse osmosis (RO) hybrid system. Empirical relationship obtained from one FO membrane element operation was used to simulate the operational performances of different FO module configurations. The main limiting criteria for module operation is to always maintain the feed pressure higher than the draw pressure throughout the housing module for safe operation without affecting membrane integrity. Experimental studies under the conditions tested in this study show that a single membrane housing cannot accommodate more than four elements as the draw pressure exceeds the feed pressure. This then indicates that a single stage housing with eight elements is not likely to be practical for safe FO operation. Hence, six different FO modular configurations were proposed and simulated. A two-stage FO configuration with multiple housings (in parallel) in the second stage using same or larger spacer thickness reduces draw pressure build-up as the draw flow rates are reduced to half in the second stage thereby allowing more than four elements in the second stage housing. The loss of feed pressure (pressure drop) and osmotic driving force in the second stage are compensated by operating under the pressure assisted osmosis (PAO) mode, which helps enhance permeate flux and maintains positive pressure differences between the feed and draw chamber. The PAO energy penalty is compensated by enhanced permeate throughput, reduced membrane area, and plant footprint. The contribution of FO/PAO to total energy consumption was not significant compared to post RO desalination (90%) indicating that the proposed two-stage FO modular configuration is one way of making the FO full-scale operation practical for FO-RO hybrid system.

Kim, JE, Phuntsho, S, Chekli, L, Choi, JY & Shon, HK 2018, 'Environmental and economic assessment of hybrid FO-RO/NF system with selected inorganic draw solutes for the treatment of mine impaired water', Desalination, vol. 429, pp. 96-104.
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© 2017 Elsevier B.V. A hybrid forward osmosis (FO) and reverse osmosis (RO)/nanofiltration (NF) system in a closed-loop operation with selected draw solutes was evaluated to treat coal mine impaired water. This study provides an insight of selecting the most suitable draw solution (DS) by conducting environmental and economic life cycle assessment (LCA). Baseline environmental LCA showed that the dominant components to energy use and global warming are the DS recovery processes (i.e. RO or NF processes) and FO membrane materials, respectively. When considering the DS replenishment in FO, the contribution of chemical use to the overall global warming impact was significant for all hybrid systems. Furthermore, from an environmental perspective, the FO-NF hybrid system with Na2SO4 shows the lowest energy consumption and global warming with additional considerations of final product water quality and FO brine disposal. From an economic perspective, the FO-NF with Na2SO4 showed the lowest total operating cost due to its lower DS loss and relatively low solute cost. In a closed-loop system, FO-NF with NaCl and Na2SO4 had the lowest total water cost at optimum NF recovery rates of 90 and 95%, respectively. FO-NF with Na2SO4 had the lowest environmental and economic impacts. Overall, draw solute performances and cost in FO and recovery rate in RO/NF play a crucial role in determining the total water cost and environmental impact of FO hybrid systems in a closed-loop operation.

Kim, S, Piao, G, Han, DS, Shon, HK & Park, H 2018, 'Solar desalination coupled with water remediation and molecular hydrogen production: a novel solar water-energy nexus', Energy & Environmental Science, vol. 11, no. 2, pp. 344-353.
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A novel solar water-energy nexus technology is presented that combines the solar desalination of saline water and desalination-driven wastewater remediation coupled with the production of H₂.

Kim, T, Sotirova, E, Shannon, A, Atanassova, V, Atanassov, K & Jang, L-C 2018, 'Interval Valued Intuitionistic Fuzzy Evaluations for Analysis of a Student’s Knowledge in University e-Learning Courses', INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS, vol. 18, no. 3, pp. 190-195.
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© The Korean Institute of Intelligent Systems. In the paper a method is proposed for evaluation of the students' knowledge obtained in the university e-learning courses and an evaluation of the whole student class. For the assessment of the student's solution of the respective assessment units the theory of intuitionistic fuzzy sets is used, while for the class evaluation, interval valued intuitionistic fuzzy sets is used. The obtained intuitionistic fuzzy estimations reflect the degree of each student's good or poor performances, for each assessment unit. The interval valued intuitionistic fuzzy evaluations are based on the separate student's evaluations. We also consider a degree of uncertainty that represents such cases wherein the student is currently unable to solve the problem. The method presented here provides the possibility for the algorithmization of the process of forming the student's evaluations.

Kok, VC, Zhang, H-W, Lin, C-T, Huang, S-C & Wu, M-F 2018, 'Positive association between hypertension and urinary bladder cancer: epidemiologic evidence involving 79,236 propensity score-matched individuals', Upsala Journal of Medical Sciences, vol. 123, no. 2, pp. 109-115.
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INTRODUCTION: We hypothesized that hypertensive patients harbor a higher risk of urinary bladder (UB) cancer. MATERIAL AND METHODS: We performed a population-based cohort study on adults using a National Health Insurance Research Database (NHIRD) dataset. Hypertension and comparison non-hypertensive (COMP) groups comprising 39,618 patients each were propensity score-matched by age, sex, index date, and medical comorbidities. The outcome was incident UB cancer validated using procedure codes. We constructed multivariable Cox models to derive adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs). Cumulative incidence was compared using a log-rank test. RESULTS: During a total follow-up duration of 380,525 and 372,020 person-years in the hypertension and COMP groups, 248 and 186 patients developed UB cancer, respectively, representing a 32% increase in the risk (aHR, 1.32; 95% CI, 1.09-1.60). Hypertensive women harbored a significantly increased risk of UB cancer (aHR, 1.55; 95% CI, 1.12-2.13) compared with non-hypertensive women, whereas men with hypertension had a statistically non-significant increased risk (aHR, 1.22; 95% CI, 0.96-1.55). The sensitivity analysis demonstrated that the increased risk was sustained throughout different follow-up durations for the entire cohort; a statistical increase in the risk was also noted among hypertensive men. CONCLUSION: This nationwide population-based propensity score-matched cohort study supports a positive association between hypertension and subsequent UB cancer development.

Kong, F, Sun, X, Guo, YJ, Leung, VCM, Zhu, Q & Zhu, H 2018, 'Queue-Aware Power Consumption Minimization in Two-Tier Heterogeneous Networks', IEEE Transactions on Vehicular Technology, vol. 67, no. 9, pp. 8875-8889.
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© 1967-2012 IEEE. In this paper, we study the network average power consumption minimization problem in a two-tier heterogeneous network by optimally tuning the activation ratio of micro base stations (BSs) under the quality of service (QoS) constraints of the network mean queueing delay and the network signal-to-interference ratio (SIR) coverage. With the consideration of dynamic packets arrivals, each BS can either be busy or be idle depending on its queueing status. The network performance is thus critically determined by the traffic intensity of each BS. With the assumption of universal frequency reuse, the average traffic intensity of each tier is characterized by a set of fixed-point equations, which can be solved by a proposed iterative method. By using the approximation that BSs of the same tier have the same SIR coverage, the cumulative distribution function of the traffic intensity of each tier is further obtained. On that basis, the network average power consumption per area, the network mean queueing delay, and the network SIR coverage are characterized. Numerical results demonstrate that if the idle power coefficient is below a certain threshold, then the optimal activation ratio equals the one to minimize the network average power consumption per area; otherwise, the optimal activation ratio can be obtained according to the QoS constraints. It is further shown that universal frequency reuse outperforms spectrum partitioning in terms of both the network average power consumption and the network SIR coverage in the considered scenario.

Kong, S, Lee, JH & Li, S 2018, 'A new distributed algorithm for efficient generalized arc-consistency propagation', Autonomous Agents and Multi-Agent Systems, vol. 32, no. 5, pp. 569-601.
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© 2018, The Author(s). Generalized arc-consistency propagation is predominantly used in constraint solvers to efficiently prune the search space when solving constraint satisfaction problems. Although many practical applications can be modelled as distributed constraint satisfaction problems, no distributed arc-consistency algorithms so far have considered the privacy of individual agents. In this paper, we propose a new distributed arc-consistency algorithm, called DisAC3.1, which leaks less private information of agents than existing distributed arc-consistency algorithms. In particular, DisAC3.1 uses a novel termination determination mechanism, which allows the agents to share domains, constraints and communication addresses only with relevant agents. We further extend DisAC3.1 to DisGAC3.1, which is the first distributed algorithm that enforces generalized arc-consistency on k-ary (k≥ 2) constraint satisfaction problems. Theoretical analyses show that our algorithms are efficient in both time and space. Experiments also demonstrate that DisAC3.1 outperforms the state-of-the-art distributed arc-consistency algorithm and that DisGAC3.1 ’s performance scales linearly in the number of agents.

Kong, S-H, Kim, M, Hoang, LM & Kim, E 2018, 'Automatic LPI Radar Waveform Recognition Using CNN', IEEE Access, vol. 6, pp. 4207-4219.
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Kook, S, Lee, C, Nguyen, TT, Lee, J, Shon, HK & Kim, IS 2018, 'Serially connected forward osmosis membrane elements of pressure-assisted forward osmosis-reverse osmosis hybrid system: Process performance and economic analysis', Desalination, vol. 448, pp. 1-12.
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© 2018 Elsevier B.V. Due to the improved dilution of draw streams, employing pressure-assisted forward osmosis (PAFO) to the hybrid system of forward osmosis (FO) followed by reverse osmosis (RO) for seawater desalination has been expected to reduce the overall economics. However, replacing FO with PAFO causes an additional energy cost in the seawater dilution step which inevitably leads to a question that PAFO-RO hybrid is truly an economically beneficial option. More importantly, though serial connection of FO elements improves the dilution of initial draw water, this economic benefit is also compensated with the additional membrane. To rationalize its overall performance and economic benefit, thorough performance and economic evaluations were conducted based on actual pilot-scale PAFO operations for serial connection of up to three 8040 FO elements. The results showed the FO-RO hybrid is not an economically feasible option unless a significant unit FO element cost cut-down is guaranteed. Meanwhile, PAFO-RO showed benefits with regards to target RO recovery and unit FO element cost, particularly when two FO elements are serially connected (SE2). It was found that PAFO-RO, indeed, has higher economic potential than FO-RO. A graphical overlapping method suggested in this work can help determine optimal serial configuration and operating conditions of PAFO-RO.

Kulasinghe, A, Schmidt, H, Perry, C, Whitfield, B, Kenny, L, Nelson, C, Warkiani, ME & Punyadeera, C 2018, 'A Collective Route to Head and Neck Cancer Metastasis', Scientific Reports, vol. 8, no. 1.
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AbstractDistant metastasis (DM) from head and neck cancers (HNC) portends a poor patient prognosis. Despite its important biological role, little is known about the cells which seed these DM. Circulating tumour cells (CTCs) represent a transient cancer cell population, which circulate in HNC patients’ peripheral blood and seed at distant sites. Capture and analysis of CTCs offers insights into tumour metastasis and can facilitate treatment strategies. Whilst the data on singular CTCs have shown clinical significance, the role of CTC clusters in metastasis remains limited. In this pilot study, we assessed 60 treatment naïve HNC patients for CTCs with disease ranging from early to advanced stages, for CTC clusters utilizing spiral CTC enrichment technology. Single CTCs were isolated in 18/60–30% (Ranging from Stage I-IV), CTC clusters in 15/60–25% (exclusively Stage IV) with 3/15–20% of CTC clusters also containing leukocytes. The presence of CTC clusters associated with the development of distant metastatic disease(P = 0.0313). This study demonstrates that CTC clusters are found in locally advanced patients, and this may be an important prognostic marker. In vivo and in vitro studies are warranted to determine the role of these CTC clusters, in particular, whether leukocyte involvement in CTC clusters has clinical relevance.

Kulasinghe, A, Wu, H, Punyadeera, C & Warkiani, ME 2018, 'The Use of Microfluidic Technology for Cancer Applications and Liquid Biopsy', Micromachines, vol. 9, no. 8, pp. 397-397.
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There is growing awareness for the need of early diagnostic tools to aid in point-of-care testing in cancer. Tumor biopsy remains the conventional means in which to sample a tumor and often presents with challenges and associated risks. Therefore, alternative sources of tumor biomarkers is needed. Liquid biopsy has gained attention due to its non-invasive sampling of tumor tissue and ability to serially assess disease via a simple blood draw over the course of treatment. Among the leading technologies developing liquid biopsy solutions, microfluidics has recently come to the fore. Microfluidic platforms offer cellular separation and analysis platforms that allow for high throughout, high sensitivity and specificity, low sample volumes and reagent costs and precise liquid controlling capabilities. These characteristics make microfluidic technology a promising tool in separating and analyzing circulating tumor biomarkers for diagnosis, prognosis and monitoring. In this review, the characteristics of three kinds of circulating tumor markers will be described in the context of cancer, circulating tumor cells (CTCs), exosomes, and circulating tumor DNA (ctDNA). The review will focus on how the introduction of microfluidic technologies has improved the separation and analysis of these circulating tumor markers.

Kumar, R, Arjuna, A, Diksha, Gupta, R, Mahajan, S, Satija, S & Mehta, M 2018, 'In vitro antioxidant and antimicrobial activity of polyherbal formulation', International Journal of Green Pharmacy, vol. 12, no. 2, pp. 80-84.
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Context: Antioxidants play a major role in protecting the body against oxidative stress that is associated with many chronic diseases and disorders including chronic wounds. Plants are the richest source for antioxidant and are effective in the management of oxidative stress, caused by free radical damage. Wound healing and antimicrobial potential are also attributed to the antioxidant potential of drugs. Aim: The aim of this study is to carry out the antioxidant and antimicrobial activity of given polyherbal formulation (PHF) to correlate with the wound healing potential of the formulation. Materials and Methods: Antioxidant potential of the PHF was evaluated by the 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging method. Agar well diffusion method was used to determine its antimicrobial activity against the Escherichia coli, Pseudomonas aeruginosa, Proteus vulgaris, Klebsiella aerogenes. Results: Results of the study demonstrated that PHF exhibited significant antioxidant activity. Antibacterial activity of polyherbal formula was evaluated against the four pathogenic microorganisms in which it showed mild-to-moderate antimicrobial activity against the E. coli and K. aerogenes, while mild antimicrobial activity against the P. aeruginosa and P. vulgaris. Conclusion: Results of this study suggested that PHF can be used for the treatment of wound infections due to its marked antioxidant and antimicrobial activity.

Kurugodu, HV, Bordoloi, S, Hong, Y, Garg, A, Garg, A, Sreedeep, S & Gandomi, AH 2018, 'Genetic programming for soil-fiber composite assessment', Advances in Engineering Software, vol. 122, pp. 50-61.
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Unconfined compressive strength (UCS) of soil is one of the basic index parameters for representing the compressive bearing strength of soil. Fiber reinforced soil is one of the most popular and practical ground improvement approaches used in geotechnical infrastructures. Analytical models for estimating UCS of soil-fiber composites have been developed in the literature. However, these models rarely incorporate the combined effects of dynamic field parameters such as fiber content, soil moisture, and density. These effects can be studied by the development of a holistic model based on a dimensionless strength improvement factor (SIF), which is defined as the ratio of UCS of reinforced soil to the unreinforced UCS. The current model estimating SIF indicates the improvement expected in UCS of soil-PP fiber composite based on the three design conditions such as fiber content, soil density, and moisture content. For this purpose, a series of 108 laboratory tests were first conducted to measure UCS of both fiber-reinforced soil and unreinforced soil under different fiber contents, soil density, and soil moisture content. Clayey silt soil and commercially used polypropylene (PP) fibers were selected in this study as soil and fiber material respectively. Genetic programming (GP) approach was then used to formulate models based on the measured data. The hidden non-linear relationships between SIF and the three inputs were determined by sensitivity and parametric analysis of the GP model. It was found that the moisture content in the soil has the highest influence on the strength factor that accounts for the change in strength. Coupled effects of soil parameters (soil moisture, soil density) and fiber content have been studied using parametric analysis which includes different possible field conditions (parameters). The results have been discussed along with the reinforcement mechanism of PP fiber for different soil conditions. It is believed that the robust GP ...

Kusakunniran, W, Wu, Q, Ritthipravat, P & Zhang, J 2018, 'Hard exudates segmentation based on learned initial seeds and iterative graph cut', Computer Methods and Programs in Biomedicine, vol. 158, pp. 173-183.
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© 2018 Elsevier B.V. (Background and Objective): The occurrence of hard exudates is one of the early signs of diabetic retinopathy which is one of the leading causes of the blindness. Many patients with diabetic retinopathy lose their vision because of the late detection of the disease. Thus, this paper is to propose a novel method of hard exudates segmentation in retinal images in an automatic way. (Methods): The existing methods are based on either supervised or unsupervised learning techniques. In addition, the learned segmentation models may often cause miss-detection and/or fault-detection of hard exudates, due to the lack of rich characteristics, the intra-variations, and the similarity with other components in the retinal image. Thus, in this paper, the supervised learning based on the multilayer perceptron (MLP) is only used to identify initial seeds with high confidences to be hard exudates. Then, the segmentation is finalized by unsupervised learning based on the iterative graph cut (GC) using clusters of initial seeds. Also, in order to reduce color intra-variations of hard exudates in different retinal images, the color transfer (CT) is applied to normalize their color information, in the pre-processing step. (Results): The experiments and comparisons with the other existing methods are based on the two well-known datasets, e_ophtha EX and DIARETDB1. It can be seen that the proposed method outperforms the other existing methods in the literature, with the sensitivity in the pixel-level of 0.891 for the DIARETDB1 dataset and 0.564 for the e_ophtha EX dataset. The cross datasets validation where the training process is performed on one dataset and the testing process is performed on another dataset is also evaluated in this paper, in order to illustrate the robustness of the proposed method. (Conclusions): This newly proposed method integrates the supervised learning and unsupervised learning based techniques. It achieves the improved performa...

Lacava, M, Camargo, A, Garcia, LF, Benamú, MA, Santana, M, Fang, J, Wang, X & Blamires, SJ 2018, 'Web building and silk properties functionally covary among species of wolf spider', Journal of Evolutionary Biology, vol. 31, no. 7, pp. 968-978.
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AbstractAlthough phylogenetic studies have shown covariation between the properties of spider major ampullate (MA) silk and web building, both spider webs and silks are highly plastic so we cannot be sure whether these traits functionally covary or just vary across environments that the spiders occupy. As MaSp2‐like proteins provideMAsilk with greater extensibility, their presence is considered necessary for spider webs to effectively capture prey. Wolf spiders (Lycosidae) are predominantly non‐web building, but a select few species build webs. We accordingly collectedMAsilk from two web‐building and six non‐web‐building species found in semirural ecosystems in Uruguay to test whether the presence of MaSp2‐like proteins (indicated by amino acid composition, silk mechanical properties and silk nanostructures) was associated with web building across the group. The web‐building and non‐web‐building species were from disparate subfamilies so we estimated a genetic phylogeny to perform appropriate comparisons. For all of the properties measured, we found differences between web‐building and non‐web‐building species. A phylogenetic regression model confirmed that web building and not phylogenetic inertia influences silk properties. Our study definitively showed an ecological influence over spider silk properties. We expect that the presence of the MaSp2‐like proteins and the subsequent nanostructures improves the mechanical performance of silks within the webs. Our study furthers our understanding of spider web and silk co‐evolution and the ecological implications of spider silk properties.

Laengle, S, Modak, NM, Merigó, JM & De La Sotta, C 2018, 'Thirty years of the International Journal of Computer Integrated Manufacturing: a bibliometric analysis', International Journal of Computer Integrated Manufacturing, vol. 31, no. 12, pp. 1247-1268.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The International Journal of Computer Integrated Manufacturing was established in 1988 with the idea of advancing research in computer integrated manufacturing (CIM) technologies and promoting the application of those technologies within industry. The journal was created to facilitate the exchange of new knowledge between industry and academia derived from both research and practical application. To celebrate the 30-year journey of the journal, this study develops a bibliometric analysis of all the publications of the journal to 2017. Information was collected using the Web of Science Core Collection database. The present study has been conducted to highlight the significant contributions of the journal in terms of impact, topics, authors, universities and countries. Finally, visualisation of similarities (VOS) viewer software was used to present graphical representations of the bibliographic coupling, co-citation, citation, co-authorship and co-occurrence of keywords.

Laengle, S, Modak, NM, Merigo, JM & Zurita, G 2018, 'Twenty-Five Years of Group Decision and Negotiation: A Bibliometric Overview', Group Decision and Negotiation, vol. 27, no. 4, pp. 505-542.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. Twenty-five years ago, in 1992, a journal named Group Decision and Negotiation was established in association with the Institute for Operations Research and the Management Sciences with the vision of promoting theoretical and empirical research, real-world applications and case studies on group decision and negotiation processes. To celebrate its 25 years of continuous and outstanding contributions, this study aims to develop a bibliometric analysis of the publications of the journal between 1992 and 2016. The Web of Science Core Collection database is used to identify the leading trends of the journal in terms of impacts, topics, authors, universities and countries. Moreover, it utilizes the visualization of similarities viewer software to analyze the bibliographic couplings, co-citations, citations, co-authorships and co-occurrences of keywords.

Lai, W, Ni, W, Wang, H & Liu, RP 2018, 'Analysis of Average Packet Loss Rate in Multi-Hop Broadcast for VANETs', IEEE Communications Letters, vol. 22, no. 1, pp. 157-160.
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© 2017 IEEE. Multi-hop relay can effectively improve the average packet loss rate (PLR) of vehicular ad hoc networks within a particular zone of interest. Challenges arise from analyzing the average PLR affected by distributed relay selections, which depend on the mobility of vehicles, the wireless channel conditions, and media access control (MAC). In this letter, we propose an average PLR analysis model taking into account the above three factors. However, the closed-form expression for the average PLR is intractable mainly due to the multiple integral of the joint distance distribution integrating with the channel conditions and vehicle mobility. An explicit expression for the upper bound of the average PLR is obtained by using Taylor series expansion, Holder's inequality, and the relay probability relaxation, which can facilitate the selection of the parameters at the physical and MAC layers for a better PLR. Simulation results validate our analyses.

Lake, C & Sheng, D 2018, 'Note of appreciation / Note de reconnaissance', Canadian Geotechnical Journal, vol. 55, no. 12, pp. v-vii.
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Lal, S, Caseley, EA, Hall, RM & Tipper, JL 2018, 'Biological Impact of Silicon Nitride for Orthopaedic Applications: Role of Particle Size, Surface Composition and Donor Variation', Scientific Reports, vol. 8, no. 1, pp. 9109-9109.
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AbstractThe adverse biological impact of orthopaedic wear debris currently limits the long-term safety of human joint replacement devices. We investigated the role of particle size, surface composition and donor variation in influencing the biological impact of silicon nitride as a bioceramic for orthopaedic applications. Silicon nitride particles were compared to the other commonly used orthopaedic biomaterials (e.g. cobalt-chromium and Ti-6Al-4V alloys). A novel biological evaluation platform was developed to simultaneously evaluate cytotoxicity, inflammatory cytokine release, oxidative stress, and genotoxicity potential of particles using peripheral blood mononuclear cells (PBMNCs) from individual human donors. Irrespective of the particle size, silicon nitride did not cause any adverse responses whereas cobalt-chromium wear particles caused donor-dependent cytotoxicity, TNF-α cytokine release, oxidative stress, and DNA damage in PBMNCs after 24 h. Despite being similar in size and morphology, silicon dioxide nanoparticles caused the release of significantly higher levels of TNF-α compared to silicon nitride nanoparticles, suggesting that surface composition influences the inflammatory response in PBMNCs. Ti-6Al-4V wear particles also released significantly elevated levels of TNF-α cytokine in one of the donors. This study demonstrated that silicon nitride is an attractive orthopaedic biomaterial due to its minimal biological impact on human PBMNCs.

Laloo, AE, Wei, J, Wang, D, Narayanasamy, S, Vanwonterghem, I, Waite, D, Steen, J, Kaysen, A, Heintz-Buschart, A, Wang, Q, Schulz, B, Nouwens, A, Wilmes, P, Hugenholtz, P, Yuan, Z & Bond, PL 2018, 'Mechanisms of Persistence of the Ammonia-Oxidizing Bacteria Nitrosomonas to the Biocide Free Nitrous Acid', Environmental Science & Technology, vol. 52, no. 9, pp. 5386-5397.
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© 2018 American Chemical Society. Free nitrous acid (FNA) exerts a broad range of antimicrobial effects on bacteria, although susceptibility varies considerably among microorganisms. Among nitrifiers found in activated sludge of wastewater treatment processes (WWTPs), nitrite-oxidizing bacteria (NOB) are more susceptible to FNA compared to ammonia-oxidizing bacteria (AOB). This selective inhibition of NOB over AOB in WWTPs bypasses nitrate production and improves the efficiency and costs of the nitrogen removal process in both the activated sludge and anaerobic ammonium oxidation (Anammox) system. However, the molecular mechanisms governing this atypical tolerance of AOB to FNA have yet to be understood. Herein we investigate the varying effects of the antimicrobial FNA on activated sludge containing AOB and NOB using an integrated metagenomics and label-free quantitative sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) metaproteomic approach. The Nitrosomonas genus of AOB, on exposure to FNA, maintains internal homeostasis by upregulating a number of known oxidative stress enzymes, such as pteridine reductase and dihydrolipoyl dehydrogenase. Denitrifying enzymes were upregulated on exposure to FNA, suggesting the detoxification of nitrite to nitric oxide. Interestingly, proteins involved in stress response mechanisms, such as DNA and protein repair enzymes, phage prevention proteins, and iron transport proteins, were upregulated on exposure to FNA. In addition enzymes involved in energy generation were also upregulated on exposure to FNA. The total proteins specifically derived from the NOB genus Nitrobacter was low and, as such, did not allow for the elucidation of the response mechanism to FNA exposure. These findings give us an understanding of the adaptive mechanisms of tolerance within the AOB Nitrosomonas to the biocidal agent FNA.

Lan, C, Peng, H, McGowan, EM, Hutvagner, G & Li, J 2018, 'An isomiR expression panel based novel breast cancer classification approach using improved mutual information', BMC Medical Genomics, vol. 11, no. S6, pp. 118-118.
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BACKGROUND:Gene expression-based profiling has been used to identify biomarkers for different breast cancer subtypes. However, this technique has many limitations. IsomiRs are isoforms of miRNAs that have critical roles in many biological processes and have been successfully used to distinguish various cancer types. Biomarker isomiRs for identifying different breast cancer subtypes has not been investigated. For the first time, we aim to show that isomiRs are better performing biomarkers and use them to explain molecular differences between breast cancer subtypes. RESULTS:In this study, a novel method is proposed to identify specific isomiRs that faithfully classify breast cancer subtypes. First, as a null hypothesis method we removed the lowly expressed isomiRs from small sequencing data generated from diverse breast cancers types. Second, we developed an improved mutual information-based feature selection method to calculate the weight of each isomiR expression. The weight of isomiR measures the importance of a given isomiR in classifying breast cancer subtypes. The improved mutual information enables to apply the dataset in which the feature is continuous data and label is discrete data; whereby, the traditional mutual information cannot be applied in this dataset. Finally, the support vector machine (SVM) classifier is applied to find isomiR biomarkers for subtyping. CONCLUSIONS:Here we demonstrate that isomiRs can be used as biomarkers in the identification of different breast cancer subtypes, and in addition, they may provide new insights into the diverse molecular mechanisms of breast cancers. We have also shown that the classification of different subtypes of breast cancer based on isomiRs expression is more effective than using published gene expression profiling. The proposed method provides a better performance outcome than Fisher method and Hellinger method for discovering biomarkers to distinguish different breast cancer subtypes. This novel techniqu...

Lanese, I & Devitt, S 2018, 'Preface for the special issue of the 8th Conference on Reversible Computation (RC 2016)', Science of Computer Programming, vol. 151, pp. 1-1.
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Laranjo, L, Dunn, AG, Tong, HL, Kocaballi, AB, Chen, J, Bashir, R, Surian, D, Gallego, B, Magrabi, F, Lau, AYS & Coiera, E 2018, 'Conversational agents in healthcare: a systematic review', Journal of the American Medical Informatics Association, vol. 25, no. 9, pp. 1248-1258.
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AbstractObjectiveOur objective was to review the characteristics, current applications, and evaluation measures of conversational agents with unconstrained natural language input capabilities used for health-related purposes.MethodsWe searched PubMed, Embase, CINAHL, PsycInfo, and ACM Digital using a predefined search strategy. Studies were included if they focused on consumers or healthcare professionals; involved a conversational agent using any unconstrained natural language input; and reported evaluation measures resulting from user interaction with the system. Studies were screened by independent reviewers and Cohen’s kappa measured inter-coder agreement.ResultsThe database search retrieved 1513 citations; 17 articles (14 different conversational agents) met the inclusion criteria. Dialogue management strategies were mostly finite-state and frame-based (6 and 7 conversational agents, respectively); agent-based strategies were present in one type of system. Two studies were randomized controlled trials (RCTs), 1 was cross-sectional, and the remaining were quasi-experimental. Half of the conversational agents supported consumers with health tasks such as self-care. The only RCT evaluating the efficacy of a conversational agent found a significant effect in reducing depression symptoms (effect size d = 0.44, p = .04). Patient safety was rarely evaluated in the included studies.ConclusionsThe use of conversational agents with unconstrained natural language input capabilities for health-related purposes is an emerging field of research, where the few published studies were mainly quasi-experimental, and rarely evaluated efficacy or safety. Future studies would benefit from more robust experimental des...

Leathersich, SJ, Vogel, JP, Tran, TS & Hofmeyr, GJ 2018, 'Acute tocolysis for uterine tachysystole or suspected fetal distress', Cochrane Database of Systematic Reviews, vol. 2018, no. 7, p. CD009770.
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BACKGROUND: Uterine tachysystole (more than 5 contractions per 10 minutes in 2 consecutive intervals) is common during labour, particularly with use of labour-stimulating agents. Tachysystole may reduce fetal oxygenation by interrupting maternal blood flow to the placenta during contractions. Reducing uterine contractions may improve placental blood flow, improving fetal oxygenation. This review aimed to evaluate the use of tocolytics to reduce or stop uterine contractions for improvement of the condition of the fetus in utero. This new review supersedes an earlier Cochrane Review on the same topic. OBJECTIVES: To assess the effects of the use of acute tocolysis during labour for uterine tachysystole or suspected fetal distress, or both, on fetal, maternal and neonatal outcomes. SEARCH METHODS: We searched Cochrane Pregnancy and Childbirth's Trials Register, ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP) (2 February 2018), and reference lists of retrieved studies. SELECTION CRITERIA: Randomised controlled trials (RCTs) evaluating acute tocolysis for uterine tachysystole, intrapartum fetal distress, or both. DATA COLLECTION AND ANALYSIS: We used standard methods expected by Cochrane. MAIN RESULTS: We included eight studies (734 women), conducted in hospital settings, predominantly in high-income countries (USA, Austria, Uruguay). Two trials were conducted in upper and lower middle-income countries (South Africa, Sri Lanka). The hospital facilities all had the capacity to perform caesarean section. Overall, the studies had a low risk of bias, except for methods to maintain blinding. All of the trials used a selective beta2 (ß2)-adrenergic agonist in one arm, however the drug used varied, as did the comparator. Limited information was available on maternal outcomes.Selective ß2-adrenergic agonist versus no tocolytic agent, whilst awaiting emergency deliveryThere were two stillbirths, both in the no tocolytic control ...

Lee, D, van Dorp Schuitman, J, Qiu, X & Burnett, I 2018, 'Development of a clarity parameter using a time-varying loudness model', The Journal of the Acoustical Society of America, vol. 143, no. 6, pp. 3455-3459.
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The perceived sound clarity is often estimated with the clarity index, which is calculated on the basis of physical acoustic measures that can correlate weakly to the way humans perceive sound for certain test conditions. Therefore, this study proposes a clarity parameter based on a binaural room impulse response processed with a time-varying loudness model. The proposed parameter is validated by calculating the correlation coefficient with subject responses collected from previous listening experiments. Results show that the parameter outperforms the clarity index in most of the tested conditions, but its performance is less robust than parameter for clarity (PCLA).

Lee, J-H, Sameen, MI, Pradhan, B & Park, H-J 2018, 'Modeling landslide susceptibility in data-scarce environments using optimized data mining and statistical methods', Geomorphology, vol. 303, pp. 284-298.
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Lee, S, Kim, Y, Park, J, Shon, HK & Hong, S 2018, 'Treatment of medical radioactive liquid waste using Forward Osmosis (FO) membrane process', Journal of Membrane Science, vol. 556, pp. 238-247.
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© 2018 Elsevier B.V. The use of forward osmosis (FO) for concentrating radioactive liquid waste from radiation therapy rooms in hospitals was systematically investigated in this study. The removal of natural and radioactive iodine using FO was first investigated with varying pHs and draw solutions (DSs) to identify the optimal conditions for FO concentration. Results showed that FO had a successful rejection rate for both natural and radioactive iodine (125I) of up to 99.3%. This high rejection rate was achieved at a high pH, mainly due to electric repulsion between iodine and membrane. Higher iodine removal by FO was also attained with a DS that exhibits a reverse salt flux (RSF) adequate to hinder iodine transport. Following this, actual radioactive medical liquid waste was collected and concentrated using FO under these optimal conditions. The radionuclides in the medical waste (131I) were removed effectively, but the water recovery rate was limited due to severe membrane fouling. To enhance the recovery rate, hydraulic washing was applied, but this had only limited success due to combined organic-inorganic fouling of the FO membrane. Finally, the effect of FO concentration on the reduction of septic tank volume was simulated as a function of recovery rate. To our knowledge, this study is the first attempt to explore the potential of FO technology for treating radioactive waste, and thus could be expanded to the dewatering of the radioactive liquid wastes from a variety of sources, such as nuclear power plants.

Lei, B, Li, W, Li, Z, Wang, G & Sun, Z 2018, 'Effect of Cyclic Loading Deterioration on Concrete Durability: Water Absorption, Freeze-Thaw, and Carbonation', Journal of Materials in Civil Engineering, vol. 30, no. 9, pp. 04018220-04018220.
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© 2018 American Society of Civil Engineers. The effect of cyclic loading deterioration on freeze-thaw and carbonation resistances of concrete were experimentally investigated in this study. A novel loading method was designed, which simultaneously considers both mechanical loading and environmental actions for concrete. It shows that with the increase of cyclic compressive loading, the porosity and water absorption of concrete initially decrease but then increase when the stress is above a threshold level because of the cracking initiation caused by cyclic compression. With the increase of concrete porosity, both dynamic elastic modulus loss and carbonation depth obviously exhibit an increasing trend. On the other hand, under the same stress level, the freeze-thaw and carbonation resistances of high-strength concrete are relatively superior to those of low-strength concrete. Compared with the unloaded concrete, the carbonation depth and dynamic elastic modulus loss after mechanical loading below the stress level threshold are lower. This is probably due to the denser microstructure compacted by the compression. However, if the loading level becomes above the threshold level, both the carbonation depth and dynamic elastic modulus loss dramatically increase, which is due to the cracks initiation and propagation after cyclic loading deterioration. Therefore, the combination of mechanical and environmental actions is more severe than a single environmental action without considering the mechanical loading.

Lei, B, Li, W, Tang, Z, Tam, VWY & Sun, Z 2018, 'Durability of recycled aggregate concrete under coupling mechanical loading and freeze-thaw cycle in salt-solution', Construction and Building Materials, vol. 163, pp. 840-849.
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© 2017 Elsevier Ltd In this study, a novel coupling testing protocol with separated repetitive loading and freezing-thaw cycles in salt-solution is designed to simulate coupling mechanical loading and complex environmental effects on durability and deterioration of recycled aggregate concrete (RAC). The Micromechanical properties and porosity of RAC were also characterized by scanning electron microscopy (SEM) and microhardness. The results show that the number and width of cracks of RAC and NAC under freeze-thaw cycles obviously increased with the increase of alternating times of repetitive load and the compressive stress level. The compressive strength losses for both RAC and NAC increase with the increase of compressive stress level and alternative times of repetitive load. However, the compressive strength of natural aggregate concrete (NAC) became lower than that of RAC after freeze-thaw cycles. It was found that the freeze-thaw resistance of RAC seems even better than that of NAC under the same freeze-thaw attacks and cyclic mechanical loading. It indicates that after freeze-thaw cycles in salt-solution, the durability of RAC is better than that of NAC. On the other hand, the microhardness and SEM characterization results indicate that the interface transition zone (ITZ) was a weak part in both RAC and NAC, and the ITZ in NAC obviously deteriorated faster than that of RAC.

Lenka, RK, Rath, AK, Tan, Z, Sharma, S, Puthal, D, Simha, NVR, Prasad, M, Raja, R & Tripathi, SS 2018, 'Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors', IEEE Access, vol. 6, pp. 30162-30173.
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© 2013 IEEE. Wireless sensors are an important component to develop the Internet of Things (IoT) Sensing infrastructure. There are enormous numbers of sensors connected with each other to form a network (well known as wireless sensor networks) to complete the IoT Infrastructure. These deployed wireless sensors are with limited energy and processing capabilities. The IoT infrastructure becomes a key factor to building cyber-physical-social networking infrastructure, where all these sensing devices transmit data toward the cloud data center. Data routing toward cloud data center using such low power sensor is still a challenging task. In order to prolong the lifetime of the IoT sensing infrastructure and building scalable cyber infrastructure, there is the requirement of sensing optimization and energy efficient data routing. Toward addressing these issues of IoT sensing, this paper proposes a novel rendezvous data routing protocol for low-power sensors. The proposed method divides the sensing area into a number of clusters to lessen the energy consumption with data accumulation and aggregation. As a result, there will be less amount of data stream to the network. Another major reason to select cluster-based data routing is to reduce the control overhead. Finally, the simulation of the proposed method is done in the Castalia simulator to observe the performance. It has been concluded that the proposed method is energy efficient and it prolongs the networks lifetime for scalable IoT infrastructure.

León-Castro, E, Avilés-Ochoa, E & Merigó, JM 2018, 'Induced Heavy Moving Averages', International Journal of Intelligent Systems, vol. 33, no. 9, pp. 1823-1839.
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León-Castro, E, Avilés-Ochoa, E, Merigó, JM & Gil-Lafuente, AM 2018, 'Heavy Moving Averages and Their Application in Econometric Forecasting', Cybernetics and Systems, vol. 49, no. 1, pp. 26-43.
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© 2017 Taylor & Francis Group, LLC. This paper presents the heavy ordered weighted moving average (HOWMA) operator. It is an aggregation operator that uses the main characteristics of two well-known techniques: the heavy ordered weighted averaging (OWA) and the moving averages. Therefore, this operator provides a parameterized family of aggregation operators from the minimum to the total operator and includes the OWA operator as a special case. It uses a heavy weighting vector in the moving average formulation and it represents the information available and the knowledge of the decision maker about the future scenarios of the phenomenon, according to his attitudinal character. Some of the main properties of this operator are studied, including a wide range of families of HOWMA operators such as the heavy moving average and heavy weighted moving average operators. The HOWMA operator is also extended using generalized and quasi-arithmetic means. An example concerning the foreign exchange rate between US dollars and Mexican pesos is also presented.

Leong, KY, Razali, I, Ku Ahmad, KZ, Ong, HC, Ghazali, MJ & Abdul Rahman, MR 2018, 'Thermal conductivity of an ethylene glycol/water-based nanofluid with copper-titanium dioxide nanoparticles: An experimental approach', International Communications in Heat and Mass Transfer, vol. 90, pp. 23-28.
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Leyendekkers, JV & Shannon, AG 2018, 'An indicator characteristic for twin prime formation independent of integer size', Notes on Number Theory and Discrete Mathematics, vol. 24, no. 1, pp. 10-15.
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Leyendekkers, JV & Shannon, AG 2018, 'Prime sequences', Notes on Number Theory and Discrete Mathematics, vol. 24, no. 3, pp. 77-83.
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Leyendekkers, JV & Shannon, AG 2018, 'The structure of prime sums', Notes on Number Theory and Discrete Mathematics, vol. 24, no. 4, pp. 86-91.
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Li, G, Chen, H, Peng, S, Li, X, Wang, C, Yu, S & Yin, P 2018, 'A Collaborative Data Collection Scheme Based on Optimal Clustering for Wireless Sensor Networks', Sensors, vol. 18, no. 8, pp. 2487-2487.
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In recent years, energy-efficient data collection has evolved into the core problem in the resource-constrained Wireless Sensor Networks (WSNs). Different from existing data collection models in WSNs, we propose a collaborative data collection scheme based on optimal clustering to collect the sensed data in an energy-efficient and load-balanced manner. After dividing the data collection process into the intra-cluster data collection step and the inter-cluster data collection step, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius. Then, we design a Cluster Heads (CHs)-linking algorithm based on the pseudo Hilbert curve to build a CH chain with the goal of collecting the compressed sensed data among CHs in an accumulative way. Furthermore, we also design a distributed cluster-constructing algorithm to construct the clusters around the virtual CHs in a distributed manner. The experimental results show that the proposed method not only reduces the total energy consumption and prolongs the network lifetime, but also effectively balances the distribution of energy consumption among CHs. By comparing it o the existing compression-based and non-compression-based data collection schemes, the average reductions of energy consumption are 17.9% and 67.9%, respectively. Furthermore, the average network lifetime extends no less than 20-times under the same comparison.

Li, H, Liu, D, Dai, Y, Luan, TH & Yu, S 2018, 'Personalized Search Over Encrypted Data With Efficient and Secure Updates in Mobile Clouds', IEEE Transactions on Emerging Topics in Computing, vol. 6, no. 1, pp. 97-109.
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Mobile cloud computing has been involved as a key enabling technology to overcome the physical limitations of mobile devices toward scalable and flexible mobile services. In the mobile cloud environment, searchable encryption, which enables direct search over encrypted data, is a key technique to maintain both the privacy and usability of outsourced data in cloud. On addressing the issue, many research efforts resolve to using the searchable symmetric encryption (SSE) and searchable public-key encryption (SPE). In this paper, we improve the existing works by developing a more practical searchable encryption technique, which can support dynamic updating operations in the mobile cloud applications. Specifically, we make our efforts on taking the advantages of both the SSE and SPE techniques, and propose PSU, a Personalized Search scheme over encrypted data with efficient and secure Updates in mobile cloud. By giving thorough security analysis, we demonstrate that the PSU can achieve a high security level. Using extensive experiments in a real-world mobile environment, we show that the PUS is more efficient compared with the existing proposals.

Li, H, Luo, Z, Gao, L & Qin, Q 2018, 'Topology optimization for concurrent design of structures with multi-patch microstructures by level sets', Computer Methods in Applied Mechanics and Engineering, vol. 331, pp. 536-561.
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© 2017 Elsevier B.V. This paper focuses on the novel concurrent design for cellular structures consisting of multiple patches of material microstructures using a level set-based topological shape optimization method. The macro structure is featured with the configuration of a cluster of non-uniformly distributed patches, while each patch hosts a number of identical material microstructures. At macro scale, a discrete element density based approach is presented to generate an overall structural layout involving different groups of discrete element densities. At micro scale, each macro element is regarded as an individual microstructure with a discrete intermediate density. Hence, all the macro elements with the same discrete densities (volume fractions) are represented by a unique microstructure. The representative microstructures corresponding to different density groups are topologically optimized by incorporating the numerical homogenization approach into a parametric level set method. The multiscale concurrent designs are integrated into a uniform optimization procedure, so as to optimize both topologies for the macrostructure and its microstructures, as well as locations of the microstructures in the design space. Numerical examples demonstrate that the proposed method can substantially improve the structural performance with an affordable computation and manufacturing cost.

Li, H, Luo, Z, Gao, L & Walker, P 2018, 'Topology optimization for functionally graded cellular composites with metamaterials by level sets', Computer Methods in Applied Mechanics and Engineering, vol. 328, pp. 340-364.
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© 2017 Elsevier B.V. The application of auxetic composites in practice often relies on a compromise between properties as auxetics are mostly too porous (not dense enough or not stiff enough) to bear structural loads. Hence, the focus of this paper is topological design optimization of new functionally graded cellular composites with auxetics using a level set method. Firstly, a new hierarchical multi-scale formulation is developed to account for both the auxetic behavior of the microstructure and the stiffness of the macrostructure. The composite, comprising multiple layers of periodic microstructures, is tailored to have functionally graded properties for stiffness and auxetic behaviors, subject to volumetric gradient constraints. Secondly, the microstructures underpinning composite layers are topologically designed under the consideration of boundary and loading conditions of the macrostructure. Finally, a level set method is applied to evolve the shape and topology of the microstructure for each layer, with the numerical homogenization method to evaluate the effective properties of the microstructures. Several numerical examples are used to demonstrate the effectiveness of the proposed method. It can be seen that such composites systematically gear together the features of the functionally graded materials, cellular composites, and metamaterials towards a new kind of man-made composites.

Li, H, Öchsner, A, Yarlagadda, PKDV, Xiao, Y, Furushima, T, Wei, D, Jiang, Z & Manabe, K-I 2018, 'A new constitutive analysis of hexagonal close-packed metal in equal channel angular pressing by crystal plasticity finite element method', Continuum Mechanics and Thermodynamics, vol. 30, no. 1, pp. 69-82.
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© 2017, Springer-Verlag GmbH Germany. Most of hexagonal close-packed (HCP) metals are lightweight metals. With the increasing application of light metal products, the production of light metal is increasingly attracting the attentions of researchers worldwide. To obtain a better understanding of the deformation mechanism of HCP metals (especially for Mg and its alloys), a new constitutive analysis was carried out based on previous research. In this study, combining the theories of strain gradient and continuum mechanics, the equal channel angular pressing process is analyzed and a HCP crystal plasticity constitutive model is developed especially for Mg and its alloys. The influence of elevated temperature on the deformation mechanism of the Mg alloy (slip and twin) is novelly introduced into a crystal plasticity constitutive model. The solution for the new developed constitutive model is established on the basis of the Lagrangian iterations and Newton Raphson simplification.

Li, H, Wang, J, Lu, H & Guo, Z 2018, 'Research and application of a combined model based on variable weight for short term wind speed forecasting', Renewable Energy, vol. 116, pp. 669-684.
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Li, J & Wu, C 2018, 'Damage evaluation of ultra-high performance concrete columns after blast loads', International Journal of Protective Structures, vol. 9, no. 1, pp. 44-64.
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As emerging advanced construction material, ultra-high performance concretes have seen increasing field applications over the past two decades to take advantages of their ultra-high mechanical strength and durability; yet the systematic study on its dynamic behaviour under impact and blast loads is not commonly seen. This article presents an experimental and numerical study on the static and dynamic behaviour of an existing ultra-high performance concrete material. Experimental study on its flexural behaviour under static loads is conducted and an inverse study is carried out to derive its uniaxial tensile constitutive law. The derived relationship is used in the material model in hydro-code LS-DYNA together with dynamic material properties to study ultra-high performance concrete columns under blast loads. The residual loading capacity of the column is studied and pressure–impulse diagrams for assessing the ultra-high performance concrete column damage under blast loads are proposed. Parametric study on effects of ultra-high performance concrete strength, column height, cross-section size and reinforcement ratio is performed and analytical equations are proposed for generating pressure–impulse diagrams for generic ultra-high performance concrete columns.

Li, J, Luo, H, Zhang, S, Yu, S & Wolf, T 2018, 'Traffic Engineering in Information-Centric Networking: Opportunities, Solutions and Challenges', IEEE Communications Magazine, vol. 56, no. 11, pp. 124-130.
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© 1979-2012 IEEE. ICN is a novel communication paradigm that assigns names to content chunks (instead of IP addresses to hosts). ICN offers inherent features such as content metadata and in-network caching, which make it possible to reduce content transmission cost and retrieval latency and to improve the users' QoE. To achieve these goals, TE techniques need to be leveraged to deal with bursty and unevenly distributed Internet traffic demand. In this article, we explore new TE opportunities in ICN based on information-centric features and provide an overview of the state-of-The-Art TE solutions that use these features.

Li, J, Nakai, K, Zheng, Y, Sato, K & Wong, L 2018, 'Introduction to Selected Papers from GIW2018', Journal of Bioinformatics and Computational Biology, vol. 16, no. 06, pp. 1802005-1802005.
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Li, J, Wei, J, Ngo, HH, Guo, W, Liu, H, Du, B, Wei, Q & Wei, D 2018, 'Characterization of soluble microbial products in a partial nitrification sequencing batch biofilm reactor treating high ammonia nitrogen wastewater', Bioresource Technology, vol. 249, pp. 241-246.
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In present study, the characterization of soluble microbial products (SMP) was evaluated in a partial nitrification sequencing batch biofilm reactor (SBBR). During the stable operation of SBBR, the NH4+-N removal efficiency and nitrite accumulation ratio were 96.70±0.41% and 93.77±1.04%, respectively. According to excitation-emission matrix (EEM), the intensities of protein-like substances were reduced under anoxic and aerobic phases, whereas humic-like substances had little change during the whole cycle. Parallel factor analysis (PARAFAC) further indentified two components and their fluorescence intensity scores were both reduced. Synchronous fluorescence spectra revealed that the fluorescence intensity of protein-like fraction decreased with reaction time. Two-dimensional correlation spectroscopy (2D-COS) further demonstrated that protein-like fraction might decrease earlier than the other fractions. The information obtained in present study is of fundamental significance for understanding the key components in SMP and their changes in partial nitrification system by using a spectral approach.

Li, J, Wu, C & Liu, Z-X 2018, 'Comparative evaluation of steel wire mesh, steel fibre and high performance polyethylene fibre reinforced concrete slabs in blast tests', Thin-Walled Structures, vol. 126, pp. 117-126.
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© 2017 Elsevier Ltd Concrete is the most widely used construction material in the modern construction practice. Due to its relatively low tensile resistance, concrete tends to experience tensile failure and cracking under external loads. To enhance the tensile performance and ductility of concrete material, possible solutions including fibre reinforcement and steel mesh reinforcement are investigated in the present study. Steel fibre, ultra-high molecular weight polyethylene (UHMWPE) fibre and steel wire meshes were mixed with varying volume fraction in the concrete matrix. Static material tests including uniaxial compression and flexural bending tests showed that the steel fibre addition yielded better strength enhancement while UHMWPE fibre provided better material ductility. Concrete samples with hybrid steel fibre-steel mesh reinforcement showed high strength and ductility. Field blast tests are designed to study the behaviour of reinforced concrete slabs under close-in detonations. Different damage profiles are observed from the blast tests. The advantages and disadvantages of using different reinforcing materials are discussed. From the results, the advantages of replacing steel fibre with UHMWPE fibre or steel wire mesh were demonstrated.

Li, J, Wu, C, Hao, H, Liu, Z & Yang, Y 2018, 'Basalt scale-reinforced aluminium foam under static and dynamic loads', Composite Structures, vol. 203, pp. 599-613.
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© 2018 Elsevier Ltd In this paper, mechanical performance and deformation behaviour of basalt scale-reinforced closed-cell aluminium foams are investigated. Quasi-static uniaxial compressive tests on the constitutive alloy material reveal that after basalt scale reinforcement, the alloy elasticity modulus and yield strength show noticeable enhancement. Quasi-static compression tests on the foam material show that while basalt scale-reinforced aluminium foam has higher plastic crush stress and plateau stress, the densification strain is lower than non-reinforced foam. A method based on energy absorption efficiency is adopted to accurately measure the densification strain for both foam materials. In the subsequent split-Hopkinson pressure bar tests, dynamic compressive behaviour of basalt scale-reinforced aluminium foams with relative densities ranged from 14% to 33% is studied experimentally under strain rate ranging from 480/s to 1720/s. Clear material rate sensitivity is noted from the dynamic tests. The results indicate that the plateau stress of aluminium foam increases with relative density and strain rate. In addition, with the increase in strain rates, an increase in the energy absorption capacity is observed and this characteristic is beneficial when the foam material is used to absorb impact energy. A mesoscopic model based on the X-ray CT for the aluminium foam material is developed. The simulations and the test data agreed well for the quasi-static loading case. However, it is noted that the mesoscale model without consideration of the base material rate sensitivity and the entrapped gas underestimated the strength enhancement under dynamic loading scenario.

Li, J, Ye, W, Wei, D, Ngo, HH, Guo, W, Qiao, Y, Xu, W, Du, B & Wei, Q 2018, 'System performance and microbial community succession in a partial nitrification biofilm reactor in response to salinity stress', Bioresource Technology, vol. 270, pp. 512-518.
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© 2018 Elsevier Ltd The system performance and microbial community succession in a partial nitrification biofilm reactor in response to salinity stress was conducted. It was found that the NH 4+ -N removal efficiency decreased from 98.4% to 42.0% after salinity stress increased to 20 g/L. Specific oxygen uptake rates suggested that AOB activity was more sensitive to the stress of salinity than that of NOB. Protein and polysaccharides contents showed an increasing tendency in both LB-EPS and TB-EPS after the salinity exposure. Moreover, EEM results indicated that protein-like substances were the main component in LB-EPS and TB-EPS as self-protection in response to salinity stress. Additionally, humic acid-like substances were identified as the main component in the effluent organic matter (EfOM) of partial nitrification biofilm, whereas fulvic acid-like substances were detected at 20 g/L salinity stress. Microbial community analysis found that Nitrosomonas as representative species of AOB were significantly inhibited under high salinity condition.

Li, JJ, Akey, A, Dunstan, CR, Vielreicher, M, Friedrich, O, Bell, DC & Zreiqat, H 2018, 'Effects of Material–Tissue Interactions on Bone Regeneration Outcomes Using Baghdadite Implants in a Large Animal Model', Advanced Healthcare Materials, vol. 7, no. 15, pp. e1800218-1800218.
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AbstractExtensive bone loss due to trauma or disease leads to impaired healing. Current bone grafts and substitutes have major drawbacks that limit their effectiveness for treating large bone defects. A number of bone substitutes in development are undergoing preclinical testing, but few studies specifically investigate the in vivo material–tissue interactions that provide an important indicator to long‐term implant safety and efficacy. This study is the first of its kind to specifically investigate in vivo material–tissue interactions at the bone–implant interface. Baghdadite scaffolds implanted in critical‐sized segmental defects in sheep tibia for 26 weeks are analyzed by focused ion beam scanning electron microscopy, multiphoton microscopy, and histology. The scaffolds are seen to induce extensive bone formation that directly abut the implant surfaces with no evidence of chronic inflammation or fibrous capsule formation. Bone remodeling is influenced by slow in vivo degradation around and within the implant, causing portions of the implant to be incorporated into the newly formed bone. These findings have important implications for predicting the long‐term effects of baghdadite ceramics in promoting defect healing, and support the translation of baghdadite scaffolds as a new generation of bone graft substitutes with improved properties for the repair of large bone defects.

Li, JJ, Ebied, M, Xu, J & Zreiqat, H 2018, 'Current Approaches to Bone Tissue Engineering: The Interface between Biology and Engineering', Advanced Healthcare Materials, vol. 7, no. 6, pp. e1701061-1701061.
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AbstractThe successful regeneration of bone tissue to replace areas of bone loss in large defects or at load‐bearing sites remains a significant clinical challenge. Over the past few decades, major progress is achieved in the field of bone tissue engineering to provide alternative therapies, particularly through approaches that are at the interface of biology and engineering. To satisfy the diverse regenerative requirements of bone tissue, the field moves toward highly integrated approaches incorporating the knowledge and techniques from multiple disciplines, and typically involves the use of biomaterials as an essential element for supporting or inducing bone regeneration. This review summarizes the types of approaches currently used in bone tissue engineering, beginning with those primarily based on biology or engineering, and moving into integrated approaches in the areas of biomaterial developments, biomimetic design, and scalable methods for treating large or load‐bearing bone defects, while highlighting potential areas for collaboration and providing an outlook on future developments.

Li, K, Gao, W, Wu, D, Song, C & Chen, T 2018, 'Spectral stochastic isogeometric analysis of linear elasticity', Computer Methods in Applied Mechanics and Engineering, vol. 332, pp. 157-190.
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© 2017 Elsevier B.V. The stochastic isogeometric analysis of linear elasticity problem is investigated in this study. The spectral stochastic analysis is introduced into isogeometric analysis (IGA), and a novel, yet robust, stochastic analysis framework, namely the spectral stochastic isogeometric analysis (SSIGA), is freshly proposed. Unlike traditional numerical solutions of the Karhunen–Loève (K-L) expansion, the non-uniform rational B-spline (NURBS) and T-spline basis functions are employed within the proposed framework of SSIGA, so the random fields acting on a continuous physical medium with complex geometry can be handled in an appropriate, physically feasible and efficient fashion. The polynomials chaos expansion (PCE) is implemented to represent the stochastic structural response (e.g., displacement, strain and stress), such that all corresponding statistical characteristics (e.g., mean and standard deviation) can be robustly acquired. Furthermore, by utilizing the nonparametric statistical analysis, both probability density functions (PDFs) and cumulative distribution functions (CDFs) of concerned structural displacements and stresses can be effectively established. Within the framework of IGA, by meticulously implementing the concept of the higher-order k-refinement, the proposed SSIGA provides a more legitimate and efficient stochastic computational approach for modern engineering structures which are complicated by both spatially dependent uncertainties and complex geometries.

Li, K, Ni, W, Duan, L, Abolhasan, M & Niu, J 2018, 'Wireless Power Transfer and Data Collection in Wireless Sensor Networks', IEEE Transactions on Vehicular Technology, vol. 67, no. 3, pp. 2686-2697.
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© 1967-2012 IEEE. In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using wireless power transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, whereas the other nodes waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes' energy consumption and data queue state information. The scheduling problem is first formulated by a centralized MDP model, assuming that the complete states of each node are well known by the base station. This presents the upper bound of the data that can be collected in a rechargeable wireless sensor network. Next, we relax the assumption of the availability of full state information so that the data transmission and WPT can be semidecentralized. The simulation results show that, in terms of network throughput and packet loss rate, the proposed algorithm significantly improves the network performance.

Li, K, Wu, D & Gao, W 2018, 'Spectral stochastic isogeometric analysis for static response of FGM plate with material uncertainty', Thin-Walled Structures, vol. 132, pp. 504-521.
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In this study, the nondeterministic structural responses of functionally graded material (FGM) plates under static loads with uncertain material property is investigated. The considered spatially dependent uncertainties are modelled as random fields with Gaussian distribution. A novel spectral stochastic isogeometric analysis (SSIGA) framework is proposed for such uncertainty quantification through the first-order shear deformation theory. Within the SSIGA framework, the non-uniform rational B-spline (NURBS) is adopted for both the geometry modelling of the random fields of the uncertain material properties and random field discretization through the Karhunen-Loève (K-L) expansion. Such new feature provides an effective and practically applicable random field modelling technique, especially for uncertain parameters over complex physical domains. The polynomial chaos expansion (PCE) is employed for estimating the statistical characteristics (e.g., mean and standard deviation) of any concerned structural responses (e.g., displacement and stress). By further implementing various statistical inference techniques, the probability density functions (PDF) and cumulative distribution functions (CDF) of structural responses can be established to determine both serviceability and strength limits of FGM plate. Two numerical examples are thoroughly investigated to illustrate the applicability, effectiveness and efficiency of the proposed computational approach.

Li, K, Wu, D, Chen, X, Cheng, J, Liu, Z, Gao, W & Liu, M 2018, 'Isogeometric Analysis of functionally graded porous plates reinforced by graphene platelets', Composite Structures, vol. 204, pp. 114-130.
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This paper investigates the static linear elasticity, natural frequency, and buckling behaviour of functionally graded porous plates reinforced by graphene platelets (GPLs). Both first- and third-order shear deformation plate theories are incorporated within the Isogeometric Analysis (IGA) framework. The pores and the GPLs within the plates are distributed in the metal matrix either uniformly or non-uniformly according to different patterns. The graded distributions of porosity and nanocomposite are achieved by material parameters varying across the thickness direction of plate. The Halpin-Tsai micromechanics model is implemented to establish the relationship between porosity coefficient and Young's modulus, as well as to obtain the mass density of the nanocomposite. The variation of Poisson's ratio is determined by the mechanical properties of closed-cell cellular solids under Gaussian Random Field scheme. A comprehensive parametric study is accomplished to investigate the effects of weight fraction, distribution pattern, geometry, and size of the GPLs reinforcement on the static linear elasticity, natural frequency, and buckling behaviour of the nanocomposite plates with diverse metal matrices and porosity coefficients. The outcome of numerical investigation shows that the inclusion of the GPLs can effectively improve the stiffness of functionally graded porous plate.

Li, L, Deng, N, Ren, W, Kou, B, Zhou, W & Yu, S 2018, 'Multi-Service Resource Allocation in Future Network With Wireless Virtualization', IEEE Access, vol. 6, pp. 53854-53868.
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© 2013 IEEE. Future network is envisioned to be a multi-service network which can support various types of terminal devices with diverse quality of service requirements. As one of the key technologies, wireless virtualization establishes different virtual networks dependent on different application scenarios and user requirements through flexibly slicing and sharing wireless resources in future networks. In this paper, we first propose a service-centric wireless virtualization model to slice network according to service types. In this model, how to share and slice wireless resource is one of the fundamental issues to be addressed. Therefore, we formulate and solve a multi-service resource allocation problem to realize spectrum virtualization. Different from the existing strategies, we decouple the multi-service resource allocation problem in the proposed virtualization model to make it easier to solve. Specifically, it is solved in two stages: inter-slice resource allocation and intra-slice resource scheduling. In the first stage, we formulate the inter-slice resource allocation as a discrete optimization problem and propose a heuristic algorithm to get sub-optimal solution of this NP-hard problem. In the second stage, we modify several existing scheduling algorithms suitable for scheduling users of several specific services. Numerical results show the superiority of the proposed scheduling algorithms over the existing ones when applied to schedule specific services. Moreover, proposed resource allocation scheme is verified to meet the properties of virtualization and solves the multi-service resource allocation problem well.

Li, L, Liu, J, Sun, Y, Xu, G, Yuan, J & Zhong, L 2018, 'Unsupervised keyword extraction from microblog posts via hashtags', Journal of Web Engineering, vol. 17, no. 1-2, pp. 93-120.
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Nowadays, huge amounts of texts are being generated for social networking purposes on Web. Keyword extraction from such texts like microblog posts benefits many applications such as advertising, search, and content filtering. Unlike traditional web pages, a microblog post usually has some special social feature like a hashtag that is topical in nature and generated by users. Extracting keywords related to hashtags can reflect the intents of users and thus provides us better understanding on post content. In this paper, we propose a novel unsupervised keyword extraction approach for microblog posts by treating hashtags as topical indicators. Our approach consists of two hashtag enhanced algorithms. One is a topic model algorithm that infers topic distributions biased to hashtags on a collection of microblog posts. The words are ranked by their average topic probabilities. Our topic model algorithm can not only find the topics of a collection, but also extract hashtag-related keywords. The other is a random walk based algorithm. It first builds a word-post weighted graph by taking into account posts themselves. Then, a hashtag biased random walk is applied on this graph, which guides the algorithm to extract keywords according to hashtag topics. Last, the final ranking score of a word is determined by the stationary probability after a number of iterations. We evaluate our proposed approach on a collection of real Chinese microblog posts. Experiments show that our approach is more effective in terms of precision than traditional approaches considering no hashtag. The result achieved by the combination of two algorithms performs even better than each individual algorithm.

Li, L, Liu, Z & Zhang, J 2018, 'Unsupervised image co-segmentation via guidance of simple images', Neurocomputing, vol. 275, pp. 1650-1661.
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© 2017 Elsevier B.V. This paper proposes a novel image co-segmentation method, which aims to segment the common objects in a group of images. The proposed method takes advantages of the reliability of simple images and successfully improves the performance. The images are first ranked by the complexities based on their saliency maps. Then, the simple images, in which objects are common and easy to be segmented, are selected and processed to obtain their segmentation results, these segmentation results are taken as the samples of the targeted objects. Finally, the remaining complicated images are segmented with the guidance of the samples. The experiments on the iCoseg dataset demonstrate the outperformance and robustness of the proposed method.

Li, L, Nimbalkar, S & Zhong, R 2018, 'Finite element model of ballasted railway with infinite boundaries considering effects of moving train loads and Rayleigh waves', Soil Dynamics and Earthquake Engineering, vol. 114, pp. 147-153.
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© 2018 Elsevier Ltd This paper proposes a three-dimensional model incorporating finite element (FE) meshes with infinite element (IE) boundaries for ballasted railways. Moving train loads are simulated with sliding motions of moving elements which have hard contact feature at the interface with supporting rails. Dynamic responses of ballasted railway under different train speeds are investigated in time domain and frequency domain to identify the predominant frequency and critical speed. Rayleigh wave (R-Wave) propagation is simulated using the combined FE-IE model to determine the velocity of R-Wave in the layered embankment model and its relationship with the critical speed of the ballasted railway. The proposed model is successfully validated against the results of Euler-Bernoulli Elastic Beam (E-BEB) model.

Li, L, Zhang, S, Yu, X & Zhang, L 2018, 'PMSC: PatchMatch-Based Superpixel Cut for Accurate Stereo Matching', IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 3, pp. 679-692.
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Estimating the disparity and normal direction of one pixel simultaneously, instead of only disparity, also known as 3D label methods, can achieve much higher subpixel accuracy in the stereo matching problem. However, it is extremely difficult to assign an appropriate 3D label to each pixel from the continuous label space R3 while maintaining global consistency because of the infinite parameter space. In this paper, we propose a novel algorithm called PatchMatch-based superpixel cut to assign 3D labels of an image more accurately. In order to achieve robust and precise stereo matching between local windows, we develop a bilayer matching cost, where a bottom-up scheme is exploited to design the two layers. The bottom layer is employed to measure the similarity between small square patches locally by exploiting a pretrained convolutional neural network, and then, the top layer is developed to assemble the local matching costs in large irregular windows induced by the tangent planes of object surfaces. To optimize the spatial smoothness of local assignments, we propose a novel strategy to update 3D labels. In the procedure of optimization, both segmentation information and random refinement of PatchMatch are exploited to update candidate 3D label set for each pixel with high probability of achieving lower loss. Since pairwise energy of general candidate label sets violates the submodular property of graph cut, we propose a novel multilayer superpixel structure to group candidate label sets into candidate assignments, which thereby can be efficiently fused by α-expansion graph cut. Extensive experiments demonstrate that our method can achieve higher subpixel accuracy in different data sets, and currently ranks first on the new challenging Middlebury 3.0 benchmark among all the existing methods.

Li, M, Liu, Y & Guo, YJ 2018, 'Shaped Power Pattern Synthesis of a Linear Dipole Array by Element Rotation and Phase Optimization Using Dynamic Differential Evolution', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 4, pp. 697-701.
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Li, M, Yang, Y, Xu, KD, Zhu, X & Wong, SW 2018, 'Microwave On-Chip Bandpass Filter Based on Hybrid Coupling Technique', IEEE Transactions on Electron Devices, vol. 65, no. 12, pp. 5453-5459.
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© 2018 IEEE. In this paper, a novel on-chip circuit design approach is proposed using hybrid coupling technique. Taking advantage of this technique, a microwave bandpass filter (BPF) is proposed as a design example for proof of concept. Based on stub-loaded stepped-impedance transmission lines and folded stepped-impedance meander line from different metal layers, the proposed BPF can generate three transmission zeros (TZs) and two transmission poles (TPs), which are excited through the hybrid mutual couplings between the inductive and capacitive metals. To understand the principle of this configuration, an equivalent LC-circuit model is presented and simplified, of which the TZs and TPs of the proposed BPF are estimated by the extracted transfer function. The calculated results exhibit good agreements with the simulated and measured ones. In addition, the bandwidth and center frequency of the proposed BPF can be tuned flexibly. Finally, to further demonstrate the feasibility of this approach in practice, the structure is implemented and fabricated in a commercial 0.13- μm SiGe (Bi)-CMOS technology. The measurement results show that the proposed BPF, whose chip size is 0.39 mm × 0.45 mm (excluding the test pads), can realize a wide bandwidth from 19.7 to 33.2 GHz with a return loss of 15.8 dB and insertion loss of 3.8 dB at the center frequency of 26.5 GHz.

Li, Q, Wu, D, Chen, X, Liu, L, Yu, Y & Gao, W 2018, 'Nonlinear vibration and dynamic buckling analyses of sandwich functionally graded porous plate with graphene platelet reinforcement resting on Winkler–Pasternak elastic foundation', International Journal of Mechanical Sciences, vol. 148, pp. 596-610.
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The nonlinear vibration and the dynamic buckling of a graphene platelet reinforced sandwich functionally graded porous (GPL-SFGP) plate are thoroughly investigated in this paper. The investigated GPL-SFGP plate consists of two metal face layers and a functionally graded porous core with graphene platelet reinforcement. The effects of the Winkler–Pasternak elastic foundation, thermal environment and damping are incorporated. The open-cell metal foam model is implemented to model the mechanical properties of the porous core. Axial compressive stress is applied on the GPL-SFGP plate by exerting various compressive loading speeds at one edge of the plate. Grounded on the classical plate theory, both motion and geometric compatibility equations of the plate are deduced by introducing the Von Kármán strain-displacement relationship and stress function. Both the Galerkin and the fourth-order Runge–Kutta methods are implemented to solve the governing equation of the dynamic system. Meticulously designed numerical experiments are conducted to identify the critical influential factors of the dynamic stability of the GPL-SFGP plate. The influences of loading speed, damping ratio, temperature variation, initial imperfection, elastic foundation parameters, porosity, GPL weight fraction and the dimensions of the GPL on the overall dynamic stability of the GPL-SFGP plate are evidently demonstrated.

Li, S, Han, K, Ansari, N, Bao, Q, Hu, D, Liu, J, Yu, S & Zhu, Z 2018, 'Improving SDN Scalability With Protocol-Oblivious Source Routing: A System-Level Study', IEEE Transactions on Network and Service Management, vol. 15, no. 1, pp. 275-288.
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Software-defined networking (SDN) has been considered as a break-through technology for the next-generation Internet. It enables fine-grained flow control that can make networks more flexible and programmable. However, this might lead to scalability issues due to the possible flow state explosion in SDN switches. SDN-based source routing can reduce the volume of flow-tables significantly by encoding the path information into packet headers. In this paper, we leverage the protocol-oblivious forwarding instruction set to design protocol-oblivious source routing (POSR), which is a protocol-independent, bandwidth-efficient, and flow-table-saving packet forwarding technique. We lay out the packet format for POSR, come up with the packet processing pipelines for realizing unicast, multicast, and link failure recovery, and implement POSR in a protocol-oblivious forwarding-enabled SDN network system. Experiments are then performed in a network testbed, which consists of 14 stand-alone SDN switches, to validate the advantages of POSR. Specifically, we compare POSR with several OpenFlow-based benchmarks for unicast, multicast, and link failure recovery, and confirm that POSR can reduce flow-table utilization effectively, shorten path setup latency and expedite link failure recovery.

Li, S, Ni, W, Sung, CK & Hedley, M 2018, 'Recent advances on cooperative wireless localization and their application in inhomogeneous propagation environments', Computer Networks, vol. 142, pp. 253-271.
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© 2018 Elsevier B.V. In this survey, we review recent advances on cooperative localization techniques and identify critical challenges in realistic cooperative localization systems. Particularly, we focus on the inhomogeneity of radio propagation environments, which has substantial impact on the accuracy of positioning systems that assume a homogeneous propagation model. Popular cooperative localization algorithms based on maximum-likelihood estimation, convex relaxation and optimization, and message passing are surveyed, with more emphasis placed on Received Signal Strength (RSS) based approaches due to their potential application in low cost devices. It is shown that most existing algorithms are based on the assumption of a propagation environment with a priori known spatially invariant propagation models. The extension of existing algorithms to capture the inhomogeneity of propagation environments are studied.

Li, T, Zhou, H, Luo, H & Yu, S 2018, 'SERvICE: A Software Defined Framework for Integrated Space-Terrestrial Satellite Communication', IEEE Transactions on Mobile Computing, vol. 17, no. 3, pp. 703-716.
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© 2017 IEEE. The existing satellite communication systems suffer from traditional design, such as slow configuration, inflexible traffic engineering, and coarse-grained Quality of Service (QoS) guarantee. To address these issues, in this paper, we propose SERvICE, a Software dEfined fRamework for Integrated spaCe-tErrestrial satellite Communication, based on Software Defined Network (SDN) and Network Function Virtualization (NFV). We first introduce the three planes of SERvICE, Management Plane, Control Plane, and Forwarding Plane. The framework is designed to achieve flexible satellite network traffic engineering and fine-grained QoS guarantee. We analyze the agility of the space component of SERvICE. Then, we give a description of the implementation of the prototype with the help of the Delay Tolerant Network (DTN) and OpenFlow. We conduct two experiments to validate the feasibility of SERvICE and the functionality of the prototype. In addition, we propose two heuristic algorithms, namely the QoS-oriented Satellite Routing (QSR) algorithm and the QoS-oriented Bandwidth Allocation (QBA) algorithm, to guarantee the QoS requirement of multiple users. The algorithms are also evaluated in the prototype. The experimental results show the efficiency of the proposed algorithms in terms of file transmission delay and transmission rate.

Li, W, Luo, Z, Long, C, Huang, Z, Huang, L, Yu, Q & Sun, Z 2018, 'Mechanical Strengths and Microstructures of Recycled Aggregate Concrete Incorporating Nanoparticles', Advances in Civil Engineering Materials, vol. 7, no. 1, pp. 188-205.
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Abstract The influences of nanoparticles on the mechanical properties and microstructures of recycled aggregate concrete (RAC) were investigated in this study. The compressive and flexural strengths of RAC with different dosages of nanoSiO2 (NS) and nanoCaCO3 (NC) were tested. Both the scanning electron microscopy (SEM) and mercury intrusion porosimetry (MIP) techniques were applied to analyze the microstructures and porosity of interfacial transition zones (ITZs) in RAC. Based on the comparison on compressive strength and flexural strength, the NS is more effective than the NC for improving the mechanical properties of RAC. Dispersion of NC particles by a superplasticizer can somewhat improve the early-age strength of RAC but is unlikely to enhance the 28-day mechanical strengths. This may be attributed to the better dispersion and pozzolanic activity of NS compared to NC. The results show that a denser microstructure and a reduction of porosity within ITZs were observed by incorporating NS, which occurred along with the improvement of the mechanical strengths of RAC. Moreover, the NS-modified RAC exhibits less total porosity than the NC-modified RAC. The NS-modified RAC mainly contains small size pores, but the NC-modified RAC has more large pores than the NS-modified RAC, which has negative effects on the mechanical properties of RAC.

Li, W, Luo, Z, Sun, Z, Hu, Y & Duan, WH 2018, 'Numerical modelling of plastic–damage response and crack propagation in RAC under uniaxial loading', Magazine of Concrete Research, vol. 70, no. 9, pp. 459-472.
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In order to better understand the failure mechanism of recycled aggregate concrete (RAC), a numerical study on modelled recycled aggregate concrete (MRAC) was conducted to investigate the plastic–damage response and crack propagation under uniaxial loading. In the numerical model, the nanoscale mechanical properties and the thickness of the interfacial transition zones (ITZs) were obtained based on advanced nanoindentation. The constitutive relationships of new and old cement mortars and corresponding ITZs were developed using plastic–damage constitutive relationships. The effects of the relative mechanical properties between new and old cement mortars on the failure pattern and stress–strain response of MRAC were investigated. After calibration and verification with the uniaxial compression test, the numerical model was found to be able to reveal the failure pattern and stress–strain curves of MRAC under uniaxial tension. The results showed that microcracks usually first appear around the weak new and old ITZs, and then propagate into the new and old cement mortars. With an increase in the relative strength between new and old cement mortars, the microcrack initiation locations gradually shifted from the new ITZs to the old ITZs. Therefore, the numerical results can provide insight into the modification of RAC using mix design optimisation and ITZ enhancement.

Li, W, Luo, Z, Wu, C & Duan, WH 2018, 'Impact performances of steel tube-confined recycled aggregate concrete (STCRAC) after exposure to elevated temperatures', Cement and Concrete Composites, vol. 86, pp. 87-97.
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© 2017 Elsevier Ltd The impact behaviours of steel tube-confined recycled aggregate concrete (STCRAC) following exposure to elevated temperatures of 20 °C, 200 °C, 500 °C and 700 °C were experimentally investigated using a 100 mm-diameter split Hopkinson pressure bar (SHPB). The recycled coarse aggregate (RCA) replacement ratios were set as 0, 50% and 100%. The effect of RCA replacement ratio and exposure temperature on the impact properties of STCRAC were analysed in terms of failure modes, stress-strain time history curve and dynamic increase factor (DIF). The results show that the fire-damaged STCRAC can maintain its integrity during impact load. However, there were evident degradations in the dynamic behaviour of STCRAC after exposure to high temperatures of 500 °C and 700 °C. The ultimate impact strength, impact secant modulus and residual impact strength of STCRAC obviously decreased because of the damage due to high temperature exposure. But the degradations of both the ultimate impact strength and impact secant modulus of STCRAC under impact loading were less severe than those under quasi-static loading. The remaining strength factor and the DIF tended to increase with the raise of the elevated temperatures. Overall, during the impact loading, the fire-deteriorated STCRAC exhibited excellent impact behaviour.

Li, W, Ni, W, Liu, D, Liu, RP & Luo, S 2018, 'Unified Ciphertext-Policy Weighted Attribute-Based Encryption for Sharing Data in Cloud Computing', Applied Sciences, vol. 8, no. 12, pp. 2519-2519.
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With the rapid development of cloud computing, it is playing an increasingly important role in data sharing. Meanwhile, attribute-based encryption (ABE) has been an effective way to share data securely in cloud computing. In real circumstances, there is often a mutual access sub-policy in different providers’ access policies, and the significance of each attribute is usual diverse. In this paper, a secure and efficient data-sharing scheme in cloud computing, which is called unified ciphertext-policy weighted attribute-based encryption (UCP-WABE), is proposed. The weighted attribute authority assigns weights to attributes depending on their importance. The mutual information extractor extracts the mutual access sub-policy and generates the mutual information. Thus, UCP-WABE lowers the total encryption time cost of multiple providers. We prove that UCP-WABE is selectively secure on the basis of the security of ciphertext-policy weighted attribute-based encryption (CP-WABE). Additionally, the results of the implementation shows that UCP-WABE is efficient in terms of time.

Li, X, Liu, YM, Li, WG, Li, CY, Sanjayan, JG, Duan, WH & Li, Z 2018, 'Corrigendum to “Effects of graphene oxide agglomerates on workability, hydration, microstructure and compressive strength of cement paste” [Constr. Build. Mater. 145 (2017) 402–410]', Construction and Building Materials, vol. 179, pp. 537-538.
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Li, X, Mei, Q, Yan, X, Dong, B, Dai, X, Yu, L, Wang, Y, Ding, G, Yu, F & Zhou, J 2018, 'Molecular characteristics of the refractory organic matter in the anaerobic and aerobic digestates of sewage sludge', RSC Advances, vol. 8, no. 58, pp. 33138-33148.
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The chemical characteristics of the refractory organic matter in anaerobic and aerobic digestates are hardly known although they are significant for further improving the degradation of organic matter during sludge digestion.

Li, X, Nie, L, Xu, H & Wang, X 2018, 'Collaborative Fall Detection Using Smart Phone and Kinect', Mobile Networks and Applications, vol. 23, no. 4, pp. 775-788.
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Li, XP, Ji, G, Eder, K, Yang, LM, Addad, A, Vleugels, J, Van Humbeeck, J, Cairney, JM & Kruth, JP 2018, 'Additive manufacturing of a novel alpha titanium alloy from commercially pure titanium with minor addition of Mo2C', Materialia, vol. 4, pp. 227-236.
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Li, Y & Ying, M 2018, 'Algorithmic analysis of termination problems for quantum programs.', Proc. ACM Program. Lang., vol. 2, pp. 35:1-35:1.
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Li, Y, Li, L, Zhang, G, Wang, Y, Chen, H, Kong, R, Pan, S & Sun, B 2018, 'Crucial microRNAs and genes in metformin’s anti-pancreatic cancer effect explored by microRNA-mRNA integrated analysis', Investigational New Drugs, vol. 36, no. 1, pp. 20-27.
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Li, Z, Nie, F, Chang, X, Nie, L, Zhang, H & Yang, Y 2018, 'Rank-Constrained Spectral Clustering With Flexible Embedding', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6073-6082.
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© 2012 IEEE. Spectral clustering (SC) has been proven to be effective in various applications. However, the learning scheme of SC is suboptimal in that it learns the cluster indicator from a fixed graph structure, which usually requires a rounding procedure to further partition the data. Also, the obtained cluster number cannot reflect the ground truth number of connected components in the graph. To alleviate these drawbacks, we propose a rank-constrained SC with flexible embedding framework. Specifically, an adaptive probabilistic neighborhood learning process is employed to recover the block-diagonal affinity matrix of an ideal graph. Meanwhile, a flexible embedding scheme is learned to unravel the intrinsic cluster structure in low-dimensional subspace, where the irrelevant information and noise in high-dimensional data have been effectively suppressed. The proposed method is superior to previous SC methods in that: 1) the block-diagonal affinity matrix learned simultaneously with the adaptive graph construction process, more explicitly induces the cluster membership without further discretization; 2) the number of clusters is guaranteed to converge to the ground truth via a rank constraint on the Laplacian matrix; and 3) the mismatch between the embedded feature and the projected feature allows more freedom for finding the proper cluster structure in the low-dimensional subspace as well as learning the corresponding projection matrix. Experimental results on both synthetic and real-world data sets demonstrate the promising performance of the proposed algorithm.

Li, Z, Nie, F, Chang, X, Yang, Y, Zhang, C & Sebe, N 2018, 'Dynamic Affinity Graph Construction for Spectral Clustering Using Multiple Features', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6323-6332.
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© 2012 IEEE. Spectral clustering (SC) has been widely applied to various computer vision tasks, where the key is to construct a robust affinity matrix for data partitioning. With the increase in visual features, conventional SC methods are facing two challenges: 1) how to effectively generate an affinity matrix based on multiple features? and 2) how to deal with high-dimensional visual features which could be redundant? To address these issues mentioned earlier, we present a new approach to: 1) learn a robust affinity matrix using multiple features, allowing us to simultaneously determine optimal weights for each feature; and 2) decide a set of optimal projection matrixes, one for each feature, that decide the lower dimensional space, as well as the optimal affinity weight of each data pair in the lower dimensional space. There are two major advantages of our new approach over the existing clustering techniques. First, our approach assigns affinity weights for data points on a per-data-pair basis. The learning procedure avoids the explicit specification of the size of the neighborhood in the affinity matrix, and the bandwidth parameter required to compute the Gaussian kernel, both of which are sensitive and yet difficult to determine beforehand. Second, the affinity weights are based on the distances in a lower dimensional space, while the low-dimensional space is inferred according to the optimized affinity weights. Both variables are jointly optimized so as to leverage mutual benefits. The experimental results outperform the compared alternatives, which indicate that the proposed method is effective in simultaneously learning the affinity graph and feature fusion, resulting in better clustering results.

Lian, D, Zheng, K, Ge, Y, Cao, L, Chen, E & Xie, X 2018, 'GeoMF++', ACM Transactions on Information Systems, vol. 36, no. 3, pp. 1-29.
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Location recommendation is an important means to help people discover attractive locations. However, extreme sparsity of user-location matrices leads to a severe challenge, so it is necessary to take implicit feedback characteristics of user mobility data into account and leverage the location’s spatial information. To this end, based on previously developed GeoMF, we propose a scalable and flexible framework, dubbed GeoMF++, for joint geographical modeling and implicit feedback-based matrix factorization. We then develop an efficient optimization algorithm for parameter learning, which scales linearly with data size and the total number of neighbor grids of all locations. GeoMF++ can be well explained from two perspectives. First, it subsumes two-dimensional kernel density estimation so that it captures spatial clustering phenomenon in user mobility data; Second, it is strongly connected with widely used neighbor additive models, graph Laplacian regularized models, and collective matrix factorization. Finally, we extensively evaluate GeoMF++ on two large-scale LBSN datasets. The experimental results show that GeoMF++ consistently outperforms the state-of-the-art and other competing baselines on both datasets in terms of NDCG and Recall. Besides, the efficiency studies show that GeoMF++ is much more scalable with the increase of data size and the dimension of latent space.

Liang, X & Wu, C 2018, 'Investigation on Thermal Conductivity of Steel Fiber Reinforced Concrete Using Mesoscale Modeling', International Journal of Thermophysics, vol. 39, no. 12.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. A mesoscale model was developed to investigate the effect of steel fiber on the thermal conductivity of steel fiber-reinforced concrete (SFRC). Delaunay triangulation was employed to generate the unstructured mesh for SFRC materials. The model was validated using the existing experimental data. Then, it was used to study how model thickness affected simulation outcomes of thermal conductivity of models with different fiber lengths, by which an appropriate thickness was determined for the later analyses. The validated and optimized model was applied to the study of relationships between thermal conductivity and factors such as fiber content, fiber aspect ratio and different parts of an SFRC block by conducting steady-state heat analyses with the finite element analysis software ANSYS. The simulation results reveal that adding steel fiber increases thermal conductivity considerably, while fiber aspect ratio only has an insignificant effect. Besides, the presence of steel fibers has an obvious impact on the distribution of temperature and heat flux vector of the SFRC blocks.

Liang, X & Wu, C 2018, 'Meso-scale modelling of steel fibre reinforced concrete with high strength', Construction and Building Materials, vol. 165, pp. 187-198.
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© 2018 Based on Delaunay triangulation, a 3D meso-scale model is successfully developed and verified. This approach modelling fibre and concrete separately and linking them with slide line contact has the capability to truly reflect the interfacial behaviour of fibre and mortar, and thus achieve high fidelity of numerical simulations. However, meso-scale modelling usually means tremendous complexity and long computational time. This paper proposes a model to achieve relatively high computation efficiency, as well as accuracy. Besides, the model has the potential to deal with small specimens cut from steel fibre reinforced concrete (SFRC) blocks.

Liang, X, Wu, C, Su, Y, Chen, Z & Li, Z 2018, 'Development of ultra-high performance concrete with high fire resistance', Construction and Building Materials, vol. 179, pp. 400-412.
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© 2018 Elsevier Ltd Fire or high temperature is a big challenge to ultra-high performance concrete (UHPC). Strength loss of UHPCs can reach up to 80% after exposure to 800 °C. In this study, a total of six UHPC mixtures were designed and tested after subjected to elevated temperatures up to 1000 °C. The effects of aggregate type, fibre type and heating rate were investigated. Residual compressive strengths and stress-strain relationships were studied. Besides, attention was paid to explosive spalling since UHPCs are usually of compact structure and thus more vulnerable to explosive spalling than other concretes. Scanning electron microscope (SEM) analysis was conducted to help understand the mechanism of variation of internal structure under different temperatures. It was found the mixture containing steel slag and hybrid fibre had excellent fire resistance. After being subjected to 1000 °C, this mixture retained a residual compressive strength of 112.8 MPa or a relative value of 69%.

Liao, H, Xu, Z, Herrera, F & Merigó, JM 2018, 'Editorial Message: Special Issue on Hesitant Fuzzy Linguistic Decision Making: Algorithms, Theory and Applications', International Journal of Fuzzy Systems, vol. 20, no. 7, pp. 2083-2083.
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Lim, S, Park, MJ, Phuntsho, S, Mai-Prochnow, A, Murphy, AB, Seo, D & Shon, H 2018, 'Dual-layered nanocomposite membrane incorporating graphene oxide and halloysite nanotube for high osmotic power density and fouling resistance', Journal of Membrane Science, vol. 564, pp. 382-393.
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© 2018 Elsevier B.V. This study introduces a thin-film composite (TFC) membrane with a dual-layered nanocomposite substrate synthesized using a dual-blade casting approach for application in osmotic power generation by the pressure-retarded osmosis (PRO) process. The approach incorporates halloysite nanotubes (HNTs) into the bottom polymer substrate layer and graphene oxide (GO) on the top layer substrate, on which a thin polyamide active layer is formed. The fabricated membrane substrate showed highly desirable membrane substrate properties such as a high porosity, opened-bottom surface, suitable top-skin surface morphology for subsequent active layer formation and high mechanical strength, which are essential for high-performance PRO processes. At a GO loading of 0.25 wt% and HNT loading of 4 wt%, the power density (PD) of the nanocomposite membrane was 16.7 W/m2 and the specific reverse solute flux (SRSF) was 2.4 g/L operated at 21 bar applied pressure using 1 M NaCl as draw solution and deionized water as feed, which is significantly higher than the those for a single-layered or commercial PRO membrane. This membrane performance was observed to be stable in the pressure cycle test and under long-term operation. The membrane substrate with HNTs incorporated exhibited high fouling resistance to sodium alginate and colloidal silica foulants, with the PD decreasing by 17% after 3 h of operation, compared to a membrane substrate without HNTs and commercial PRO membranes, which decreased by 26% and 57%, respectively. A fluorescence microscope study of the membranes subjected to feed water containing Escherichia coli confirmed the good antibacterial properties of the dual-layered TFC membrane. The study provides an attractive alternative approach for developing PRO membranes with high PD and fouling resistance.

Lin, C-T, Chiu, T-C, Wang, Y-K, Chuang, C-H & Gramann, K 2018, 'Granger causal connectivity dissociates navigation networks that subserve allocentric and egocentric path integration', Brain Research, vol. 1679, pp. 91-100.
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© 2017 Elsevier B.V. Studies on spatial navigation demonstrate a significant role of the retrosplenial complex (RSC) in the transformation of egocentric and allocentric information into complementary spatial reference frames (SRFs). The tight anatomical connections of the RSC with a wide range of other cortical regions processing spatial information support its vital role within the human navigation network. To better understand how different areas of the navigational network interact, we investigated the dynamic causal interactions of brain regions involved in solving a virtual navigation task. EEG signals were decomposed by independent component analysis (ICA) and subsequently examined for information flow between clusters of independent components (ICs) using direct short-time directed transfer function (sdDTF). The results revealed information flow between the anterior cingulate cortex and the left prefrontal cortex in the theta (4–7 Hz) frequency band and between the prefrontal, motor, parietal, and occipital cortices as well as the RSC in the alpha (8–13 Hz) frequency band. When participants prefered to use distinct reference frames (egocentric vs. allocentric) during navigation was considered, a dominant occipito-parieto–RSC network was identified in allocentric navigators. These results are in line with the assumption that the RSC, parietal, and occipital cortices are involved in transforming egocentric visual-spatial information into an allocentric reference frame. Moreover, the RSC demonstrated the strongest causal flow during changes in orientation, suggesting that this structure directly provides information on heading changes in humans.

Lin, C-T, Hsieh, T-Y, Liu, Y-T, Lin, Y-Y, Fang, C-N, Wang, Y-K, Yen, G, Pal, NR & Chuang, C-H 2018, 'Minority Oversampling in Kernel Adaptive Subspaces for Class Imbalanced Datasets', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 5, pp. 950-962.
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© 1989-2012 IEEE. The class imbalance problem in machine learning occurs when certain classes are underrepresented relative to the others, leading to a learning bias toward the majority classes. To cope with the skewed class distribution, many learning methods featuring minority oversampling have been proposed, which are proved to be effective. To reduce information loss during feature space projection, this study proposes a novel oversampling algorithm, named minority oversampling in kernel adaptive subspaces (MOKAS), which exploits the invariant feature extraction capability of a kernel version of the adaptive subspace self-organizing maps. The synthetic instances are generated from well-trained subspaces and then their pre-images are reconstructed in the input space. Additionally, these instances characterize nonlinear structures present in the minority class data distribution and help the learning algorithms to counterbalance the skewed class distribution in a desirable manner. Experimental results on both real and synthetic data show that the proposed MOKAS is capable of modeling complex data distribution and outperforms a set of state-of-the-art oversampling algorithms.

Lin, C-T, Huang, C-S, Yang, W-Y, Singh, AK, Chuang, C-H & Wang, Y-K 2018, 'Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering', Journal of Healthcare Engineering, vol. 2018, pp. 1-11.
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Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research.

Lin, C-T, King, J-T, Fan, J-W, Appaji, A & Prasad, M 2018, 'The Influence of Acute Stress on Brain Dynamics During Task Switching Activities', IEEE Access, vol. 6, pp. 3249-3255.
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© 2013 IEEE. Task switching is a common method to investigate executive functions such as working memory and attention. This paper investigates the effect of acute stress on brain activity using task switching. Surprisingly few studies have been conducted in this area. There is behavioral and physiological evidence to indicate that acute stress makes the participants more tense which results in a better performance. In this current study, under stressful conditions, the participants gave quick responses with high accuracy. However, unexpected results were found in relation to salivary cortisol. Furthermore, the electroencephalogram results showed that acute stress was pronounced at the frontal and parietal midline cortex, especially on the theta, alpha, and gamma bands. One possible explanation for these results may be that the participants changed their strategy in relation to executive functions during stressful conditions by paying more attention which resulted in a higher working memory capacity which enhanced performance during the task switching.

Lin, C-T, King, J-T, Singh, AK, Gupta, A, Ma, Z, Lin, J-W, Machado, AMC, Appaji, A & Prasad, M 2018, 'Voice Navigation Effects on Real-World Lane Change Driving Analysis Using an Electroencephalogram', IEEE Access, vol. 6, pp. 26483-26492.
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© 2018 IEEE. Improving the degree of assistance given by in-car navigation systems is an important issue for the safety of both drivers and passengers. There is a vast body of research that assesses the usability and interfaces of the existing navigation systems but very few investigations study the impact on the brain activity based on navigation-based driving. In this paper, a real-world experiment is designed to acquire the electroencephalography (EEG) and in-car information to analyze the dynamic brain activity while the driver is performing the lane-changing task based on the auditory instructions from an in-car navigation system. The results show that auditory cues can influence the speed and increase the frontal EEG delta and beta power, which is related to motor preparation and decision making during a lane change. However, there were no significant results on the alpha power. A better lane-change assessment can be obtained using specific vehicle information (lateral acceleration and heading angle) with EEG features for future naturalized driving study.

Lin, C-T, Nascimben, M, King, J-T & Wang, Y-K 2018, 'Task-related EEG and HRV entropy factors under different real-world fatigue scenarios', Neurocomputing, vol. 311, pp. 24-31.
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© 2018 Elsevier B.V. We classified the alertness levels of 17 subjects in different experimental sessions in a six-month longitudinal study based on a daily sampling system and related alertness to performance on a psychomotor vigilance task (PVT). As to our best knowledge, this is the first EEG-based longitudinal study for real-world fatigue. Alertness and PVT performance showed a monotonically increasing relationship. Moreover, we identified two measures in the entropy domain from electroencephalography (EEG) and heart rate variability (HRV) signals that were able to identify the extreme classes of PVT performers. Wiener entropy on selected leads from the frontal-parietal axis was able to discriminate the group of best performers. Sample entropy from the HRV signal was able to identify the worst performers. This joint EEG-HRV quantification provides complementary indexes to indicate more reliable human performance.

Lin, C-T, Prasad, M, Chung, C-H, Puthal, D, El-Sayed, H, Sankar, S, Wang, Y-K, Singh, J & Sangaiah, AK 2018, 'IoT-Based Wireless Polysomnography Intelligent System for Sleep Monitoring', IEEE Access, vol. 6, pp. 405-414.
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© 2013 IEEE. Polysomnography (PSG) is considered the gold standard in the diagnosis of obstructive sleep apnea (OSA). The diagnosis of OSA requires an overnight sleep experiment in a laboratory. However, due to limitations in relation to the number of labs and beds available, patients often need to wait a long time before being diagnosed and eventually treated. In addition, the unfamiliar environment and restricted mobility when a patient is being tested with a polysomnogram may disturb their sleep, resulting in an incomplete or corrupted test. Therefore, it is posed that a PSG conducted in the patient's home would be more reliable and convenient. The Internet of Things (IoT) plays a vital role in the e-Health system. In this paper, we implement an IoT-based wireless polysomnography system for sleep monitoring, which utilizes a battery-powered, miniature, wireless, portable, and multipurpose recorder. A Java-based PSG recording program in the personal computer is designed to save several bio-signals and transfer them into the European data format. These PSG records can be used to determine a patient's sleep stages and diagnose OSA. This system is portable, lightweight, and has low power-consumption. To demonstrate the feasibility of the proposed PSG system, a comparison was made between the standard PSG-Alice 5 Diagnostic Sleep System and the proposed system. Several healthy volunteer patients participated in the PSG experiment and were monitored by both the standard PSG-Alice 5 Diagnostic Sleep System and the proposed system simultaneously, under the supervision of specialists at the Sleep Laboratory in Taipei Veteran General Hospital. A comparison of the results of the time-domain waveform and sleep stage of the two systems shows that the proposed system is reliable and can be applied in practice. The proposed system can facilitate the long-Term tracing and research of personal sleep monitoring at home.

Lin, J-Y, Wong, S-W, Wu, Y-M, Zhu, L, Yang, Y & He, Y 2018, 'A New Concept and Approach for Integration of Three-State Cavity Diplexer Based on Triple-Mode Resonators', IEEE Transactions on Microwave Theory and Techniques, vol. 66, no. 12, pp. 5272-5279.
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Lin, J-Y, Wong, S-W, Zhu, L, Yang, Y, Zhu, X, Xie, Z-M & He, Y 2018, 'A Dual-Functional Triple-Mode Cavity Resonator With the Integration of Filters and Antennas', IEEE Transactions on Antennas and Propagation, vol. 66, no. 5, pp. 2589-2593.
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Lin, M, Shan, S, Liu, P, Ma, L, Huang, L, Yang, M, Lawson, T, Wang, Z, Huang, Z, Shi, B, Yan, L & Liu, Y 2018, 'Hydroxyl-Functional Groups on Graphene Trigger the Targeted Delivery of Antitumor Drugs', Journal of Biomedical Nanotechnology, vol. 14, no. 8, pp. 1420-1429.
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© 2018 American Scientific Publishers. An efficient and targeted treatment for tumor cells is demonstrated. This targeting is based upon the strong affinity between hydroxyl-functional groups on graphene and acidic tumors. The hydroxylated graphene (GOH) with a unique 2D architecture further improve the targeting capacity of the system via an enhanced permeability and retention (EPR) process. Polyethylene glycol (PEG) was employed for better biocompatibility and the antitumor drug doxorubicin (DOX) was then incorporated. These additions created a biocompatible system with a superior pH-dependent drug release property. Its proficiency was due to its ability to pass through cell membranes via a process of endocytosis and exocytosis. The results from a Transwell co-culture system discovered that the PEG-GOH-DOX system had a large impact on tumor cell viability (less than 10% survived after treatment) and little influence on normal cells (more than 80% survived). An in vitro 3D tumor model study demonstrated that the size of the PEG-GOH-DOX treated tumor was 50% less than that of the pristine DOX treated tumor. In vivo data indicated that the PEG-GOH-DOX system was able to inhibit the size of tumors by a factor of 6.5 when compared to the untreated tumors.

Lin, S, Yu, J, Ni, W & Liu, R 2018, 'Decoupling 5G Network Control: Centralised Coordination and Distributed Adaptation', International Journal of Computers Communications & Control, vol. 13, no. 2, pp. 192-204.
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Fifth generation mobile networks (5G) will be featured by miniaturised cells and massive dense deployment. Traditional centralised network control cannot adapt to high signalling delay, and is therefore not scalable for future 5G networks.To address this issue, we adopt the software-defined networking (SDN) approach of decoupled network control and data transmission. In particular, delay-sensitive interference suppression for data transmission is decoupled from delay-tolerant topology control and base station coordination. This substantially alleviates the requirement of network control on delay and complexity, hence simplifying 5G control plane design, reducing signalling overhead, and enhancing network scalability. Case studies show that our decoupled network control is effective for timely interference mitigation and reliable topology management. The stability and scalability of our approach are also demonstrated.

Liu, A, Lu, J, Liu, F & Zhang, G 2018, 'Accumulating regional density dissimilarity for concept drift detection in data streams', Pattern Recognition, vol. 76, pp. 256-272.
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© 2017 Elsevier Ltd In a non-stationary environment, newly received data may have different knowledge patterns from the data used to train learning models. As time passes, a learning model's performance may become increasingly unreliable. This problem is known as concept drift and is a common issue in real-world domains. Concept drift detection has attracted increasing attention in recent years. However, very few existing methods pay attention to small regional drifts, and their accuracy may vary due to differing statistical significance tests. This paper presents a novel concept drift detection method, based on regional-density estimation, named nearest neighbor-based density variation identification (NN-DVI). It consists of three components. The first is a k-nearest neighbor-based space-partitioning schema (NNPS), which transforms unmeasurable discrete data instances into a set of shared subspaces for density estimation. The second is a distance function that accumulates the density discrepancies in these subspaces and quantifies the overall differences. The third component is a tailored statistical significance test by which the confidence interval of a concept drift can be accurately determined. The distance applied in NN-DVI is sensitive to regional drift and has been proven to follow a normal distribution. As a result, the NN-DVI's accuracy and false-alarm rate are statistically guaranteed. Additionally, several benchmarks have been used to evaluate the method, including both synthetic and real-world datasets. The overall results show that NN-DVI has better performance in terms of addressing problems related to concept drift-detection.

Liu, B, Zhou, W, Gao, L, Zhou, H, Luan, TH & Wen, S 2018, 'Malware Propagations in Wireless Ad Hoc Networks', IEEE Transactions on Dependable and Secure Computing, vol. 15, no. 6, pp. 1016-1026.
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© 2004-2012 IEEE. Accurate malware propagation modeling in wireless ad hoc networks (WANETs) represents a fundamental and open research issue which shows distinguished challenges due to complicated access competition, severe channel interference, and dynamic connectivity. As an effort towards the issue, in this paper, we investigate the malware propagation under two spread schemes including Unicast and Broadcast, in Spread Mode and Communication Mode, respectively. We highlight our contributions in three-fold in the light of previous literature works. First, a bound of malware infection rate for each scheme is provided by applying the wireless network capacity theories. Second, the impact of mobility on malware propagations has been studied. Third, discussion of the relationship between different schemes and practical applications is provided. Numerical simulations and detailed performance analysis show that the Broadcast Scheme with Spread Mode is most dangerous in the sense of malware propagation speed in WANETs, and mobility will greatly increase the risk further. The results achieved in this paper not only provide insights on the malware propagation characteristics in WANETs, but also serve as fundamental guidelines on designing defense schemes.

Liu, B, Zhou, W, Zhu, T, Gao, L & Xiang, Y 2018, 'Location Privacy and Its Applications: A Systematic Study', IEEE Access, vol. 6, pp. 17606-17624.
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© 2013 IEEE. This paper surveys the current research status of location privacy issues in mobile applications. The survey spans five aspects of study: the definition of location privacy, attacks and adversaries, mechanisms to preserve the privacy of locations, location privacy metrics, and the current status of location-based applications. Through this comprehensive review, all the interrelated aspects of location privacy are integrated into a unified framework. Additionally, the current research progress in each area is reviewed individually, and the links between existing academic research and its practical applications are identified. This in-depth analysis of the current state-of-play in location privacy is designed to provide a solid foundation for future studies in the field.

Liu, C, Li, X, Lei, G, Ma, B, Chen, L, Wang, Y & Zhu, J 2018, 'Performance Evaluation of an Axial Flux Claw Pole Machine With Soft Magnetic Composite Cores', IEEE Transactions on Applied Superconductivity, vol. 28, no. 3, pp. 1-5.
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© 2017 IEEE. By using the powder metallurgy technology and the magnetic isotropy characteristic of the soft magnet composite (SMC) material, various kinds of permanent magnet machines can be designed and fabricated easily. However, the torque density of permanent magnet machines with SMC cores are generally lower than those with silicon steels, with the traditional machine topology, since the permeability of the SMC is much lower than that of silicon steels. To develop the potential of SMC in high-performance drive applications, we propose a novel axial flux claw pole machine (AFCPM) with SMC cores. To eliminate the unwanted axial force in the AFCPM, the two-phase configuration concept is adopted, both the configuration of the stator-rotor-stator and the rotor-stator-rotor AFCPM are designed, analyzed, and compared. Based on the 3-D finite-element method, it can be found that the AFCPM with the configuration of the stator-rotor-stator can have very low cogging torque and torque ripple; moreover, since the rotor is in between of the two stator cores, the unbalanced axial force has been decreased greatly. On the other hand, the two-phases AFCPM with the rotor-stator-rotor can have the highest torque density and efficiency.

Liu, D, Yang, L, He, X, Wang, R & Luo, Q 2018, 'Atomistic-scale simulations of mechanical behavior of suspended single-walled carbon nanotube bundles under nanoprojectile impact', Computational Materials Science, vol. 142, pp. 237-243.
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Liu, F, Lu, J & Zhang, G 2018, 'Unsupervised Heterogeneous Domain Adaptation via Shared Fuzzy Equivalence Relations', IEEE Transactions on Fuzzy Systems, vol. 26, no. 6, pp. 3555-3568.
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Liu, H & Zhang, J-M 2018, 'Investigation on structure, electronic and magnetic properties of Cr doped (ZnO)12 clusters: First-principles calculations', Physica E: Low-dimensional Systems and Nanostructures, vol. 99, pp. 51-57.
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Liu, H, Wei, S, Zhi, L, Liu, L, Cao, T, Wang, S, Chen, Q & Liu, D 2018, 'Synovial GATA1 mediates rheumatoid arthritis progression via transcriptional activation of NOS2 signaling', Microbiology and Immunology, vol. 62, no. 9, pp. 594-606.
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ABSTRACTTranscriptional regulation of inducible nitric oxide synthase (iNOS) is critically involved in the pathogenesis and progression of rheumatoid arthritis (RA); however, the specific transcription factors that control this process remain largely unidentified. In the present study, it was discovered that expression of the key erythroid factor, globin transcription factor 1 (GATA1), is significantly greater in human RA synovial tissues than in osteoarthritis (OA) tissues. IL 6 was found to induce synovial GATA1 expression in a signal transducer and activator of transcription 3‐dependent manner. Functionally, knockdown of GATA1 expression using specific small interfering RNA treatment was found to compromise immunoreaction‐elicited expression of proinflammatory cytokines and thus impair invasiveness of the human fibroblast‐like synovial cell line MH7A, whereas introduction of exogenous GATA1 was found to promote production of proinflammatory cytokines, leading to greater aggressiveness of MH7A cells. Mechanistically, GATA1 acts as the transcriptional coactivator of NOS2 (the gene encoding iNOS) transcription. Collectively, these data suggest that synovial GATA1 is an essential contributor to development and exacerbation of RA, presumably by inducing NOS2 transcription.

Liu, J, Hossain, MJ, Lu, J, Rafi, FHM & Li, H 2018, 'A hybrid AC/DC microgrid control system based on a virtual synchronous generator for smooth transient performances', Electric Power Systems Research, vol. 162, pp. 169-182.
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This paper presents a high-performance control strategy to support an optimised transient performance for a hybrid AC/DC microgrid system based on an improved virtual synchronous generator (VSG). The standard VSG is modified and an improved control strategy is developed. A pre-synchronization controller is embedded within the improved VSG controller for grid-connection use. In addition, this paper builds the small-signal model for the improved VSG controller in order to analyse the system's stability. A controller for the battery energy storage system is developed in order to assist the power output of the hybrid microgrid. The microgrid system is designed in a MATLAB/SIMULINK simulation environment based on the under-construction hybrid AC/DC microgrid system at Griffith University, Australia. A comparative study of droop control, conventional VSG control, and the improved VSG control is carried out under different possible transient cases. The pre-synchronization method is also tested. The simulation results show that the improved VSG control strategy is evidently able to ensure smooth variations in frequency, voltage and active power during transient cases.

Liu, J, Wu, C, Li, J, Su, Y & Chen, X 2018, 'Numerical investigation of reactive powder concrete reinforced with steel wire mesh against high-velocity projectile penetration', Construction and Building Materials, vol. 166, pp. 855-872.
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© 2018 Elsevier Ltd This paper numerically investigates the effects of steel wire mesh reinforcement on reactive powder concrete (RPC) targets subjected to high-velocity projectile penetration. A numerical model based on a computer program called LS-DYNA was validated with experimental data concerning the depth of penetration (DOP) and crater diameter of reinforced RPC targets. With the validated numerical model, a series of parametric studies are conducted to investigate how the variables of steel wire mesh reinforcement such as the configuration of steel wire meshes, number of layers, space between layers, space between steel wires per layer, as well as the diameter and tensile strength of steel wires affect DOP and crater diameter of reinforced RPC targets. Moreover, the energy evolution of projectile and steel wire meshes during the projectile penetration is discussed. Based on the results of parametric studies, an empirical equation derived from the simulation data is proposed to predict DOP of reinforced RPC targets.

Liu, J, Wu, C, Su, Y, Li, J, Shao, R, Chen, G & Liu, Z 2018, 'Experimental and numerical studies of ultra-high performance concrete targets against high-velocity projectile impacts', Engineering Structures, vol. 173, pp. 166-179.
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© 2018 Elsevier Ltd Ultra-high performance concrete (UHPC) which is known for high strength, high toughness, excellent ductility and good energy absorption capacity can be adopted as an ideal material in the impact resistant design of structures. In the present study, impact responses of UHPC targets with 3 vol-% ultra-high molecular weight polyethylene (UHMWPE) fibres and UHPC targets with 3 vol-% steel fibres are experimentally investigated subjected to high-velocity projectile penetration, and plain concrete targets under the same loading scenarios are also tested as control specimens for comparative purpose. In addition, numerical studies are conducted to simulate the projectile penetration process into UHPC targets with the assistance of a computer program LS-DYNA. The numerical results in terms of the depth of penetration (DOP) and crater diameter as well as projectile abrasions and damages are compared with the experimental results. Moreover, DOPs of these two types of UHPC targets obtained from tests are compared with the previously proposed empirical model.

Liu, K, Law, SS & Zhu, XQ 2018, 'A layered beam element for modeling de-bonding of steel bars in concrete and its detection using static measurements', Structural Control and Health Monitoring, vol. 25, no. 4, pp. e2142-e2142.
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Copyright © 2018 John Wiley & Sons, Ltd. In the formulation of finite elements, the variation of elemental internal forces and displacements are interpolated. The force interpolation functions are known to reproduce the variations of forces better than the interpolation functions on the displacements. Layered section beam model is not as complicated as the fiber model, and yet, it is much more accurate than ordinary beam model. The force-based finite element is revisited in this paper with its application in the numerical studies of a damage detection strategy for a reinforced concrete beam under static load. Two kinds of damages are studied including the cracking or other local damage of the concrete and the bonding between the concrete and the steel bar. Both kinds of damages in an element can be detected separately or in combinations with the proposed strategy. The force-based layered finite element is shown to be a practical, accurate, and efficient representation of the bonding damage of steel bars in concrete structures.

Liu, K, Li, Q, Wu, C, Li, X & Li, J 2018, 'A study of cut blasting for one-step raise excavation based on numerical simulation and field blast tests', International Journal of Rock Mechanics and Mining Sciences, vol. 109, pp. 91-104.
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© 2018 Elsevier Ltd Over the past several decades, raise excavation has been widely employed in underground mining, civil engineering and military engineering. One-step raise excavation with burn cuts, where all the boreholes are pre-drilled and detonated at one time and no workers need to be underneath the freshly blasted and dangerous ground, is an important and promising method in raise excavation. Cut parameters, especially the parameters of prime cut which used empty hole as a free surface and swelling space, have significant influence on the effect of raise formed. In this study, two small-scale experimental methods, spiral hole spacing method and observation hole method, are designed to determine the prime cut parameters such as hole spacing (L), stemming length (Ls1, Ls2) and air deck length (La) which are normally determined by empirical formula. In order to study the feasibility of the two methods, numerical analysis and experimental tests are conducted in V zone of Sandaozhuang molybdenum mine (SMM), in which there are large numbers of underground goafs need to be controlled by filled raise. The Riedel–Hiermaier–Thoma (RHT) material model, which considers compression damage and tension damage effect under blasting loading, is employed in the LS-DYNA software to study the rock damage zone. Meanwhile, the field tests are carried out according to the two small-scale experimental methods. The comparison results show that the damage zone of numerical simulation has a good agreement with the experimental data. Further, the optimal prime cut parameters obtained from experimental tests are applied in one-step filled-raise excavation, and a 23 m raise that meets the design requirements is formed through the proposed technology. The results indicate that these cut parameters determined by the small-scale experiments are suited for one-step raise excavation. This study can provide two simple field experiments to determine the important prime cut paramet...

Liu, M, Gurr, PA, Fu, Q, Webley, PA & Qiao, GG 2018, 'Two-dimensional nanosheet-based gas separation membranes', Journal of Materials Chemistry A, vol. 6, no. 46, pp. 23169-23196.
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Two-dimensional nanosheets as building blocks for the preparation of high-performance gas separation membranes.

Liu, M, Xie, K, Nothling, MD, Gurr, PA, Tan, SSL, Fu, Q, Webley, PA & Qiao, GG 2018, 'Ultrathin Metal–Organic Framework Nanosheets as a Gutter Layer for Flexible Composite Gas Separation Membranes', ACS Nano, vol. 12, no. 11, pp. 11591-11599.
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Ultrathin metal-organic framework (MOF) nanosheets show great potential in various separation applications. In this study, MOF nanosheets are incorporated as a gutter layer in high-performance, flexible thin-film composite membranes (TFCMs) for CO2 separation. Ultrathin MOF nanosheets (∼3-4 nm) were prepared via a surfactant-assisted method and subsequently coated onto a flexible porous support by vacuum filtration. This produced an ultrathin (∼25 nm), extremely flat MOF layer, which serves as a highly permeable gutter with reduced gas resistance when compared with conventional polydimethylsiloxane gutter layers. Subsequent spin-coating of the ultrathin MOF gutter layer with a polymeric selective layer (Polyactive) afforded a TFCM exhibiting the best CO2 separation performance yet reported for a flexible composite membrane (CO2 permeance of ∼2100 GPU with a CO2/N2 ideal selectivity of ∼30). Several unique MOF nanosheets were examined as gutter layers, each differing with regard to structure and thickness (∼10 and ∼80 nm), with results indicating that flexibility in the ultrathin MOF layer is critical for optimized membrane performance. The inclusion of ultrathin MOF nanosheets into next-generation TFCMs has the potential for major improvements in gas separation performance over current composite membrane designs.

Liu, M, Xu, M, Xue, Y, Ni, W, Huo, S, Wu, L, Yang, Z & Yan, Y-M 2018, 'Efficient Capacitive Deionization Using Natural Basswood-Derived, Freestanding, Hierarchically Porous Carbon Electrodes', ACS Applied Materials & Interfaces, vol. 10, no. 37, pp. 31260-31270.
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Liu, P, Liu, J & Merigó, JM 2018, 'Partitioned Heronian means based on linguistic intuitionistic fuzzy numbers for dealing with multi-attribute group decision making', Applied Soft Computing, vol. 62, pp. 395-422.
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© 2017 Elsevier B.V. Heronian mean (HM) operator has the advantages of considering the interrelationships between parameters, and linguistic intuitionistic fuzzy number (LIFN), in which the membership and non-membership are expressed by linguistic terms, can more easily describe the uncertain and the vague information existing in the real world. In this paper, we propose the partitioned Heronian mean (PHM) operator which assumes that all attributes are partitioned into several parts and members in the same part are interrelated while in different parts there are no interrelationships among members, and develop some new operational rules of LIFNs to consider the interactions between membership function and non-membership function, especially when the degree of non-membership is zero. Then we extend PHM operator to LIFNs based on new operational rules, and propose the linguistic intuitionistic fuzzy partitioned Heronian mean (LIFPHM) operator, the linguistic intuitionistic fuzzy weighted partitioned Heronian mean (LIFWPHM) operator, the linguistic intuitionistic fuzzy partitioned geometric Heronian mean (LIFPGHM) operator and linguistic intuitionistic fuzzy weighted partitioned geometric Heronian mean (LIFWPGHM) operator. Further, we develop two methods to solve multi-attribute group decision making (MAGDM) problems with the linguistic intuitionistic fuzzy information. Finally, we give some examples to verify the effectiveness of two proposed methods by comparing with the existing

Liu, Q, Chen, P, Wang, B, Zhang, J & Li, J 2018, 'dbMPIKT: a database of kinetic and thermodynamic mutant protein interactions', BMC Bioinformatics, vol. 19, no. 1.
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Liu, Q, Chen, P, Wang, B, Zhang, J & Li, J 2018, 'Hot spot prediction in protein-protein interactions by an ensemble system', BMC Systems Biology, vol. 12, no. S9, pp. 132-132.
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BACKGROUND:Hot spot residues are functional sites in protein interaction interfaces. The identification of hot spot residues is time-consuming and laborious using experimental methods. In order to address the issue, many computational methods have been developed to predict hot spot residues. Moreover, most prediction methods are based on structural features, sequence characteristics, and/or other protein features. RESULTS:This paper proposed an ensemble learning method to predict hot spot residues that only uses sequence features and the relative accessible surface area of amino acid sequences. In this work, a novel feature selection technique was developed, an auto-correlation function combined with a sliding window technique was applied to obtain the characteristics of amino acid residues in protein sequence, and an ensemble classifier with SVM and KNN base classifiers was built to achieve the best classification performance. CONCLUSION:The experimental results showed that our model yields the highest F1 score of 0.92 and an MCC value of 0.87 on ASEdb dataset. Compared with other machine learning methods, our model achieves a big improvement in hot spot prediction. AVAILABILITY:http://deeplearner.ahu.edu.cn/web/HotspotEL.htm .

Liu, Q, Gao, R, Tam, VWY, Li, W & Xiao, J 2018, 'Strain monitoring for a bending concrete beam by using piezoresistive cement-based sensors', Construction and Building Materials, vol. 167, pp. 338-347.
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© 2018 Elsevier Ltd Graphite nanoplatelets (GNPs), promising in improving electrical properties of cement-based materials and its smartness, were used to prepare piezoresistive cement-based strain sensors (PCSSs) in this study. Their piezoresistive responses along vertical, horizontal and inclined directions were measured during applying a vertical cyclic compression. After calibrating free PCSSs by analyzing their gauge factors, three PCSSs are embedded in a four-point bending beam at different stress zones, i.e. uniaxial compression, uniaxial tension and combined shear and compression. In addition to investigating piezoresistive responses of PCSSs embedded in the beam, traditional strain gauges and finite element method (FEM) were also used to grasp the strains at relevant positions for comparison. For free PCSSs, It was found that the electrical resistances along vertical, horizontal and diagonal directions drop by amplitudes of 5.5%, 1.8% and 6.7% respectively, as the increasing of vertical compression. The gauge factor along loading direction was calculated to be −160.8, which illustrated a better sensitivity. In the four-point bending beam, the PCSSs in compressive zone and tensile zone can be used to presume the strain variation by considering the gauge factor obtained from the free PCSS. The reaction of the PCSS in shear zone can illustrate its strain features because a slight volume variation happened in this area, which can also be testified to be only 0.012‰with FEM analysis.

Liu, Q, Li, P, Zhao, W, Cai, W, Yu, S & Leung, VCM 2018, 'A Survey on Security Threats and Defensive Techniques of Machine Learning: A Data Driven View', IEEE Access, vol. 6, pp. 12103-12117.
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© 2013 IEEE. Machine learning is one of the most prevailing techniques in computer science, and it has been widely applied in image processing, natural language processing, pattern recognition, cybersecurity, and other fields. Regardless of successful applications of machine learning algorithms in many scenarios, e.g., facial recognition, malware detection, automatic driving, and intrusion detection, these algorithms and corresponding training data are vulnerable to a variety of security threats, inducing a significant performance decrease. Hence, it is vital to call for further attention regarding security threats and corresponding defensive techniques of machine learning, which motivates a comprehensive survey in this paper. Until now, researchers from academia and industry have found out many security threats against a variety of learning algorithms, including naive Bayes, logistic regression, decision tree, support vector machine (SVM), principle component analysis, clustering, and prevailing deep neural networks. Thus, we revisit existing security threats and give a systematic survey on them from two aspects, the training phase and the testing/inferring phase. After that, we categorize current defensive techniques of machine learning into four groups: security assessment mechanisms, countermeasures in the training phase, those in the testing or inferring phase, data security, and privacy. Finally, we provide five notable trends in the research on security threats and defensive techniques of machine learning, which are worth doing in-depth studies in future.

Liu, Q, Shen, H, Wu, Y, Xia, Z, Fang, J & Li, Q 2018, 'Crash responses under multiple impacts and residual properties of CFRP and aluminum tubes', Composite Structures, vol. 194, pp. 87-103.
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© 2018 Elsevier Ltd This study aimed to explore the impact responses and residual properties of thin-walled carbon fiber reinforced plastics (CFRP) tubes and aluminum (Al) tubes subjected to multiple axial impacts. Five repeated impacts with the same impact energy were first conducted to evaluate the effect of repeated impact number, and then the crushing tests were performed to explore the post-impact residual behavior. Regardless of number of repeated impacts, the progressive end crushing modes for the CFRP tubes and stable progressive folding mode for aluminum tubes were identified under repeated dynamic impacts. The CFRP tubes exhibited the highest specific energy absorption (SEA) under the 1st impact, then the similar SEA values in the other four subsequent impacts; whereas the SEA of aluminum tubes fluctuated with the repeated impact numbers which were related to formation of different folds. The quasi-static crushing tests revealed that the residual SEAs of the CFRP tubes and aluminum tubes were not much influenced by the impact number, only within a difference of 5% under the 5 repetitive impacts conducted. It was demonstrated that the CFRP tubes had much better performance in energy absorption capability in comparison with the aluminum tubes in terms of repeated impacts and residual crushing tests.

Liu, Q, Thoms, JAI, Nunez, AC, Huang, Y, Knezevic, K, Packham, D, Poulos, RC, Williams, R, Beck, D, Hawkins, NJ, Ward, RL, Wong, JWH, Hesson, LB, Sloane, MA & Pimanda, JE 2018, 'Disruption of a −35 kb Enhancer Impairs CTCF Binding and MLH1 Expression in Colorectal Cells', Clinical Cancer Research, vol. 24, no. 18, pp. 4602-4611.
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Abstract Purpose: MLH1 is a major tumor suppressor gene involved in the pathogenesis of Lynch syndrome and various sporadic cancers. Despite their potential pathogenic importance, genomic regions capable of regulating MLH1 expression over long distances have yet to be identified. Experimental Design: Here, we use chromosome conformation capture (3C) to screen a 650-kb region flanking the MLH1 locus to identify interactions between the MLH1 promoter and distal regions in MLH1-expressing and nonexpressing cells. Putative enhancers were functionally validated using luciferase reporter assays, chromatin immunoprecipitation, and CRISPR-Cas9–mediated deletion of endogenous regions. To evaluate whether germline variants in the enhancer might contribute to impaired MLH1 expression in patients with suspected Lynch syndrome, we also screened germline DNA from a cohort of 74 patients with no known coding mutations or epimutations at the MLH1 promoter. Results: A 1.8-kb DNA fragment, 35 kb upstream of the MLH1 transcription start site enhances MLH1 gene expression in colorectal cells. The enhancer was bound by CTCF and CRISPR-Cas9–mediated deletion of a core binding region impairs endogenous MLH1 expression. A total of 5.4% of suspected Lynch syndrome patients have a rare single-nucleotide variant (G &gt; A; rs143969848; 2.5% in gnomAD European, non-Finnish) within a highly conserved CTCF-binding motif, which disrupts enhancer activity in SW620 colorectal carcinoma cells. Conclusions: A CTCF-bound region within the MLH1-35 enhancer regulates MLH1 expression in colorectal cells and is worthy of scrutiny in future genetic screening strategies for suspected Lynch syndrome associated with loss of MLH1 expression. Clin Cancer Res; 24(18); 4602–11. ©2018 AACR.

Liu, Q, Wu, R, Chen, E, Xu, G, Su, Y, Chen, Z & Hu, G 2018, 'Fuzzy Cognitive Diagnosis for Modelling Examinee Performance', ACM Transactions on Intelligent Systems and Technology, vol. 9, no. 4, pp. 1-26.
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Recent decades have witnessed the rapid growth of educational data mining (EDM), which aims at automatically extracting valuable information from large repositories of data generated by or related to people’s learning activities in educational settings. One of the key EDM tasks is cognitive modelling with examination data, and cognitive modelling tries to profile examinees by discovering their latent knowledge state and cognitive level (e.g. the proficiency of specific skills). However, to the best of our knowledge, the problem of extracting information from both objective and subjective examination problems to achieve more precise and interpretable cognitive analysis remains underexplored. To this end, we propose a fuzzy cognitive diagnosis framework (FuzzyCDF) for examinees’ cognitive modelling with both objective and subjective problems. Specifically, to handle the partially correct responses on subjective problems, we first fuzzify the skill proficiency of examinees. Then we combine fuzzy set theory and educational hypotheses to model the examinees’ mastery on the problems based on their skill proficiency. Finally, we simulate the generation of examination score on each problem by considering slip and guess factors. In this way, the whole diagnosis framework is built. For further comprehensive verification, we apply our FuzzyCDF to three classical cognitive assessment tasks, i.e., predicting examinee performance, slip and guess detection, and cognitive diagnosis visualization. Extensive experiments on three real-world datasets for these assessment tasks prove that FuzzyCDF can reveal the knowledge states and cognitive level of the examinees effectively and interpretatively.

Liu, T, Zhang, W, McLean, P, Ueland, M, Forbes, SL & Su, SW 2018, 'Electronic Nose-Based Odor Classification using Genetic Algorithms and Fuzzy Support Vector Machines', International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1309-1320.
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© 2018, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. Electronic nose devices consisting of a matrix of sensors to sense the smell of various target gases have received considerable attention during the past two decades. This paper presents an efficient classification algorithm for a self-designed electronic nose, which integrates both genetic algorithms (GAs) and fuzzy support vector machines (FSVMs) to detect the target odor. GAs are applied to select the informative features and the optimal model parameters of FSVMs. FSVMs are adopted as fitness evaluation criterion and the sequent odor classifier, which can reduce the outlier effects and provide a robust and accurate classification. This proposed algorithm has been compared with some commonly used learning algorithms, such as support vector machine, the k-nearest neighbors and other combination algorithms. This study is based on experimental data collected from the response of the UTS NOS.E, which is the electronic nose system developed by the University of Technology Sydney NOS.E team. In comparison with other approaches, the experiment results show that the proposed odor classification algorithm can significantly improve the classification accuracy by selecting high-quality features and reach to 92.05% classification accuracy.

Liu, W, Chang, X, Yan, Y, Yang, Y & Hauptmann, AG 2018, 'Few-Shot Text and Image Classification via Analogical Transfer Learning', ACM Transactions on Intelligent Systems and Technology, vol. 9, no. 6, pp. 1-20.
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Learning from very few samples is a challenge for machine learning tasks, such as text and image classification. Performance of such task can be enhanced via transfer of helpful knowledge from related domains, which is referred to as transfer learning. In previous transfer learning works, instance transfer learning algorithms mostly focus on selecting the source domain instances similar to the target domain instances for transfer. However, the selected instances usually do not directly contribute to the learning performance in the target domain. Hypothesis transfer learning algorithms focus on the model/parameter level transfer. They treat the source hypotheses as well-trained and transfer their knowledge in terms of parameters to learn the target hypothesis. Such algorithms directly optimize the target hypothesis by the observable performance improvements. However, they fail to consider the problem that instances that contribute to the source hypotheses may be harmful for the target hypothesis, as instance transfer learning analyzed. To relieve the aforementioned problems, we propose a novel transfer learning algorithm, which follows an analogical strategy. Particularly, the proposed algorithm first learns a revised source hypothesis with only instances contributing to the target hypothesis. Then, the proposed algorithm transfers both the revised source hypothesis and the target hypothesis (only trained with a few samples) to learn an analogical hypothesis. We denote our algorithm as Analogical Transfer Learning. Extensive experiments on one synthetic dataset and three real-world benchmark datasets demonstrate the superior performance of the proposed algorithm.

Liu, W, Yan, X, Huang, S, Yang, C & Wang, G 2018, 'Advanced Control for Singular Systems with Applications', Mathematical Problems in Engineering, vol. 2018, pp. 1-2.
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Liu, W, Zhang, H, Chen, X & Yu, S 2018, 'Managing consensus and self-confidence in multiplicative preference relations in group decision making', Knowledge-Based Systems, vol. 162, pp. 62-73.
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© 2018 Elsevier B.V. Preference relations have been widely used in Group Decision Making (GDM) to represent decision makers’ preferences over alternatives. Recently, a new kind of preference relation called the self-confident multiplicative preference relation has been presented, which is formed considering multiple self-confidence levels into the multiplicative preference relation. This paper proposes an iteration-based consensus building framework for GDM problems with self-confident multiplicative preference relations. In this consensus building framework, an extended logarithmic least squares method is presented to derive the individual and collective priority vectors from the self-confident multiplicative preference relations. Then, a two-step feedback adjustment mechanism is used to assist the decision makers to improve the consensus level, which adjusts both the preference values and the self-confidence levels. The simulation experiments are devised to testify the efficiency of the proposed consensus building framework. Simulation results show that compared with only adjusting the preference values in the iteration-based consensus model, adjusting both the preference values and the self-confidence levels can accelerate the consensus success ratio and improve the consensus success ratio.

Liu, X, Ni, S-Q, Guo, W, Wang, Z, Ahmad, HA, Gao, B & Fang, X 2018, 'N₂O emission and bacterial community dynamics during realization of the partial nitrification process', RSC Advances, vol. 8, no. 43, pp. 24305-24311.
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In this study, greenhouse gas emissions and microbial community succession during the realization of the partial nitrification (PN) process were studied.

Liu, X, Xu, Q, Wang, D, Yang, Q, Wu, Y, Yang, J, Gong, J, Ye, J, Li, Y, Wang, Q, Liu, Y, Ni, B-J, Zeng, G & Li, X 2018, 'Revealing the Underlying Mechanisms of How Initial pH Affects Waste Activated Sludge Solubilization and Dewaterability in Freezing and Thawing Process', ACS Sustainable Chemistry & Engineering, vol. 6, no. 11, pp. 15822-15831.
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Copyright © 2018 American Chemical Society. In this study, the effect of initial pH ranging from 3 to 11 on waste activated sludge solubilization and dewaterability in the freezing and thawing (F/T) process was investigated. Experimental results showed that alkaline conditions enhanced the solubilization of sludge in F/T treatment, whereas acidic conditions improved the dewaterability of sludge. Optimum solubilization with organic substances being 189.7 mg COD/g VSS occurred at initial pH 10, which was 12.9 times higher and more biodegradable than the control. Optimal dewaterability performance was achieved at initial pH 4, with capillary suction time and specific resistance to filterability reduction being reached to 85.4% and 87.8%, respectively. It was found that F/T treatment at initial alkaline condition also obtained good dewatering performance, and F/T treatment at initial acidic condition acquired fine solubilization too. Mechanism explorations exhibited that the OH- and freezing had synergetic effects on the degradation of extracellular polymeric substances (EPS) to enhance sludge solubilization, and OH- can be concentrated to a much higher level in the liquid-like boundary region upon freezing, which further strengthened this effects. The H+ and freezing also showed synergetic effects on the protonation of functional groups of EPS and flocculation of the colloidal sludge to improve sludge dewaterability. This study clearly reveals the role and mechanisms of initial pH on the F/T process aiming at solubilization and dewaterability of sludge, and might provide supports for the application of F/T-based strategy in field situations in the future.

Liu, X, Xu, Q, Wang, D, Zhao, J, Wu, Y, Liu, Y, Ni, B-J, Wang, Q, Zeng, G, Li, X & Yang, Q 2018, 'Improved methane production from waste activated sludge by combining free ammonia with heat pretreatment: Performance, mechanisms and applications', Bioresource Technology, vol. 268, pp. 230-236.
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© 2018 Elsevier Ltd Anaerobic digestion of waste activated sludge (WAS) is often limited by low hydrolysis efficiencies and poor methane potentials. This work presents a novel pretreatment technology for WAS anaerobic digestion, i.e., combining free ammonia with heat pretreatment (CFHP). Experimental results showed that compared with control, solo free ammonia (135.4 mg NH3-N/L) and solo heat (70 °C) pretreatment, the combined free ammonia and heat (135.4 mg NH3-N/L with 70 °C) obtained 52.2%, 25.5% and 30.2% faster in hydrolysis rate and 25.2%, 17.9% and 16.5% higher in biochemical methane potential, respectively. Mechanism investigations showed that the combined pretreatment not only largely facilitated the disintegration of WAS but also increased the proportion of biodegradable organic matters, thereby providing better contract between biodegradable organics and the anaerobic microbes for methane production. Considering its effectiveness and renewability, the combined pretreatment is an attractive technology for the application in real-world situations.

Liu, Y, Bai, J, Xu, KD, Xu, Z, Han, F, Liu, QH & Jay Guo, Y 2018, 'Linearly Polarized Shaped Power Pattern Synthesis With Sidelobe and Cross-Polarization Control by Using Semidefinite Relaxation', IEEE Transactions on Antennas and Propagation, vol. 66, no. 6, pp. 3207-3212.
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© 1963-2012 IEEE. In this communication, the problem of synthesizing a linearly polarized shaped power pattern with accurate control on both sidelobe and cross-polarization (XP) levels is considered. For a user-defined desired polarization direction, the definitions of realizable co-polarization (COP) and XP directions for an arbitrary propagation direction in the shaped pattern are presented. With the help of such definitions, the considered problem is formulated as finding appropriate excitations so as to produce a shaped power pattern in which the realizable COP component meets prescribed lower and upper bounds, the realizable XP component and the total power pattern are less than their upper bounds in the regions of interest. The semidefinite relaxation method in the literature is then extended to solve this vectorial pattern synthesis problem. The proposed method can include the mutual coupling and platform effects by using vectorial active element patterns of an antenna array. A set of synthesis examples with different array geometries and radiation requirements are conducted to validate the effectiveness and advantages of the proposed method.

Liu, Y, Cheng, J, Xu, KD, Yang, S, Liu, QH & Guo, YJ 2018, 'Reducing the Number of Elements in the Synthesis of a Broadband Linear Array With Multiple Simultaneous Frequency-Invariant Beam Patterns', IEEE Transactions on Antennas and Propagation, vol. 66, no. 11, pp. 5838-5848.
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© 2018 IEEE. The problem of reducing the number of elements in a broadband linear array with multiple simultaneous crossover frequency-invariant (FI) patterns is considered. Different from the single FI pattern array case, every element channel in the multiple FI pattern array is divided and followed by multiple finite-impulse-response (FIR) filters, and each of the multiple FIR filters has a set of coefficients. In this situation, a collective filter coefficient vector and its energy bound are introduced for each element, and then the problem of reducing the number of elements is transformed as minimizing the number of active collective filter coefficient vectors. In addition, the radiation characteristics including beam pointing direction, mainlobe FI property, sidelobe level, and space-frequency notching requirement for each of the multiple patterns can be formulated as multiple convex constraints. The whole synthesis method is implemented by performing an iterative second-order cone programming (SOCP). This method can be considered as a significant extension of the original SOCP for synthesizing broadband sparse array with single FI pattern. Numerical synthesis results show that the proposed method by synthesizing multiple discretized crossover FI patterns can save more elements than the original iterative SOCP by using a single continuously scannable FI pattern for covering the same space range. Moreover, even for multiple FI-patterns case with complicated space-frequency notching, the proposed method is still effective in the reduction of the number of elements.

Liu, Y, Li, J, Guo, W, Ngo, HH, Hu, J & Gao, M-T 2018, 'Use of magnetic powder to effectively improve the performance of sequencing batch reactors (SBRs) in municipal wastewater treatment', Bioresource Technology, vol. 248, no. Part B, pp. 135-139.
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This study aims to investigate the effect of adding magnetic powder in the sequencing batch reactor (SBR) on the reactor performance and microbial community. Results indicated that, the magnetic activated sludge sequencing batch reactor (MAS-SBR) had 7.76% and 4.76% higher ammonia nitrogen (NH4(+)-N) and chemical oxygen demand (COD) removal efficiencies than that of the conventional SBR (C-SBR). The MAS-SBR also achieved 6.86% sludge reduction compared with the C-SBR. High-throughput sequencing demonstrated that the dominant phyla of both SBRs (present as ≥1% of the sequence reads) were Protebacteria, Bacteroidetes, Chloroflexi, Saccharibacteria, Chlorobi, Firmicutes, Actinobactoria, Acidobacteria, Planctomycetes and unclassified_Bacteria. The relative abundance of Protebacteria and Bacteroidetes simultaneously declined whereas the other 8 phyla increased following the addition of magnetic powder. Adding magnetic powder in the SBR significantly affected the microbial diversity and richness of activated sludge, consequently affecting the reactor performance.

Liu, Y, Liu, Q, Li, J, Ngo, HH, Guo, W, Hu, J, Gao, M-T, Wang, Q & Hou, Y 2018, 'Effect of magnetic powder on membrane fouling mitigation and microbial community/composition in membrane bioreactors (MBRs) for municipal wastewater treatment', Bioresource Technology, vol. 249, pp. 377-385.
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This study aims to investigate the usefulness of magnetic powder addition in membrane bioreactors (MBRs) for membrane fouling mitigation and its effect on microbial community and composition. The comparison between the two MBRs (one with magnetic powder (MAS-MBR) and one without magnetic powder (C-MBR)) was carried out to treat synthetic municipal wastewater. Results showed that bioflocculation and adsorption of magnetic powder contributed only minimally to membrane fouling mitigation while the slower fouling rate might be ascribed to magnetic bio-effect. The macromolecules (larger than 500 kDa and 300-500 kDa) of soluble microbial product from the MAS-MBR were reduced by 24.06% and 11.11%, respectively. High-throughput sequencing demonstrated the most abundant genera of biofilm sludge indicated lower abundance in bulk sludge from the MAS-MBR compared to the C-MBR. It is possible that less membrane fouling is connected to reductions in large molecules and pioneer bacteria from bulk sludge.

Liu, Y, Ngo, HH, Guo, W, Peng, L, Chen, X, Wang, D, Pan, Y & Ni, B 2018, 'Modeling electron competition among nitrogen oxides reduction and N₂O accumulation in hydrogenotrophic denitrification', Biotechnology and Bioengineering, vol. 115, no. 4, pp. 978-988.
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AbstractHydrogenotrophic denitrification is a novel and sustainable process for nitrogen removal, which utilizes hydrogen as electron donor, and carbon dioxide as carbon source. Recent studies have shown that nitrous oxide (N2O), a highly undesirable intermediate and potent greenhouse gas, can accumulate during this process. In this work, a new mathematical model is developed to describe nitrogen oxides dynamics, especially N2O, during hydrogenotrophic denitrification for the first time. The model describes electron competition among the four steps of hydrogenotrophic denitrification through decoupling hydrogen oxidation and nitrogen reduction processes using electron carriers, in contrast to the existing models that couple these two processes and also do not consider N2O accumulation. The developed model satisfactorily describes experimental data on nitrogen oxides dynamics obtained from two independent hydrogenotrophic denitrifying cultures under various hydrogen and nitrogen oxides supplying conditions, suggesting the validity and applicability of the model. The results indicated that N2O accumulation would not be intensified under hydrogen limiting conditions, due to the higher electron competition capacity of N2O reduction in comparison to nitrate and nitrite reduction during hydrogenotrophic denitrification. The model is expected to enhance our understanding of the process during hydrogenotrophic denitrification and the ability to predict N2O accumulation.

Liu, Y, Zhang, X, Hao Ngo, H, Guo, W, Wen, H, Deng, L, Li, Y & Guo, J 2018, 'Specific approach for membrane fouling control and better treatment performance of an anaerobic submerged membrane bioreactor', Bioresource Technology, vol. 268, pp. 658-664.
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This paper investigated a strategy to minimize membrane fouling and increase treatment efficiency through an investigation of a specific approach by adding sponges into a conventional submerged anaerobic membrane bioreactor (CAnSMBR). During the operation, the protein-based soluble microbial products as the main factor affecting the membrane fouling could be reduced by sponge addition in the CAnSMBR (SAnSMBR). Furthermore, reducing HRT from 18 h to 12 h could shorten the membrane fouling cycle to 62% and 87% in CAnSMBR and SAnSMBR, respectively. At the initial of COD/NO3 ratio ranges from 5 to 4, only 88% of nitrogen in CAnSMBR was removed, while the SAnSMBR could remove more than 90%. TOC removal efficiency could reach more than 95% under a good stirring scenario. It is evident that the SAnSMBR is a promising solution for improving overall CAnSMBR performance and substantially mitigating membrane fouling.

Liu, Y-T, Pal, NR, Marathe, AR & Lin, C-T 2018, 'Weighted Fuzzy Dempster–Shafer Framework for Multimodal Information Integration', IEEE Transactions on Fuzzy Systems, vol. 26, no. 1, pp. 338-352.
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© 1993-2012 IEEE. This study proposes an architecture based on a weighted fuzzy Dempster-Shafer framework (WFDSF), which can adjust weights associated with inconsistent evidence obtained by different classification approaches, to realize a fusion system for integrating multimodal information. The Dempster-Shafer theory (D-S theory) of evidence enables us to integrate heterogeneous information from multiple sources to obtain collaborative inferences for a given problem. To conquer various uncertainties associated with the collected information, our system assigns beliefs and plausibilities to possible hypotheses of each decision maker and uses a combination rule to fuse multimodal information. For information fusion, an important step in D-S aggregation is to find an appropriate basic probability assignment scheme for allocating support to each possible hypothesis/class, which remains an arduous and unsolved problem. Here, we propose a mathematical structure to aggregate weighted evidence extracted from two different types of approaches: fuzzy Naïve Bayes and nearest mean classification rule. Further, an intuitionistic belief assignment is employed to address uncertainties between hypotheses/classes. Finally, 12 benchmark problems from the UCI machine learning repository for classification are employed to validate the proposed WFDSF-based scheme. In addition, an application of WFDSF to a practical brain-computer interface problem involving multimodal data fusion is demonstrated in this study. The experimental results show that the WFDSF is superior to several existing methods.

Liu, Z, Wang, D, Liang, J, Wu, F & Wu, C 2018, 'The fast multi-pole indirect BEM for solving high-frequency seismic wave scattering by three-dimensional superficial irregularities', Engineering Analysis with Boundary Elements, vol. 90, pp. 86-99.
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© 2018 Elsevier Ltd Taking full advantage of the indirect boundary element method (IBEM) and fast multi-pole expansion algorithm, this paper proposes a fast multi-pole indirect boundary element method (FM-IBEM) to solve the scattering of high-frequency seismic waves by three-dimensional (3-D) superficial irregularities or heterogeneity in a solid half-space. First, IBEM utilizes an exact dynamic Green's function for a full-space to construct the scattered wave field. Subsequently, by employing plane waves expansion of 3-D potential functions of compressional and shear waves, the multi-pole expansion and local expansion coefficients were derived. Implementation of FM-IBEM is presented in detail for wave-scattering problems. Numerical examples illustrate that the proposed FM-IBEM can reduce the memory required by more than an order of magnitude and also greatly improve the computing efficiency, retaining excellent accuracy as well. Ultimately, several high-frequency plane wave scattering problems of 3-D superficial irregularities in a solid half-space are illustrated, and several important scattering characteristics are described based on the high-precision numerical results.

Liyanaarachchi, S, Muthukumaran, S, Kaiser, J, Rogers, P, Shu, L, Shon, HK & Jegatheesan, V 2018, 'Computing the effective diffusion coefficient of solutes in a multi-salts solutions during forward osmosis (FO) membrane filtration: Experiments and mathematical modelling', Journal of Environmental Management, vol. 214, pp. 215-223.
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Diffusion coefficient of solutes through a porous membrane media is different from diffusion coefficient through a free homogenous media. Porosity, tortuosity and the thickness of the membrane significantly affect the diffusion through a specific thickness of a membrane and therefore it is termed as effective diffusion coefficient (Deff) which is lower than the actual diffusion coefficient, D. The Deff of single or dual solutes through a porous membrane layer are well documented but not for multiple salts. Therefore, in this study, single, dual and multiple salt mixtures were passed through a flat sheet cellulose triacetate Forward Osmosis (FO) membrane to obtain a semi-empirical relationship with the Deff and its water flux. This will allow computing the structural coefficient of FO membranes. Research community have spent tremendous efforts in membrane modification to reduce the structural coefficient to improve FO process efficiency. Our finding suggests that optimising the draw solution chemistry can achieve this goal.

Llano-Serna, MA, Farias, MM, Pedroso, DM, Williams, DJ & Sheng, D 2018, 'An assessment of statistically based relationships between critical state parameters', Géotechnique, vol. 68, no. 6, pp. 556-560.
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Reliability-based design (RBD) has been proved effective in the application of probability theory to research and practice in geotechnical engineering. However, the limited field and laboratory information makes it difficult to build robust predictions. This note shows some statistical relationships that may help with additional information in this area. Descriptive statistics are performed in the note followed by demonstrations of the close relationship between deformabilty parameters. The strong correlation between the slope of the critical state line and the earth pressure coefficient at rest is found. The applicability of the statistical relationships is also examined using RBD. Numerical analysis of oedometer tests demonstrates how RBD can consider the influence of the uncertainty of the critical state parameters.

Llano-Serna, MA, Farias, MM, Pedroso, DM, Williams, DJ & Sheng, D 2018, 'Considerations on the Experimental Calibration of the Fall Cone Test', Geotechnical Testing Journal, vol. 41, no. 6, pp. 1131-1138.
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Abstract The fall cone test is widely used in soil mechanics to determine the liquid limit of fine-grained soils as an aid to soil classification. The test can also be used to obtain the undrained shear strength of a fine-grained soil, based on the “cone factor,” K. Reports from different authors show K values ranging from 0.4–1.33. Differences are mostly attributed to the cone surface roughness. This article presents a reinterpretation of several experimental observations available in the literature. It is observed that besides the cone roughness, testing methods have a clear influence when calibrating the fall cone for determining the undrained shear strength of materials with low and very low consistency. The results show that existing K reports should be extrapolated with care. Finally, we propose a series of recommendations and good practices for future calibrations.

Llopis-Albert, C, Merigó, JM, Liao, H, Xu, Y, Grima-Olmedo, J & Grima-Olmedo, C 2018, 'Water Policies and Conflict Resolution of Public Participation Decision-Making Processes Using Prioritized Ordered Weighted Averaging (OWA) Operators', Water Resources Management, vol. 32, no. 2, pp. 497-510.
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© 2017, Springer Science+Business Media B.V. There is a growing interest in environmental policies about how to implement public participation engagement in the context of water resources management. This paper presents a robust methodology, based on ordered weighted averaging (OWA) operators, to conflict resolution decision-making problems under uncertain environments due to both information and stakeholders’ preferences. The methodology allows integrating heterogeneous interests of the general public and stakeholders on account of their different degree of acceptance or preference and level of influence or power regarding the measures and policies to be adopted, and also of their level of involvement (i.e., information supply, consultation and active involvement). These considerations lead to different environmental and socio-economic outcomes, and levels of stakeholders’ satisfaction. The methodology establishes a prioritization relationship over the stakeholders. The individual stakeholders’ preferences are aggregated through their associated weights, which depend on the satisfaction of the higher priority decision maker. The methodology ranks the optimal management strategies to maximize the stakeholders’ satisfaction. It has been successfully applied to a real case study, providing greater fairness, transparency, social equity and consensus among actors. Furthermore, it provides support to environmental policies, such as the EU Water Framework Directive (WFD), improving integrated water management while covering a wide range of objectives, management alternatives and stakeholders.

Llopis‐Albert, C, Merigó, JM, Xu, Y & Liao, H 2018, 'Application of Fuzzy Set/Qualitative Comparative Analysis to Public Participation Projects in Support of the EU Water Framework Directive', Water Environment Research, vol. 90, no. 1, pp. 74-83.
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ABSTRACT: This study analyzes the level of satisfaction of stakeholders in the public participation process (PPP) of water resources management, which is mandatory according to the EU Water Framework Directive (WFD). The methodology uses a fuzzy set/qualitative comparative analysis (fsQCA), which allows the identification of a combination of factors that lead to the outcome that is stakeholders' satisfaction. It allows dealing with uncertain environments due to the heterogeneous nature of stakeholders and factors. The considered causes range from environmental objectives pursued, actual capacity of efficiently carrying out those objectives, socioeconomic development of the region, level of involvement and means of participation of the stakeholders engaged in the PPP, and alternative policies and measures that should be performed. Results support the argument that different causal paths explain the stakeholders' satisfaction. The methodology may help in the implementation of the WFD and conflict resolution since it leads to greater fairness, social equity, and consensus among stakeholders.

Lloret-Cabot, M, Wheeler, SJ, Pineda, JA, Romero, E & Sheng, D 2018, 'From saturated to unsaturated conditions and vice versa', Acta Geotechnica, vol. 13, no. 1, pp. 15-37.
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Lloret-Cabot, M, Wheeler, SJ, Pineda, JA, Romero, E & Sheng, D 2018, 'Reply to “Discussion of “From saturated to unsaturated conditions and vice versa” by M. Lloret-Cabot et al. (DOI 10.1007/s11440-017-0577-6)” by S. Qi et al. (DOI 10.1007/s11440-017-0625-2)', Acta Geotechnica, vol. 13, no. 2, pp. 493-495.
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Loganathan, P, Shim, WG, Sounthararajah, DP, Kalaruban, M, Nur, T & Vigneswaran, S 2018, 'Modelling equilibrium adsorption of single, binary, and ternary combinations of Cu, Pb, and Zn onto granular activated carbon', Environmental Science and Pollution Research, vol. 25, no. 17, pp. 16664-16675.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Elevated concentrations of heavy metals in water can be toxic to humans, animals, and aquatic organisms. A study was conducted on the removal of Cu, Pb, and Zn by a commonly used water treatment adsorbent, granular activated carbon (GAC), from three single, three binary (Cu-Pb, Cu-Zn, Pb-Zn), and one ternary (Cu-Pb-Zn) combination of metals. It also investigated seven mathematical models on their suitability to predict the metals adsorption capacities. Adsorption of Cu, Pb, and Zn increased with pH with an abrupt increase in adsorption at around pH 5.5, 4.5, and 6.0, respectively. At all pHs tested (2.5–7.0), the adsorption capacity followed the order Pb > Cu > Zn. The Langmuir and Sips models fitted better than the Freundlich model to the data in the single-metal system at pH 5. The Langmuir maximum adsorption capacities of Pb, Cu, and Zn (mmol/g) obtained from the model’s fits were 0.142, 0.094, and 0.058, respectively. The adsorption capacities (mmol/g) for these metals at 0.01 mmol/L equilibrium liquid concentration were 0.130, 0.085, and 0.040, respectively. Ideal Adsorbed Solution (IAS)-Langmuir and IAS-Sips models fitted well to the binary and ternary metals adsorption data, whereas the Extended Langmuir and Extended Sips models’ fits to the data were poor. The selectivity of adsorption followed the same order as the metals’ capacities and affinities of adsorption in the single-metal systems.

Long, G, Liu, H, Ma, K, Xie, Y & Li, W 2018, 'Development of High-Performance Self-Compacting Concrete Applied as the Filling Layer of High-Speed Railway', Journal of Materials in Civil Engineering, vol. 30, no. 2, pp. 04017268-04017268.
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© 2017 American Society of Civil Engineers. The filling layer of a China rail track system III (CRTS III) type ballastless track structure of a high-speed railway is a complicated structure typically constructed from self-compacting concrete (SCC). Excellent properties of SCC are of great importance to ensure the quality of construction technology and long-term service performance of the filling layer. In this study, preparation methodologies and properties of SCC applied as a filling layer are systematically investigated by series of experiments. The results indicate that high-performance SCC with high stability in a fresh state and low deformation in a hardened state was successfully achieved by optimizing aggregates and binder components. Use of viscosity-enhancing compounds can not only effectively improve the workability of fresh SCC, but also significantly enhance mechanical properties and decrease drying shrinkage and creep of hardened concrete.

Lopez, AM, Quevedo, DE, Aguilera, RP, Geyer, T & Oikonomou, N 2018, 'Limitations and Accuracy of a Continuous Reduced-Order Model for Modular Multilevel Converters', IEEE Transactions on Power Electronics, vol. 33, no. 7, pp. 6292-6303.
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© 1986-2012 IEEE. This paper analyzes the limitations of a reduced-order model for modular multilevel converters (MMCs) by elucidating the relation between its accuracy, operating frequency, and converter parameters. A reduced-order simplifies the analysis of the MMC and thereby may provide additional information about the converter behavior. However, the accuracy of such model depends on several factors. In this paper, the effect of approximating the converter as a continuous system by neglecting quantization issues associated with having a finite number of modules is studied in detail. The analysis is done based on Fourier-series approximations with which it is possible to elucidate the relationship between the resonant frequencies of the MMC and the error of the reduced-order model. With the Fourier approximation, it is also possible to characterize resonant frequencies of the converter, both numerically and analytically, in terms of the converter parameters. The results can serve as a tool to identify situations when the reduced-order model produces good and also less accurate approximations especially when a low number of modules is available.

Lozano, FJ, Lozano, R, Freire, P, Jiménez-Gonzalez, C, Sakao, T, Ortiz, MG, Trianni, A, Carpenter, A & Viveros, T 2018, 'New perspectives for green and sustainable chemistry and engineering: Approaches from sustainable resource and energy use, management, and transformation', Journal of Cleaner Production, vol. 172, pp. 227-232.
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© 2017 Elsevier Ltd The special volume on green and sustainable chemistry and engineering has fourteen papers that were considered relevant to the present day issues and discussion, such as adequate use of raw materials and efficient energy, besides considering renewable sources for materials and energy; and changing economical canons towards circular economy. Businesses, governments and Society are facing a number of challenges to tread the sustainability path and provide wellbeing for future generations. This special volume relevance provides discussions and contributions to foster that desirable future. Chemicals are ubiquitous in everyday activities. Their widespread presence provides benefits to societies’ wellbeing, but can have some deleterious effects. To counteract such effect, green engineering and sustainable assessment in industrial processes have been gathering momentum in the last thirty years. Green chemistry, green engineering, eco-efficiency, and sustainability are becoming a necessity for assessing and managing products and processes in the chemical industry. This special volume presents fourteen articles related to sustainable resource and energy use (five articles), circular economy (one article), cleaner production and sustainable process assessment (five article), and innovation in chemical products (three articles). Green and sustainable chemistry, as well as sustainable chemical engineering and renewable energy sources are required to foster and consolidate a transition towards more sustainable societies. This special volume present current trends in chemistry and chemical engineering, such as sustainable resource and energy use, circular economy, cleaner production and sustainable process assessment, and innovation in chemical products. This special volume provides insights in this direction and complementing other efforts towards such transition.

Lu, C, Yang, D, Guo, J, Xie, Z, Song, Y, Xing, Y, Ngo, HH, Han, Y & Li, H 2018, 'The catalysis biodecolorization characteristics of novel recyclable insoluble redox mediators onto magnetic nanoparticles', Desalination and Water Treatment, vol. 107, pp. 62-71.
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© 2018 Desalination Publications. All rights reserved. The insoluble redox mediators (RMs) were prepared to overcome limitations of soluble RMs that are eluted with water flow in wastewater treatment process. Magnetic nanoparticles possess good performance, due to their high specific surface area, the absence of internal diffusion resistance and easy separation in presence of an external magnetic field. In this study, insoluble RMs were prepared by immobilizing anthraquinone-2-sulfate (AQS) onto magnetic nanoparticles. AQS modified magnetic nanoparticles (FeSi@AQS) were formed by chemical reaction between the sulfochlorides group of anthraquinone-2-sulfonyl choride and amino-modified magnetic nanoparticles, with formation confirmed by Fourier transform infrared spectra. Results of energy dispersive X-ray and thermal grav-imetric analysis showed that AQS occupied a 21.47 wt.% proportion of the FeSi@AQS complex. FeSi@ AQS was used as insoluble RMs to catalyze biodecolorization of several kinds of azo dyes. When the concentration of FeSi@AQS was as low as 40 mg/L, biodecolorization rate of reactivered K-2BP was increased by 2.18-fold. FeSi@AQ Scan then be separated and gathered from wastewater by magnetic attraction and reused for further catalysis of azo dye decolorization in a modified SBR system. These findings show that the immobilization of RMs on magnetic nanoparticle surfaces, benefits potential industrial applications of RMs.

Lu, J, Liu, A, Dong, F, Gu, F, Gama, J & Zhang, G 2018, 'Learning under Concept Drift: A Review', IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 12, pp. 1-1.
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IEEE Concept drift describes unforeseeable changes in the underlying distribution of streaming data over time. Concept drift research involves the development of methodologies and techniques for drift detection, understanding and adaptation. Data analysis has revealed that machine learning in a concept drift environment will result in poor learning results if the drift is not addressed. To help researchers identify which research topics are significant and how to apply related techniques in data analysis tasks, it is necessary that a high quality, instructive review of current research developments and trends in the concept drift field is conducted. In addition, due to the rapid development of concept drift in recent years, the methodologies of learning under concept drift have become noticeably systematic, unveiling a framework which has not been mentioned in literature. This paper reviews over 130 high quality publications in concept drift related research areas, analyzes up-to-date developments in methodologies and techniques, and establishes a framework of learning under concept drift including three main components: concept drift detection, concept drift understanding, and concept drift adaptation. This paper lists and discusses 10 popular synthetic datasets and 14 publicly available benchmark datasets used for evaluating the performance of learning algorithms aiming at handling concept drift. Also, concept drift related research directions are covered and discussed. By providing state-of-the-art knowledge, this survey will directly support researchers in their understanding of research developments in the field of learning under concept drift.

Lu, J, Xuan, J, Zhang, G & Luo, X 2018, 'Structural property-aware multilayer network embedding for latent factor analysis', Pattern Recognition, vol. 76, pp. 228-241.
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© 2017 Elsevier Ltd Multilayer network is a structure commonly used to describe and model the complex interaction between sets of entities/nodes. A three-layer example is the author-paper-word structure in which authors are linked by co-author relation, papers are linked by citation relation, and words are linked by semantic relation. Network embedding, which aims to project the nodes in the network into a relatively low-dimensional space for latent factor analysis, has recently emerged as an effective method for a variety of network-based tasks, such as collaborative filtering and link prediction. However, existing studies of network embedding both focus on the single-layer network and overlook the structural properties of the network, e.g., the degree distribution and communities, which are significant for node characterization, such as the preferences of users in a social network. In this paper, we propose four multilayer network embedding algorithms based on Nonnegative Matrix Factorization (NMF) with consideration given to four structural properties: whole network (NNMF), community (CNMF), degree distribution (DNMF), and max spanning tree (TNMF). Experiments on synthetic data show that the proposed algorithms are able to preserve the desired structural properties as designed. Experiments on real-world data show that multilayer network embedding improves the accuracy of document clustering and recommendation, and the four embedding algorithms corresponding to the four structural properties demonstrate the differences in performance on these two tasks. These results can be directly used in document clustering and recommendation systems.

Lu, L, Wang, T, Ni, W, Li, K & Gao, B 2018, 'Fog Computing‐Assisted Energy‐Efficient Resource Allocation for High‐Mobility MIMO‐OFDMA Networks', Wireless Communications and Mobile Computing, vol. 2018, no. 1, pp. 1-8.
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This paper presents a suboptimal approach for resource allocation of massive MIMO‐OFDMA systems for high‐speed train (HST) applications. An optimization problem is formulated to alleviate the severe Doppler effect and maximize the energy efficiency (EE) of the system. We propose to decouple the problem between the allocations of antennas, subcarriers, and transmit powers and solve the problem by carrying out the allocations separately and iteratively in an alternating manner. Fast convergence can be achieved for the proposed approach within only several iterations. Simulation results show that the proposed algorithm is superior to existing techniques in terms of system EE and throughput in different system configurations of HST applications.

Lu, S, Huang, S, Li, K, Li, J, Chen, J, Lu, D, Ji, Z, Shen, Y, Zhou, D & Zeng, B 2018, 'Separability-entanglement classifier via machine learning', Physical Review A, vol. 98, no. 1.
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© 2018 American Physical Society. The problem of determining whether a given quantum state is entangled lies at the heart of quantum information processing. Despite the many methods - such as the positive partial transpose criterion and the k-symmetric extendibility criterion - to tackle this problem, none of them enables a general, practical solution due to the problem's NP-hard complexity. Explicitly, separable states form a high-dimensional convex set of vastly complicated structures. In this work, we build a different separability-entanglement classifier underpinned by machine learning techniques. We use standard tools from machine learning to learn the entanglement feature of arbitrary given quantum states. We perform substantial numerical tests on two-qubit and two-qutrit systems, and the results indicate that our method can outperform the existing methods in generic cases in terms of both speed and accuracy. This opens up avenues to explore quantum entanglement via the machine learning approach.

Lu, W, Lu, P, Sun, Q, Yu, S & Zhu, Z 2018, 'Profit-Aware Distributed Online Scheduling for Data-Oriented Tasks in Cloud Datacenters', IEEE Access, vol. 6, pp. 15629-15642.
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As there is an increasing trend to deploy geographically distributed (geo-distributed) cloud datacenters (DCs), the scheduling of data-oriented tasks in such cloud DC systems becomes an appealing research topic. Specifically, it is challenging to achieve the distributed online scheduling that can handle the tasks' acceptance, data-transfers, and processing jointly and efficiently. In this paper, by considering the store-and-forward and anycast schemes, we formulate an optimization problem to maximize the time-average profit from serving data-oriented tasks in a cloud DC system and then leverage the Lyapunov optimization techniques to propose an efficient scheduling algorithm, i.e., GlobalAny. We also extend the proposed algorithm by designing a data-transfer acceleration scheme to reduce the data-transfer latency. Extensive simulations verify that our algorithms can maximize the time-average profit in a distributed online manner. The results also indicate that GlobalAny and GlobalAnyExt (i.e., GlobalAny with data-transfer acceleration) outperform several existing algorithms in terms of both time-average profit and computation time.

Lu, Z-H, Li, H, Li, W, Zhao, Y-G & Dong, W 2018, 'An empirical model for the shear strength of corroded reinforced concrete beam', Construction and Building Materials, vol. 188, pp. 1234-1248.
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© 2018 Elsevier Ltd A total of 158 experimental tests of shear behavior of corroded reinforced concrete (CRC) beams under action of concentrated load, published in the literature were collected and compiled into a shear strength database. This database was firstly used to discuss important parameters which affect the shear strength of CRC beams. The results show that the effect of stirrups’ corrosion on shear capacity of CRC beams is greater than that of longitudinal reinforcement corrosion. The shear span-to-depth ratio is also an important factor on shear strength of CRC beams. Total 9 available empirical models for predicting the residual shear strength are evaluated and compared based on the test database. It is found that eight of the nine models underestimate the shear strength of CRC beams while the other model gives the overestimated results. It is in this regard that a new empirical model for predicting the residual shear strength of CRC beams is proposed, in which a reduction coefficient is incorporated with the consideration of the effect of stirrups’ corrosion as well as shear span-to-depth ratio. The comparison studies demonstrate that the new proposal can provide an effective and accurate prediction of the shear capacity of CRC beams with a wide range of reinforcement corrosion damages.

Luo, L, Jiang, Z, Wei, D, Wang, X, Zhou, C & Huang, Q 2018, 'Micro-hydromechanical deep drawing of metal cups with hydraulic pressure effects', Frontiers of Mechanical Engineering, vol. 13, no. 1, pp. 66-73.
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© 2018, Higher Education Press and Springer-Verlag GmbH Germany. Micro-metal products have recently enjoyed high demand. In addition, metal microforming has drawn increasing attention due to its net-forming capability, batch manufacturing potential, high product quality, and relatively low equipment cost. Micro-hydromechanical deep drawing (MHDD), a typical microforming method, has been developed to take advantage of hydraulic force. With reduced dimensions, the hydraulic pressure development changes; accordingly, the lubrication condition changes from the macroscale to the microscale. A Voronoi-based finite element model is proposed in this paper to consider the change in lubrication in MHDD according to open and closed lubricant pocket theory. Simulation results agree with experimental results concerning drawing force. Changes in friction significantly affect the drawing process and the drawn cups. Moreover, defined wrinkle indexes have been shown to have a complex relationship with hydraulic pressure. High hydraulic pressure can increase the maximum drawing ratio (drawn cup height), whereas the surface finish represented by the wear is not linearly dependent on the hydraulic pressure due to the wrinkles.

Luo, M, Chang, X, Nie, L, Yang, Y, Hauptmann, AG & Zheng, Q 2018, 'An Adaptive Semisupervised Feature Analysis for Video Semantic Recognition', IEEE Transactions on Cybernetics, vol. 48, no. 2, pp. 648-660.
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© 2017 IEEE. Video semantic recognition usually suffers from the curse of dimensionality and the absence of enough high-quality labeled instances, thus semisupervised feature selection gains increasing attentions for its efficiency and comprehensibility. Most of the previous methods assume that videos with close distance (neighbors) have similar labels and characterize the intrinsic local structure through a predetermined graph of both labeled and unlabeled data. However, besides the parameter tuning problem underlying the construction of the graph, the affinity measurement in the original feature space usually suffers from the curse of dimensionality. Additionally, the predetermined graph separates itself from the procedure of feature selection, which might lead to downgraded performance for video semantic recognition. In this paper, we exploit a novel semisupervised feature selection method from a new perspective. The primary assumption underlying our model is that the instances with similar labels should have a larger probability of being neighbors. Instead of using a predetermined similarity graph, we incorporate the exploration of the local structure into the procedure of joint feature selection so as to learn the optimal graph simultaneously. Moreover, an adaptive loss function is exploited to measure the label fitness, which significantly enhances model's robustness to videos with a small or substantial loss. We propose an efficient alternating optimization algorithm to solve the proposed challenging problem, together with analyses on its convergence and computational complexity in theory. Finally, extensive experimental results on benchmark datasets illustrate the effectiveness and superiority of the proposed approach on video semantic recognition related tasks.

Luo, M, Nie, F, Chang, X, Yang, Y, Hauptmann, AG & Zheng, Q 2018, 'Adaptive Unsupervised Feature Selection With Structure Regularization', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 4, pp. 944-956.
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© 2012 IEEE. Feature selection is one of the most important dimension reduction techniques for its efficiency and interpretation. Since practical data in large scale are usually collected without labels, and labeling these data are dramatically expensive and time-consuming, unsupervised feature selection has become a ubiquitous and challenging problem. Without label information, the fundamental problem of unsupervised feature selection lies in how to characterize the geometry structure of original feature space and produce a faithful feature subset, which preserves the intrinsic structure accurately. In this paper, we characterize the intrinsic local structure by an adaptive reconstruction graph and simultaneously consider its multiconnected-components (multicluster) structure by imposing a rank constraint on the corresponding Laplacian matrix. To achieve a desirable feature subset, we learn the optimal reconstruction graph and selective matrix simultaneously, instead of using a predetermined graph. We exploit an efficient alternative optimization algorithm to solve the proposed challenging problem, together with the theoretical analyses on its convergence and computational complexity. Finally, extensive experiments on clustering task are conducted over several benchmark data sets to verify the effectiveness and superiority of the proposed unsupervised feature selection algorithm.

Luo, W, Xie, M, Song, X, Guo, W, Ngo, HH, Zhou, JL & Nghiem, LD 2018, 'Biomimetic aquaporin membranes for osmotic membrane bioreactors: Membrane performance and contaminant removal', Bioresource Technology, vol. 249, pp. 62-68.
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© 2017 Elsevier Ltd In this study, we investigated the performance of an osmotic membrane bioreactor (OMBR) enabled by a novel biomimetic aquaporin forward osmosis (FO) membrane. Membrane performance and removal of 30 trace organic contaminants (TrOCs) were examined. Results show that the aquaporin FO membrane had better transport properties in comparison with conventional cellulose triacetate and polyamide thin-film composite FO membranes. In particular, the aquaporin FO membrane exhibited much lower salt permeability and thus smaller reverse salt flux, resulting in a less severe salinity build-up in the bioreactor during OMBR operation. During OMBR operation, the aquaporin FO membrane well complemented biological treatment for stable and excellent contaminant removal. All 30 TrOCs selected here were removed by over 85% regardless of their diverse properties. Such high and stable contaminant removal over OMBR operation also indicates the stability and compatibility of the aquaporin FO membrane in combination with activated sludge treatment.

Luo, Y, Pan, J, Zhang, JA & Huang, S 2018, 'Worst-Case Performance Optimization Beamformer with Embedded Array’s Active Pattern', International Journal of Antennas and Propagation, vol. 2018, pp. 1-5.
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This paper proposes an adaptive array beamforming method by embedding antennas’ active pattern in the worst-case performance optimization algorithm. This method can significantly reduce the beamformer’s performance degradation caused by inconsistency between hypothesized ideal array models and practical ones. Simulation and measured results consistently demonstrate the robustness and effectiveness of the proposed method in dealing with array manifold mismatches.

Lv, X, Ma, Y, He, X, Huang, H & Yang, J 2018, 'CciMST: A Clustering Algorithm Based on Minimum Spanning Tree and Cluster Centers', Mathematical Problems in Engineering, vol. 2018, pp. 1-14.
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The minimum spanning tree- (MST-) based clustering method can identify clusters of arbitrary shape by removing inconsistent edges. The definition of the inconsistent edges is a major issue that has to be addressed in all MST-based clustering algorithms. In this paper, we propose a novel MST-based clustering algorithm through the cluster center initialization algorithm, called cciMST. First, in order to capture the intrinsic structure of the data sets, we propose the cluster center initialization algorithm based on geodesic distance and dual densities of the points. Second, we propose and demonstrate that the inconsistent edge is located on the shortest path between the cluster centers, so we can find the inconsistent edge with the length of the edges as well as the densities of their endpoints on the shortest path. Correspondingly, we obtain two groups of clustering results. Third, we propose a novel intercluster separation by computing the distance between the points at the intersection of clusters. Furthermore, we propose a new internal clustering validation measure to select the best clustering result. The experimental results on the synthetic data sets, real data sets, and image data sets demonstrate the good performance of the proposed MST-based method.

Ly, QV, Nghiem, LD, Cho, J & Hur, J 2018, 'Insights into the roles of recently developed coagulants as pretreatment to remove effluent organic matter for membrane fouling mitigation', Journal of Membrane Science, vol. 564, pp. 643-652.
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Ly, QV, Nghiem, LD, Sibag, M, Maqbool, T & Hur, J 2018, 'Effects of COD/N ratio on soluble microbial products in effluent from sequencing batch reactors and subsequent membrane fouling', Water Research, vol. 134, pp. 13-21.
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The relative ratios of chemical oxygen demand (COD) to nitrogen (N) in wastewater are known to have profound effects on the characteristics of soluble microbial products (SMP) from activated sludge. In this study, the changes in the SMP characteristics upon different COD/N ratios and the subsequent effects on ultrafiltration (UF) membrane fouling potentials were examined in sequencing batch reactors (SBR) using excitation emission matrix-parallel factor analysis (EEM-PARAFAC) and size exclusion chromatography (SEC). Three unique fluorescent components were identified from the SMP samples in the bioreactors operated at the COD/N ratios of 100/10 (N rich), 100/5 (N medium), and 100/2 (N deficient). The tryptophan-like component (C1) was the most depleted at the N medium condition. Fulvic-like (C2) and humic-like (C3) components were more abundant with N rich wastewater. Greater abundances of large size biopolymer (BP) and low molecular weight neutrals (LMWN) were found under the N deficient and N rich conditions, respectively. SMPs from various COD/N exhibited a greater degree on membrane fouling following the order of 100/2 > 100/10 > 100/5. C1 and C2 had close associations with reversible and irreversible fouling, respectively, while the reversible fouling potential of C3 depended on the COD/N ratios. No significant impact of COD/N ratio was observed on the relative contributions of SMP size fractions to either reversible or irreversible fouling potential. However, the COD/N ratios likely altered the BP foulants' composition with greater contribution of proteinaceous substances to reversible fouling under the N deficient condition than at other N richer conditions. The opposite trend was observed for irreversible fouling. Our results provided further insight into changes in different SMP constitutes and their membrane fouling in response to microbial activities under different COD/N ratios.

Lyu, X, Ni, W, Tian, H, Liu, RP, Wang, X, Giannakis, GB & Paulraj, A 2018, 'Distributed Online Optimization of Fog Computing for Selfish Devices With Out-of-Date Information', IEEE Transactions on Wireless Communications, vol. 17, no. 11, pp. 7704-7717.
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© 2002-2012 IEEE. By performing fog computing, a device can offload delay-tolerant computationally demanding tasks to its peers for processing, and the results can be returned and aggregated. In distributed wireless networks, the challenges of fog computing include lack of central coordination, selfish behaviors of devices, and multi-hop signaling delays, which can result in outdated network knowledge and prevent effective cooperations beyond one hop. This paper presents a new approach to enable cooperations of N selfish devices over multiple hops, where selfish behaviors are discouraged by a tit-for-tat mechanism. The tit-for-tat incentive of a device is designed to be the gap between the helps (in terms of energy) the device has received and offered; and indicates how much help the device can offer at the next time slot. The tit-for-tat incentives can be evaluated at every device by having all devices broadcast how much help they offered in the past time slot, and used by all devices to schedule task offloading and processing. The approach achieves asymptotic optimality in a fully distributed fashion with a time-complexity of less than O(N2). The optimality loss resulting from multi-hop signaling delays and consequently outdated tit-for-tat incentives is proved to asymptotically diminish. Simulation results show that our approach substantially reduces the time-average energy consumption of the state of the art by 50% and accommodates more tasks, by engaging devices hops away under multi-hop delays.

Lyu, X, Ren, C, Ni, W, Tian, H & Liu, RP 2018, 'Distributed Optimization of Collaborative Regions in Large-Scale Inhomogeneous Fog Computing', IEEE Journal on Selected Areas in Communications, vol. 36, no. 3, pp. 574-586.
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© 1983-2012 IEEE. Fog computing enables resource-limited network devices to help each other with computationally demanding tasks, but has yet to be implemented in large scales due to sophisticated control and network inhomogeneity. This paper presents a new fully distributed online optimization to asymptotically minimize the time-average cost of fog computing, where tasks are selected to be offloaded and processed independently between different links and devices by measuring their cost effectiveness at each time slot. A key contribution is that we optimize the cost-effectiveness measures which achieve the asymptotic optimality over infinite time. Another contribution is that we optimize placeholders at the devices; which create collaborative computing regions of tasks in the vicinity of the point of capture, prevent tasks being offloaded beyond, preserve the asymptotic optimality and reduce delay. This is achieved in a distributed fashion by discovering the optimal substructure of the placeholders. Simulations show that the average size of collaborative regions is only 3.2 out of total 500 servers, and the system income increases by 43% as compared with existing techniques.

Lyu, X, Ren, C, Ni, W, Tian, H, Liu, RP & Guo, YJ 2018, 'Multi-Timescale Decentralized Online Orchestration of Software-Defined Networks', IEEE Journal on Selected Areas in Communications, vol. 36, no. 12, pp. 2716-2730.
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© 1983-2012 IEEE. Decentralized orchestration of the control plane is critical to the scalability and reliability of software-defined network (SDN). However, existing orchestrations of SDN are either one-off or centralized, and would be inefficient the presence of temporal and spatial variations in traffic requests. In this paper, a fully distributed orchestration is proposed to minimize the time-average cost of SDN, adapting to the variations. This is achieved by stochastically optimizing the on-demand activation of controllers, adaptive association of controllers and switches, and real-time request processing and dispatching. The proposed approach is able to operate at multiple timescales for activation and association of controllers, and request processing and dispatching, thereby alleviating potential service interruptions caused by orchestration. A new analytic framework is developed to confirm the asymptotic optimality of the proposed approach in the presence of non-negligible signaling delays between controllers. Corroborated from extensive simulations, the proposed approach can save up to 73% the time-average operational cost of SDN, as compared to the existing static orchestration.

Lyu, X, Tian, H, Ni, W, Zhang, Y, Zhang, P & Liu, RP 2018, 'Energy-Efficient Admission of Delay-Sensitive Tasks for Mobile Edge Computing', IEEE Transactions on Communications, vol. 66, no. 6, pp. 2603-2616.
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© 1972-2012 IEEE. Task admission is critical to delay-sensitive applications in mobile edge computing, but is technically challenging due to its combinatorial mixed nature and consequently limited scalability. We propose an asymptotically optimal task admission approach which is able to guarantee task delays and achieve (1 - ∈)-approximation of the computationally prohibitive maximum energy saving at a time-complexity linearly scaling with devices. ∈ is linear to the quantization interval of energy. The key idea is to transform the mixed integer programming of task admission to an integer programming (IP) problem with the optimal substructure by pre-admitting resource-restrained devices. Another important aspect is a new quantized dynamic programming algorithm which we develop to exploit the optimal substructure and solve the IP. The quantization interval of energy is optimized to achieve an [O(∈),O(1/∈)]-tradeoff between the optimality loss and time complexity of the algorithm. Simulations show that our approach is able to dramatically enhance the scalability of task admission at a marginal cost of extra energy, as compared with the optimal branch and bound method, and can be efficiently implemented for online programming.

Ma, B, Lei, G, Liu, C, Zhu, J & Guo, Y 2018, 'Robust Tolerance Design Optimization of a PM Claw Pole Motor With Soft Magnetic Composite Cores', IEEE Transactions on Magnetics, vol. 54, no. 3, pp. 1-4.
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© 1965-2012 IEEE. In the past decades, various methods have been investigated for assessing performance variation and robust optimization for electromagnetic device design under uncertainties and/or tolerances. However, in actual production, the manufacturing tolerances are variable to a certain extent, which can be optimized for integrating the performance, manufacturing cost, and production quality. This paper proposes a tolerance design optimization approach by optimizing the design parameters and tolerances simultaneously based on design for six sigma technique. A permanent magnet claw pole motor with soft magnetic composite cores is optimized by using the proposed approach. For this high-dimensional optimization problem involving electromagnetic and thermal performance, Kriging model and 3-D thermal network model are employed under the multilevel framework for increasing the optimization efficiency. Finally, through the analysis, the proposed robust tolerance optimization method shows good performance with improved motor performance as well as the diversity controlling without cost increasing.

Ma, C, Chen, C, Li, Q, Gao, H, Kang, Q, Fang, J, Cui, H, Teng, K & Lv, X 2018, 'Analytical Calculation of No-Load Magnetic Field of External Rotor Permanent Magnet Brushless Direct Current Motor Used as In-Wheel Motor of Electric Vehicle', IEEE Transactions on Magnetics, vol. 54, no. 4, pp. 1-6.
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© 1965-2012 IEEE. An analytical method for calculating the no-load magnetic field of external rotor permanent magnet brushless direct current motor (PMBLDCM) used as in-wheel motor of electric vehicle in the stator static coordinate and the rotor motion coordinate is presented in this paper. First, the analytic formulas of slotless permanent magnetic field in both coordinate systems are derived, respectively. Then, the complex relative permeance of external rotor PMBLDCM in both coordinate systems is calculated. Finally, the analytical solution of the no-load magnetic field in both coordinate systems is derived by applying the magnetic potential multiplied by the complex relative permeance. In this paper, a 46-pole-51-slot external rotor PMBLDCM is taken as an example, and the accuracy of the proposed analytical model is verified by the finite-element results. Based on the analytical model, the influences of the stator slotting effect on the no-load magnetic field of the external rotor and the inner stator are analyzed. The spatial order characteristics and frequency characteristics of the no-load magnetic field of the external rotor PMBLDCM in both coordinate systems are revealed, respectively.

Ma, H, Xiong, R, Wang, Y, Kodagoda, S & Shi, L 2018, 'Towards open-set semantic labeling in 3D point clouds : Analysis on the unknown class', Neurocomputing, vol. 275, pp. 1282-1294.
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© 2017 Elsevier B.V. There has been a growing interest in the research of semantic labeling on scenes represented by 3D point clouds. A fundamental issue that has been largely ignored is the unavoidable presence of unknown objects and the lack of effective ways of dealing with them. Traditional methods usually label unknown objects as one of the pre-trained classes which is either a meaningful target class or a defined unknown class that collectively refers to all uninterested objects. Due to the fact that the class of unknown in essence is a collection of many unseen or uninterested classes, in which the in-class variation is significant and less manageable. It is challenging to solve the unknown problem in a pre-trained manner. In order to advance the research on semantic labeling with the presence of unknown objects, this study investigates the feasibility of adopting an open-set approach, i.e. train a model without unknown objects and reject them accurately in the test. In this paper, we propose a method that exploits the conflict of different labeling results in order to withstand the negative effect of unknown objects. The proposed framework relies on a Conditional Random Field (CRF) to capture inherent spatial relationships and appearance similarities between objects, and employs a Probability of Inclusion Support Vector Machine (P I SVM) to estimate an unknown likelihood for each training class. The probabilistic outputs from both CRF and P I SVM are then proposed to be combined under the Dempster Shafer theory for conflict measurement and unkno wn rejection. The novelty lies in that the method encodes both contextual constrains and unknown likelihood for performance enhancement. Comprehensive experimental results on publicly available data sets are presented to show the negative effects of unknown objects and the improvements on labeling accuracy achieved by the proposed method.

Ma, H, Yu, S, Gabbouj, M & Mueller, P 2018, 'Guest Editorial Special Issue on Multimedia Big Data in Internet of Things', IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3405-3407.
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Ma, J, Fan, F, Zhang, L, Wu, C & Zhi, X 2018, 'Failure modes and failure mechanisms of single-layer reticulated domes subjected to interior blasts', Thin-Walled Structures, vol. 132, pp. 208-216.
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© 2018 Single-layer reticulated domes are very common spatial structures. As landmarks, these types of structures can more easily be the targets of terrorist attacks than other buildings. However, blast resistance is not taken into consideration in the design of most civil structures. Therefore, it is important to know the damage level that may be imparted to single-layer reticulated domes after a blast attack. In this study, the dynamic response of reticulated domes subjected to an interior blast was investigated with numerical simulations, and five typical failure modes were identified from the results. In addition, the effects of some important parameters were investigated with a case study. Relationships between failure modes and interior blast impulses were summarised. Finally, the failure mechanisms were analysed, which could provide some design suggestions to decrease the probability of severe damage in spatial structures subjected to extreme dynamic loads.

Ma, X, Liang, J, Liu, R, Ni, W, Li, Y, Li, R, Ma, W & Qi, C 2018, 'A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems', Sensors, vol. 18, no. 2, pp. 546-546.
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In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.

Ma, X-L, Shang, F, Ni, W, Zhu, J, Luo, B & Zhang, Y-Q 2018, 'MicroRNA-338-5p plays a tumor suppressor role in glioma through inhibition of the MAPK-signaling pathway by binding to FOXD1', Journal of Cancer Research and Clinical Oncology, vol. 144, no. 12, pp. 2351-2366.
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Ma, XY, Li, Q, Wang, XC, Wang, Y, Wang, D & Ngo, HH 2018, 'Micropollutants removal and health risk reduction in a water reclamation and ecological reuse system', Water Research, vol. 138, pp. 272-281.
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Ma, Y, Yu, Z, Han, G, Li, J & Anh, V 2018, 'Identification of pre-microRNAs by characterizing their sequence order evolution information and secondary structure graphs', BMC Bioinformatics, vol. 19, no. S19, pp. 521-521.
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BACKGROUND:Distinction between pre-microRNAs (precursor microRNAs) and length-similar pseudo pre-microRNAs can reveal more about the regulatory mechanism of RNA biological processes. Machine learning techniques have been widely applied to deal with this challenging problem. However, most of them mainly focus on secondary structure information of pre-microRNAs, while ignoring sequence-order information and sequence evolution information. RESULTS:We use new features for the machine learning algorithms to improve the classification performance by characterizing both sequence order evolution information and secondary structure graphs. We developed three steps to extract these features of pre-microRNAs. We first extract features from PSI-BLAST profiles and Hilbert-Huang transforms, which contain rich sequence evolution information and sequence-order information respectively. We then obtain properties of small molecular networks of pre-microRNAs, which contain refined secondary structure information. These structural features are carefully generated so that they can depict both global and local characteristics of pre-microRNAs. In total, our feature space covers 591 features. The maximum relevance and minimum redundancy (mRMR) feature selection method is adopted before support vector machine (SVM) is applied as our classifier. The constructed classification model is named MicroRNA -NHPred. The performance of MicroRNA -NHPred is high and stable, which is better than that of those state-of-the-art methods, achieving an accuracy of up to 94.83% on same benchmark datasets. CONCLUSIONS:The high prediction accuracy achieved by our proposed method is attributed to the design of a comprehensive feature set on the sequences and secondary structures, which are capable of characterizing the sequence evolution information and sequence-order information, and global and local information of pre-microRNAs secondary structures. MicroRNA -NHPred is a valuable method for pre-microRNAs i...

Mahamedi, B, Zhu, JG, Eskandari, M, Fletcher, JE & Li, L 2018, 'Protection of inverter‐based microgrids from ground faults by an innovative directional element', IET Generation, Transmission & Distribution, vol. 12, no. 22, pp. 5918-5927.
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The complicated response of inverter‐interfaced distributed generators (IIDG) to faults has been reported, which severely affects all parts of relaying, i.e. fault sensing and polarisation, and faulted phase selection. Given this, the root causes of difficulties in dealing with the protection of inverter‐based microgrids are explained. Then, the study describes a directional element using unique features of zero‐sequence components that retains satisfactory performance even in IIDG‐based microgrids. The zero‐sequence component is the only sequence component that can be calculated in the time domain without time delay and thus can cause less delay in the outcome of protective schemes compared with the other two sequences. With this, instantaneous zero‐sequence power is defined and one term derived from it, zero‐sequence reactive power, is utilised to polarise ground faults. It is proven that the zero‐sequence reactive power is negative for forwarding ground faults and positive for reverse ground faults. An interesting feature is that the zero‐sequence reactive power is calculated by averaging a new quantity in the time domain over half a power cycle. Hence, the time delay is half that of the conventional phasor‐based methods. A sample microgrid is simulated in MATLAB/SIMULINK to evaluate the directional element and the results demonstrate the improvements.

Mahlia, TMI, Lim, JY, Aditya, L, Riayatsyah, TMI, Pg Abas, AE & Nasruddin 2018, 'Methodology for implementing power plant efficiency standards for power generation: potential emission reduction', Clean Technologies and Environmental Policy, vol. 20, no. 2, pp. 309-327.
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© 2017, The Author(s). Some methods of generating power such as power generation through coal, natural gas, oil result in inevitable emissions of greenhouse gases. While power generation is necessary due to its increasing demand, it is important for power companies to generate their power in an efficient manner to reduce its effect on the environment. One of the most effective ways of tackling inefficiency issues is through the implementation of efficiency standard. While there exist a lot of studies addressing the topic of energy efficiency standards, there are very few papers that deal specifically with efficiency standard for power generation plant. This paper presents methodology for the implementation of power plant efficiency standard; as mandatory or voluntary regulatory instrument, that may be implemented by the government to control greenhouse emissions from power plants. It is hoped that through its implementation, power companies shall become more conscious of their efficiency and emission quality, hereby encouraging the adoption of more efficient energy sources and latest available technologies. In this paper, methods of calculating greenhouse intensity value and its corresponding allowable ranges have been demonstrated. Case study on a 10-year-old base-load multi-fuel-fired power plant in Malaysia has shown that the power plant is in conformance to the power plant efficiency standard, with an actual greenhouse intensity of 859.4461 kgCO2/MWh sent-out, well within the allowable range of greenhouse intensities for that power plant which is between 760 and 890 kgCO2/MWh sent-out. It has also been demonstrated that older power plants are allowed to have higher values of greenhouse intensity. Benefits of utilising natural gas and operating the power plant at full load have also been shown.

Mahmud, K, Amin, U, Hossain, MJ & Ravishankar, J 2018, 'Computational tools for design, analysis, and management of residential energy systems', Applied Energy, vol. 221, pp. 535-556.
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Mahmud, K, Hossain, MJ & Town, GE 2018, 'Peak-Load Reduction by Coordinated Response of Photovoltaics, Battery Storage, and Electric Vehicles', IEEE Access, vol. 6, pp. 29353-29365.
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Peak-load management is an important process that allows energy providers to reshape load profiles, increase energy efficiency, and reduce overall operational costs and carbon emissions. This paper presents an improved decision-tree-based algorithm to reduce the peak load in residential distribution networks by coordinated control of electric vehicles (EVs), photovoltaic (PV) units, and battery energy-storage systems (BESSs). The peak-load reduction is achieved by reading the domestic load in real time through a smart meter and taking appropriate coordinated action by a controller using the proposed algorithm. The proposed control algorithm was tested on a real distribution network using real load patterns and load dynamics, and validated in a laboratory experiment. Two types of EVs with fast and flexible charging capability, a PV unit, and BESSs were used to test the performance of the proposed control algorithm, which is compared with that of an artificial-neural-network technique. The results show that using the proposed method, the peak demand on the distribution grid can be reduced significantly, thereby greatly improving the load factor.

Mahmud, K, Town, GE, Morsalin, S & Hossain, MJ 2018, 'Integration of electric vehicles and management in the internet of energy', Renewable and Sustainable Energy Reviews, vol. 82, pp. 4179-4203.
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Mai, HT, Tran, TS, Ho-Le, TP, Pham, TT, Center, JR, Eisman, JA & Nguyen, TV 2018, 'Low-trauma rib fracture in the elderly: Risk factors and mortality consequence', Bone, vol. 116, pp. 295-300.
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© 2018 Elsevier Inc. Purpose: Low trauma rib fracture (hereinafter, rib fracture) is common in the elderly, but its risk factors and mortality consequence are rarely studied. We sought to define the epidemiology of rib fracture and the association between rib fracture and postfracture mortality. Methods: The study was part of the Dubbo Osteoporosis Epidemiology Study, which was designed as a population-based prospective study, and consisted of 2041 women and men (aged ≥ 60). The incidence of rib fracture was ascertained from X-ray reports. Bone mineral density (BMD) was measured by DXA (GE-Lunar). The time-dependent Cox model was used to access the relationship between rib fracture and mortality. Results: During the median follow-up of 13 years, 59 men and 78 women had sustained a rib fracture, making the annual incidence of 4.8/1000 person-years. Each SD (0.15 g/cm 2 ) lower in femoral neck BMD was associated with ~2-fold increase in the hazard of fracture (hazard ratio [HR] 1.9; 95% CI, 1.4 to 2.6 in men; and HR 2.1; 95% CI, 1.6 to 2.8 in women). Among those with a rib fracture, the incidence of subsequent fractures was 10.2/100 person-years. Compared with those without a fracture, the risk of mortality among those with a fracture was increased by ~7.8-fold (95% CI, 2.7 to 22.5) in men and 4.9-fold (95% CI 2.0 to 11.8) in women within the first year postfracture. Conclusions: A rib fracture signifies an increased risk of subsequent fractures and mortality. The increased risk of mortality during the first 2.5 years postfracture suggests a window of opportunity for treatment.

Maina, JW, Gonzalo, CP, Merenda, A, Kong, L, Schütz, JA & Dumée, LF 2018, 'The growth of high density network of MOF nano-crystals across macroporous metal substrates – Solvothermal synthesis versus rapid thermal deposition', Applied Surface Science, vol. 427, pp. 401-408.
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Fabrication of metal organic framework (MOF) films and membranes across macro-porous metal substrates is extremely challenging, due to the large pore sizes across the substrates, poor wettability, and the lack of sufficient reactive functional groups on the surface, which prevent high density nucleation of MOF crystals. Herein, macroporous stainless steel substrates (pore size 44 × 40 μm) are functionalized with amine functional groups, and the growth of ZIF-8 crystals investigated through both solvothermal synthesis and rapid thermal deposition (RTD), to assess the role of synthesis routes in the resultant membranes microstructure, and subsequently their performance. Although a high density of well interconnected MOF crystals was observed across the modified substrates following both techniques, RTD was found to be a much more efficient route, yielding high quality membranes under 1 h, as opposed to the 24 h required for solvothermal synthesis. The RTD membranes also exhibited high gas permeance, with He permeance of up to 2.954 ± 0.119 × 10 −6 mol m −2 s −1 Pa −1 , and Knudsen selectivities for He/N 2 , Ar/N 2 and CO 2 /N 2 , suggesting the membranes were almost defect free. This work opens up route for efficient fabrication of MOF films and membranes across macro-porous metal supports, with potential application in electrically mediated separation applications.

Maldonado, S, Merigó, J & Miranda, J 2018, 'Redefining support vector machines with the ordered weighted average', Knowledge-Based Systems, vol. 148, pp. 41-46.
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© 2018 Elsevier B.V. In this work, the classical soft-margin Support Vector Machine (SVM) formulation is redefined with the inclusion of an Ordered Weighted Averaging (OWA) operator. In particular, the hinge loss function is rewritten as a weighted sum of the slack variables to guarantee adequate model fit. The proposed two-step approach trains a soft-margin SVM first to obtain the slack variables, which are then used to induce the order for the OWA operator in a second SVM training. Originally developed as a linear method, our proposal extends it to nonlinear classification thanks to the use of Kernel functions. Experimental results show that the proposed method achieved the best overall performance compared with standard SVM and other well-known data mining methods in terms of predictive performance.

Male, SA, Gardner, A, Figueroa, E & Bennett, D 2018, 'Investigation of students’ experiences of gendered cultures in engineering workplaces', European Journal of Engineering Education, vol. 43, no. 3, pp. 360-377.
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© 2017 SEFI. Women remain severely under-represented in engineering in Australia as in all Western countries. This limits the pool of talent, standpoints and approaches within the profession. Furthermore, this under-representation equates to restriction of the benefits of being an engineer mainly to men. Gendered workplace experiences have been found to contribute to women leaving the profession. In this study we explore students’ experiences of gendered cultures in engineering workplaces, using interviews with a purposive sample of 13 students (4 male) recruited following a previous survey. Although the overall experience of workplace learning is positive for many students, male and female engineering students reported experiences consistent with masculine cultures. Educators and employers must proactively lead improvements to the culture in engineering workplaces, prepare students for gendered workplaces and support students to reflect during and after workplace experiences. The experiences presented here could be adapted to enhance inclusivity training.

Man, X, Liu, T, Xia, B, Luo, Z, Xie, L & Liu, J 2018, 'Space-coiling fractal metamaterial with multi-bandgaps on subwavelength scale', Journal of Sound and Vibration, vol. 423, pp. 322-339.
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© 2018 Elsevier Ltd Acoustic metamaterials are remarkably different from conventional materials, as they can flexibly manipulate and control the propagation of sound waves. Unlike the locally resonant metamaterials introduced in earlier studies, we designed an ultraslow artificial structure with a sound speed much lower than that in air. In this paper, the space-coiling approach is proposed for achieving artificial metamaterial for extremely low-frequency airborne sound. In addition, the self-similar fractal technique is utilized for designing space-coiling Mie-resonance-based metamaterials (MRMMs) to obtain a band-dispersive spectrum. The band structures of two-dimensional (2D) acoustic metamaterials with different fractal levels are illustrated using the finite element method. The low-frequency bandgap can easily be formed, and multi-bandgap properties are observed in high-level fractals. Furthermore, the designed MRMMs with higher order fractal space coiling shows a good robustness against irregular arrangement. Besides, the proposed artificial structure was found to modify and control the radiation field arbitrarily. Thus, this work provides useful guidelines for the design of acoustic filtering devices and acoustic wavefront shaping applications on the subwavelength scale.

Mangca, DC, Gerasta, OJ, Luna, AL, Zhu, X & Hora, JA 2018, 'On-the-fly Computation Method in Field-Programmable Gate Array for Analog-to-Digital Converter Linearity Testing', Journal of Engineering and Technological Sciences, vol. 50, no. 5, pp. 589-606.
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This paper presents a new approach to linearity testing of analog-to-digital converters (ADCs) through on-the-fly computation in field-programmable gate array (FPGA) hardware. The proposed method computes the linearity while it is processing without compromising the accuracy of the measurement, so very little overhead time is required to compute the final linearity. The results will be displayed immediately after a single ramp is supplied to the device under test. This is a cost-effective chip testing solution for semiconductor companies, achieved by reducing computing time and utilization of low-cost and low-specification automatic test equipment (ATE). The experimental results showed that the on-the-fly computation method significantly reduced the computation time (up to 44.4%) compared to the conventional process. Thus, for every 100M 12-bit ADC tested with 32 hits per code, the company can save up to 139,972 Php on electricity consumption.

Mann, G, Breitling, F, Vocks, C, Aurass, H, Steinmetz, M, Strassmeier, KG, Bisi, MM, Fallows, RA, Gallagher, P, Kerdraon, A, Mackinnon, A, Magdalenic, J, Rucker, H, Anderson, J, Asgekar, A, Avruch, IM, Bell, ME, Bentum, MJ, Bernardi, G, Best, P, Bîrzan, L, Bonafede, A, Broderick, JW, Brüggen, M, Butcher, HR, Ciardi, B, Corstanje, A, de Gasperin, F, de Geus, E, Deller, A, Duscha, S, Eislöffel, J, Engels, D, Falcke, H, Fender, R, Ferrari, C, Frieswijk, W, Garrett, MA, Grießmeier, J, Gunst, AW, van Haarlem, M, Hassall, TE, Heald, G, Hessels, JWT, Hoeft, M, Hörandel, J, Horneffer, A, Juette, E, Karastergiou, A, Klijn, WFA, Kondratiev, VI, Kramer, M, Kuniyoshi, M, Kuper, G, Maat, P, Markoff, S, McFadden, R, McKay-Bukowski, D, McKean, JP, Mulcahy, DD, Munk, H, Nelles, A, Norden, MJ, Orru, E, Paas, H, Pandey-Pommier, M, Pandey, VN, Pizzo, R, Polatidis, AG, Rafferty, D, Reich, W, Röttgering, H, Scaife, AMM, Schwarz, DJ, Serylak, M, Sluman, J, Smirnov, O, Stappers, BW, Tagger, M, Tang, Y, Tasse, C, ter Veen, S, Thoudam, S, Toribio, MC, Vermeulen, R, van Weeren, RJ, Wise, MW, Wucknitz, O, Yatawatta, S, Zarka, P & Zensus, JA 2018, 'Tracking of an electron beam through the solar corona with LOFAR', Astronomy & Astrophysics, vol. 611, pp. A57-A57.
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The Sun’s activity leads to bursts of radio emission, among other phenomena. An example is type-III radio bursts. They occur frequently and appear as short-lived structures rapidly drifting from high to low frequencies in dynamic radio spectra. They are usually interpreted as signatures of beams of energetic electrons propagating along coronal magnetic field lines. Here we present novel interferometric LOFAR (LOw Frequency ARray) observations of three solar type-III radio bursts and their reverse bursts with high spectral, spatial, and temporal resolution. They are consistent with a propagation of the radio sources along the coronal magnetic field lines with nonuniform speed. Hence, the type-III radio bursts cannot be generated by a monoenergetic electron beam, but by an ensemble of energetic electrons with a spread distribution in velocity and energy. Additionally, the density profile along the propagation path is derived in the corona. It agrees well with three-fold coronal density model by (1961, ApJ, 133, 983).

Mann, RL & Bremner, MJ 2018, 'Approximation Algorithms for Complex-Valued Ising Models on Bounded Degree Graphs', Quantum, vol. 3, p. 162.
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We study the problem of approximating the Ising model partition function withcomplex parameters on bounded degree graphs. We establish a deterministicpolynomial-time approximation scheme for the partition function when theinteractions and external fields are absolutely bounded close to zero.Furthermore, we prove that for this class of Ising models the partitionfunction does not vanish. Our algorithm is based on an approach due to Barvinokfor approximating evaluations of a polynomial based on the location of thecomplex zeros and a technique due to Patel and Regts for efficiently computingthe leading coefficients of graph polynomials on bounded degree graphs.Finally, we show how our algorithm can be extended to approximate certainoutput probability amplitudes of quantum circuits.

Mannan, A, Sabri, MFM, Kalam, MA & Hassan, MH 2018, 'Tribological performance of DLC/DLC and steel/DLC contacts in the presence of additivated oil', International Journal of Surface Science and Engineering, vol. 12, no. 1, pp. 60-60.
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Marjanovic, O & Dinter, B 2018, 'Learning from the history of Business Intelligence and Analytics Research at HICSS – A Semantic Text Mining Approach', Communications of the Association for Information Systems, vol. 43, pp. 775-791.
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Marsavela, G, Aya-Bonilla, CA, Warkiani, ME, Gray, ES & Ziman, M 2018, 'Melanoma circulating tumor cells: Benefits and challenges required for clinical application', Cancer Letters, vol. 424, pp. 1-8.
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© 2018 The implementation of novel therapeutic interventions has improved the survival rates of melanoma patients with metastatic disease. Nonetheless, only 33% of treated cases exhibit long term responses. Circulating tumor cell (CTC) measurements are currently of clinical value in breast, prostate and colorectal cancers. However, the clinical utility of melanoma CTCs (MelCTCs) is still unclear due to challenges that appear intrinsic to MelCTCs (i.e. rarity, heterogeneity) and a lack of standardization in their isolation, across research laboratories. Here, we review the latest developments, pinpoint the challenges in MelCTC isolation and address their potential role in melanoma management.

Martínez-López, FJ, Merigó, JM, Valenzuela-Fernández, L & Nicolás, C 2018, 'Fifty years of the European Journal of Marketing: a bibliometric analysis', European Journal of Marketing, vol. 52, no. 1/2, pp. 439-468.
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PurposeThe European Journal of Marketing was created in 1967. In 2017, the journal celebrates its 50th anniversary. Therefore, the purpose of this study is to present a bibliometric overview of the leading trends of the journal during this period.Design/methodology/approachThis work uses the Scopus database to analyse the most productive authors, institutions and countries, as well as the most cited papers and the citing articles. The investigation uses bibliometric indicators to represent the bibliographic data, including the total number of publications and citations between 1967 and 2017. Additionally, the article also develops a graphical visualization of the bibliographic material by using the visualization of similarities viewer software to map journals, keywords and institutions with bibliographic coupling and co-citation analysis.FindingsBritish authors and institutions are the most productive in the journal, although Australians’ are growing significantly the number of papers published. Continental European institutions are also increasing the number of publications, but they are still far from reaching the British contribution so far. In the mid-term, however, these zone’s authors and institutions, especially those from big European countries like France, Germany, Italy and Spain, should reach a closer performance to British ones; more as less long, historic, but more recent periods of analysis are considered.Practical implicationsThis article is useful for any reader of this journal to understand questions such as papers’ Eu...

Masoudi, M, Jokar, P & Pradhan, B 2018, 'A new approach for land degradation and desertification assessment using geospatial techniques', Natural Hazards and Earth System Sciences, vol. 18, no. 4, pp. 1133-1140.
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Abstract. Land degradation reduces the production of biomass and vegetation cover for all forms of land use. The lack of specific data related to degradation is a severe limitation for its monitoring. Assessment of the current state of land degradation or desertification is very difficult because this phenomenon includes several complex processes. For that reason, no common agreement has been achieved among the scientific community for its assessment. This study was carried out as an attempt to develop a new approach for land degradation assessment, based on its current state by modifying of Food and Agriculture Organization (FAO)–United Nations Environment Programme (UNEP) index and the normalized difference vegetation index (NDVI) index in Khuzestan province, southwestern Iran. Using the proposed evaluation method it is easy to understand the degree of destruction caused by the pursuit of low costs and in order to save time. Results showed that based on the percent of hazard classes in the current condition of land degradation, the most and least widespread areas of hazard classes are moderate (38.6 %) and no hazard (0.65 %) classes, respectively. Results in the desert component of the study area showed that the severe class is much more widespread than the other hazard classes, which could indicate an environmentally dangerous situation. Statistical results indicated that degradation is highest in deserts and rangeland areas compared to dry cultivated areas and forests. Statistical tests also showed that the average degradation amount in the arid region is higher than in other climates. It is hoped that this study's use of geospatial techniques will be found to be applicable in other regions of the world and can also contribute to better planning and management of land.

Matin, SS, Farahzadi, L, Makaremi, S, Chelgani, SC & Sattari, G 2018, 'Variable selection and prediction of uniaxial compressive strength and modulus of elasticity by random forest', Applied Soft Computing, vol. 70, pp. 980-987.
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Mauleon-mendez, E, Genovart-balaguer, J, Merigo, J & Mulet-forteza, C 2018, 'Sustainable Tourism Research Towards Twenty-Five Years of the Journal of Sustainable Tourism', Advances in Hospitality and Tourism Research (AHTR), vol. 6, no. 1, pp. 23-46.
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The Journal of Sustainable Tourism(JOST) is a main journal in ‘Geography, Planning and Development’. This paperpresents a general overview of the journal over its lifetime by using bibliometricindicators. The paper uses the Scopus database to analyse the bibliometricdata. This analysis includes key issues such as the publication and citationstructure of the journal; the most cited articles; the leading authors,institutions, and countries in the journal; and the keywords that are mostoften used. This paper also uses the visualization of similarities tographically map the bibliographic material. This analysis provides furtherinsights into how JOST links to other journals and how it links researchersacross the globe. These results indicate that JOST is one of the leadingjournals in the areas where the journal is indexed,with a wide range of authors from institutions and countries from allover the world publishing in it. 

Mazaheri, H, Ong, HC, Masjuki, HH, Amini, Z, Harrison, MD, Wang, C-T, Kusumo, F & Alwi, A 2018, 'Rice bran oil based biodiesel production using calcium oxide catalyst derived from Chicoreus brunneus shell', Energy, vol. 144, pp. 10-19.
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Meng, F, Rui, X, Wang, Z, Xing, Y & Cao, L 2018, 'Coupled Node Similarity Learning for Community Detection in Attributed Networks', Entropy, vol. 20, no. 6, pp. 471-471.
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Attributed networks consist of not only a network structure but also node attributes. Most existing community detection algorithms only focus on network structures and ignore node attributes, which are also important. Although some algorithms using both node attributes and network structure information have been proposed in recent years, the complex hierarchical coupling relationships within and between attributes, nodes and network structure have not been considered. Such hierarchical couplings are driving factors in community formation. This paper introduces a novel coupled node similarity (CNS) to involve and learn attribute and structure couplings and compute the similarity within and between nodes with categorical attributes in a network. CNS learns and integrates the frequency-based intra-attribute coupled similarity within an attribute, the co-occurrence-based inter-attribute coupled similarity between attributes, and coupled attribute-to-structure similarity based on the homophily property. CNS is then used to generate the weights of edges and transfer a plain graph to a weighted graph. Clustering algorithms detect community structures that are topologically well-connected and semantically coherent on the weighted graphs. Extensive experiments verify the effectiveness of CNS-based community detection algorithms on several data sets by comparing with the state-of-the-art node similarity measures, whether they involve node attribute information and hierarchical interactions, and on various levels of network structure complexity.

Meng, J, Huang, J, Sheng, D & Sloan, SW 2018, 'Closure to “Quasi-Static Rheology of Granular Media Using the Static DEM” by J. Meng, J. Huang, D. Sheng, and S. W. Sloan', International Journal of Geomechanics, vol. 18, no. 12, pp. 07018016-07018016.
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Meng, J, Huang, J, Sloan, SW & Sheng, D 2018, 'Discrete modelling jointed rock slopes using mathematical programming methods', Computers and Geotechnics, vol. 96, pp. 189-202.
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Meng, J, Huang, J, Yao, C & Sheng, D 2018, 'A discrete numerical method for brittle rocks using mathematical programming', Acta Geotechnica, vol. 13, no. 2, pp. 283-302.
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Merigó, JM, Gil-Lafuente, AM, Yu, D & Llopis-Albert, C 2018, 'Fuzzy decision making in complex frameworks with generalized aggregation operators', Applied Soft Computing, vol. 68, pp. 314-321.
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© 2018 Elsevier B.V. This article presents a new aggregation system applied to fuzzy decision making. The fuzzy generalized unified aggregation operator (FGUAO) is a system that integrates many operators by adding a new aggregation process that considers the relevance that each operator has in the analysis. It also deals with an uncertain environment where the information is studied with fuzzy numbers. A wide range of particular cases and properties are studied. This approach is further extended by using quasi-arithmetic means. The paper ends studying the applicability in decision making problems regarding the European Union decisions. For doing so, the work uses a multi-person aggregation process obtaining the multi-person – FGUAO operator. An example concerning the fixation of the interest rate by the European Central Bank is presented.

Merigó, JM, Pedrycz, W, Weber, R & de la Sotta, C 2018, 'Fifty years of Information Sciences: A bibliometric overview', Information Sciences, vol. 432, pp. 245-268.
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© 2017 Elsevier Inc. Information Sciences is a leading international journal in computer science launched in 1968, so becoming fifty years old in 2018. In order to celebrate its anniversary, this study presents a bibliometric overview of the leading publication and citation trends occurring in the journal. The aim of the work is to identify the most relevant authors, institutions, countries, and analyze their evolution through time. The paper uses the Web of Science Core Collection in order to search for the bibliographic information. Our study also develops a graphical mapping of the bibliometric material by using the visualization of similarities (VOS) viewer. With this software, the work analyzes bibliographic coupling, citation and co-citation analysis, co-authorship, and co-occurrence of keywords. The results underline the significant growth of the journal through time and its international diversity having publications from countries all over the world.

Merigó, JM, Zhou, L, Yu, D, Alrajeh, N & Alnowibet, K 2018, 'Probabilistic OWA distances applied to asset management', Soft Computing, vol. 22, no. 15, pp. 4855-4878.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Average distances are widely used in many fields for calculating the distances between two sets of elements. This paper presents several new average distances by using the ordered weighted average, the probability and the weighted average. First, the work presents the probabilistic ordered weighted averaging weighted average distance (POWAWAD) operator. POWAWAD is a new aggregation operator that uses distance measures in a unified framework between the probability, the weighted average and the ordered weighted average (OWA) operator that considers the degree of importance that each concept has in the aggregation. The POWAWAD operator includes a wide range of particular cases including the maximum distance, the minimum distance, the normalized Hamming distance, the weighted Hamming distance and the ordered weighted average distance (OWAD). The article also presents further generalizations by using generalized and quasi-arithmetic means forming the generalized probabilistic ordered weighted averaging weighted average distance (GPOWAWAD) operator and the quasi-POWAWAD operator. The study ends analysing the applicability of this new approach in the calculation of the average fixed assets. Particularly, the work focuses on measuring the average distances between the ideal percentage of fixed assets that the companies of a specific country should have versus the real percentage of fixed assets they have. The illustrative example focuses on the Asian market.

Mesgari, S, Hjerrild, N, Arandiyan, H & Taylor, RA 2018, 'Carbon nanotube heat transfer fluids for solar radiant heating of buildings', Energy and Buildings, vol. 175, pp. 11-16.
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Solar-based radiant heating systems represent a sustainable, and relatively low-cost, technology to raise the temperature of the interior thermal mass of our buildings. Through the use of direct absorption solar thermal collectors, the same working fluid which absorbs the solar energy can be used to transfer the energy for storage in the thermal mass of the structure using a network of pipes embedded in concrete floors. This study investigates a promising working fluid which can be used in such systems – one which is based on multi-walled carbon-nanotubes suspended in normal base fluids. A major stumbling block affecting the wide spread use of carbon-nanotube nanofluids is their low dispersion stability at elevated temperatures, which significantly reduces the absorption capabilities of the nanofluids and could lead to clogging of the pumps used to circulate the fluids. In this paper, we report on a scalable UV-ozone (UVO) treatment technique to produce highly stable dispersions for the elevated temperatures experienced by working fluids in radiant heating systems. To probe suitability of UVO treated multi-walled carbon-nanotube (MWCNTs) for solar-assisted radiant heating systems, this paper investigates the effects of exposure time and temperature on stability, optical absorbance properties, the extent of functionalisation, and the photothermal conversion performance of UVO-treated MWCNT nanofluids. No agglomeration or degradation of the MWCNTs was observed at elevated temperatures (up to 150 °C), highlighting the stability of proposed nanofluids.

Metia, S, Ha, QP, Duc, HN & Azzi, M 2018, 'Estimation of Power Plant Emissions With Unscented Kalman Filter', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 8, pp. 2763-2772.
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© 2008-2012 IEEE. Emissions from power plants constitute a major part of air pollution and should be adequately estimated. In this paper, we consider the problem of estimating nitrogen dioxide (NO-X ) emission of power plants by developing an inverse method to integrate satellite observations of atmospheric pollutant column concentrations with species concentrations and direct sensitivities predicted by a regional air quality model, in order to discern biases in the emissions of the pollutant precursors. Using this method, the emission fields are analyzed using a 'bottom-up' approach, with an inversion performed by an unscented Kalman filter (UKF) to improve estimation profiles from emissions inventories data for the Sydney metropolitan area. The idea is to integrate information from the original inventories with tropospheric nitrogen dioxide (NO-2) emissions estimated during one month from the air pollution model-chemical transport model, and then, for validation, to compare the resulting model with satellite retrievals from the ozone monitoring instrument (OMI) above the region. The UKF-based estimation of NO-2 emissions shows better agreement with OMI observations, implying a significant improvement in accuracy as compared with the original inventories. Therefore, the proposed method is a promising tool for estimation of air emissions in urban areas.

Mezaal, MR & Pradhan, B 2018, 'An improved algorithm for identifying shallow and deep-seated landslides in dense tropical forest from airborne laser scanning data', CATENA, vol. 167, pp. 147-159.
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© 2018 Landslides are natural disasters that cause environmental and infrastructure damage worldwide. They are difficult to be recognized, particularly in densely vegetated regions of the tropical forest areas. Consequently, an accurate inventory map is required to analyze landslides susceptibility, hazard, and risk. Several studies were done to differentiate between different types of landslide (i.e. shallow and deep-seated); however, none of them utilized any feature selection techniques. Thus, in this study, three feature selection techniques were used (i.e. correlation-based feature selection (CFS), random forest (RF), and ant colony optimization (ACO)). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Random forest (RF) was used to evaluate the performance of each feature selection algorithms. The overall accuracies of the RF classifier revealed that CFS algorithm exhibited higher ranks in differentiation landslide types. Moreover, the results of the transferability showed that this method is easy, accurate, and highly suitable for differentiating between types of landslides (shallow and deep-seated). In summary, the study recommends that the outlined approaches are significant to improve in distinguishing between shallow and deep-seated landslide in the tropical areas, such as; Malaysia.

Mezaal, MR & Pradhan, B 2018, 'Data Mining-Aided Automatic Landslide Detection Using Airborne Laser Scanning Data in Densely Forested Tropical Areas', KOREAN JOURNAL OF REMOTE SENSING, vol. 34, no. 1, pp. 45-74.
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Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

Mezaal, MR, Pradhan, B & Rizeei, HM 2018, 'Improving Landslide Detection from Airborne Laser Scanning Data Using Optimized Dempster–Shafer', Remote Sensing, vol. 10, no. 7, pp. 1029-1029.
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A detailed and state-of-the-art landslide inventory map including precise landslide location is greatly required for landslide susceptibility, hazard, and risk assessments. Traditional techniques employed for landslide detection in tropical regions include field surveys, synthetic aperture radar techniques, and optical remote sensing. However, these techniques are time consuming and costly. Furthermore, complications arise for the generation of accurate landslide location maps in these regions due to dense vegetation in tropical forests. Given its ability to penetrate vegetation cover, high-resolution airborne light detection and ranging (LiDAR) is typically employed to generate accurate landslide maps. The object-based technique generally consists of many homogeneous pixels grouped together in a meaningful way through image segmentation. In this paper, in order to address the limitations of this approach, the final decision is executed using Dempster–Shafer theory (DST) rule combination based on probabilistic output from object-based support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN) classifiers. Therefore, this research proposes an efficient framework by combining three object-based classifiers using the DST method. Consequently, an existing supervised approach (i.e., fuzzy-based segmentation parameter optimizer) was adopted to optimize multiresolution segmentation parameters such as scale, shape, and compactness. Subsequently, a correlation-based feature selection (CFS) algorithm was employed to select the relevant features. Two study sites were selected to implement the method of landslide detection and evaluation of the proposed method (subset “A” for implementation and subset “B” for the transferrable). The DST method performed well in detecting landslide locations in tropical regions such as Malaysia, with potential applications in other similarly vegetated regions.

Mihăiţă, AS, Dupont, L & Camargo, M 2018, 'Multi-objective traffic signal optimization using 3D mesoscopic simulation and evolutionary algorithms', Simulation Modelling Practice and Theory, vol. 86, pp. 120-138.
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© 2018 Elsevier B.V. Modern cities are currently facing rapid urban growth and struggle to maintain a sustainable development. In this context, “eco-neighbourhoods” became the perfect place for testing new innovative ideas that would reduce congestion and optimize traffic flow. The main motivation of this work is a true and stated need of the Department of Transport in Nancy, France, to improve the traffic flow in a central eco-neighbourhood currently under reconfiguration, reduce travel times and test various traffic control scenarios for a better interconnectivity between urban intersections. Therefore, this paper addresses a multi-objective simulation-based signal control problem through the case study of “Nancy Grand Cœur” (NGC) eco-neighbourhood with the purpose of finding the optimal traffic control plan to reduce congestion during peak hours. Firstly, we build the 3D mesoscopic simulation model of the most circulated intersection (C129) based on specifications from the traffic management centre. The simulation outputs from various scenario testing will be then used as inputs for the optimisation and comparative analysis modules. Secondly, we propose a multi-objective optimization method by using evolutionary algorithms and find the optimal traffic control plan to be used in C129 during morning and evening rush hours. Lastly, we take a more global view and extend the 3D simulation model to three other interconnected intersections, in order to analyse the impact of local optimisation on the surrounding traffic conditions in the eco-neighbourhood. The current proposed simulation-optimisation framework aims at supporting the traffic engineering decision-making process and the smart city dynamic by favouring a sustainable mobility.

Milano, J, Ong, HC, Masjuki, HH, Silitonga, AS, Chen, W-H, Kusumo, F, Dharma, S & Sebayang, AH 2018, 'Optimization of biodiesel production by microwave irradiation-assisted transesterification for waste cooking oil-Calophyllum inophyllum oil via response surface methodology', Energy Conversion and Management, vol. 158, pp. 400-415.
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In this study, microwave irradiation-assisted alkaline-catalysed transesterification was used to produce W70CI30 biodiesel from a mixture of waste cooking oil and Calophyllum inophyllum oil. The methanol/oil ratio, catalyst concentration, stirring speed, and reaction time were optimized using response surface methodology based on the Box-Behnken experimental design in order to maximize the biodiesel yield. The quadratic response surface regression model was used to predict the biodiesel yield. It is found that the optimum methanol/oil ratio, catalyst concentration, stirring speed, and reaction time are 59.60 (v/v)%, 0.774 (w/w)%, 600 rpm, and 7.15 min, respectively, and the predicted biodiesel yield is 97.40%. Experiments were conducted using the optimum process parameters and the average biodiesel yield is 97.65%, which is in excellent agreement with the predicted value. The physicochemical properties of the W70CI30 biodiesel produced using the optimum process parameters were measured and it is found that the biodiesel has significantly higher oxidation stability (18.03 h) compared with the waste cooking oil biodiesel (4.61 h). In addition, the physicochemical properties and cold flow properties of the biodiesel fulfil the fuel specifications stipulated in the ASTM D6751 and EN 14214 standards. It can be concluded that microwave irradiation-assisted transesterification is effective to boost the biodiesel yield and produce biodiesel of superior quality. In addition, this method significantly reduces the reaction time of the transesterification process to 9.15 min and the process is energy-efficient. It is believed that the findings of this study will be beneficial for microwave irradiation-assisted biodiesel synthesis on the industrial scale.

Milano, J, Ong, HC, Masjuki, HH, Silitonga, AS, Kusumo, F, Dharma, S, Sebayang, AH, Cheah, MY & Wang, C-T 2018, 'Physicochemical property enhancement of biodiesel synthesis from hybrid feedstocks of waste cooking vegetable oil and Beauty leaf oil through optimized alkaline-catalysed transesterification', Waste Management, vol. 80, pp. 435-449.
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Recycling waste cooking vegetable oils by reclaiming and using these oils as biodiesel feedstocks is one of the promising solutions to address global energy demands. However, producing these biodiesels poses a significant challenge because of their poor physicochemical properties due the high free fatty acid content and impurities present in the feedstock, which will reduce the biodiesel yields. Hence, this study implemented the following strategy in order to address this issue: (1) 70 vol% of waste cooking vegetable oil blended with 30 vol% of Calophyllum inophyllum oil named as WC70CI30 used to alter its properties, (2) a three-stage process (degumming, esterification, and transesterification) was conducted which reduces the free fatty acid content and presence of impurities, and (3) the transesterification process parameters (methanol/oil ratio, reaction temperature, reaction time, and catalyst concentration) were optimized using response surface methodology in order to increase the biodiesel conversion yield. The results show that the WC70CI30 biodiesel has favourable physicochemical properties, good cold flow properties, and high oxidation stability (22.4 h), which fulfil the fuel specifications stated in the ASTM D6751 and EN 14214 standards. It found that the WC70CI30 biodiesel has great potential as a diesel substitute without the need for antioxidants and pour point depressants.

Ming, C, Rizwanul Fattah, IM, Chan, QN, Pham, PX, Medwell, PR, Kook, S, Yeoh, GH, Hawkes, ER & Masri, AR 2018, 'Combustion characterization of waste cooking oil and canola oil based biodiesels under simulated engine conditions', Fuel, vol. 224, pp. 167-177.
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Alternative fuels will come from a variety of feed stocks and refinement processes. Understanding the fundamentals of combustion and pollutants formation processes of these fuels will be useful for their implementation in different combustion systems. In this work, optical diagnostics were performed to waste cooking oil (WCO) and canola oil (CAO) based biodiesel sprays to assess their combustion and soot formation processes. Conventional diesel was used as a reference fuel for comparison with the biodiesels. The experiments were conducted in an optically-accessible constant-volume combustion chamber (CVCC) with simulated compression-ignition engine conditions, with different degree of exhaust gas recirculation. The liquid length and lift-off length results indicate that there was no significant interaction between the liquid phases of the fuels and their combustion regions. The flame lift-off lengths were found to be affected by both the chemical and physical properties of the fuels. It was observed that a larger difference between the lift-off length and the first-luminosity distance was correlated with lesser downstream soot formation, although the molecular structure of the fuel was found to affect the process too. Assessing the sooting and combustion characteristics of the biodiesel and diesel flames across the varied ambient O atmospheres revealed that the estimated soot contents of the biodiesel and diesel flames peaked at 15 and 21 vol.% O concentration, respectively. The peak soot contents of the WCO and CAO biodiesel flames were found be comparable, but lower than that of diesel, across the various O environment. The results also demonstrated that the biodiesels have higher normalized peak pressure values than diesel at all O conditions. Two-color pyrometry data demonstrated that the measured soot temperature and soot KL factors of the flames were similar at 15 and 21 vol.% O , but varied with further reduction of ambient O concentration. ...

Mirtalaie, MA, Hussain, OK, Chang, E & Hussain, FK 2018, 'Extracting sentiment knowledge from pros/cons product reviews: Discovering features along with the polarity strength of their associated opinions', Expert Systems with Applications, vol. 114, pp. 267-288.
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Sentiment knowledge extraction is a growing area of research in the literature. It helps in analyzing users’ opinions about different entities or events, which can then be utilized by analysts for various purposes. Particularly, feature-based sentiment analysis is one of the challenging research areas that analyzes users’ opinions on various features of a product or service. Of the three formats for the product reviews, our focus in this paper is limited to analyzing the pros/cons type. Due to the nature of pros/cons reviews, they are mostly concise and follow a different structure from other review types. Therefore, specialized techniques are needed to analyze these reviews and extract the customers’ discussed product features along with their personal attitudes. In this paper, we propose the Pros/Cons Sentiment Analyzer (PCSA) framework that exploits dependency relations in extracting sentiment knowledge from pros/cons reviews. We also utilize two different lexicons to ascertain the polarity strength of the extracted features based on the customers’ opinions. Several experiments are conducted to evaluate the performance of PCSA in its different phases.

Mirzababaei, M, Arulrajah, A, Haque, A, Nimbalkar, S & Mohajerani, A 2018, 'Effect of fiber reinforcement on shear strength and void ratio of soft clay', Geosynthetics International, vol. 25, no. 4, pp. 471-480.
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In this study, a series of multi-stage drained reverse direct shear tests were carried out on soft clay samples reinforced with 0.25% and 0.50% polypropylene fibers of 6 mm, 10 mm and 19 mm in length. Tests were carried out at different normal effective stresses and cumulative horizontal shear displacement of 1.17 times of the sample width. Results showed an increase of the shear strength with the increase of fiber content and length. However, the rate of improvement was capped with the normal effective stress applied during the shearing stage. At a high normal effective stress, the shear strength of the fiber-reinforced soft clay approached that of the unreinforced clay regardless of the amount of fiber inclusion. The rate of shear strength improvement decayed with the number of shear cycles. Fiber reinforcement also resulted in a reduction of the compressibility of the soft clay at consecutive consolidation and shear stages. Although the effective internal friction angle of the soft clay was not altered significantly with the fiber reinforcement, the effective cohesion of the soft clay improved significantly as much as 6.4 and 8.5 times with the inclusion of 0.25% and 0.50% of 10 mm long fibers, respectively.

Mishra, DK, Panigrahi, TK, Ray, PK & Mohanty, A 2018, 'Performance enhancement of AGC under open market scenario using TDOFPID and IPFC controller', Journal of Intelligent & Fuzzy Systems, vol. 35, no. 5, pp. 4933-4943.
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Mishra, SK, Puthal, D, Rodrigues, JJPC, Sahoo, B & Dutkiewicz, E 2018, 'Sustainable Service Allocation Using a Metaheuristic Technique in a Fog Server for Industrial Applications', IEEE Transactions on Industrial Informatics, vol. 14, no. 10, pp. 4497-4506.
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© 2005-2012 IEEE. Reducing energy consumption in the fog computing environment is both a research and an operational challenge for the current research community and industry. There are several industries such as finance industry or healthcare industry that require a rich resource platform to process big data along with edge computing in fog architecture. As a result, sustainable computing in a fog server plays a key role in fog computing hierarchy. The energy consumption in fog servers depends on the allocation techniques of services (user requests) to a set of virtual machines (VMs). This service request allocation in a fog computing environment is a nondeterministic polynomial-time hard problem. In this paper, the scheduling of service requests to VMs is presented as a bi-objective minimization problem, where a tradeoff is maintained between the energy consumption and makespan. Specifically, this paper proposes a metaheuristic-based service allocation framework using three metaheuristic techniques, such as particle swarm optimization (PSO), binary PSO, and bat algorithm. These proposed techniques allow us to deal with the heterogeneity of resources in the fog computing environment. This paper has validated the performance of these metaheuristic-based service allocation algorithms by conducting a set of rigorous evaluations.

Mitchell, BG, Gardner, A, Stone, PW, Hall, L & Pogorzelska-Maziarz, M 2018, 'Hospital Staffing and Health Care–Associated Infections: A Systematic Review of the Literature', The Joint Commission Journal on Quality and Patient Safety, vol. 44, no. 10, pp. 613-622.
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Moayedi, H & Jahed Armaghani, D 2018, 'Optimizing an ANN model with ICA for estimating bearing capacity of driven pile in cohesionless soil', Engineering with Computers, vol. 34, no. 2, pp. 347-356.
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Moazzam, P, Tavassoli, H, Razmjou, A, Warkiani, ME & Asadnia, M 2018, 'Mist harvesting using bioinspired polydopamine coating and microfabrication technology', Desalination, vol. 429, pp. 111-118.
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© 2017 Elsevier B.V. The fascinating biopolymer of polydopamine (PDA) and negative photolithography method was utilized to produce porous membrane surfaces with contrast wettabilities via creating hydrophilic patterns (nanoscale PDA coated SU-8 bumps) on the hydrophobic background of polypropylene (PP) membranes. The high rate of water collection (97 mg cm− 2 h− 1) highlighted the impact of hydrophilic patterns and wetting properties on mist-harvesting results. Modified samples exhibited droplet motion by coalescence rather than rolling which means created hydrophilic patterns also have a significant impact on the behavior of the droplets on these surfaces. Surface characterization including Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and contact angle as well as surface free energy measurement were performed to study the effect of topography and roughness on the system performance. This created structure has the great potential to be fabricated in large scale. Also, due to the porous nature of its hydrophobic background, water collection rate can be substantially increased by using vacuum pressure, makes it attractive for industry.

Moghimi, M, Liu, J, Jamborsalamati, P, Rafi, F, Rahman, S, Hossain, J, Stegen, S & Lu, J 2018, 'Internet of Things Platform for Energy Management in Multi-Microgrid System to Improve Neutral Current Compensation', Energies, vol. 11, no. 11, pp. 3102-3102.
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In this paper, an Internet of Things (IoT) platform is proposed for Multi-Microgrid (MMG) system to improve unbalance compensation functionality employing three-phase four-leg (3P-4L) voltage source inverters (VSIs). The two level communication system connects the MMG system, implemented in Power System Computer Aided Design (PSCAD), to the cloud server. The local communication level utilizes Modbus Transmission Control Protocol/Internet Protocol (TCP/IP) and Message Queuing Telemetry Transport (MQTT) is used as the protocol for global communication level. A communication operation algorithm is developed to manage the communication operation under various communication failure scenarios. To test the communication system, it is implemented on an experimental testbed to investigate its functionality for MMG neutral current compensation (NCC). To compensate the neutral current in MMG, a dynamic NCC algorithm is proposed, which enables the MGs to further improve the NCC by sharing their data using the IoT platform. The performance of the control and communication system using dynamic NCC is compared with the fixed capacity NCC for unbalance compensation under different communication failure conditions. The impact of the communication system performance on the NCC sharing is the focus of this research. The results show that the proposed system provides better neutral current compensation and phase balancing in case of MMG operation by sharing the data effectively even if the communication system is failing partially.

Mohamad, ET, Armaghani, DJ, Momeni, E, Yazdavar, AH & Ebrahimi, M 2018, 'Rock strength estimation: a PSO-based BP approach', Neural Computing and Applications, vol. 30, no. 5, pp. 1635-1646.
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Mohammadi-Moghaddam, T, Razavi, SMA, Taghizadeh, M, Pradhan, B, Sazgarnia, A & Shaker-Ardekani, A 2018, 'Hyperspectral imaging as an effective tool for prediction the moisture content and textural characteristics of roasted pistachio kernels', Journal of Food Measurement and Characterization, vol. 12, no. 3, pp. 1493-1502.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. The objective of this study was to develop calibration models for prediction of moisture content and textural characteristics (fracture force, hardness, apparent modulus of elasticity and compressive energy) of pistachio kernels roasted in different conditions (temperatures 90, 120 and 150 °C; times 20, 35 and 50 min and air velocities 0.5, 1.5 and 2.5 m/s) using Vis/NIR hyperspectral imaging and multivariate analysis. The effects of different pre-processing methods and spectral treatments such as normalization [multiplicative scatter correction (MSC), standard normal variate transformation (SNV)], smoothing (median filter, Savitzky–Golay and Wavelet) and differentiation (first derivative, D1 and second derivative, D2) on the obtained data were investigated. The prediction models were developed by partial least square regression (PLSR) and artificial neural network (ANN). The results indicated that ANN models have higher potential to predict moisture content and textural characteristics of roasted pistachio kernels comparing to PLSR models. High correlation was observed between reflectance data and fracture force (R2 = 0.957 and RMSEP = 3.386) using MSC, Savitzky–Golay and D1, compressive energy (R2 = 0.907 and RMSEP = 15.757) using the combination of MSC, Wavelet and D1, moisture content (R2 = 0.907 and RMSEP = 0.179) and apparent modulus of elasticity (R2 = 0.921 and RMSEP = 2.366) employing combination of SNV, Wavelet and D1, respectively. Moreover, Vis–NIR data correlated well with hardness (R2 = 0.876 and RMSEP = 5.216) using SNV, Wavelet and D2. These results showed the capability of Vis/NIR hyperspectral imaging and the central role of multivariate analysis in developing accurate models for prediction of moisture content and textural properties of roasted pistachio kernels.

Mohsen, M, Ahmed, MB & Zhou, JL 2018, 'Particulate matter concentrations and heavy metal contamination levels in the railway transport system of Sydney, Australia', Transportation Research Part D: Transport and Environment, vol. 62, pp. 112-124.
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© 2018 Elsevier Ltd Sampling campaign was conducted over six weeks to determine particulate matter (PM) concentrations from Sydney Trains airport line (T2) at both underground and ground levels using DustTrak. Dust samples were collected and analysed for 12 metals (Fe, Ca, Mn, Cr, Zn, Cu, Pb, Al, Co, Ni, Ba and Na) by atomic emission spectroscopy. Average underground PM10 and PM2.5 concentrations from inside the trains were 2.8 and 2.5 times greater than at ground level. Similarly, PM10 and PM2.5 concentrations on underground platforms were 2.7 and 2.5 times greater than ground level platforms. Average underground PM concentrations exceeded the national air quality standards for both PM10 (50 µg/m3) and PM2.5 (25 µg/m3). Correlation analysis showed a strong to moderate association between PM concentrations at ground level and background PM concentrations (r2 from 0.952 to 0.500). The findings suggested that underground PM concentrations were less influenced by the ambient background than at ground level. The metal concentrations decreased in the order of Fe, Cr, Ca, Al, Na, Ba, Mn, Zn, Cu, Ni, Co and Pb. The pollution index (PI) and enrichment factor (EF) values were calculated to identify the levels and sources of contamination in the underground railway microenvironments. PM was remarkably rich in Fe with a mean concentration of 73.51 mg/g and EF of 61.31, followed by Ni and Cr. These results noticeably indicated a high level of metal contamination in the underground environments, with the principal contribution from track abrasion and wear processes.

Mokhtar, ES, Pradhan, B, Ghazali, AH & Shafri, HZM 2018, 'Assessing flood inundation mapping through estimated discharge using GIS and HEC-RAS model', Arabian Journal of Geosciences, vol. 11, no. 21.
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© 2018, Saudi Society for Geosciences. Water discharge is the main parameter in hydraulic modeling for flood hazard assessment. However, the unavailability of data on discharge and observed river morphologies resulted in erroneous calculations and irregularities in flood inundation mapping. The objectives of this study are (i) to investigate uncertainties of hydraulic parameters (width, cross-sectional depth, and channel slope) used in discharge equation and (ii) to examine the influence of estimate discharge on water extent and flood depth with different boundary conditions on interferometric synthetic aperture radar (IFSAR) and modified IFSAR DEMs. Sensitivity analysis was conducted with the Monte Carlo simulation method to generate random data combinations. Bjerklie’s equation was used to calculate discharge based on the three variables, and Manning’s n was substituted into the Hydrologic Engineering Center River Analysis System (HEC-RAS) model. TerraSAR-X was used to distinguish existing flood water bodies and normal water extent. The uncertainty of the combined variables was assessed with the likelihood measures such as F-statistic, mean absolute error, root mean square error, and Nash–Sutcliffe efficiency which compares observed and predicted inundated area as well as flood water depth simulated using the HEC-RAS model.

Moloudi, R, Oh, S, Yang, C, Ebrahimi Warkiani, M & Naing, MW 2018, 'Inertial particle focusing dynamics in a trapezoidal straight microchannel: application to particle filtration', Microfluidics and Nanofluidics, vol. 22, no. 3.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Inertial microfluidics has emerged recently as a promising tool for high-throughput manipulation of particles and cells for a wide range of flow cytometric tasks including cell separation/filtration, cell counting, and mechanical phenotyping. Inertial focusing is profoundly reliant on the cross-sectional shape of channel and its impacts on not only the shear field but also the wall-effect lift force near the wall region. In this study, particle focusing dynamics inside trapezoidal straight microchannels was first studied systematically for a broad range of channel Re number (20 OpenSPiltSPi Re OpenSPiltSPi 800). The altered axial velocity profile and consequently new shear force arrangement led to a cross-lateral movement of equilibration toward the longer side wall when the rectangular straight channel was changed to a trapezoid; however, the lateral focusing started to move backward toward the middle and the shorter side wall, depending on particle clogging ratio, channel aspect ratio, and slope of slanted wall, as the channel Reynolds number further increased (Re CloseSPigtSPi 50). Remarkably, an almost complete transition of major focusing from the longer side wall to the shorter side wall was found for large-sized particles of clogging ratio K ~ 0.9 (K = a/Hmin) when Re increased noticeably to ~ 650. Finally, based on our findings, a trapezoidal straight channel along with a bifurcation was designed and applied for continuous filtration of a broad range of particle size (0.3 OpenSPiltSPi K OpenSPiltSPi 1) exiting through the longer wall outlet with ~ 99% efficiency (Re OpenSPiltSPi 100).

Moloudi, R, Oh, S, Yang, C, Teo, KL, Lam, AT-L, Warkiani, ME & Naing, MW 2018, 'Inertial-Based Filtration Method for Removal of Microcarriers from Mesenchymal Stem Cell Suspensions', Scientific Reports, vol. 8, no. 1.
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AbstractRapidly evolving cell-based therapies towards clinical trials demand alternative approaches for efficient expansion of adherent cell types such as human mesenchymal stem cells (hMSCs). Using microcarriers (100–300 µm) in a stirred tank bioreactor offers considerably enhanced surface to volume ratio of culture environment. However, downstream purification of the harvested cell product needs to be addressed carefully due to distinctive features and fragility of these cell products. This work demonstrates a novel alternative approach which utilizes inertial focusing to separate microcarriers (MCs) from the final cell suspension. First, we systematically investigated MC focusing dynamics inside scaled-up curved channels with trapezoidal and rectangular cross-sections. A trapezoidal spiral channel with ultra-low-slope (Tan(α) = 0.0375) was found to contribute to strong MC focusing (~300 < Re < ~400) while managing high MC volume fractions up to ~1.68%. Accordingly, the high-throughput trapezoidal spiral channel successfully separated MCs from hMSC suspension with total cell yield~94% (after two passes) at a high volumetric flow rate of ~30 mL/min (Re~326.5).

Momeni, E, Armaghani, DJ, Fatemi, SA & Nazir, R 2018, 'Prediction of bearing capacity of thin-walled foundation: a simulation approach', Engineering with Computers, vol. 34, no. 2, pp. 319-327.
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Mooney, G, Burdon, S & Kang, K 2018, 'That’s Entertainment: Crafting a Creative Ecology within Public Television', International Journal on Media Management, vol. 20, no. 4, pp. 263-276.
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Television has gone through a period of rapid disruption in the last few years. New technologies, increased globalization, shifting demographics, and evolving consumer demand have impelled widespread change to business models. Consequently, Broadcasters have been forced to re-examine their approaches to creativity and ideation including capacities and enabling methods. Following analysis of recorded interviews with key personnel behind three recent television productions a better understanding of the cultural ecology surrounding creativity was developed. Findings emphasized the decisive influence that internal sense of community, tacit realization practices, and quality leadership – all working together – play in delivering a distinctive production to a mass-market media audience.

Moreira, C & Wichert, A 2018, 'Are quantum-like Bayesian networks more powerful than classical Bayesian networks?', Journal of Mathematical Psychology, vol. 82, pp. 73-83.
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Morstyn, T, Savkin, AV, Hredzak, B & Tuan, HD 2018, 'Scalable Energy Management for Low Voltage Microgrids Using Multi-Agent Storage System Aggregation', IEEE Transactions on Power Systems, vol. 33, no. 2, pp. 1614-1623.
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© 1969-2012 IEEE. This paper proposes multi-agent energy storage system aggregation as a means of scaling energy management to low voltage microgrids with distributed energy storage systems. Based on this concept, a hierarchical control strategy is developed for an AC microgrid with distributed battery and ultracapacitor energy storage systems. On the tertiary control level, the energy management problem is made scalable by considering each type of energy storage system in aggregate. This addresses the 'curse of dimensionality,' since additional energy storage systems do not increase the optimization problem dimension, and allows nonlinear energy storage models to be used for optimization, accounting for variable efficiency, self-discharge, and lifetime degradation. On the secondary control level, multi-agent state of charge balancing, reactive power sharing, frequency restoration, and voltage restoration are combined, to aggregate energy storage systems for the tertiary control. This includes the novel use of multi-agent sliding mode control for state of charge balancing between AC microgrid energy storage systems. Unlike a linear state of charge balancing strategy, circulating currents are prevented, increasing efficiency and reducing lifetime degradation. An RTDS Technologies real-time digital simulator was used to verify the performance of the proposed control strategy.

Mortazavi, M, Sharafi, P, Ronagh, H, Samali, B & Kildashti, K 2018, 'Lateral behaviour of hybrid cold-formed and hot-rolled steel wall systems: Experimental investigation', Journal of Constructional Steel Research, vol. 147, pp. 422-432.
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The seismic design of light steel frames (LSF) can not only rely on the application of cold-formed steel (CFS). Some mixed systems and integrated solutions such as hybrid systems can offer new possibilities, in particular with regard to applications in mid-rise construction. A hybrid solution is to replace some CFS chord studs with hot-rolled square hollow section SHS, in order to achieve higher capacity. This paper provides the results of experimental studies on the lateral behaviour of a hybrid light-weight steel panel and investigates the implication of any further system improvements for mid-rise construction. Each hybrid wall panel (HWP) consists of a hot-rolled SHS frame, laterally incorporated in a cold-formed panel. The study includes investigating the lateral performance of HWP, while a CFS top chord acting as a load collector, and a hot-rolled steel frame acting as a lateral load resisting system. The behaviour of specimens is investigated under monotonic and cyclic loads, and the step-by-step enhancement is implemented according to the results. The outcomes revealed that although the hysteretic behaviour of the HWP represents pinching effect, mainly due to poor performance of the cold-formed steel collector, by strengthening the top chord design the behaviour is improved. Relying on the cold-formed part to resist the major portion of gravity loads, while the hot-rolled collector transfers the entire lateral load to the hot-rolled frame, results in significantly improved hysteretic behaviour.

Moshksayan, K, Kashaninejad, N, Warkiani, ME, Lock, JG, Moghadas, H, Firoozabadi, B, Saidi, MS & Nguyen, N-T 2018, 'Spheroids-on-a-chip: Recent advances and design considerations in microfluidic platforms for spheroid formation and culture', Sensors and Actuators B: Chemical, vol. 263, pp. 151-176.
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© 2018 Elsevier B.V. A cell spheroid is a three-dimensional (3D) aggregation of cells. Synthetic, in-vitro spheroids provide similar metabolism, proliferation, and species concentration gradients to those found in-vivo. For instance, cancer cell spheroids have been demonstrated to mimic in-vivo tumor microenvironments, and are thus suitable for in-vitro drug screening. The first part of this paper discusses the latest microfluidic designs for spheroid formation and culture, comparing their strategies and efficacy. The most recent microfluidic techniques for spheroid formation utilize emulsion, microwells, U-shaped microstructures, or digital microfluidics. The engineering aspects underpinning spheroid formation in these microfluidic devices are therefore considered. In the second part of this paper, design considerations for microfluidic spheroid formation chips and microfluidic spheroid culture chips (μSFCs and μSCCs) are evaluated with regard to key parameters affecting spheroid formation, including shear stress, spheroid diameter, culture medium delivery and flow rate. This review is intended to benefit the microfluidics community by contributing to improved design and engineering of microfluidic chips capable of forming and/or culturing three-dimensional cell spheroids.

Motamedi, M, Warkiani, ME & Taylor, RA 2018, 'Transparent Surfaces Inspired by Nature', Advanced Optical Materials, vol. 6, no. 14, pp. 1800091-1800091.
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AbstractNature has long inspired scientists and engineers. As one ubiquitous example of this, nature has provided all with several clever methods to absorb, repel, and/or allow both sunlight and water to pass through surfaces. Moth's eyes (highly antireflective) and lotus leaves (highly hydrophobic and self‐cleaning) represent durable natural surfaces which exhibit nearly ideal physical and optical properties. Man‐made transparent surfaces must also be able to cope with water and dust while reaching the maximum possible light transmission for solar collectors, displays, and other optical devices. To explore the link between these – particularly for transparent surfaces – this review puts the physics, progress, and limitations of synthetic materials in context with natural materials. This perspective reveals that there is still much more to learn (and implement) if it is hoped to match the multifunctionality and resilience of natural materials.

Movassaghi, S, Smith, DB, Abolhasan, M & Jamalipour, A 2018, 'Opportunistic Spectrum Allocation for Interference Mitigation Amongst Coexisting Wireless Body Area Networks', ACM Transactions on Sensor Networks, vol. 14, no. 2, pp. 1-22.
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Wireless Body Area Networks (WBANs) are seen as the enabling technology for developing new generations of medical applications, such as remote health monitoring. As such it is expected that WBANs will predominantly transport mission-critical and delay sensitive data. A key strategy towards building a reliable WBAN is to ensure such networks are highly immune to interference. To achieve this, new and intelligent wireless spectrum allocation strategies are required not only to avoid interference, but also to make best-use of the limited available spectrum. This article presents a new spectrum allocation scheme referred to as Smart Channel Assignment (SCA), which maximizes the resource usage and transmission speed by deploying a partially-orthogonal channel assignment scheme between coexisting WBANs as well as offering a convenient tradeoff among spectral reuse efficiency, transmission rate, and outage. Detailed analytical studies verify that the proposed SCA strategy is robust to variations in channel conditions, increase in sensor node-density within each WBAN, and an increase in number of coexisting WBANs.

Mueller, F, Toups, Z, Johnson, D, Wyeth, P, Schouten, B, Hämäläinen, P, Iacovides, J, Mekler, E, Koenitz, H, Wallner, G, Birk, M, Bozgeyikli, L & Gerling, K 2018, 'Chi play 2018 welcome', CHI PLAY 2018 - Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play, pp. iii-vi.

Mueller, FF, Andres, J, Marshall, J, Svanæs, D, schraefel, MC, Gerling, K, Tholander, J, Martin-Niedecken, AL, Segura, EM, van den Hoven, E, Graham, N, Höök, K & Sas, C 2018, 'Body-centric computing', Interactions, vol. 25, no. 4, pp. 34-39.
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Mueller, FF, Toups, Z, Johnson, D, Wyeth, P & Schouten, B 2018, 'Chi play 2018 welcome', CHI PLAY 2018 - Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts, pp. III-VI.

Mulet-Forteza, C, Martorell-Cunill, O, Merigó, JM, Genovart-Balaguer, J & Mauleon-Mendez, E 2018, 'Twenty five years of theJournal of Travel & Tourism Marketing: a bibliometric ranking', Journal of Travel & Tourism Marketing, vol. 35, no. 9, pp. 1201-1221.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The Journal of Travel & Tourism Marketing (JTTM) is a leading international journal in “Marketing” and “Tourism, Leisure and Hospitality Management.” JTTM published its first issue in 1992. In 2017, the journal has celebrated its twenty-fifth anniversary. For that reason, this study analyzes all the publications in the journal since its creation by using a bibliometric approach. The objective is to provide a complete overview of the main factors that affect the journal. This analysis includes key issues such as the distribution of annual publications and citations, the most cited papers, the h-index, citations per paper, the keywords that are mostly used, the influence on the publishing industry and authors, universities, and the countries that have the most publications. The paper uses the Scopus database to analyze the bibliometric data. Additionally, the paper also uses the visualization of similarities (VOS) viewer software to map graphically the bibliographic material. The graphical analysis uses bibliographic coupling, co-citation, citation, and co-occurrence of keywords. These results indicate that JTTM is one of the leading journals in the areas where the journal is indexed, with publications from a wide range of authors, institutions, and countries around the world.

Murray, A, Gilbert, RI & Castel, A 2018, 'Spacing of Cracks in Reinforced Concrete Based on a Variable Transfer Length Model', Journal of Structural Engineering, vol. 144, no. 7, pp. 04018090-04018090.
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Musa, IA, Mashiri, FR & Zhu, X 2018, 'Parametric study and equation of the maximum SCF for concrete filled steel tubular T-joints under axial tension', Thin-Walled Structures, vol. 129, pp. 145-156.
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© 2018 Concrete-filled steel tubular joints are increasingly being used for built infrastructure such as bridges and towers. In this study, the variation of the maximum Stress Concentration Factor (SCFmax) with non-dimensional geometric parameters in concrete-filled steel tubular (CFST) T-joints under axial tension has been investigated. A database of the maximum SCFs in CFST T-joints under axial tension is developed based on three-dimensional (3D) finite element (FE) models. The 3D FE models developed using ABAQUS software have been verified using experimental results. Graphs showing variation of the maximum SCF, in CFST T-joints, with non-dimensional geometric parameters have been produced and compared with those for non-filled empty T-joints. A parametric equation for predicting the maximum SCFs in CFST T-joints, a useful parameter for design, has been developed in a multiple nonlinear regression analysis. There is a good agreement between the maximum SCFs predicted by the parametric equation and those determined from the experiments.

Musa, IA, Mashiri, FR, Zhu, X & Tong, L 2018, 'EXPERIMENTAL STRESS CONCENTRATION FACTOR IN CONCRETE-FILLED STEEL TUBULAR T-JOINTS', Journal of Constructional Steel Research, vol. 150, pp. 442-451.
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© 2018 Elsevier Ltd An experimental investigation of stress concentration factor (SCF) in Steel circular hollow section brace welded to concrete-filled circular hollow section chord (CHS-to-CFCHS) T-joints has been performed under axial tension, axial compression, in-plane bending and out-of-plane bending. The distribution of SCF around the welded brace-to-chord intersection on both the brace and chord has been investigated using three CHS-to-CFCHS T-joint specimens. The experimental SCF results have been compared with the predicted SCF in empty T-joints. The relationship between the maximum SCF in relation to parameter β, with fixed other geometrical parameters, has been investigated for the basic load conditions. The experimental maximum SCF under axial tension has been compared with the predicted maximum SCF from parametric equations for CHS-to-CFCHS T-joints previously developed by the authors. The results show that the concrete has a significant effect in reducing the SCF, mostly under axial tension and the parametric equations for predicting SCFs in empty T-joints are not suitable for CHS-to-CFCHS T-joints. The effect of parameter β on the maximum SCF in CHS-to-CFCHS T-joints is significant under axial tension and out-of-plane bending moment.

Mustapha, S, Braytee, A & Ye, L 2018, 'Multisource Data Fusion for Classification of Surface Cracks in Steel Pipes', Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems, vol. 1, no. 2.
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This paper focuses on the development and validation of a robust framework for surface crack detection and assessment in steel pipes based on measured vibration responses collected using a network of piezoelectric (PZT) wafers. The pipe structure considered in this study contained multiple progressive cracks occurring at different locations and with various orientations (along the circumference or length). The fusion of data collected from multiple PZT wafers was investigated based on two approaches: (a) combining the raw data from all sensors before establishing a statistical model for damage classification and (b) combining the features from each sensor after applying a multiclass support vector machine recursive feature elimination (MCSVM-RFE), for dimensionality reduction, and taking the union of discriminative features among the different sources of data. A MCSVM learning algorithm was employed to train the data and generate a statistical classifier. The dataset consisted of ten classes, consisting of nine damage cases and the healthy state. The accuracy of the prediction based on the two fusion approaches resulted in a high accuracy, exceeding 95%, but the number of features needed to enrich the accuracy (95%) differed between the two approaches. Furthermore, the performance and the precision in the prediction of the classifier were evaluated when the data from only a single sensor was used compared with the combined data from all the sensors within the network. Very promising results in the classification of damage were obtained, based on the case study that included multiple damage scenarios with different lengths and orientations.

Naderpour, M & Khakzad, N 2018, 'Texas LPG fire: Domino effects triggered by natural hazards', Process Safety and Environmental Protection, vol. 116, pp. 354-364.
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© 2018 Institution of Chemical Engineers On February 2007, a massive fire in a propane de-asphalting unit in an oil refinery in Texas, USA happened due to liquid propane release from a cracked pipe in a control station injuring four people, damaging extensive equipment, causing significant business interruption, and resulting in more than $50 million losses. The accident was triggered by a natural hazard: freezing of piping at a control station caused an inlet pipe elbow to crack, which in turn, led to the release of high-pressure liquid propane which was rapidly ignited. In addition, there were two near-miss events due to potential domino effects. In fact, the accident could reasonably have resulted in much more severe consequences due to the exposure of large butane storage spheres and chlorine containers, increasing the possibility of a catastrophic domino effect. This paper develops a Natech (natural hazard triggering technological disasters) risk assessment methodology that relies upon Bayesian network capabilities and takes into account the potential Natech domino effects. The methodology is implemented in the intended refinery and mathematically graphically represents the dynamic cause–effect relations between units involved in the scenario, and handles uncertainties among the interactions. In addition, the methodology can provide a risk value for the entire scenario that can be used further for risk-based decision making.

Naghibi, SA, Vafakhah, M, Hashemi, H, Pradhan, B & Alavi, SJ 2018, 'Groundwater Augmentation through the Site Selection of Floodwater Spreading Using a Data Mining Approach (Case study: Mashhad Plain, Iran)', Water, vol. 10, no. 10, pp. 1405-1405.
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It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression tree (CART) to identify suitable areas for artificial recharge through floodwater spreading (FWS). At first, suitable areas for the FWS project were identified in a basin in north-eastern Iran based on the national guidelines and a literature survey. Using the same methodology, an identical number of FWS unsuitable areas were also determined. Afterward, a set of different FWS conditioning factors were selected for modeling FWS suitability. The models were applied using 70% of the suitable and unsuitable locations and validated with the rest of the input data (i.e., 30%). Finally, a receiver operating characteristics (ROC) curve was plotted to compare the produced FWS suitability maps. The findings depicted acceptable performance of the BRT, CART, and WoE for FWS suitability mapping with an area under the ROC curves of 92, 87.5, and 81.6%, respectively. Among the considered variables, transmissivity, distance from rivers, aquifer thickness, and electrical conductivity were determined as the most important contributors in the modeling. FWS suitability maps produced by the proposed method in this study could be used as a guideline for water resource managers to control flood damage and obtain new sources of groundwater. This methodology could be easily replicated to produce FWS suitability maps in other regions with similar hydrogeological conditions.

Nahhas, FH, Shafri, HZM, Sameen, MI, Pradhan, B & Mansor, S 2018, 'Deep Learning Approach for Building Detection Using LiDAR–Orthophoto Fusion', Journal of Sensors, vol. 2018, pp. 1-12.
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This paper reports on a building detection approach based on deep learning (DL) using the fusion of Light Detection and Ranging (LiDAR) data and orthophotos. The proposed method utilized object-based analysis to create objects, a feature-level fusion, an autoencoder-based dimensionality reduction to transform low-level features into compressed features, and a convolutional neural network (CNN) to transform compressed features into high-level features, which were used to classify objects into buildings and background. The proposed architecture was optimized for the grid search method, and its sensitivity to hyperparameters was analyzed and discussed. The proposed model was evaluated on two datasets selected from an urban area with different building types. Results show that the dimensionality reduction by the autoencoder approach from 21 features to 10 features can improve detection accuracy from 86.06% to 86.19% in the working area and from 77.92% to 78.26% in the testing area. The sensitivity analysis also shows that the selection of the hyperparameter values of the model significantly affects detection accuracy. The best hyperparameters of the model are 128 filters in the CNN model, the Adamax optimizer, 10 units in the fully connected layer of the CNN model, a batch size of 8, and a dropout of 0.2. These hyperparameters are critical to improving the generalization capacity of the model. Furthermore, comparison experiments with the support vector machine (SVM) show that the proposed model with or without dimensionality reduction outperforms the SVM models in the working area. However, the SVM model achieves better accuracy in the testing area than the proposed model without dimensionality reduction. This study generally shows that the use of an autoencoder in DL models can improve the accuracy of building recognition in fused LiDAR–orthophoto data.

Naidu, G, Jeong, S, Choi, Y, Song, MH, Oyunchuluun, U & Vigneswaran, S 2018, 'Valuable rubidium extraction from potassium reduced seawater brine', Journal of Cleaner Production, vol. 174, pp. 1079-1088.
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© 2017 Elsevier Ltd Extraction of rubidium (Rb) which is an economically valuable metal from seawater reverse osmosis (SWRO) brine is beneficial. However, potassium (K) in SWRO brine hinders Rb extraction. Natural clinoptilolite zeolite in powder form was able to selectively remove K from SWRO brine (Langmuir maximum sorption, Qmax (cal.) = 57.47 ± 0.09 mg/g). An integrated submerged membrane sorption reactor (SMSR) containing zeolite powder achieved 65% K removal from SWRO brine. Periodic replacement of zeolite in SMSR, coupled with membrane backwashing was effective in maintaining a high K removal efficiency and a stable transmembrane pressure. Less than 5% Rb losses occurred along with K sorption, establishing the high K selectivity by zeolite in SWRO brine. Utilization of K loaded zeolite as a slow release fertilizer would be beneficial for agriculture. In SWRO brine with reduced K contents, the Rb sorption efficiency of polymer encapsulated potassium copper hexacyanoferrate (KCuFC(PAN)) sorbent, increased significantly from 18% to 83%.

Naidu, G, Zhong, X & Vigneswaran, S 2018, 'Comparison of membrane distillation and freeze crystallizer as alternatives for reverse osmosis concentrate treatment', Desalination, vol. 427, pp. 10-18.
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© 2017 Elsevier B.V. Membrane distillation (MD) and freeze crystallizer (FC) were evaluated as alternative reverse osmosis concentrate (ROC) treatment options. A direct contact MD (DCMD) was capable of obtaining 60% water recovery with chemically pretreated ROC. Nevertheless, in repeated cycles, DCMD displayed a trend of reduced water recovery and declining permeate quality. At elevated concentrations, ROC caused scaling and membrane hydrophobicity reduction, indicating reduced membrane life span. On the other hand, FC in three-stage freeze/thaw approach was able to concentrate ROC by 2.3 time, achieving a 57% water recovery with no scaling issues. The fresh ice water quality (total dissolved solids) obtained from FC was within the range of 0.08–0.37 g/L. A brief techno-economic evaluation highlighted advantages and limitations of both options. The efficiency of DCMD as a compact, low thermal process for ROC treatment was compromised by membrane scaling, indicating the necessity for a scaling mitigation pretreatment. This invariably incurs an additional cost. FC was advantageous as a scaling and chemical free process. The high freezing requirement of FC could be met by coupling with refrigerant coolant from liquefied natural gas. Nevertheless, the practical industrial application of FC is inherently restricted due to complex scaling up issues.

Naik, GR, Selvan, SE, Arjunan, SP, Acharyya, A, Kumar, DK, Ramanujam, A & Nguyen, HT 2018, 'An ICA-EBM-Based sEMG Classifier for Recognizing Lower Limb Movements in Individuals With and Without Knee Pathology', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, no. 3, pp. 675-686.
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Surface electromyography (sEMG) data acquired during lower limb movements has the potential for investigating knee pathology. Nevertheless, a major challenge encountered with sEMG signals generated by lower limb movements is the intersubject variability, because the signals recorded from the leg or thigh muscles are contingent on the characteristics of a subject such as gait activity and muscle structure. In order to cope with this difficulty, we have designed a three-step classification scheme. First, the multichannel sEMG is decomposed into activities of the underlying sources by means of independent component analysis via entropy bound minimization. Next, a set of time-domain features, which would best discriminate various movements, are extracted from the source estimates. Finally, the feature selection is performed with the help of the Fisher score and a scree-plot-based statistical technique, prior to feeding the dimension-reduced features to the linear discriminant analysis. The investigation involves 11 healthy subjects and 11 individuals with knee pathology performing three different lower limb movements, namely, walking, sitting, and standing, which yielded an average classification accuracy of 96.1% and 86.2%, respectively. While the outcome of this study per se is very encouraging, with suitable improvement, the clinical application of such an sEMG-based pattern recognition system that distinguishes healthy and knee pathological subjects would be an attractive consequence.

Najafpoor, AA, Jonidi Jafari, A, Hosseinzadeh, A, Khani Jazani, R & Bargozin, H 2018, 'Optimization of non-thermal plasma efficiency in the simultaneous elimination of benzene, toluene, ethyl-benzene, and xylene from polluted airstreams using response surface methodology', Environmental Science and Pollution Research, vol. 25, no. 1, pp. 233-241.
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Nampak, H, Pradhan, B, Mojaddadi Rizeei, H & Park, H 2018, 'Assessment of land cover and land use change impact on soil loss in a tropical catchment by using multitemporal SPOT‐5 satellite images and Revised Universal Soil Loss Equation model', Land Degradation & Development, vol. 29, no. 10, pp. 3440-3455.
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AbstractSoil erosion is a common land degradation problem and has disastrous impacts on natural ecosystems and human life. Therefore, researchers have focused on detection of land cover–land use changes (LCLUC) with respect to monitoring and mitigating the potential soil erosion. This article aims to appraise the relationship between LCLUC and soil erosion in the Cameron Highlands (Malaysia) by using multitemporal satellite images and ancillary data. Land clearing and heavy rainfall events in the study area has resulted in increased soil loss. Moreover, unsustainable development and agricultural practices, mismanagement, and lack of land use policies increase the soil erosion rate. Hence, the main contribution of this study lies in the application of appropriate land management practices in relation to water erosion through identification and prediction of the impacts of LCLUC on the spatial distribution of potential soil loss in a region susceptible to natural hazards such as landslide. The LCLUC distribution within the study area was mapped for 2005, 2010, and 2015 by using SPOT‐5 temporal satellite imagery and object‐based image classification. A projected land cover–land use map was also produced for 2025 through integration of Markov chain and cellular automata models. An empirical‐based approach (Revised Universal Soil Loss Equation) coupled with geographic information system was applied to measure soil loss and susceptibility to erosion over the study area for four periods (2005, 2010, 2015, and 2025). The model comprises five parameters, namely, rainfall factor, soil erodibility, topographical factor, conservation factor, and support practice factor. Results exhibited that the average amount of soil loss increased by 31.77 t ha−1 yr−1 from 2005 to 2015 and was predicted to dramatically increase in 2025. The results generated from this research recommends that awareness of...

Namvar, A, Siami, M, Rabhi, F & Naderpour, M 2018, 'Credit risk prediction in an imbalanced social lending environment', International Journal of Computational Intelligence Systems, vol. 11, no. 1, pp. 925-925.
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© 2018, the Authors. Credit risk prediction is an effective way of evaluating whether a potential borrower will repay a loan, particularly in peer-to-peer lending where class imbalance problems are prevalent. However, few credit risk prediction models for social lending consider imbalanced data and, further, the best resampling technique to use with imbalanced data is still controversial. In an attempt to address these problems, this paper presents an empirical comparison of various combinations of classifiers and resampling techniques within a novel risk assessment methodology that incorporates imbalanced data. The credit predictions from each combination are evaluated with a G-mean measure to avoid bias towards the majority class, which has not been considered in similar studies. The results reveal that combining random forest and random under-sampling may be an effective strategy for calculating the credit risk associated with loan applicants in social lending markets.

Nan, Y, Huang, X & Guo, YJ 2018, 'Generalized Continuous Wave Synthetic Aperture Radar for High Resolution and Wide Swath Remote Sensing', IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 12, pp. 7217-7229.
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© 2018 IEEE. A generalized continuous wave synthetic aperture radar (GCW-SAR) concept is proposed in this paper. By using full-duplex radio frontend and continuous wave signaling, the GCW-SAR system can overcome a number of limitations inherent within the existing SAR systems and achieve high-resolution and wide-swath remote sensing with low-power signal transmission. Unlike the conventional pulsed SAR and the frequency-modulated continuous-wave SAR, the GCW-SAR reconstructs a radar image by directly correlating the received 1-D raw data after self-interference cancellation with predetermined location-dependent reference signals. A fast imaging algorithm, called the piecewise constant Doppler (PCD) algorithm, is also proposed, which produces the radar image recursively in the azimuth direction without any intermediate step, such as range compression and migration compensation, as required by conventional algorithms. By removing the stop-and-go assumption or slow-time sampling in azimuth, the PCD algorithm not only achieves better imaging quality but also allows for more flexible waveform and system designs. Analyses and simulations show that the GCW-SAR tolerates significant self-interference and works well with a large selection of various system parameters. The work presented in this paper establishes a solid theoretical foundation for next-generation imaging radars.

Nasir, AA, Tuan, HD & Duong, TQ 2018, 'Fractional Time Exploitation for Serving IoT Users with Guaranteed QoS by 5G Spectrum', IEEE Communications Magazine, vol. 56, no. 10, pp. 128-133.
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© 1979-2012 IEEE. It is generally understood that forthcoming 5G communication technologies such as full duplex (FD), massive multiple-input multiple-output (MIMO), non-orthogonal multiple access (NOMA), and simultaneous wireless information and power transfer (SWIPT) aim at the maximal use of communication spectrum to provide a new experience of service for users. FD provides simultaneous signal transmission and reception over the same frequency band. Massive MIMO uses massive numbers of antennas to provide high throughput connectivity for users. NOMA improves network throughput by allowing some users to access information intended for other users. SWIPT provides simultaneous information and power transfer. However, it is still very challenging to utilize these spectrum exploitation technologies to secure the needed quality of service for users in the age of the Internet of Things. In FD, the signal transmission interference to signal reception, even after analog and digital self-interference cancellation, is considerable, which downgrades both transmission and reception throughput. To maintain the favored channel characteristics, massive MIMO means to serve a few users per time unit only. In NOMA, the users' throughput is improved by compromising communication privacy. Information and power transmissions head to conflicting targets that are difficult to achieve simultaneously with SWIPT. This article introduces a new technique, called the fractional-time approach, which ensures guaranteed and better transmission and reception throughput without the need for complex FD, enables serving a massive number of users in a massive MIMO system, provides guaranteed users' throughput without security compromise as in NOMA, and delivers high volumes of both information and power transfer within a time unit.

Navaratnarajah, SK & Indraratna, B 2018, 'Closure to “Use of Rubber Mats to Improve the Deformation and Degradation Behavior of Rail Ballast under Cyclic Loading” by Sinniah K. Navaratnarajah and Buddhima Indraratna', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 7, pp. 07018014-07018014.
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Navaratnarajah, SK, Indraratna, B & Ngo, NT 2018, 'Influence of Under Sleeper Pads on Ballast Behavior Under Cyclic Loading: Experimental and Numerical Studies', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 9, pp. 04018068-04018068.
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Railway industries are placing greater emphasis on implementing fast and heavy haul corridors for bulk freight and commuter transport in order to deliver more efficient and cost-effective services. However, increasing dynamic stresses from the passage of trains progressively degrades and fouls the primary load-bearing ballast layer, which inevitably leads to excessive settlement and instability, damage to track elements, and more frequent maintenance. Ballasted tracks are subjected to even greater stresses and faster deterioration in sections where a reduced ballast thickness is used (e.g., bridge decks) or at locations where heavier concrete sleepers are used instead of lightweight timber sleepers. The inclusion of under sleeper pads (USPs) at the base of a concrete sleeper is one measure used to minimize dynamic stresses and subsequent track deterioration. In this study, cyclic loads from fast and heavy haul trains were simulated using a large-scale process simulation prismoidal triaxial apparatus (PSPTA) to investigate the performance of ballast improved by USPs. The laboratory results indicate that the inclusion of an elastic element at the harder interface of the concrete sleeper-ballast reduces the stresses transmitted to the ballast and the underlying layers and minimizes the amount of deformation and degradation of the ballast. A three-dimensional finite-element model was used to predict the behavior of ballast, and the influence of USPs on the stress-strain responses of ballast generally agree with the experimental findings.

Nawaz, F, Asadabadi, MR, Janjua, NK, Hussain, OK, Chang, E & Saberi, M 2018, 'An MCDM method for cloud service selection using a Markov chain and the best-worst method', Knowledge-Based Systems, vol. 159, pp. 120-131.
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© 2018 Elsevier B.V. Due to the increasing number of cloud services, service selection has become a challenging decision for many organisations. It is even more complicated when cloud users change their preferences based on the requirements and the level of satisfaction of the experienced service. The purpose of this paper is to overcome this drawback and develop a cloud broker architecture for cloud service selection by finding a pattern of the changing priorities of User Preferences (UPs). To do that, a Markov chain is employed to find the pattern. The pattern is then connected to the Quality of Service (QoS) for the available services. A recently proposed Multi Criteria Decision Making (MCDM) method, Best Worst Method (BWM), is used to rank the services. We show that the method outperforms the Analytic Hierarchy Process (AHP). The proposed methodology provides a prioritized list of the services based on the pattern of changing UPs. The methodology is validated through a case study using real QoS performance data of Amazon Elastic Compute (Amazon EC2) cloud services.

Nawaz, F, Janjua, NK, Hussain, OK, Hussain, FK, Chang, E & Saberi, M 2018, 'Event-driven approach for predictive and proactive management of SLA violations in the Cloud of Things', Future Generation Computer Systems, vol. 84, pp. 78-97.
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© 2018 Elsevier B.V. In a dynamic environment such as the cloud-of-things, one of the most critical factors for successful service delivery is the QoS under defined constraints. Even though guarantees in the form of service level agreements (SLAs) are provided to users, many services exhibit dynamic Quality of Service (QoS) variations. This QoS variation as well as changes in the behavior and state of the service is caused by some internal events (such as varying loads) and external events (such as location and weather), which results in frequent SLA violations. Most of the existing violation prediction approaches use historic data to predict future QoS values. They do not consider dynamic changes and the events that cause these changes in QoS attributes. In this paper, we propose an event-driven-based proactive approach for predicting SLA violations by combining logic-based reasoning and probabilistic inferencing. The results show that our proposed approach is efficient and proactively identifies SLA violations under uncertain QoS observations.

Neri, A, Cagno, E, Di Sebastiano, G & Trianni, A 2018, 'Industrial sustainability: Modelling drivers and mechanisms with barriers', Journal of Cleaner Production, vol. 194, pp. 452-472.
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© 2018 Elsevier Ltd Sustainability's relevance is constantly increasing among industrial decision makers, policy-makers and scholars. To improve sustainability performance, firms must adopt industrial sustainability measures. These have been proven to positively impact on overall firm's performance, but their rate of adoption is still low, and barriers to their adoption need to be properly tackled by drivers. This work is based on a review of literature on drivers to sustainability and to the areas of occupational health and safety, eco efficiency, and energy efficiency, and contributes to industrial sustainability research presenting a novel framework of drivers. The framework comprehends a model of drivers and a model of mechanisms: the former encompasses previous literature contributions and aims to characterize drivers for the adoption of measures in all areas of industrial sustainability; the latter aims to evaluate if a driver may tackle specific barrier or boost the action of another driver. We conducted a preliminary validation of the framework in nine Italian manufacturing firms. Regarding model of drivers, capacity to represent, usefulness and ease of use were evaluated; concerning model of mechanisms usefulness and ease of use were evaluated. Results seem to be sound with an overall positive evaluation of the framework by all the interviewees. Model of drivers was appreciated for its structure and completeness, and for its ability to enhance knowledge and awareness; model of mechanisms was considered useful for properly foster the adoption of a measure within the firm. The framework could be useful for industrial decision makers and policy-makers to better direct resources and efforts to foster the adoption of industrial sustainability measures.

Ngo, NT, Indraratna, B, Ferreira, FB & Rujikiatkamjorn, C 2018, 'Improved performance of geosynthetics enhanced ballast: laboratory and numerical studies', Proceedings of the Institution of Civil Engineers - Ground Improvement, vol. 171, no. 4, pp. 202-222.
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Ballasted rail tracks form one of the most important worldwide transportation modes in terms of traffic tonnage, serving the needs of bulk freight and passenger movement. High impact and cyclic loads can cause a significant deformation leading to poor track geometry. In order to mitigate these problems, the concept of the inclusion of geosynthetics in rail tracks is introduced. This paper presents the current state-of-the-art knowledge of rail track geomechanics, including results obtained from laboratory testing, field investigations and numerical modelling to study the load–deformation behaviour of ballast improved by geosynthetics. The shear stress–strain and deformation behaviour of geosynthetic-reinforced ballast are investigated in the laboratory using a large-scale direct shear test device, a track process simulation apparatus and a drop-weight impact testing equipment. Computational modelling using the discrete-element method is employed to simulate geosynthetic-reinforced ballasted tracks, capturing the discrete nature of ballast aggregates when subjected to various types of loading and boundary conditions. Discrete-element modelling is also used to conduct micromechanical analysis at the interface between ballast and geogrid, providing further insight into the behaviour of ballast subjected to cyclic loadings. These results provide promising approaches to incorporate into existing track design routines catering for future high-speed trains and heavier heavy hauls.

Ngo, P-TT, Hoang, N-D, Pradhan, B, Nguyen, QK, Tran, XT, Nguyen, QM, Nguyen, VN, Samui, P & Tien Bui, D 2018, 'A Novel Hybrid Swarm Optimized Multilayer Neural Network for Spatial Prediction of Flash Floods in Tropical Areas Using Sentinel-1 SAR Imagery and Geospatial Data', Sensors, vol. 18, no. 11, pp. 3704-3704.
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Flash floods are widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood-prone areas is crucial for public safety and emergency management. This research proposes a new methodology for spatial prediction of flash floods based on Sentinel-1 SAR imagery and a new hybrid machine learning technique. The SAR imagery is used to detect flash flood inundation areas, whereas the new machine learning technique, which is a hybrid of the firefly algorithm (FA), Levenberg–Marquardt (LM) backpropagation, and an artificial neural network (named as FA-LM-ANN), was used to construct the prediction model. The Bac Ha Bao Yen (BHBY) area in the northwestern region of Vietnam was used as a case study. Accordingly, a Geographical Information System (GIS) database was constructed using 12 input variables (elevation, slope, aspect, curvature, topographic wetness index, stream power index, toposhade, stream density, rainfall, normalized difference vegetation index, soil type, and lithology) and subsequently the output of flood inundation areas was mapped. Using the database and FA-LM-ANN, the flash flood model was trained and verified. The model performance was validated via various performance metrics including the classification accuracy rate, the area under the curve, precision, and recall. Then, the flash flood model that produced the highest performance was compared with benchmarks, indicating that the combination of FA and LM backpropagation is proven to be very effective and the proposed FA-LM-ANN is a new and useful tool for predicting flash flood susceptibility.

Nguyen, AQ, Wickham, R, Nguyen, LN, Phan, HV, Galway, B, Bustamante, H & Nghiem, LD 2018, 'Impact of anaerobic co-digestion between sewage sludge and carbon-rich organic waste on microbial community resilience', Environmental Science: Water Research & Technology, vol. 4, no. 12, pp. 1956-1965.
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This study examines the changes in microbial community diversity and structure in response to anaerobic co-digestion (AcoD) between sewage sludge and a carbon-rich organic waste.

Nguyen, DN, Dutkiewicz, E & Krunz, M 2018, 'Harvesting Short-Lived White Spaces via Opportunistic Traffic Offloading Between Mobile Service Providers', IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 3, pp. 635-647.
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Currently, Wi-Fi (IEEE 802.11) is the most widely adopted wireless technology for mobile traffic offloading at hot spots. Despite its great success, Wi-Fi is constrained by the over-crowded unlicensed spectrum, which leads to poor user experience, especially in urban areas. This paper introduces an opportunistic cooperation framework that allows mobile service providers (MSPs) to offload traffic onto each other's network by harvesting short-lived spectrum/resources of cellular systems. Specifically, through traffic offloading, MSPs aim to maximize their profit while maintaining their quality of service (QoS) commitments. For that purpose, we model the strategic cooperation between MSPs as a stochastic Markov game in which the dynamics of resource availability and user behaviors are captured via a Markov decision process. We prove that the game is irreducible and admits a Nash Equilibrium at which all MSPs benefit from traffic offloading. A practical algorithm that uses only local information to govern traffic offloading at MSPs is then developed. Numerical simulations show that by designing appropriate profit sharing contracts, our proposed algorithm can achieve almost the same performance as that of a socially optimal solution. The derived traffic offloading strategies not only improve QoS and revenue for MSPs, but also can be used to guide MSPs on when to turn off their base stations while the traffic volume is light (e.g., during nighttime).

Nguyen, DN, Krunz, M & Dutkiewicz, E 2018, 'Full-Duplex MIMO Radios: A Greener Networking Solution', IEEE Transactions on Green Communications and Networking, vol. 2, no. 3, pp. 652-665.
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© 2017 IEEE. Relative to half-duplex (HD) radios, in-band full-duplex (FD) radios have the potential to double a link's capacity. However, such gain may not necessarily extend to the network-wide throughput, which may actually degrade under FD radios due to excessive network interference. This paper identifies the unique advantages of FD radios and leverages multi-input multioutput (MIMO) communications to translate the FD spectral efficiency gain at the PHY level to the throughput and power efficiency gain at the network layer. We first derive sufficient conditions under which FD-MIMO radios can asymptotically double the throughput of the same network of HD-MIMO ones. Specifically, if a network of 2N HD radios (N links) can achieve a total throughput of dN bps (i.e., d bps per link), then an FD-capable network with the same number of links and network/channel realization can achieve 2N (d-1) bps [i.e., (d-1) bps per direction of a bidirectional link]. To leverage this theoretical gain, we exploit the 'spatial signature' readily captured in the network interference to design an MAC protocol that allows multiple FD links to concurrently communicate while adapting their radiation patterns to minimize network interference. The protocol does not require any feedback nor coordination among nodes. Extensive simulations show that the proposed MAC design dramatically outperforms traditional CSMA-based and the non-orthogonal multiple access protocols with either HD or FD radios with respect to both throughput and energy efficiency. Note that in the literature, network interference is often treated as colored noise that then gets whiten during the signal detection process. However, through our MAC protocol, we emphasize that, unlike random noise, network interference has its own structure that can be 'mined' for 'intelligence' to better align the transceiver's signal.

Nguyen, LD, Tuan, HD, Duong, TQ, Dobre, OA & Poor, HV 2018, 'Downlink Beamforming for Energy-Efficient Heterogeneous Networks With Massive MIMO and Small Cells', IEEE Transactions on Wireless Communications, vol. 17, no. 5, pp. 3386-3400.
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© 2002-2012 IEEE. A heterogeneous network (HetNet) of a macrocell base station equipped with a large-scale massive multi-in multi-out (MIMO) antenna array overlaying a number of small cell base stations (small cells) can provide high quality of service (QoS) to multiple users under low transmit power budget. However, the circuit power for operating such a network, which is proportional to the number of transmit antennas, poses a problem in terms of its energy efficiency (EE). This paper addresses the beamforming design at the base stations to optimize the network EE under the QoS constraints and a transmit power budget. Beamforming tailored for weak, strong, and medium cross-tier interference HetNets is proposed. In contrast to the conventional transmit strategy for power efficiency in meeting the users' QoS requirements, which suggest the use of a few hundred antennas, it is found out that the overall network EE quickly drops if this number exceeds 50. It is found that, for a given number of antennas, HetNet is more energy efficient than massive MIMO when considering the overall energy consumption.

Nguyen, LN, Nghiem, LD & Oh, S 2018, 'Aerobic biotransformation of the antibiotic ciprofloxacin by Bradyrhizobium sp. isolated from activated sludge', Chemosphere, vol. 211, pp. 600-607.
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Nguyen, LT, Nguyen, UDT, Nguyen, TDT, Ho-Pham, LT & Nguyen, TV 2018, 'Contribution of bone turnover markers to the variation in bone mineral density: a study in Vietnamese men and women', Osteoporosis International, vol. 29, no. 12, pp. 2739-2744.
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© 2018, International Osteoporosis Foundation and National Osteoporosis Foundation. Summary: The present cross-sectional study constructed reference ranges for bone resorption marker beta isomerized form of C-terminal crosslinking telopeptides of type I collagen (beta-CTX) and bone formation marker procollagen type 1 N-terminal propeptide (PINP) for the Vietnamese population. We have further shown that for a given age and weight, higher levels of beta-CTX were significantly associated with bone mineral density in men and women. Introduction: Normal bone is constantly renewed by two opposing processes of resorption and formation which can be reflected by bone turnover markers (BTMs). This study sought to define the contribution of BTMs to the variation in bone mineral density (BMD) in normal individuals. Methods: The study involved 205 men and 432 women aged between 18 and 87, who were randomly selected from various districts within Ho Chi Minh City, Vietnam. Fasting serum levels of PINP and beta-CTX were determined by electrochemiluminescence (Roche, ECLIA). BMD at the lumbar spine (LS) and femoral neck (FN) was measured by dual-energy x-ray absorptiometry (Hologic, Waltham, MA, USA). Results: Among those aged < 50 years, women had lower PINP and beta-CTX levels than men, but among those aged > 50 years, women had higher PINP and beta-CTX levels than men. In the multiple linear regression analysis, beta-CTX—but not PINP—was significantly associated with both femoral neck (P = 0.008) and lumbar spine BMD (P = 0.008) and the association was independent of gender, age, and body weight. The proportion of variance in BMD attributable to beta-CTX was 1% for femoral neck BMD and 2% for lumbar spine BMD. Conclusion: The elevation in bone formation marker PINP and bone resorption marker beta-CTX in postmenopausal women was greater than in elderly men. However, only beta-CTX was modestly but significantly associated with BMD.

Nguyen, NC, Chen, S-S, Jain, S, Nguyen, HT, Ray, SS, Ngo, HH, Guo, W, Lam, NT & Duong, HC 2018, 'Exploration of an innovative draw solution for a forward osmosis-membrane distillation desalination process', Environmental Science and Pollution Research, vol. 25, no. 6, pp. 5203-5211.
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Forward osmosis (FO) has emerged as a viable technology to alleviate the global water crisis. The greatest challenge facing the application of FO technology is the lack of an ideal draw solution with high water flux and low reverse salt flux. Hence, the objective of this study was to enhance FO by lowering reverse salt flux and maintaining high water flux; the method involved adding small concentrations of Al2(SO4)3 to a MgCl2 draw solution. Results showed that 0.5 M MgCl2 mixed with 0.05 M of Al2(SO4)3 at pH 6.5 achieved a lower reverse salt flux (0.53 gMH) than that of pure MgCl2 (1.55 gMH) using an FO cellulose triacetate nonwoven (CTA-NW) membrane. This was due possibly to the flocculation of aluminum hydroxide in the mixed draw solution that constricted membrane pores, resulting in reduced salt diffusion. Moreover, average water fluxes of 4.09 and 1.74 L/m(2)-h (LMH) were achieved over 180 min, respectively, when brackish water (5 g/L) and sea water (35 g/L) were used as feed solutions. Furthermore, three types of membrane distillation (MD) membranes were selected for draw solution recovery; of these, a polytetrafluoroethylene membrane with a pore size of 0.45 μm proved to be the most effective in achieving a high salt rejection (99.90%) and high water flux (5.41 LMH) in a diluted draw solution.

Nguyen, NC, Chen, S-S, Nguyen, HT, Chen, Y-H, Ngo, HH, Guo, W, Ray, SS, Chang, H-M & Le, QH 2018, 'Applicability of an integrated moving sponge biocarrier-osmotic membrane bioreactor MD system for saline wastewater treatment using highly salt-tolerant microorganisms', Separation and Purification Technology, vol. 198, pp. 93-99.
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© 2017 Elsevier B.V.Osmotic membrane bioreactors (OsMBRs) are a recent breakthrough technology designed to treat wastewater. Nevertheless, their application in high-salinity wastewater treatment is not widespread because of the effects of saline conditions on microbial community activity. In response, this study developed an integrated sponge biocarrier-OsMBR system using highly salt-tolerant microorganisms for treating saline wastewater. Results showed that the sponge biocarrier-OsMBR obtained an average water flux of 2L/m2 h during a 92-day operation when 1M MgCl2 was used as the draw solution. The efficiency in removing dissolved organic compounds from the proposed system was more than 99%, and nutrient rejection was close to 100%, indicating excellent performance in simultaneous nitrification and denitrification processes in the biofilm layer on the carriers. Moreover, salt-tolerant microorganisms in the sponge biocarrier-OsMBR system worked efficiently in salt concentrations of 2.4%. A polytetrafluoroethylene MD membrane (pores=0.45μm) served to regenerate the diluted draw solution in the closed-loop system and produce high-quality water. The moving sponge biocarrier-OsMBR/MD hybrid system demonstrated its potential to treat salinity wastewater treatment, with 100% nutrient removal and 99.9% conductivity rejection.

Nguyen, N-P, Ngo, HQ, Duong, TQ, Tuan, HD & Tourki, K 2018, 'Secure Massive MIMO With the Artificial Noise-Aided Downlink Training', IEEE Journal on Selected Areas in Communications, vol. 36, no. 4, pp. 802-816.
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Nguyen, QD, Khan, MSH & Castel, A 2018, 'Engineering Properties of Limestone Calcined Clay Concrete', Journal of Advanced Concrete Technology, vol. 16, no. 8, pp. 343-357.
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In this paper, various engineering properties of both fresh and hardened concrete with various limestone and calcined clay contents are investigated. Two concrete grades were considered: 50 MPa or 30 MPa average 28 days compressive strength. A low grade calcined clay was used with about 50% amorphous phase. A reduction in concrete workability was observed with the increase in General Purpose (GP) cement substitution. Superplasticiser was required to obtain a slump equivalent to that of reference GP cement concrete. With 15% GP cement replacement rate, the 28 days compressive strength achieved was superior to that of reference grade 50 MPa concrete, reaching 58 MPa. However, the average 28 days compressive strength reduced significantly with 30% and 45% GP cement replacement, reaching about 35 MPa. Considering concretes with similar 28-day compressive strength, results showed that the 7-day compressive strength was only marginally affected by the limestone and calcined clay substitution. Mercury intrusion porosimetry results revealed that incorporating calcined clay and limestone led to significant refinement of the porosity: increase in the quantity of pores inferior to 0.01µm and reduction in the quantity of coarse pores (with size > 0.1 µm).

Nguyen, TC, Loganathan, P, Nguyen, TV, Kandasamy, J, Naidu, R & Vigneswaran, S 2018, 'Adsorptive removal of five heavy metals from water using blast furnace slag and fly ash', Environmental Science and Pollution Research, vol. 25, no. 21, pp. 20430-20438.
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© 2017, Springer-Verlag GmbH Germany. Heavy metals can be serious pollutants of natural water bodies causing health risks to humans and aquatic organisms. The purpose of this study was to investigate the removal of five heavy metals from water by adsorption onto an iron industry blast furnace slag waste (point of zero charge (PZC) pH 6.0; main constituents, Ca and Fe) and a coal industry fly ash waste (PZC 3.0; main constituents, Si and Al). Batch study revealed that rising pH increased the adsorption of all metals with an abrupt increase at pH 4.0–7.0. The Langmuir adsorption maximum for fly ash at pH 6.5 was 3.4–5.1 mg/g with the adsorption capacity for the metals being in the order Pb > Cu > Cd, Zn, Cr. The corresponding values for furnace slag were 4.3 to 5.2 mg/g, and the order of adsorption capacities was Pb, Cu, Cd > Cr > Zn. Fixed-bed column study on furnace slag/sand mixture (1:1 w/w) revealed that the adsorption capacities were generally less in the mixed metal system (1.1–2.1 mg/g) than in the single metal system (3.4–3.5 mg/g). The data for both systems fitted well to the Thomas model, with the adsorption capacity being the highest for Pb and Cu in the single metal system and Pb and Cd in the mixed metal system. Our study showed that fly ash and blast furnace slag are effective low-cost adsorbents for the simultaneous removal of Pb, Cu, Cd, Cr and Zn from water.

Nguyen, TD, La Fontaine, A, Yang, L, Cairney, JM, Zhang, J & Young, DJ 2018, 'Atom probe study of impurity segregation at grain boundaries in chromia scales grown in CO2 gas', Corrosion Science, vol. 132, pp. 125-135.
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Nguyen, TT, Indraratna, B & Carter, J 2018, 'Laboratory Investigation into Biodegradation of Jute Drains with Implications for Field Behavior', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 6, pp. 04018026-04018026.
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Naturally occurring materials such as jute and coir have some favorable engineering characteristics and also degrade over time, so they have increasingly been used in engineering applications in recent years. The efficient way that naturally prefabricated vertical drains made from those materials help accelerate soil consolidation has been shown in previous studies, but they also tend to decompose rapidly in adverse environments, where cellulose-degrading bacteria cause a serious deterioration of their favorable drainage properties. This study presents a laboratory investigation into the biodegradation of prefabricated vertical jute drains in saturated soft soils, where the tensile strength of jute and coir fibers and the discharge capacity of drains decrease in response to different environments. Micro-observation also shows a transformation of the jute fibers and destruction of the drain structure due to biodegradation. DNA extraction and sequencing techniques to determine the microbial properties of these decayed fibers indicate that bacteria such as species of the genera Clostridium and Bacillus can cause rapid decomposition of cellulose-based material (i.e., jute), whereas other organic matter-consuming microbes such as sulfate-reducing bacteria do not directly contribute to the biodegradation of jute. In response, an analytical approach that incorporates various forms of drain discharge capacity over time is proposed to predict soil consolidation. The results indicate there is considerable deviation in dissipating the excess pore pressure when the drain degrades in different ways.

Nguyen, TT, Indraratna, B & Rujikiatkamjorn, C 2018, 'Challenges and solutions towards natural prefabricated vertical drains', Australian Geomechanics Journal, vol. 53, no. 4, pp. 89-100.
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In recent years, natural fibres such as jute and coir are emerging as a reasonable alternative to synthetic materials because they do not only have favourable engineering characteristics but also degrade biologically over time. Of promising applications of those environmentally friendly materials, natural prefabricated vertical drains (NPVDs) have received considerable attention, however their application is still limited. This paper summarises existing issues which are hampering these novel drains from a wider application, followed by studies carried out by the authors to overcome those limitations. Particularly this includes: (1) hydraulic properties of NPVDs considering macro and micro features; (2) modelling NPVDS including analytical method and a novel numerical approach to capture micro-hydraulic behavior of fibre drains considering fluid-fibre interaction; (3) bioderadable characteristics of NPVDs exposed to saturated soft soils; (4) analytical and numerical solutions to incorporate biodegradation of NPVDs into consolidation of soil.

Nguyen, TV 2018, 'Individualized fracture risk assessment: State-of-the-art and room for improvement', Osteoporosis and Sarcopenia, vol. 4, no. 1, pp. 2-10.
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Fragility fracture is a serious clinical event, because it is associated with increased risk of mortality and reduced quality of life. The risk of fracture is determined by multiple risk factors, and their effects may be interactional. Over the past 10 years, a number of predictive models (e.g., FRAX, Garvan Fracture Risk Calculator, and Qfracture) have been developed for individualized assessment of fracture risk. These models use different risk profiles to estimate the probability of fracture over 5- and 10-year period. The ability of these models to discriminate between those individuals who will and will not have a fracture (i.e., area under the receiver operating characteristic curve [AUC]) is generally acceptable-to-good (AUC, 0.6 to 0.8), and is highly variable between populations. The calibration of existing models is poor, particularly in Asian populations. There is a strong need for the development and validation of new prediction models based on Asian data for Asian populations. We propose approaches to improve the accuracy of existing predictive models by incorporating new markers such as genetic factors, bone turnover markers, trabecular bone score, and time-variant factors. New and more refined models for individualized fracture risk assessment will help identify those most likely to sustain a fracture, those most likely to benefit from treatment, and encouraging them to modify their risk profile to decrease risk.

Nguyen, TV & Eisman, JA 2018, 'Assessment of Fracture Risk: Population Association Versus Individual Prediction', Journal of Bone and Mineral Research, vol. 33, no. 3, pp. 386-388.
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Nguyen, VV, Li, J, Erkmen, E, Alamdari, MM & Dackermann, U 2018, 'FRF Sensitivity-Based Damage Identification Using Linkage Modeling for Limited Sensor Arrays', International Journal of Structural Stability and Dynamics, vol. 18, no. 08, pp. 1840002-1840002.
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This paper presents a novel method to localize and quantify damage in a jack arch structure by introducing a linkage modeling technique to overcome issues caused by having limited sensors. The main strategy in the proposed Frequency Response Function (FRF)-based sensitivity model updating approach is to divide the specimen into partitions. The Young’s modulus of each partition is then updated to detect stiffness reduction caused by damage. System Equivalent Reduction Expansion Process (SEREP) is used to reduce the full finite element (FE) model to a linkage model. The number of measured degrees of freedom (DOFs) is then expanded to the linkage model using the mass and stiffness matrices of the linkage model for the synthesis of interpolated FRFs. The FRF sensitivities are then formulated using the linkage model along with the interpolated FRFs to iteratively calculate the values of the updating parameters until convergence is achieved. The methodology and theory behind this procedure are discussed and verified using a numerical and experimental study. The successful implementation of this method has the potential to detect the location and severity of damage where sensor placement is limited.

Nguyen, XC, Chang, SW, Nguyen, TL, Ngo, HH, Kumar, G, Banu, JR, Vu, MC, Le, HS & Nguyen, DD 2018, 'A hybrid constructed wetland for organic-material and nutrient removal from sewage: Process performance and multi-kinetic models', Journal of Environmental Management, vol. 222, pp. 378-384.
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© 2018 Elsevier Ltd A pilot-scale hybrid constructed wetland with vertical flow and horizontal flow in series was constructed and used to investigate organic material and nutrient removal rate constants for wastewater treatment and establish a practical predictive model for use. For this purpose, the performance of multiple parameters was statistically evaluated during the process and predictive models were suggested. The measurement of the kinetic rate constant was based on the use of the first-order derivation and Monod kinetic derivation (Monod) paired with a plug flow reactor (PFR) and a continuously stirred tank reactor (CSTR). Both the Lindeman, Merenda, and Gold (LMG) analysis and Bayesian model averaging (BMA) method were employed for identifying the relative importance of variables and their optimal multiple regression (MR). The results showed that the first-order–PFR (M2) model did not fit the data (P > 0.05, and R2 < 0.5), whereas the first-order–CSTR (M1) model for the chemical oxygen demand (CODCr) and Monod–CSTR (M3) model for the CODCr and ammonium nitrogen (NH4−N) showed a high correlation with the experimental data (R2 > 0.5). The pollutant removal rates in the case of M1 were 0.19 m/d (CODCr) and those for M3 were 25.2 g/m2∙d for CODCr and 2.63 g/m2∙d for NH4-N. By applying a multi-variable linear regression method, the optimal empirical models were established for predicting the final effluent concentration of five days' biochemical oxygen demand (BOD5) and NH4-N. In general, the hydraulic loading rate was considered an important variable having a high value of relative importance, which appeared in all the optimal predictive models.

Ni, W, Zhang, JA, Fang, Z, Abolhasan, M, Liu, RP & Guo, YJ 2018, 'Analysis of Finite Buffer in Two-Way Relay: A Queueing Theoretic Point of View', IEEE Transactions on Vehicular Technology, vol. 67, no. 4, pp. 3690-3694.
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© 1967-2012 IEEE. The impact of a finite relay buffer on the throughput of two-way relay is analyzed from a new queueing theoretic point of view. Distinctively from recent Markov model based analyses, the proposed queueing theoretic analysis is able to infer closed-form asymptotic upper bounds for the throughput, shed valuable insights, and point out limitations in the recent analyses. Validated by simulations, our queueing theoretic analysis reveals that the throughput is increasingly insusceptible to the size of the relay buffer, as the buffer enlarges. Moreover, locking the relay in transmitting xored packets can hardly improve the throughput, especially under balanced channel conditions. This is due to the fact that the relay queues stabilize nonempty, and hence, xored packets are forwarded in most cases.

Niamir, L, Filatova, T, Voinov, A & Bressers, H 2018, 'Transition to low-carbon economy: Assessing cumulative impacts of individual behavioral changes', Energy Policy, vol. 118, pp. 325-345.
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© 2018 The Authors Changing residential energy demand can play an essential role in transitioning to a green economy. Environmental psychology suggests that behavioral changes regarding energy use are affected by knowledge, awareness, motivation and social learning. Data on various behavioral drivers of change can explain energy use at the individual level, but it provides little information about implications for macro energy demand on regional or national levels. We address this challenge by presenting a theoretically-based and empirically-driven agent-based model to track aggregated impacts of behavioral changes among heterogeneous households. We focus on the representation of the multi-step changes in individual energy use behavior and on a quantitative assessment of their aggregated impacts on the regional level. We understand the behavioral complexity of household energy use as a dynamic process unfolding in stages, and explore the barriers for utilizing the full potential of a region for emissions reduction. We suggest a policy mix that facilitates mutual learning among consumers.

Niazi, M, Mishra, A & Gill, AQ 2018, 'What Do Software Practitioners Really Think About Software Process Improvement Project Success? An Exploratory Study', Arabian Journal for Science and Engineering, vol. 43, no. 12, pp. 7719-7735.
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© 2018, King Fahd University of Petroleum & Minerals. Software practitioners have always shown a significant interest in implementing software process improvement (SPI) initiatives to ensure the delivery of quality products. Software industry and SPI methodologies have evolved over a period of time; however, still many SPI initiatives have not been successful. There is a need to understand software practitioners’ perspectives on SPI success which can be helpful for tailoring or improving effective situation-specific SPI methodologies. This research presents an exploratory study of Turkish software development organizations. The main research question is: What software practitioners’ really think about SPI project success. This study was conducted with 27 Turkish software development organizations to identity and analyse important SPI factors that contribute to the success of SPI projects. The results reveal that professional growth, increased professional recognition, project planning, monitoring of project risks, providing technical support, adoption of current technologies, strong leadership and commitment are among the highest ranked factors that contribute towards the success of SPI initiatives. The findings of this research provide a foundation for further work in tailoring and improving situation-specific SPI methodologies for software project environments.

Nie, L, Wang, X, Wan, L, Yu, S, Song, H & Jiang, D 2018, 'Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks', Wireless Communications and Mobile Computing, vol. 2018, no. 1, pp. 1-10.
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Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT) and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low‐pass component of network traffic that describes the long‐range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low‐pass component. Otherwise, for the remaining high‐pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

Nimbalkar, S, Annapareddy, VSR & Pain, A 2018, 'A simplified approach to assess seismic stability of tailings dams', Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 6, pp. 1082-1090.
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© 2018 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences In the zones of high seismic activity, tailings dam should be assessed for the stability against earthquake forces. In the present paper, a simplified method is proposed to compute the factor of safety of tailings dams. The strain-dependent dynamic properties are used to assess the stability of tailings dams under seismic conditions. The effect of foundation soil properties on the seismic stability of tailings dams is studied using the proposed method. For the given input parameters, the factor of safety for low-frequency input motions is nearly 26% lower than that for high-frequency input excitations. The impedance ratio and the depth of foundation have significant effect on the seismic factor of safety of tailings dams. The results from the proposed method are well compared with the existing pseudo-static method of analysis. Tailings dams are vulnerable to damage for low-frequency input motions.

Nimbalkar, S, Dash, SK & Indraratna, B 2018, 'Performance of ballasted track under impact loading and applications of recycled rubber inclusion', Geotechnical Engineering, vol. 49, no. 4, pp. 79-91.
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In this paper a review of the sources of impact loads and their effect on the performance of ballasted track is presented. The typical characteristics and implications of impact loading on track deterioration, particularly ballast degradation, are discussed. None of the procedures so far developed to design rail track incorporate the impact that dynamic loading has on the breakage of ballast and therefore it can be said to be incomplete. An intensive study on the impact of induced ballast breakage is needed in order to understand this phenomenon and then use the knowledge gained to further advance the design methodology. A stiff track structure can create severe dynamic loading under operating conditions which causes large scale component failure and increases maintenance requirements. Installing resilient mats such as rubber pads (ballast mat, soffit pad) in rail tracks can attenuate the dynamic force and improve overall performance. The efficacy of ballast mats to reduce structural noise and ground vibration has been studied extensively, but a few recent studies has reported how ballast mats and soffit pads reduce ballast degradation, thus obviating the necessity of a comprehensive study in this direction.

Niu, T, Wang, J, Lu, H & Du, P 2018, 'Uncertainty modeling for chaotic time series based on optimal multi-input multi-output architecture: Application to offshore wind speed', Energy Conversion and Management, vol. 156, pp. 597-617.
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© 2017 Elsevier Ltd Wind energy is attracting more attention with the growing demand for energy. However, the efficient development and utilization of wind energy are restricted due to the intermittency and randomness of wind speed. Although abundant investigations concerning wind speed forecasting have been conducted by numerous researchers, most of the studies merely attach importance to point forecasts, which cannot quantitatively characterize the uncertainties as developing intervals. In this study, a novel interval prediction architecture has been designed, aiming at constructing effective prediction intervals for a wind speed series, composed of a preprocessing module, a feature selection module, an optimization module, a forecast module and an evaluation module. The feature selection module, in cooperation with the preprocessing module, is developed to determine the optimal model input. Furthermore, the forecast module optimized by the optimization module is considered a predictor for giving prediction intervals. The experimental results shed light on the architecture that not only outperforms the benchmark models considered, but also has great potential for application to wind power systems.

Niu, W, Guo, J, Lian, J, Ngo, HH, Li, H, Song, Y, Li, H & Yin, P 2018, 'Effect of fluctuating hydraulic retention time (HRT) on denitrification in the UASB reactors', Biochemical Engineering Journal, vol. 132, pp. 29-37.
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© 2017 Elsevier B.V. This study cultivated denitrifying granular sludge in three up-flow anaerobic sludge blanket (UASB) reactors using different fluctuation hydraulic retention time (HRT) strategies (reactor 1 (RC): constant HRT (C-HRT); reactor 2 (RDF): downward fluctuation HRT (DF-HRT); and reactor 3 (RUF): upward fluctuation HRT (UF-HRT)). The results verified that these fluctuation HRT strategies could enhance microbial diversity, while robust against fluctuations in nutrient load of the denitrifying granular sludge. Microbial aggregates appeared in RC, RUF and RDF on days 22, 12 and 7, respectively. The sludge in RUF and RDF achieved complete granulation on days 22 and 14, respectively. Compared to the results of RC and RUF, the acyl homoserine lactones (AHLs) concentration rapidly increased, and changed the components of extracellular polymeric substances (EPS) resulted in the rapid formation of denitrifying granular sludge in RDF. These results demonstrate that microbial community, AHLs, EPS, and the denitrifying sludge granulation process were associated with each other. Informed from quorum sensing system, a mechanism for the granulation of denitrifying sludge using the DF-HRT strategy was proposed. The DF-HRT strategy is an economical and fast method to cultivate denitrifying granular sludge. We hope that the results of our research would provide some theoretical support for wastewater producing unstable plants.

Norhasyima, RS & Mahlia, TMI 2018, 'Advances in CO₂ utilization technology: A patent landscape review', Journal of CO2 Utilization, vol. 26, pp. 323-335.
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© 2018 Elsevier Ltd. All rights reserved. There is rising concern on the increasing trend of global warming due to anthropogenic CO2 emission which steers progress of carbon capture and storage (CCS) projects worldwide. However, due to high cost and uncertainties in long term geological storage, there is a growing inclination to include utilization, which re-use the CO2, hence carbon capture utilization and storage (CCUS). Additionally, it is expected to generate income to offset the initial costs. This study methodically review patents on CO2 utilization technologies for CCUS application published between year 1980-2017. It was conducted using the Derwent Innovation patent database and more than 3000 number of patents was identified. The patents identified are in the field of enhanced oil recovery (EOR) and enhanced coal-bed methane (ECBM), chemical and fuel, mineral carbonation, biological algae cultivation and enhanced geothermal system (EGS). Over 60% of these patents were published since the last 10 years, and a sharp increase in patents were seen in the last 5 years (∼38%). The top major patent types are patents granted in the United States (US), China (CN) and Canada (CA) which makes of 3/5 of the overall patent type found. Recent patents published include enhancements to the state-of-the-art technologies and hybrid concepts such as in photo-bioreactor in algae cultivation, chemical reaction and EGS. From this study, it was found that further research for the best CO2 utilization method which fulfil the need of an economic, safe, non-location dependent and environmentally friendly whilst efficiently mitigate the worldwide global warming issue is much needed.

Noushini, A & Castel, A 2018, 'Performance-based criteria to assess the suitability of geopolymer concrete in marine environments using modified ASTM C1202 and ASTM C1556 methods', Materials and Structures, vol. 51, no. 6.
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© 2018, RILEM. In marine or coastal zones, the most harmful exposure for reinforced concrete structures to chloride ions. The ASTM C1556 chloride diffusion test (or its European equivalent NT BUILD 443) has been widely used as the most reliable testing method to assess the performance of concrete against chloride penetration. However, this test is time demanding and labour intensive. As a result, accelerated test ASTM C1202 (RCPT) is often preferred, providing fast and acceptable assessment of chloride penetrability of Ordinary Portland Cement Concrete. This study aimed to investigate the suitability of RCPT to assess the performance of Geopolymer Concrete (GPC) in chloride environment. The correlation between several GPC properties [i.e. compressive strength, volume of permeable voids (VPV) and sorptivity] and the chloride diffusion coefficient are examined. Results indicate that the compressive strength, the VPV and the sorptivity coefficient are not suitable indicators of the GPC performance. The ASTM C1202 standard RCPT failed to measure the charges passed through most of the GPCs tested. A modified version of RCPT using 10 V (as opposed to 60 V specified by standard ASTM C1202) is proposed in this paper, allowing to successfully measure the charges passed through all GPC samples using a wide range of binders. A good correlation was observed between modified ASTM C1202 and Standard ASTM C1556 test results. Performance-based recommendations are proposed in this paper. Both experimental results from this study and appropriate reference concretes from the literature were used to calibrate the modified ASTM C1202 and ASTM C1556 performance-based requirements for GPCs.

Noushini, A, Hastings, M, Castel, A & Aslani, F 2018, 'Mechanical and flexural performance of synthetic fibre reinforced geopolymer concrete', Construction and Building Materials, vol. 186, pp. 454-475.
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© 2018 A comprehensive experimental program was undertaken to analyse the structural and material characteristics of synthetic fibre reinforced geopolymer concrete. This study focused on the effect of monofilament and fibrillated polypropylene fibres and monofilament structural polyolefin fibres on mechanical and flexural performance of fly ash based geopolymer concrete. Five types of synthetic fibres at a 0.5% volume fraction were added to geopolymer concretes. The specimens’ compressive strength, indirect tensile strength, modulus of elasticity, modulus of rupture, flexural toughness and fracture energy were determined. Where possible, comparative analyses where conducted to assess the performance of fibre reinforced geopolymer concrete against conventional Portland cement based systems. The flexural toughness parameters were obtained using procedure laid down in ASTM C1018, JCI-SF4 and ASTM C1609. The results indicated that the macro polyolefin fibres exhibited the largest fracture energy which is likely due to high mechanical bonding and low fibre aspect ratio. Relationships are established to predict the compressive and tensile strengths, modulus of elasticity, compressive stress–strain curve and relation between the deflection and CMOD of synthetic fibre reinforced geopolymer concrete.

Nur, T, Loganathan, P, Ahmed, MB, Johir, M, Kandasamy, J & Vigneswaran, S 2018, 'Struvite production using membrane-bioreactor wastewater effluent and seawater', Desalination, vol. 444, pp. 1-5.
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© 2018 Elsevier B.V. Wastewater phosphorus (P) released into natural water bodies such as lakes and rivers, can cause water pollution as a result of eutrophication. If this P is effectively removed from wastewaters and economically recovered for use as fertilisers, not only can the water pollution be controlled, but also reduce the anticipated global shortage of P. This scarcity will result from the natural phosphate rock reserve being exhausted. Three experiments were conducted using membrane-bioreactor effluent (MBR, 35 mg PO 4 /L) and reverse osmosis concentrate (ROC, 10 mg PO 4 /L) waters to supply phosphate, and sea water (1530 mg Mg/L) to supply Mg for the production of struvite. The phosphate in the MBR and ROC was concentrated approximately 15 times by adsorption onto an ion exchange resin column followed by desorption. Struvite was precipitated by mixing the desorbed solution with seawater and NH 4 Cl. The chemical composition and mineral structure of the precipitates agreed with those of the reference struvite. When Ca in seawater (300 mg Ca/L) was removed before mixing the water with MBR or ROC, the purity of the struvite improved.

Nur, T, Loganathan, P, Johir, MAH, Kandasamy, J & Vigneswaran, S 2018, 'Removing rubidium using potassium cobalt hexacyanoferrate in the membrane adsorption hybrid system', Separation and Purification Technology, vol. 191, pp. 286-294.
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© 2017 Elsevier B.V. Highly-priced rubidium (Rb) can be effectively extracted from seawater using potassium cobalt hexacyanoferrate (KCoFC) and ammonium molybdophosphate (AMP) adsorbents in the membrane adsorption hybrid system (MAHS). KCoFC (<0.075 mm), KCoFC (0.075–0.15 mm), and AMP (<0.075 mm) had Langmuir adsorption capacities of 145, 113, and 77 mg/g at pH 6.5–7.5, respectively. When KCoFC (<0.075 mm) at a dose of 0.2 g/L was initially added to 4 L of a solution containing 5 mg Rb/L in the MAHS and 25% of the initial dose was repeatedly added every hour, the amount of Rb removed remained steady at 90–96% for the experiment's 26 h duration. The removal of Rb by AMP under similar conditions was 80–82%. The cumulative Rb removed by KCoFC (<0.075 mm) in MAHS was only 33% reduced in the presence of high concentrations of other cations in synthetic seawater compared to that in solution containing only Rb. Approximately 30% of the adsorbed Rb was desorbed using 1 M KCl. When the desorbed solution was passed through a column containing resorcinol formaldehyde (RF), 35% of the Rb in the desorbed solution was adsorbed on RF. Furthermore 50% of the Rb adsorbed on RF was recovered by 1 M HCl leaching of the column. This sequence of concentration and separation of Rb in the presence of other cations in synthetic seawater is an efficient method for recovering pure Rb from real seawater and seawater reverse osmosis brine.

Nuruzzaman, M, Liu, Y, Rahman, MM, Naidu, R, Dharmarajan, R, Shon, HK & Woo, YC 2018, 'Core–Shell Interface-Oriented Synthesis of Bowl-Structured Hollow Silica Nanospheres Using Self-Assembled ABC Triblock Copolymeric Micelles', Langmuir, vol. 34, no. 45, pp. 13584-13596.
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© 2018 American Chemical Society. Hollow porous silica nanospheres (HSNs) are emerging classes of cutting-edge nanostructured materials. They have elicited much interest as carriers of active molecule delivery due to their amorphous chemical structure, nontoxic nature, and biocompatibility. Structural development with hierarchical morphology is mostly required to obtain the desired performance. In this context, large through-holes or pore openings on shells are desired so that the postsynthesis loading of active-molecule onto HSNs via a simple immersion method can be facilitated. This study reports the synthesis of HSNs with large through-holes or pore openings on shells, which are subsequently termed bowl-structured hollow porous silica nanospheres (BHSNs). The synthesis of BHSNs was mediated by the core-shell interfaces of the core-shell corona-structured micelles obtained from a commercially available ABC triblock copolymer (polystyrene-b-poly(2-vinylpyridine)-b-poly(ethylene oxide) (PS-P2VP-PEO)). In this synthesis process, polymer@SiO2 composite structure was formed because of the deposition of silica (SiO2) on the micelles' core. The P2VP block played a significant role in the hydrolysis and condensation of the silica precursor, i.e., tetraethylorthosilicate (TEOS) and then maintaining the shell's growth. The PS core of the micelles built the void spaces. Transmission electron microscopy (TEM) images revealed a spherical hollow structure with an average particle size of 41.87 ± 3.28 nm. The average diameter of void spaces was 21.71 ± 1.22 nm, and the shell thickness was 10.17 ± 1.68 nm. According to the TEM image analysis, the average large pore was determined to be 15.95 nm. Scanning electron microscopy (SEM) images further confirmed the presence of large single pores or openings in shells. These were formed as a result of the accumulated ethanol on the PS core acting to prevent the growth of silica.

Oberst, S & Tuttle, S 2018, 'Nonlinear dynamics of thin-walled elastic structures for applications in space', Mechanical Systems and Signal Processing, vol. 110, pp. 469-484.
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© 2018 Elsevier Ltd Driven by the need for multi-functionality and increasing demands for low mass and compact-stowing, unfolding, self-deploying or –morphing smart mechanical structures have become popular space engineering designs for flexible appendages. Extensive research has been conducted on the use of tape springs as hinge deployment mechanisms for space booms, solar sails, or optical membranes or directly for used as antennas. However, the vibrational behaviour of tape springs and its related dynamics have rarely been addressed in detail, even though missions are underway with similarly flexible appendages installed. By conducting quasi-static bending tests on a tape spring antenna, we evidence hysteresis behaviours in both the opposite- and equal sense bending directions. Apart from the well-known snap-through buckling, the structure exhibits torsional buckling in the equal sense bending direction before collapsing. Micro-vibrational excitation triggers nonlinear jump phenomena and the period-doubling route to chaos. Using a computational tape spring model and simplified environmental loads similar to those encountered in near-Earth orbits, coupling between the first bending and torsional modes generates a dynamic instability which is predicted by a complex eigenvalue analysis step. The current study highlights that high perturbation sensitivity and system-inherent nonlinearities can lead to stability issues. In the course of designing a spacecraft with thin-walled appendages, system-level trade-offs are routinely performed. Since it is unclear how severely the vibrations of flexible appendages might affect their proper functioning or the control of the spacecraft, it is of paramount importance to validate experimentally thin-walled structures thoroughly for their dynamic and stability behaviours.

Oberst, S, Baetz, J, Campbell, G, Lampe, F, Lai, JCS, Hoffmann, N & Morlock, M 2018, 'Vibro-acoustic and nonlinear analysis of cadavric femoral bone impaction in cavity preparations', International Journal of Mechanical Sciences, vol. 144, pp. 739-745.
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© 2018 Elsevier Ltd Owing to an ageing population, the impact of unhealthy lifestyle, or simply congenital or gender specific issues (dysplasia), degenerative bone and joint disease (osteoarthritis) at the hip pose an increasing problem in many countries. Osteoarthritis is painful and causes mobility restrictions; amelioration is often only achieved by replacing the complete hip joint in a total hip arthroplasty (THA). Despite significant orthopaedic progress related to THA, the success of the surgical process relies heavily on the judgement, experience, skills and techniques used of the surgeon. One common way of implanting the stem into the femur is press fitting uncemented stem designs into a prepared cavity. By using a range of compaction broaches, which are impacted into the femur, the cavity for the implant is formed. However, the surgeon decides whether to change the size of the broach, how hard and fast it is impacted or when to stop the excavation process, merely based on acoustic, haptic or visual cues which are subjective. It is known that non-ideal cavity preparations increase the risk of peri-prosthetic fractures especially in elderly people. This study reports on a simulated hip replacement surgery on a cadaver and the analysis of impaction forces and the microphone signals during compaction. The recorded transient signals of impaction forces and acoustic pressures (≈ 80 µs–2 ms) are statistically analysed for their trend, which shows increasing heteroscedasticity in the force-pressure relationship between broach sizes. TIKHONOV regularisation, as inverse deconvolution technique, is applied to calculate the acoustic transfer functions from the acoustic responses and their mechanical impacts. The extracted spectra highlight that system characteristics altered during the cavity preparation process: in the high-frequency range the number of resonances increased with impacts and broach size. By applying nonlinear time series analysis the syste...

Oberst, S, Lai, JCS & Evans, TA 2018, 'Key physical wood properties in termite foraging decisions', Journal of The Royal Society Interface, vol. 15, no. 149, pp. 20180505-20180505.
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As eusocial and wood-dwelling insects, termites have been shown to use vibrations to assess their food, to eavesdrop on competitors and predators and to warn nest-mates. Bioassay choice experiments used to determine food preferences in animals often consider single factors only but foraging decisions can be influenced by multiple factors such as the quantity and quality of the food and the wood as a medium for communication. A statistical analysis framework is developed here to design a single bioassay experiment to study multifactorial foraging choice (Pinus radiata) in the basal Australian termite speciesCoptotermes(C.)acinaciformis(Isoptera: Rhinotermitidae). By employing a correlation analysis, 17 measured physical properties of 1417Pinus radiataveneer discs were reduced to five key material properties: density, moisture absorption, early wood content, first resonance frequency and damping. By applying a fuzzyc-means clustering technique, these veneer discs were optimally paired for treatment and control trials to study food preference by termites based on these five key material properties. A multifactorial analysis of variance was compared to a permutation analysis of the results indicating for the first time thatC. acinaciformistakes into account multiple factors when making foraging decisions.C. acinaciformisprefer denser wood with large early wood content, preferably humid and highly damped. Results presented here have practical implications for food choice experiments and for studies concerned with communication in termites as well as their ecology and coevolution with trees as their major food source.

Oberst, S, Niven, RK, Lester, DR, Ord, A, Hobbs, B & Hoffmann, N 2018, 'Detection of unstable periodic orbits in mineralising geological systems', Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 28, no. 8, pp. 085711-085711.
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Worldwide, mineral exploration is suffering from rising capital costs, due to the depletion of readily recoverable reserves and the need to discover and assess more inaccessible or geologically complex deposits. For gold exploration, this problem is particularly acute. We propose an innovative approach to mineral exploration and orebody characterisation, based on the analysis of geological core data as a spatial dynamical system, using the mathematical tools of dynamical system analysis. This approach is highly relevant for orogenic gold deposits, which—in contrast to systems formed at chemical equilibrium—exhibit many features of nonlinear dynamical systems, including episodic fluctuations on various length and time scales. Feedback relationships between thermo-chemical and deformation processes produce recurrent fluid temperatures and pressures and the deposition of vein-filling minerals such as pyrite and gold. We therefore relax the typical assumption of chemical equilibrium and analyse the underlying processes as aseismic, non-adiabatic, and inherent to a hydrothermal, nonlinear dynamical open-flow chemical reactor. These processes are approximated using the Gray-Scott model of reaction-diffusion as a complex toy system, which captures some of the features of the underlying mineralisation processes, including the spatiotemporal Turing patterns of unsteady chemical reactions. By use of this analysis, we demonstrate the capability of recurrence plots, recurrence power spectra, and recurrence time probabilities to detect underlying unstable periodic orbits as one sign of deterministic dynamics and their robustness for the analysis of data contaminated by noise. Recurrence plot based quantification is then applied to three mineral concentrations in the core data from the Sunrise Dam gold deposit in the Yilgarn region of Western Australia. Using a moving window, we reveal the episodic recurring low-dimensional dynamic structures and the period d...

Oberst, S, Tuttle, SL, Griffin, D, Lambert, A & Boyce, RR 2018, 'Experimental validation of tape springs to be used as thin-walled space structures', Journal of Sound and Vibration, vol. 419, pp. 558-570.
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© 2018 Elsevier Ltd With the advent of standardised launch geometries and off-the-shelf payloads, space programs utilising nano-satellite platforms are growing worldwide. Thin-walled, flexible and self-deployable structures are commonly used for antennae, instrument booms or solar panels owing to their lightweight, ideal packaging characteristics and near zero energy consumption. However their behaviour in space, in particular in Low Earth Orbits with continually changing environmental conditions, raises many questions. Accurate numerical models, which are often not available due to the difficulty of experimental testing under 1g-conditions, are needed to answer these questions. In this study, we present on-earth experimental validations, as a starting point to study the response of a tape spring as a representative of thin-walled flexible structures under static and vibrational loading. Material parameters of tape springs in a singly (straight, open cylinder) and a doubly curved design, are compared to each other by combining finite element calculations, with experimental laser vibrometry within a single and multi-stage model updating approach. While the determination of the Young's modulus is unproblematic, the damping is found to be inversely proportional to deployment length. With updated material properties the buckling instability margin is calculated using different slenderness ratios. Results indicate a high sensitivity of thin-walled structures to miniscule perturbations, which makes proper experimental testing a key requirement for stability prediction on thin-elastic space structures. The doubly curved tape spring provides closer agreement with experimental results than a straight tape spring design.

Olvera, C, Berbegal-Mirabent, J & Merigó, JM 2018, 'A Bibliometric Overview of University-Business Collaboration between 1980 and 2016', Computación y Sistemas, vol. 22, no. 4, pp. 1171-1190.
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© 2018 Instituto Politecnico Nacional. All rights reserved. Bibliometrics is a research field that analyses bibliographic material from a quantitative point of view. Aiming at providing a comprehensive overview, this study scrutinises the academic literature in university business collaboration and technology transfer research for the period post the Bayh-Dole Act (1980-2016). The study employs the Web of Science as the main database from where information is collected. Bibliometric indicators such as number of publications, citations, productivity, and the H-index are used to analyse the results. The main findings are displayed in the form of tables and are further discussed. The focus is on the identification of the most relevant journals in this area, the most cited papers, most prolific authors, leading institutions, and countries. The results show that the USA, England, Spain, Italy, and the Netherlands are highly active in this area. Scientific production tends to fall within the research areas of business and economics, engineering or public administration, and is mainly published in journals such as Research Policy, Technovation and Journal of Technology Transfer.

Ooi, CY, Carter, DR, Liu, B, Mayoh, C, Beckers, A, Lalwani, A, Nagy, Z, De Brouwer, S, Decaesteker, B, Hung, T-T, Norris, MD, Haber, M, Liu, T, De Preter, K, Speleman, F, Cheung, BB & Marshall, GM 2018, 'Network Modeling of microRNA–mRNA Interactions in Neuroblastoma Tumorigenesis Identifies miR-204 as a Direct Inhibitor of MYCN', Cancer Research, vol. 78, no. 12, pp. 3122-3134.
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Abstract Neuroblastoma is a pediatric cancer of the sympathetic nervous system where MYCN amplification is a key indicator of poor prognosis. However, mechanisms by which MYCN promotes neuroblastoma tumorigenesis are not fully understood. In this study, we analyzed global miRNA and mRNA expression profiles of tissues at different stages of tumorigenesis from TH-MYCN transgenic mice, a model of MYCN-driven neuroblastoma. On the basis of a Bayesian learning network model in which we compared pretumor ganglia from TH-MYCN+/+ mice to age-matched wild-type controls, we devised a predicted miRNA–mRNA interaction network. Among the miRNA–mRNA interactions operating during human neuroblastoma tumorigenesis, we identified miR-204 as a tumor suppressor miRNA that inhibited a subnetwork of oncogenes strongly associated with MYCN-amplified neuroblastoma and poor patient outcome. MYCN bound to the miR-204 promoter and repressed miR-204 transcription. Conversely, miR-204 directly bound MYCN mRNA and repressed MYCN expression. miR-204 overexpression significantly inhibited neuroblastoma cell proliferation in vitro and tumorigenesis in vivo. Together, these findings identify novel tumorigenic miRNA gene networks and miR-204 as a tumor suppressor that regulates MYCN expression in neuroblastoma tumorigenesis. Significance: Network modeling of miRNA–mRNA regulatory interactions in a mouse model of neuroblastoma identifies miR-204 as a tumor suppressor and negative regulator of MYCN. Cancer Res; 78(12); 3122–34. ©2018 AACR.

Orth, D, Thurgood, C & van den Hoven, E 2018, 'Designing objects with meaningful associations', International Journal of Design, vol. 12, no. 2, pp. 91-104.
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Objects often become cherished for their ties to beliefs, experiences, memories, people, places or values that are significant to their owner. These ties can reflect the ways in which we as humans use objects to characterise, communicate and develop our sense of self. This paper outlines our approach to applying product attachment theory to design practices. We created six artefacts that were inspired by interviews conducted with three individuals who discussed details of their life stories. We then evaluated the associations that came to mind for our participants when interacting with these newly designed artefacts to determine whether these links brought meaning to them. Our findings highlight the potential of design to bring emotional value to products by embodying significant aspects of a person’s self-identity. To do so, designers must consider both the importance and authenticity of the associations formed between an object and an individual.

Ouyang, Y, Guo, B, Guo, T, Cao, L & Yu, Z 2018, 'Modeling and Forecasting the Popularity Evolution of Mobile Apps', Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 2, no. 4, pp. 1-23.
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In recent years, with the rapid development of mobile app ecosystem, the number and categories of mobile apps have grown tremendously. However, the global prevalence of mobile apps also leads to fierce competition. As a result, many apps will disappear. To thrive in this competitive app market, it is vital for app developers to understand the popularity evolution of their mobile apps, and inform strategic decision-making for better mobile app development. Therefore, it is significant and necessary to model and forecast the future popularity evolution of mobile apps. The popularity evolution of mobile apps is usually a long-term process, affected by various complex factors. However, existing works lack the capabilities to model such complex factors. To better understand the popularity evolution, in this paper, we aim to forecast the popularity evolution of mobile apps by incorporating complex factors, i.e., exogenous stimulis and endogenous excitations. Specifically, we propose a model based on the Multivariate Hawkes Process (MHP), which is an exogenous stimulis-driven self-exciting point process, to model the exogenous stimulis and endogenous excitations simultaneously. Extensive experimental studies on a real-world dataset from app store demonstrate that MHP outperforms the state-of-the-art methods regarding popularity evolution forecasting.

Oviatt, S, Hang, K, Zhou, J, Yu, K & Chen, F 2018, 'Dynamic Handwriting Signal Features Predict Domain Expertise', ACM Transactions on Interactive Intelligent Systems, vol. 8, no. 3, pp. 1-21.
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As commercial pen-centric systems proliferate, they create a parallel need for analytic techniques based on dynamic writing. Within educational applications, recent empirical research has shown that signal-level features of students’ writing, such as stroke distance, pressure and duration, are adapted to conserve total energy expenditure as they consolidate expertise in a domain. The present research examined how accurately three different machine-learning algorithms could automatically classify users’ domain expertise based on signal features of their writing, without any content analysis. Compared with an unguided machine-learning classification accuracy of 71%, hybrid methods using empirical-statistical guidance correctly classified 79–92% of students by their domain expertise level. In addition to improved accuracy, the hybrid approach contributed a causal understanding of prediction success and generalization to new data. These novel findings open up opportunities to design new automated learning analytic systems and student-adaptive educational technologies for the rapidly expanding sector of commercial pen systems.

Pace, B, Munroe, P, Marjo, CE, Thomas, P, Gong, B, Shepherd, J, Buss, W & Joseph, S 2018, 'The mechanisms and consequences of inorganic reactions during the production of ferrous sulphate enriched bamboo biochars', Journal of Analytical and Applied Pyrolysis, vol. 131, pp. 101-112.
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Pain, A, Ramakrishna Annapareddy, VS & Nimbalkar, S 2018, 'Seismic Active Thrust on Rigid Retaining Wall Using Strain Dependent Dynamic Properties', International Journal of Geomechanics, vol. 18, no. 12, pp. 06018034-06018034.
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Pal, DR, Saha, G & Saha, KC 2018, 'Parameters Effect on Heat Transfer Augmentation in a Cavity with Moving Horizontal Walls', Journal of Applied Mathematics and Physics, vol. 06, no. 09, pp. 1907-1915.
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Paler, A & Devitt, SJ 2018, 'Specification format and a verification method of fault-tolerant quantum circuits', Physical Review A, vol. 98, no. 2, pp. 1-9.
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© 2018 American Physical Society. Quantum computations are expressed in general as quantum circuits, which are specified by ordered lists of quantum gates. The resulting specifications are used during the optimization and execution of the expressed computations. However, the specification format makes it difficult to verify that optimized or executed computations still conform to the initial gate list specifications: showing the computational equivalence between two quantum circuits expressed by different lists of quantum gates is exponentially complex in the worst case. In order to solve this issue, this work presents a derivation of the specification format tailored specifically for fault-tolerant quantum circuits. The circuits are considered a form consisting entirely of single qubit initializations, cnot gates, and single qubit measurements (ICM form). This format allows, under certain assumptions, to efficiently verify optimized (or implemented) computations. Two verification methods based on checking stabilizer circuit structures are presented.

Pan, Y, Han, B & Tsang, IW 2018, 'Stagewise learning for noisy k-ary preferences', Machine Learning, vol. 107, no. 8-10, pp. 1333-1361.
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© 2018, The Author(s). The aggregation of k-ary preferences is a novel ranking problem that plays an important role in several aspects of daily life, such as ordinal peer grading, online image-rating, meta-search and online product recommendation. Meanwhile, crowdsourcing is increasingly emerging as a way to provide a plethora of k-ary preferences for these types of ranking problems, due to the convenience of the platforms and the lower costs. However, preferences from crowd workers are often noisy, which inevitably degenerates the reliability of conventional aggregation models. In addition, traditional inferences usually lead to massive computational costs, which limits the scalability of aggregation models. To address both of these challenges, we propose a reliable CrowdsOUrced Plackett–LucE (COUPLE) model combined with an efficient Bayesian learning technique. To ensure reliability, we introduce an uncertainty vector for each crowd worker in COUPLE, which recovers the ground truth of the noisy preferences with a certain probability. Furthermore, we propose an Online Generalized Bayesian Moment Matching (OnlineGBMM) algorithm, which ensures that COUPLE is scalable to large-scale datasets. Comprehensive experiments on four large-scale synthetic datasets and three real-world datasets show that, COUPLE with OnlineGBMM achieves substantial improvements in reliability and noisy worker detection over other well-known approaches.

Pang, YL, Tee, SF, Limg, S, Abdullah, AZ, Ong, HC, Wu, C-H, Chong, WC, Mohammad, AW & Mahmoudi, E 2018, 'Enhancement of photocatalytic degradation of organic dyes using ZnO decorated on reduced graphene oxide (rGO)', Desalination and Water Treatment, vol. 108, pp. 311-321.
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Park, MJ, Gonzales, RR, Abdel-Wahab, A, Phuntsho, S & Shon, HK 2018, 'Hydrophilic polyvinyl alcohol coating on hydrophobic electrospun nanofiber membrane for high performance thin film composite forward osmosis membrane', Desalination, vol. 426, pp. 50-59.
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© 2017 Elsevier B.V. In this study, the hydrophilic property of polyvinyl alcohol (PVA) was utilized to improve the hydrophilicity and mechanical strength of electrospun polyvinylidene fluoride (PVDF)-supported thin film composite (TFC) forward osmosis (FO) membranes. The PVDF nanofiber support was modified with PVA via dip coating and acid-catalyzed crosslinking with glutaraldehyde prior to formation of polyamide active layer on the support via interfacial polymerization. The influence of PVA modification on the morphology and physical properties of PVDF support was evaluated through several characterization techniques while the flux performance was assessed using lab-scale FO membrane unit. The fabricated PVA-modified TFC FO membranes exhibited high hydrophilicity, porosity, and mechanical strength. FO performance tests reveal excellent flux performance (34.2 LMH using 1 M NaCl and DI water as draw and feed solution, respectively) and low structural parameters (154 μm) of the PVA-modified TFC FO membrane. Dip coating of the nanofiber support in PVA is therefore a simple and effective method for the improvement of PVDF support hydrophilicity to fabricate high performance TFC FO membranes.

Parraga, J, Khalilpour, KR & Vassallo, A 2018, 'Polygeneration with biomass-integrated gasification combined cycle process: Review and prospective', Renewable and Sustainable Energy Reviews, vol. 92, no. C, pp. 219-234.
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The integrated gasification combined cycle (IGCC) process is an energy conversion system for concurrent power and chemical production. The key capability of this technology is the synthesis of versatile chemical products from various carbonaceous feed material, such as coal, biomass, and by-products from the petroleum refining process. This flexibility places the IGCC as a viable alternative for conventional Rankine cycles which suffer from inflexibility in response to the volatile electricity market. To date, there are few commercial examples of this technology predominantly due to the high capital cost requirement and operation complexity. However, the economic feasibility of the IGCC could be significantly improved with carbon capture obligations. This is due to its lower carbon capture costs as a result of treating high-pressure and high-concentrated CO2 stream, unlike conventional power generation systems. This paper provides a comprehensive review of polygeneration IGCC process with multiple-feed and multiple-product flexibility. Then process fundamentals are critically reviewed and technological barriers are discussed.

Partridge, S, Tipper, JL, Al‐Hajjar, M, Isaac, GH, Fisher, J & Williams, S 2018, 'Evaluation of a new methodology to simulate damage and wear of polyethylene hip replacements subjected to edge loading in hip simulator testing', Journal of Biomedical Materials Research Part B: Applied Biomaterials, vol. 106, no. 4, pp. 1456-1462.
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AbstractWear and fatigue of polyethylene acetabular cups have been reported to play a role in the failure of total hip replacements. Hip simulator testing under a wide range of clinically relevant loading conditions is important. Edge loading of hip replacements can occur following impingement under extreme activities and can also occur during normal gait, where there is an offset deficiency and/or joint laxity. This study evaluated a hip simulator method that assessed wear and damage in polyethylene acetabular liners that were subjected to edge loading. The liners tested to evaluate the method were a currently manufactured crosslinked polyethylene acetabular liner and an aged conventional polyethylene acetabular liner. The acetabular liners were tested for 5 million standard walking cycles and following this 5 million walking cycles with edge loading. Edge loading conditions represented a separation of the centers of rotation of the femoral head and the acetabular liner during the swing phase, leading to loading of the liner rim on heel strike. Rim damage and cracking was observed in the aged conventional polyethylene liner. Steady‐state wear rates assessed gravimetrically were lower under edge loading compared to standard loading. This study supports previous clinical findings that edge loading may cause rim cracking in liners, where component positioning is suboptimal or where material degradation is present. The simulation method developed has the potential to be used in the future to test the effect of aging and different levels of severity of edge loading on a range of cross‐linked polyethylene materials. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 1456–1462, 2018.

Patel, J, Lal, S, Nuss, K, Wilshaw, SP, von Rechenberg, B, Hall, RM & Tipper, JL 2018, 'Recovery of low volumes of wear debris from rat stifle joint tissues using a novel particle isolation method', Acta Biomaterialia, vol. 71, pp. 339-350.
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Less than optimal particle isolation techniques have impeded analysis of orthopaedic wear debris in vivo. The purpose of this research was to develop and test an improved method for particle isolation from tissue. A volume of 0.018 mm3 of clinically relevant CoCrMo, Ti-6Al-4V or Si3N4 particles was injected into rat stifle joints for seven days of in vivo exposure. Following sacrifice, particles were located within tissues using histology. The particles were recovered by enzymatic digestion of periarticular tissue with papain and proteinase K, followed by ultracentrifugation using a sodium polytungstate density gradient. Particles were recovered from all samples, observed using SEM and the particle composition was verified using EDX, which demonstrated that all isolated particles were free from contamination. Particle size, aspect ratio and circularity were measured using image analysis software. There were no significant changes to the measured parameters of CoCrMo or Si3N4 particles before and after the recovery process (KS tests, p > 0.05). Titanium particles were too few before and after isolation to analyse statistically, though size and morphologies were similar. Overall the method demonstrated a significant improvement to current particle isolation methods from tissue in terms of sensitivity and efficacy at removal of protein, and has the potential to be used for the isolation of ultra-low wearing total joint replacement materials from periprosthetic tissues. STATEMENT OF SIGNIFICANCE:This research presents a novel method for the isolation of wear particles from tissue. Methodology outlined in this work would be a valuable resource for future researchers wishing to isolate particles from tissues, either as part of preclinical testing, or from explants from patients for diagnostic purposes. It is increasingly recognised that analysis of wear particles is critical to evaluating the safety of an orthopaedic device.

Patel, J, Lal, S, Wilshaw, SP, Hall, RM & Tipper, JL 2018, 'Development and optimisation data of a tissue digestion method for the isolation of orthopaedic wear particles', Data in Brief, vol. 20, pp. 173-177.
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© 2018 The Authors The data contained within this article relate to several enzymatic tissue digestion experiments which were performed to produce an optimised protocol for the digestion of tissue samples. The digestion experiments involved a total of four different digestion protocols. The first protocol involved digestion with proteinase K, without the use of glycine. The second protocol involved digestion with proteinase K in the presence of glycine. The third protocol consisted of proteinase K digestion in the presence of glycine, with more frequent enzyme replenishment. The final protocol was similar to the third protocol but included a papain digestion stage prior to digestion with proteinase K. The data contained within this article are photographs of tissue samples which were captured at key stages of the four protocols and written descriptions based on visual observation of the tissue samples, which document the appearance of the tissue digests.

Patel, J, Lal, S, Wilshaw, SP, Hall, RM & Tipper, JL 2018, 'Recovery rate data for silicon nitride nanoparticle isolation using sodium polytungstate density gradients', Data in Brief, vol. 19, pp. 1474-1476.
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The average recovery rate of silicon nitride nanoparticles isolated from serum using the method detailed in previous article "A novel method for isolation and recovery of ceramic nanoparticles and metal wear debris from serum lubricants at ultra-low wear rate" (Lal et al., 2016) [1] was tested gravimetrically by weighing particles doped into serum before and after the isolation process. An average recovery rate of approximately 89.6% (± 7.1 SD) was achieved.

Patel, J, Lal, S, Wilshaw, SP, Hall, RM & Tipper, JL 2018, 'Validation of a novel particle isolation procedure using particle doped tissue samples', Data in Brief, vol. 18, pp. 1802-1807.
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A novel particle isolation method for tissue samples was developed and tested using particle-doped peri-articular tissues from ovine cadavers. This enabled sensitivity of the isolation technique to be established by doping tissue samples of 0.25 g with very low particle volumes of 2.5 µm3 per sample. Image analysis was used to verify that the method caused no changes to particle size or morphologies.

Pathak, N, Fortunato, L, Li, S, Chekli, L, Phuntsho, S, Ghaffour, N, Leiknes, T & Shon, HK 2018, 'Evaluating the effect of different draw solutes in a baffled osmotic membrane bioreactor-microfiltration using optical coherence tomography with real wastewater', Bioresource Technology, vol. 263, pp. 306-316.
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© 2018 Elsevier Ltd This study investigated the performance of an integrated osmotic and microfiltration membrane bioreactor for real sewage employing baffles in the reactor. To study the biofouling development on forward osmosis membranes optical coherence tomography (OCT) technique was employed. On-line monitoring of biofilm growth on a flat sheet cellulose triacetate forward osmosis (CTA-FO) membrane was conducted for 21 days. Further, the process performance was evaluated in terms of water flux, organic and nutrient removal, microbial activity in terms of soluble microbial products (SMP) and extracellular polymeric substance (EPS), and floc size. The measured biofouling layer thickness was in the order sodium chloride (NaCl) > ammonium sulfate (SOA) > potassium dihydrogen phosphate (KH2PO4). Very high organic removal (96.9 ± 0.8%) and reasonably good nutrient removal efficiency (85.2 ± 1.6% TN) was achieved. The sludge characteristics and biofouling layer thickness suggest that less EPS and higher floc size were the governing factors for less fouling.

Pathak, N, Li, S, Kim, Y, Chekli, L, Phuntsho, S, Jang, A, Ghaffour, N, Leiknes, T & Shon, HK 2018, 'Assessing the removal of organic micropollutants by a novel baffled osmotic membrane bioreactor-microfiltration hybrid system', Bioresource Technology, vol. 262, pp. 98-106.
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© 2018 Elsevier Ltd A novel approach was employed to study removal of organic micropollutants (OMPs) in a baffled osmotic membrane bioreactor-microfiltration (OMBR-MF) hybrid system under oxicanoxic conditions. The performance of OMBR-MF system was examined employing three different draw solutes (DS), and three model OMPs. The highest forward osmosis (FO) membrane rejection was attained with atenolol (100%) due to its higher molar mass and positive charge. With inorganic DS caffeine (94–100%) revealed highest removal followed by atenolol (89–96%) and atrazine (16–40%) respectively. All three OMPs exhibited higher removal with organic DS as compared to inorganic DS. Significant anoxic removal was observed for atrazine under very different redox conditions with extended anoxic cycle time. This can be linked with possible development of different microbial consortia responsible for diverse enzymes secretion. Overall, the OMBR-MF process showed effective removal of total organic carbon (98%) and nutrients (phosphate 97% and total nitrogen 85%), respectively.

Patten, T, Martens, W & Fitch, R 2018, 'Monte Carlo planning for active object classification', Autonomous Robots, vol. 42, no. 2, pp. 391-421.
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© 2017, Springer Science+Business Media New York. Classifying objects in complex unknown environments is a challenging problem in robotics and is fundamental in many applications. Modern sensors and sophisticated perception algorithms extract rich 3D textured information, but are limited to the data that are collected from a given location or path. We are interested in closing the loop around perception and planning, in particular to plan paths for better perceptual data, and focus on the problem of planning scanning sequences to improve object classification from range data. We formulate a novel time-constrained active classification problem and propose solution algorithms that employ a variation of Monte Carlo tree search to plan non-myopically. Our algorithms use a particle filter combined with Gaussian process regression to estimate joint distributions of object class and pose. This estimator is used in planning to generate a probabilistic belief about the state of objects in a scene, and also to generate beliefs for predicted sensor observations from future viewpoints. These predictions consider occlusions arising from predicted object positions and shapes. We evaluate our algorithms in simulation, in comparison to passive and greedy strategies. We also describe similar experiments where the algorithms are implemented online, using a mobile ground robot in a farm environment. Results indicate that our non-myopic approach outperforms both passive and myopic strategies, and clearly show the benefit of active perception for outdoor object classification.

Paull, NJ, Irga, PJ & Torpy, FR 2018, 'Active green wall plant health tolerance to diesel smoke exposure', Environmental Pollution, vol. 240, pp. 448-456.
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© 2018 Elsevier Ltd Poor air quality is an emerging world-wide problem, with most urban air pollutants arising from vehicular emissions. As such, localized high pollution environments, such as traffic tunnels pose a significant health risk. Phytoremediation, including the use of active (ventilated) green walls or botanical biofilters, is gaining recognition as a potentially effective method for air pollution control. Research to date has tested the capacity of these systems to remove low levels of pollutants from indoor environments. If botanical biofilters are to be used in highly polluted environments, the plants used in these systems must be resilient, however, this idea has received minimal research. Thus, testing was conducted to assess the hardiness of the vegetated component of a botanical biofilter to simulated street level air pollutant exposure. A range of morphological, physiological, and biochemical tests were conducted on 8 common green wall plant species prior to and post 5-week exposure to highly concentrated diesel fuel combustion effluent; as a pilot study to investigate viability in in situ conditions. The results indicated that species within the fig family were the most tolerant species of those assessed. It is likely that species within the fig family can withstand enhanced air pollutant conditions, potentially a result of its leaf morphology and physiology. Other species tested were all moderately tolerant to the pollution treatment. We conclude that most common green wall plant species have the capacity to withstand high pollutant environments, however, extended experimentation is needed to rule out potential long term effects along with potential decreases in filter efficiency from accumulative effects on the substrate. MS capsule summary: The results obtained from the multi-trait plant health assessment provide proof-of-concept that active botanical biozfilters are able to withstand short term, high level pollutant exposure.

Peng, H, Zheng, Y, Blumenstein, M, Tao, D & Li, J 2018, 'CRISPR/Cas9 cleavage efficiency regression through boosting algorithms and Markov sequence profiling', Bioinformatics, vol. 34, no. 18, pp. 3069-3077.
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AbstractMotivationCRISPR/Cas9 system is a widely used genome editing tool. A prediction problem of great interests for this system is: how to select optimal single-guide RNAs (sgRNAs), such that its cleavage efficiency is high meanwhile the off-target effect is low.ResultsThis work proposed a two-step averaging method (TSAM) for the regression of cleavage efficiencies of a set of sgRNAs by averaging the predicted efficiency scores of a boosting algorithm and those by a support vector machine (SVM). We also proposed to use profiled Markov properties as novel features to capture the global characteristics of sgRNAs. These new features are combined with the outstanding features ranked by the boosting algorithm for the training of the SVM regressor. TSAM improved the mean Spearman correlation coefficiencies comparing with the state-of-the-art performance on benchmark datasets containing thousands of human, mouse and zebrafish sgRNAs. Our method can be also converted to make binary distinctions between efficient and inefficient sgRNAs with superior performance to the existing methods. The analysis reveals that highly efficient sgRNAs have lower melting temperature at the middle of the spacer, cut at 5’-end closer parts of the genome and contain more ‘A’ but less ‘G’ comparing with inefficient ones. Comprehensive further analysis also demonstrates that our tool can predict an sgRNA’s cutting efficiency with consistently good performance no matter it is expressed from an U6 promoter in cells or from a T7 promoter in vitro.Availability and implementationOnline tool is available at http://www.aai-bioinfo.com/CRISPR/. Python and Matlab source codes are freely available at https://github.com/penn-hui/TSAM.Supplementary information

Peng, H, Zheng, Y, Zhao, Z, Liu, T & Li, J 2018, 'Recognition of CRISPR/Cas9 off-target sites through ensemble learning of uneven mismatch distributions', Bioinformatics, vol. 34, no. 17, pp. i757-i765.
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Abstract Motivation CRISPR/Cas9 is driving a broad range of innovative applications from basic biology to biotechnology and medicine. One of its current issues is the effect of off-target editing that should be critically resolved and should be completely avoided in the ideal use of this system. Results We developed an ensemble learning method to detect the off-target sites of a single guide RNA (sgRNA) from its thousands of genome-wide candidates. Nucleotide mismatches between on-target and off-target sites have been studied recently. We confirm that there exists strong mismatch enrichment and preferences at the 5′-end close regions of the off-target sequences. Comparing with the on-target sites, sequences of no-editing sites can be also characterized by GC composition changes and position-specific mismatch binary features. Under this novel space of features, an ensemble strategy was applied to train a prediction model. The model achieved a mean score 0.99 of Aera Under Receiver Operating Characteristic curve and a mean score 0.45 of Aera Under Precision-Recall curve in cross-validations on big datasets, outperforming state-of-the-art methods in various test scenarios. Our predicted off-target sites also correspond very well to those detected by high-throughput sequencing techniques. Especially, two case studies for selecting sgRNAs to cure hearing loss and retinal degeneration partly prove the effectiveness of our method. Availability and implementation The python and matlab version of source codes for detecting off-target sites of a given sgRNA and the supplementary files are...

Peng, L, Dai, X, Liu, Y, Sun, J, Song, S & Ni, B-J 2018, 'Model-based assessment of estrogen removal by nitrifying activated sludge', Chemosphere, vol. 197, pp. 430-437.
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© 2018 Elsevier Ltd Complete removal of estrogens such as estrone (E1), estradiol (E2), estriol (E3) and ethinylestradiol (EE2) in wastewater treatment is essential since their release and accumulation in natural water bodies are giving rise to environment and health issues. To improve our understanding towards the estrogen bioremediation process, a mathematical model was proposed for describing estrogen removal by nitrifying activated sludge. Four pathways were involved in the developed model: i) biosorption by activated sludge flocs; ii) cometabolic biodegradation linked to ammonia oxidizing bacteria (AOB) growth; iii) non-growth biodegradation by AOB; and iv) biodegradation by heterotrophic bacteria (HB). The degradation kinetics was implemented into activated sludge model (ASM) framework with consideration of interactions between substrate update and microorganism growth as well as endogenous respiration. The model was calibrated and validated by fitting model predictions against two sets of batch experimental data under different conditions. The model could satisfactorily capture all the dynamics of nitrogen, organic matters (COD), and estrogens. Modeling results suggest that for E1, E2 and EE2, AOB-linked biodegradation is dominant over biodegradation by HB at all investigated COD dosing levels. However, for E3, the increase of COD dosage triggers a shift of dominant pathway from AOB biodegradation to HB biodegradation. Adsorption becomes the main contributor to estrogen removal at high biomass concentrations.

Peng, L, Dai, X, Liu, Y, Wei, W, Sun, J, Xie, G-J, Wang, D, Song, S & Ni, B-J 2018, 'Kinetic assessment of simultaneous removal of arsenite, chlorate and nitrate under autotrophic and mixotrophic conditions', Science of The Total Environment, vol. 628-629, pp. 85-93.
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© 2018 In this work, a kinetic model was proposed to evaluate the simultaneous removal of arsenite (As (III)), chlorate (ClO3−) and nitrate (NO3−) in a granule-based mixotrophic As (III) oxidizing bioreactor for the first time. The autotrophic kinetics related to growth-linked As (III) oxidation and ClO3− reduction by As (III) oxidizing bacteria (AsOB) were calibrated and validated based on experimental data from batch test and long-term reactor operation under autotrophic conditions. The heterotrophic kinetics related to non-growth linked As (III) oxidation and ClO3− reduction by heterotrophic bacteria (HB) were evaluated based on the batch experimental data under heterotrophic conditions. The existing kinetics related to As (III) oxidation with NO3− as the electron acceptor together with heterotrophic denitrification were incorporated into the model framework to assess the bioreactor performance in treatment of the three co-occurring contaminants. The results revealed that under autotrophic conditions As (III) was completely oxidized by AsOB (over 99%), while ClO3− and NO3− were poorly removed. Under mixotrophic conditions, the simultaneous removal of the three contaminants was achieved with As (III) oxidized mostly by AsOB and ClO3− and NO3− removed mostly by HB. Both hydraulic retention time (HRT) and influent organic matter (COD) concentration significantly affected the removal efficiency. Above 90% of As (III), ClO3− and NO3− were removed in the mixotrophic bioreactor under optimal operational conditions of HRT and influent COD.

Peng, L, Ngo, HH, Guo, WS, Liu, Y, Wang, D, Song, S, Wei, W, Nghiem, LD & Ni, BJ 2018, 'A novel mechanistic model for nitrogen removal in algal-bacterial photo sequencing batch reactors', Bioresource Technology, vol. 267, pp. 502-509.
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© 2018 Elsevier Ltd A comprehensive mathematical model was constructed to evaluate the complex substrate and microbial interaction in algal-bacterial photo sequencing batch reactors (PSBR). The kinetics of metabolite, growth and endogenous respiration of ammonia oxidizing bacteria, nitrite oxidizing bacteria and heterotrophic bacteria were coupled to those of microalgae and then embedded into widely-used activated sludge model series. The impact of light intensity was considered for microalgae growth, while the effect of inorganic carbon was considered for each microorganism. The integrated model framework was assessed using experimental data from algal-bacterial consortia performing sidestream nitritation/denitritation. The validity of the model was further evaluated based on dataset from PSBR performing mainstream nitrification. The developed model could satisfactorily capture the dynamics of microbial populations and substrates under different operational conditions (i.e. feeding, carbon dosing and illuminating mode, light intensity, influent ammonium concentration), which might serve as a powerful tool for optimizing the novel algal-bacterial nitrogen removal processes.

Peng, S, Zhou, Y, Cao, L, Yu, S, Niu, J & Jia, W 2018, 'Influence analysis in social networks: A survey', Journal of Network and Computer Applications, vol. 106, pp. 17-32.
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Complementary to the fancy applications of social networks, influence analysis is an indispensable technique supporting these practical applications. In recent years, this emerging research branch has obtained significant attention from both industry and academia. In this new territory, researchers are facing many unprecedented theoretical and practical challenges. Thus, in this survey, we aim to pave a comprehensive and solid starting ground for interested readers by soliciting the latest work in this area. Firstly, we provide an overview of social networks, including definition, and types of social networks. Secondly, we present the current understanding of social influence analysis from different levels, such as its definition, properties, architecture, applications, and diffusion models. Thirdly, we discuss the evaluation metrics for social influence. Fourthly, we summarize the existing evaluation models on social influence in social networks. We further provide an overview of the existing methods for influence maximization. Finally, we discuss the problems of current algorithms and future trends from various perspectives in this field. We hope this work will shed light for more and more forthcoming researchers to further explore the uncharted part of this promising research field.

Pettit, T, Irga, PJ & Torpy, FR 2018, 'Towards practical indoor air phytoremediation: A review', Chemosphere, vol. 208, pp. 960-974.
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© 2018 Elsevier Ltd Indoor air quality has become a growing concern due to the increasing proportion of time people spend indoors, combined with reduced building ventilation rates resulting from an increasing awareness of building energy use. It has been well established that potted-plants can help to phytoremediate a diverse range of indoor air pollutants. In particular, a substantial body of literature has demonstrated the ability of the potted-plant system to remove volatile organic compounds (VOCs) from indoor air. These findings have largely originated from laboratory scale chamber experiments, with several studies drawing different conclusions regarding the primary VOC removal mechanism, and removal efficiencies. Advancements in indoor air phytoremediation technology, notably active botanical biofilters, can more effectively reduce the concentrations of multiple indoor air pollutants through the action of active airflow through a plant growing medium, along with vertically aligned plants which achieve a high leaf area density per unit of floor space. Despite variable system designs, systems available have clear potential to assist or replace existing mechanical ventilation systems for indoor air pollutant removal. Further research is needed to develop, test and confirm their effectiveness and safety before they can be functionally integrated in the broader built environment. The current article reviews the current state of active air phytoremediation technology, discusses the available botanical biofiltration systems, and identifies areas in need of development.

Pham, TM, Farrell, R, Dooley, J, Dutkiewicz, E, Nguyen, DN & Tran, L-N 2018, 'Efficient Zero-Forcing Precoder Design for Weighted Sum-Rate Maximization With Per-Antenna Power Constraint', IEEE Transactions on Vehicular Technology, vol. 67, no. 4, pp. 3640-3645.
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© 1967-2012 IEEE. This paper proposes an efficient (semi-closed-form) zero-forcing (ZF) precoder design for the weighted sum-rate maximization problem under per-antenna power constraint (PAPC). Existing approaches for this problem are based on either interior-point methods that do not favorably scale with the problem size or subgradient methods that are widely known to converge slowly. To address these shortcomings, our proposed method is derived from three elements: minimax duality, alternating optimization (AO), and successive convex approximation (SCA). Specifically, the minimax duality is invoked to transform the considered problem into an equivalent minimax problem, for which we then recruit AO and SCA to find a saddle point, which enables us to take advantages of closed-form expressions and hence achieve fast convergence rate. Moreover, the complexity of the proposed method scales linearly with the number of users, compared to cubically for the standard interior-point methods. We provide an analytical proof for the convergence of the proposed method and numerical results to demonstrate its superior performance over existing approaches. Our proposed method offers a powerful tool to characterize the achievable rate region of ZF schemes under PAPC for massive multiple-input multiple-output.

Pham, TT, Nguyen, DN, Dutkiewicz, E, Center, JR, Eisman, JA & Nguyen, TV 2018, 'A profiling analysis of contributions of cigarette smoking, dietary calcium intakes, and physical activity to fragility fracture in the elderly', Scientific Reports, vol. 8, no. 1.
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AbstractFragility fracture and bone mineral density (BMD) are influenced by common and modifiable lifestyle factors. In this study, we sought to define the contribution of lifestyle factors to fracture risk by using a profiling approach. The study involved 1683 women and 1010 men (50+ years old, followed up for up to 20 years). The incidence of new fractures was ascertained by X-ray reports. A “lifestyle risk score” (LRS) was derived as the weighted sum of effects of dietary calcium intake, physical activity index, and cigarette smoking. Each individual had a unique LRS, with higher scores being associated with a healthier lifestyle. Baseline values of lifestyle factors were assessed. In either men or women, individuals with a fracture had a significantly lower age-adjusted LRS than those without a fracture. In men, each unit lower in LRS was associated with a 66% increase in the risk of total fracture (non-adjusted hazard ratio [HR] 1.66; 95% CI, 1.26 to 2.20) and still significant after adjusting for age, weight or BMD. However, in women, the association was uncertain (HR 1.30; 95% CI, 1.11 to 1.53). These data suggest that unhealthy lifestyle habits are associated with an increased risk of fracture in men, but not in women, and that the association is mediated by BMD.

Pham, VVH, Yu, S, Sood, K & Cui, L 2018, 'Privacy issues in social networks and analysis: a comprehensive survey', IET Networks, vol. 7, no. 2, pp. 74-84.
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Social networks have become part of today's life; however, they also create numerous privacy problems for their users as they reveal sensitive information. Thus, the privacy preservation has become a big problem in social networks and there are several researches related to this topic. However, the current research achievements for this issue are only ad hoc solutions and the broad picture of the problem is not clear. This paper surveys a wide range of related researches and realises that the topic includes many sub-areas; for example, the privacy in publishing social network data for the use of third-party consumers or the privacy of users in the leakage of individuals' information to unexpected people in their social circle. The study also analyses the advantages as well as limitations of proposed solutions. On the basis of that the research outlines key outstanding issues and recommends directions for the future research. Moreover, the research also investigates common privacy metrics and popular privacy-preserving techniques to provide readers some basic tools to resolve open problems in the topic. The ultimate purpose of this research is to pave a solid background for people, who are interested in the topic, to do research further.

Phan, HV, Wickham, R, Xie, S, McDonald, JA, Khan, SJ, Ngo, HH, Guo, W & Nghiem, LD 2018, 'The fate of trace organic contaminants during anaerobic digestion of primary sludge: A pilot scale study', Bioresource Technology, vol. 256, pp. 384-390.
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© 2018 A pilot-scale study was conducted to investigate the fate of trace organic contaminants (TrOCs) during anaerobic digestion of primary sludge. Of the 44 TrOCs monitored, 24 were detected in all primary sludge samples. Phase distribution of TrOCs was correlated well with their hydrophobicity (>67% mass in the solid phase when LogD > 1.5). The pilot-scale anaerobic digester achieved a steady performance with a specific methane yield of 0.39–0.92 L/gVSremoved and methane composition of 63–65% despite considerable variation in the primary sludge. The fate of TrOCs in the aqueous and solid phases was governed by their physicochemical properties. Biotransformation was significant (>83%) for five TrOCs with logD < 1.5 and electron donating functional groups in molecular structure. The remaining TrOCs with logD < 1.5 were persistent and thus accumulated in the aqueous phase. Most TrOCs with logD > 1.5 were poorly removed under anaerobic conditions. Sorption onto the solid phase appears to impede the biodegradation of these TrOCs.

Phwan, CK, Ong, HC, Chen, W-H, Ling, TC, Ng, EP & Show, PL 2018, 'Overview: Comparison of pretreatment technologies and fermentation processes of bioethanol from microalgae', Energy Conversion and Management, vol. 173, pp. 81-94.
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Pileggi, SF 2018, 'Looking deeper into academic citations through network analysis: popularity, influence and impact', Universal Access in the Information Society, vol. 17, no. 3, pp. 541-548.
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© 2017 Springer-Verlag GmbH Germany Google Scholar (GS) has progressively emerged as a tool which “provides a simple way to broadly search for scholarly literature across many disciplines and sources.” As a free tool that provides citation metrics, GS has opened the academic word to a much larger audience, according to an open information philosophy. GS’ profiles are largely used not only to have a quick look at the authors and their works but, more and more often, as a “de facto” metric to quickly evaluate the research impact. This process looks unstoppable and discussing about its fairness, advantages and disadvantages, as well as about social implications is out of the scope of this paper. We rather prefer to (1) briefly discuss the changes and the innovation that GS has introduced and to (2) propose possible improvements for analysis on academic citations. Our methods are aimed at considering a GS profile in its proper context, providing a social perspective on academic citations: Although maintaining a fundamentally quantitative focus, novel approaches, based on complex network analysis, distinguish between a research impact on the authors’ research network and a more general impact on the scientific community.

Pinho, AV, Van Bulck, M, Chantrill, L, Arshi, M, Sklyarova, T, Herrmann, D, Vennin, C, Gallego-Ortega, D, Mawson, A, Giry-Laterriere, M, Magenau, A, Leuckx, G, Baeyens, L, Gill, AJ, Phillips, P, Timpson, P, Biankin, AV, Wu, J & Rooman, I 2018, 'ROBO2 is a stroma suppressor gene in the pancreas and acts via TGF-β signalling', Nature Communications, vol. 9, no. 1.
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AbstractWhereas genomic aberrations in the SLIT-ROBO pathway are frequent in pancreatic ductal adenocarcinoma (PDAC), their function in the pancreas is unclear. Here we report that in pancreatitis and PDAC mouse models, epithelial Robo2 expression is lost while Robo1 expression becomes most prominent in the stroma. Cell cultures of mice with loss of epithelial Robo2 (Pdx1Cre;Robo2F/F) show increased activation of Robo1+ myofibroblasts and induction of TGF-β and Wnt pathways. During pancreatitis, Pdx1Cre;Robo2F/F mice present enhanced myofibroblast activation, collagen crosslinking, T-cell infiltration and tumorigenic immune markers. The TGF-β inhibitor galunisertib suppresses these effects. In PDAC patients, ROBO2 expression is overall low while ROBO1 is variably expressed in epithelium and high in stroma. ROBO2low;ROBO1high patients present the poorest survival. In conclusion, Robo2 acts non-autonomously as a stroma suppressor gene by restraining myofibroblast activation and T-cell infiltration. ROBO1/2 expression in PDAC patients may guide therapy with TGF-β inhibitors or other stroma /immune modulating agents.

Piorkowski, D, Blackledge, TA, Liao, C, Doran, NE, Wu, C, Blamires, SJ & Tso, I 2018, 'Humidity‐dependent mechanical and adhesive properties of Arachnocampa tasmaniensis capture threads', Journal of Zoology, vol. 305, no. 4, pp. 256-266.
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AbstractBioluminescent glow‐worms (Arachnocampa spp.) capture prey in glue‐coated silk capture threads hung from their nests on damp cave and wet forest substrates. In a dry environment, these animals are very susceptible to desiccation as their bodies can become life threateningly dry and their silk has been anecdotally observed to become non‐sticky. Water has a plasticizing effect on the structural proteins of several invertebrate silks, including those used in caddisfly nets, mussel byssus and spider webs. Moreover, water facilitates interfacial adhesion by spreading adhesive biomolecules in functionally analogous velvet worm slime and spider silk glue. We tested the effects of water on the mechanics and adhesion of Arachnocampa tasmaniensis capture threads sampled within damp caves. We found that threads tested at high humidity were three times more compliant and over 10‐fold more extensible than those tested at low humidity (30% RH). We also found the threads to be significantly more adhesive in high humidity with force at detachment increasing two orders of magnitude and work of adhesion increasing by five orders of magnitude compared to threads tested at low humidity. Our results unequivocally demonstrate that A. tasmaniensis capture thread functionality is dependent upon exposure to high humidity. Our results both confirm previous reports and indicate that the foraging habitat of these animals is restricted to caves and cave‐like environments, such as wet forests.

Piorkowski, D, Blamires, SJ, Doran, NE, Liao, C, Wu, C & Tso, I 2018, 'Ontogenetic shift toward stronger, tougher silk of a web‐building, cave‐dwelling spider', Journal of Zoology, vol. 304, no. 2, pp. 81-89.
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AbstractAnimal morphological traits may vary across life stages. Web‐building spiders are diverse insectivores that can display ontogenetic shifts in the design and properties of their webs. Nevertheless, we know little about how a critical component of their webs, major ampullate silk (MAS), varies in property across life stages, inferably owing to a difficulty in finding suitable model species. The Tasmanian cave spider Hickmania troglodytes presents as a good model as it is long‐lived and grows to a large body size with overlapping generations. We collected MAS from the webs of different‐sized H. troglodytes and performed tensile tests on MAS fibers collected from their webs to search for shifts in properties over life stages. We found that strength and toughness (i.e. ability to deform and absorb energy) of the MAS increased with spider carapace width and body length. We expect that such a shift in silk performance across life stages has distinctive advantages, including enhanced prey capture capabilities, an improvement in the economy of silk production and ability of the web to support the spider's larger body.

Pitsis, A, Clegg, S, Freeder, D, Sankaran, S & Burdon, S 2018, 'Megaprojects redefined – complexity vs cost and social imperatives', International Journal of Managing Projects in Business, vol. 11, no. 1, pp. 7-34.
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PurposeThe purpose of this paper is to provide a brief overview from the literature on how best to define megaprojects in contemporary contexts. There is a need for a definition that encompasses a complex matrix of characteristics, inclusive of positive and negative aspects, which are not necessarily industry or sector specific. Whilst megaprojects have often been described and defined in terms of cost, they are more accurately delineated by their convolutions. Intricacies arise from political intrigues surrounding funding of such projects and managing and governing complex social and organizational relations. Points for future research are also identified.Design/methodology/approachAn analysis of international megaproject literature over the past five years combined with seminal works was undertaken, drawing on the broad literature of project and program management combined with elements of organizational theory. Whilst some examples are cited, in-depth case analysis has not been covered.FindingsAlbeit that the scale of some megaprojects is comparable to national GDPs, seven more characteristics beyond size have been identified, which distinguish megaprojects from large projects. These include: reach; duration; risks and uncertainties; widely disparate actors; areas of controversy such as dispute resolution; and legal and regulatory issues.Research limitations/implicationsThe paper takes a broad overview and whilst some examples are cited, in-depth case analysis has not been covered. The overview does however provide a good synopsis of the future research areas that warrant...

Plattner, J, Kazner, C, Naidu, G, Wintgens, T & Vigneswaran, S 2018, 'Removal of selected pesticides from groundwater by membrane distillation', Environmental Science and Pollution Research, vol. 25, no. 21, pp. 20336-20347.
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© 2017, Springer-Verlag Berlin Heidelberg. The removal of five selected pesticide compounds in a brackish model groundwater solution was examined using a bench scale direct contact membrane distillation (DCMD) system. It was found that the rejection rate of the pesticides in DCMD is mainly influenced by its properties. Compounds with low hydrophobic characteristics and low vapour pressure showed a high rejection rate (70–99%), whereas compounds with a high vapour pressure or high hydrophobicity (LogD) showed a reduced rejection (30–50%) at a water recovery of 75%. The influence of groundwater feed solution contents such as the presence of organics (humic acid) and inorganic ions (Na+, Ca2+, Mg2+, Cl− and SO42−) as well as feed temperature (40, 55 and 70 °C) on the rejection of the pesticides in DCMD operation was also evaluated. The results showed that the presence of inorganic ions and organics in the feed solution influences the pesticides rejection in DCMD operation to a minor degree. In contrast, reduced rejection of pesticides with high vapour pressure was observed. A rapid small-scale column test (RSSCT) was carried out to study the removal of any remaining substances in the permeate by adsorption onto granular activated carbon (GAC). RSSCT showed promising performance of GAC as a post-treatment option.

Ploderer, B & Leong, TW 2018, 'Manual engagement and automation in amateur photography', Media International Australia, vol. 166, no. 1, pp. 44-56.
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Automation has been central to the development of modern photography and, in the age of digital and smartphone photography, now largely defines everyday experience of the photographic process. In this article, we question the acceptance of automation as the default position for photography, arguing that discussions of automation need to move beyond binary concerns of whether to automate or not and, instead, to consider what is being automated and the degree of automation couched within the particularities of people’s practices. We base this upon findings from ethnographic fieldwork with people engaging manually with film-based photography. While automation liberates people from having to interact with various processes of photography, participants in our study reported a greater sense of control, richer experiences and opportunities for experimentation when they were able to engage manually with photographic processes.

Pourghasemi, HR, Teimoori Yansari, Z, Panagos, P & Pradhan, B 2018, 'Analysis and evaluation of landslide susceptibility: a review on articles published during 2005–2016 (periods of 2005–2012 and 2013–2016)', Arabian Journal of Geosciences, vol. 11, no. 9.
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© 2018, Saudi Society for Geosciences. Landslides are one of the most important environmental hazards occur naturally or human-induced with large-scale social, economic, and environmental impacts. Landslide susceptibility zoning, which has been widely performed in the last decades, allows identifying spatial prediction of areas of landslides, which could be used for land use planning and land management. The present study was conducted as a review with the aim of investigating the research background of landslide susceptibility in the world during the period of 2005–2016. The results showed that the publication of papers related to landslide susceptibility during the period of investigation has been on the rise, and China has produced a larger number of papers and authors (13% of total). In addition, this article reviews the most popularly used models and the most frequently used input factors. Among different models, the logistic regression has been used as the most common method for assessing landslide susceptibility in 28.4% of the articles, and the slope gradient is considered as the most important conditioning factor in landslide occurrence in 94.2% of the articles. Finally, it is concluded that the recent technological developments in the field of remote sensing, computing technologies and Geographic Information Systems (GIS), the increased data availability, and the awareness has arisen among media and recent policy developments are important elements for increasing the research interest in landslide susceptibility.

Pourreza, P, Saberi, M, Azadeh, A, Chang, E & Hussain, O 2018, 'Health, Safety, Environment and Ergonomic Improvement in Energy Sector Using an Integrated Fuzzy Cognitive Map–Bayesian Network Model', International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1346-1356.
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© 2018, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. Health, safety, environment and ergonomics (HSEE) are important factors for any organization. In fact, organizations always have to assess their compliance in these factors to the required benchmarks and take proactive actions to improve them if required. In this paper, we propose a fuzzy cognitive map–Bayesian network (BN) model in order to assist organizations in undertaking this process. The fuzzy cognitive map (FCM) method is used for constructing graphical models of BN to ascertain the relationships between the inputs and the impact which they will have on the quantified HSEE. Using the notion of Fuzzy logic assists us to work with humans and their linguistic inputs in the process of experts’ opinion solicitation. The noisy-OR method and the EM are used to ascertain the conditional probability between the inputs and quantifying the HSEE value. Using this, we find out that the most influential input factor on HSEE quantification which can then be managed for improving an organization’s compliance to HSEE. Finding the same influential input factor in both BN models which are based on the noisy-OR method and EM demonstrate how FCM is useful in constructing a reliable BN model. Leveraging the power of Bayesian network in modelling HSEE and augmenting it with FCM is the main contribution of this research work which opens the new line of research in the area of HSE management.

Pradeepkumar, A, Zielinski, M, Bosi, M, Verzellesi, G, Gaskill, DK & Iacopi, F 2018, 'Electrical leakage phenomenon in heteroepitaxial cubic silicon carbide on silicon', Journal of Applied Physics, vol. 123, no. 21, pp. 215103-215103.
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Heteroepitaxial 3C-SiC films on silicon substrates are of technological interest as enablers to integrate the excellent electrical, electronic, mechanical, thermal, and epitaxial properties of bulk silicon carbide into well-established silicon technologies. One critical bottleneck of this integration is the establishment of a stable and reliable electronic junction at the heteroepitaxial interface of the n-type SiC with the silicon substrate. We have thus investigated in detail the electrical and transport properties of heteroepitaxial cubic silicon carbide films grown via different methods on low-doped and high-resistivity silicon substrates by using van der Pauw Hall and transfer length measurements as test vehicles. We have found that Si and C intermixing upon or after growth, particularly by the diffusion of carbon into the silicon matrix, creates extensive interstitial carbon traps and hampers the formation of a stable rectifying or insulating junction at the SiC/Si interface. Although a reliable p-n junction may not be realistic in the SiC/Si system, we can achieve, from a point of view of the electrical isolation of in-plane SiC structures, leakage suppression through the substrate by using a high-resistivity silicon substrate coupled with deep recess etching in between the SiC structures.

Pradhan, B, Jung, H-S & Beydoun, G 2018, 'Systems and Sensors in Geoscience Applications.', J. Sensors, vol. 2018, pp. 7242495:1-7242495:1.
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Pradhan, B, Moneir, AAA & Jena, R 2018, 'Sand dune risk assessment in Sabha region, Libya using Landsat 8, MODIS, and Google Earth Engine images', Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 1280-1305.
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Globally, sand dunes are a major environmental problem that causes damage to urban areas, transportation, and population. The current study proposes a comprehensive investigation on sand dune risk modeling in Sabha located in the southwestern part of Libya. Data from various sources were collected and prepared in a GIS database. Data from 2016 were used to derive several controlling factors, such as altitude, rainfall, soil texture, wind direction and speed, land cover, and population density. Next, sand dune susceptibility, hazard and vulnerability assessments were performed. Finally, a risk map was produced. Results indicate that land use and soil are the most influential factors affecting the sand dunes in the study area, whereas rainfall is the least significant factor. Results indicate that, southern part has a higher chance of sand dune occurrence than the northern part, whereas the highest risk zone is located in the middle part, where the urban and agricultural lands are present. More than 200 km2 of the study area are under high and very high risk zones. Overall, this study provides an effective tool for assessing sand dune risk in Sabha, which can be useful for land management.

Pradhan, B, Rizeei, HM & Abdulle, A 2018, 'Quantitative Assessment for Detection and Monitoring of Coastline Dynamics with Temporal RADARSAT Images', Remote Sensing, vol. 10, no. 11, pp. 1705-1705.
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This study aims to detect coastline changes using temporal synthetic aperture radar (SAR) images for the state of Kelantan, Malaysia. Two active images, namely, RADARSAT-1 captured in 2003 and RADARSAT-2 captured in 2014, were used to monitor such changes. We applied noise removal and edge detection filtering on RADARSAT images for preprocessing to remove salt and pepper distortion. Different segmentation analyses were also applied to the filtered images. Firstly, multiresolution segmentation, maximum spectral difference and chessboard segmentation were performed to separate land pixels from ocean ones. Next, the Taguchi method was used to optimise segmentation parameters. Subsequently, a support vector machine algorithm was applied on the optimised segments to classify shorelines with an accuracy of 98% for both temporal images. Results were validated using a thematic map from the Department of Survey and Mapping of Malaysia. The change detection showed an average difference in the shoreline of 12.5 m between 2003 and 2014. The methods developed in this study demonstrate the ability of active SAR sensors to map and detect shoreline changes, especially during low or high tides in tropical regions where passive sensor imagery is often masked by clouds.

Pratihast, M, Al‐Ani, A, Chai, R, Su, S & Naik, G 2018, 'Changes in lower limb muscle synchronisation during walking on high‐heeled shoes', Healthcare Technology Letters, vol. 5, no. 6, pp. 236-238.
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The goal of this research was to investigate the effect of wearing high‐heeled shoes (HHS) on lower limb muscle synchronisation during walking, using beta band (15–30 Hz) coherence analysis. Fifteen females with no previous neuromuscular disorders volunteered in this study. Surface electromyography in frequency domain was studied from rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM) and semitendinosus (ST) muscles during walking by subjects wearing HHS of three different heel heights (low – 4 cm, medium – 6 cm and high – 10 cm). Average coherence values were calculated for RF‐VL, RF‐VM and RF‐ST muscles in beta band to analyse muscle pair synchronisation. In this study, significant increase in beta band coherence was found in all three muscle pairs during walking on HHS of different heel heights (p<0.05). Increased beta band coherence obtained from this study suggested that walking on HHS demands higher muscle pair synchronisation, to maintain stability around the knee joint.

Praveena, SM, Pradhan, B & Aris, AZ 2018, 'Assessment of bioavailability and human health exposure risk to heavy metals in surface soils (Klang district, Malaysia)', Toxin Reviews, vol. 37, no. 3, pp. 196-205.
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In urban area surface soil the heavy metal concentrations followed the order: Pb (76.15 mg/kg) > Fe (12.96 mg/kg) > Cu (11.58 mg/kg) > Al (10.3 mg/kg) > Zn (6.42 mg/kg) > Co (0.21 mg/kg) > Cd (0.18 mg/kg) > Cr (0.07 mg/kg). For the industrial area surface soil, heavy metal concentrations followed the sequence: Pb (55.28 mg/kg) > Al (15.5 mg/kg) > Fe (14.73 mg/kg)> Cu (14.68 mg/kg) > Zn (4.48 mg/kg) > Co (0.26 mg/kg) > Cr (0.11 mg/kg) > Cd (0.11 mg/kg). PCA output showed that the first and second principal components are attributed due to the presence of “urban metals” in the urban areas while third principal component reflects the anthropogenic factor in the industrial areas. Total Cancer Risk values are more than the incremental lifetime (1.0E − 05), showing the likelihood of a cancer threat for adults and children. For non-carcinogenic risks, Hazard Index values <1 one indicating no potential risks.

Pruitt, K & Shannon, AG 2018, 'Modular class primes in the Sundaram sieve', International Journal of Mathematical Education in Science and Technology, vol. 49, no. 6, pp. 944-947.
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© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The purpose of this paper is to consider analogues of the twin-prime conjecture in various classes within modular rings.

Pupatwibul, P, Banjar, A, Hossain, I, Braun, R & Moulton, B 2018, 'A novel software-defined networking controller: The Distributed Active Information Model (DAIM)', International Journal of Electronics and Telecommunications, vol. 64, no. 2, pp. 209-216.
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This paper presents a new OpenFlow controller: the Distributed Active Information Model (DAIM). The DAIM controller was developed to explore the viability of a logically distributed control plane. It is implemented in a distributed way throughout a software-defined network, at the level of the switches. The method enables local process flows, by way of local packet switching, to be controlled by the distributed DAIM controller (as opposed to a centralised OpenFlow controller). The DAIM ecosystem is discussed with some sample code, together with flowcharts of the implemented algorithms. We present implementation details, a testing methodology, and an experimental evaluation. A performance analysis was conducted using the Cbench open benchmarking tool. Comparisons were drawn with respect to throughput and latency. It is concluded that the DAIM controller can handle a high throughput, while keeping the latency relatively low. We believe the results to date are potentially very interesting, especially in light of the fact that a key feature of the DAIM controller is that it is designed to enable the future development of autonomous local flow process and management strategies.

Puthal, D, Obaidat, MS, Nanda, P, Prasad, M, Mohanty, SP & Zomaya, AY 2018, 'Secure and Sustainable Load Balancing of Edge Data Centers in Fog Computing', IEEE Communications Magazine, vol. 56, no. 5, pp. 60-65.
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© 1979-2012 IEEE. Fog computing is a recent research trend to bring cloud computing services to network edges. EDCs are deployed to decrease the latency and network congestion by processing data streams and user requests in near real time. EDC deployment is distributed in nature and positioned between cloud data centers and data sources. Load balancing is the process of redistributing the work load among EDCs to improve both resource utilization and job response time. Load balancing also avoids a situation where some EDCs are heavily loaded while others are in idle state or doing little data processing. In such scenarios, load balancing between the EDCs plays a vital role for user response and real-Time event detection. As the EDCs are deployed in an unattended environment, secure authentication of EDCs is an important issue to address before performing load balancing. This article proposes a novel load balancing technique to authenticate the EDCs and find less loaded EDCs for task allocation. The proposed load balancing technique is more efficient than other existing approaches in finding less loaded EDCs for task allocation. The proposed approach not only improves efficiency of load balancing; it also strengthens the security by authenticating the destination EDCs.

Qi, H, Niu, L, Zhang, J, Chen, J, Wang, S, Yang, J, Guo, S, Lawson, T, Shi, B & Song, C 2018, 'Large-area gold nanohole arrays fabricated by one-step method for surface plasmon resonance biochemical sensing', Science China Life Sciences, vol. 61, no. 4, pp. 476-482.
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Qi, Y, Indraratna, B & Vinod, JS 2018, 'Behavior of Steel Furnace Slag, Coal Wash, and Rubber Crumb Mixtures with Special Relevance to Stress–Dilatancy Relation', Journal of Materials in Civil Engineering, vol. 30, no. 11, pp. 04018276-04018276.
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Qi, Y, Indraratna, B, Heitor, A & Vinod, J 2018, 'Effect of Rubber Crumbs on the Cyclic Behaviour of Steel Furnace Slag and Coal Wash Mixtures', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 2.
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Qi, Y, Indraratna, B, Heitor, A & Vinod, JS 2018, 'Effect of Rubber Crumbs on the Cyclic Behavior of Steel Furnace Slag and Coal Wash Mixtures', Journal of Geotechnical and Geoenvironmental Engineering, vol. 144, no. 2, pp. 04017107-04017107.
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The practical application of waste materials such as steel furnace slag (SFS) and coal wash (CW) is becoming more prevalent in many geotechnical projects. While adding rubber crumbs (RCs) from recycled tires into mixtures of SFS and CW not only solves the problem of large stockpiles of waste tires, it also can provide an energy-absorbing medium that will reduce vibration and prevent track degradation. Thus, the engineering insight into the effect that rubber crumbs have on the dynamic behavior of SFS + CW + RC mixtures is in urgent demand. In this study the influence that RC contents and confining pressures have on the deformation, resilient modulus, damping ratio, and shear modulus was investigated by cyclic triaxial tests. Test results reveal that with the inclusion of RC, the axial strain, volumetric strain, damping ratio, and energy-absorbing capacity of the SFS + CW + RC mixture increase, while its resilient modulus and shear modulus decrease. Based on these properties, an amount of 10% RC is recommended as an optimal blended mix to be used as railway subballast. A three-dimensional (3D) empirical model of the relationship between the maximum axial strain, volumetric strain, and resilient modulus with RC contents and the effective confining pressure was developed, and the energy-absorbing capacity of these waste mixtures has also been analyzed for practical purposes based on their comprehensive parameters.

Qin, C, Ni, W, Tian, H, Liu, RP & Guo, YJ 2018, 'Joint Beamforming and User Selection in Multiuser Collaborative MIMO SWIPT Systems With Nonnegligible Circuit Energy Consumption', IEEE Transactions on Vehicular Technology, vol. 67, no. 5, pp. 3909-3923.
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© 1967-2012 IEEE. Multiantenna beamforming has potential to improve the efficiency of simultaneous wireless information and power transfer (SWIPT). Existing designs are focused on the downlink of multiple-input-single-output under the assumption of single-antenna users and negligible energy consumption in users' circuitry, despite the fact that using multiple antennas on the user side can further improve system efficiency. In this paper, novel multiuser collaborative multiple-input multiple-output SWIPT systems are studied under the assumption of nonnegligible circuit energy consumption. Particularly, we convexify and maximize the uplink sum rate of active users, while maintaining the quality of service of their downlink data. The beamformers and durations of both links, and the power splitting factors of individual users are jointly optimized, using semidefinite programming and golden search. Further, the selection of active users is optimized, where all users are assumed to be active in the beginning and those detrimental to the sum-rate maximization are continually deactivated. Evident from simulations, the proposed approaches can eliminate the need for computationally prohibitive combinatorial integer programming at a marginal cost of the sum rate.

Qin, L, Hu, M, Lu, DD-C, Feng, Z, Wang, Y & Kan, J 2018, 'Buck–Boost Dual-Leg-Integrated Step-Up Inverter With Low THD and Single Variable Control for Single-Phase High-Frequency AC Microgrids', IEEE Transactions on Power Electronics, vol. 33, no. 7, pp. 6278-6291.
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© 1986-2012 IEEE. To support the development of high-frequency ac microgrids in terms of compact design, high-voltage gain and low total harmonic distortion (THD), a buck-boost dual-leg-integrated step-up inverter is proposed in this paper. The inverter is formed by integrating a buck-boost converter into a conventional single-phase full-bridge inverter by sharing the upper switch and the body diode of the lower switch in both bridge-legs. Consequently, the component count is significantly reduced over the step-up inverter counterparts. In addition, to address the drawbacks of hybrid modulation methods adopted by existing dual-leg-integrated inverters, such as double-variable control, and high THD of output voltage/current at high input voltage and heavy load conditions, unipolar frequency doubling sinusoidal pulse width modulation scheme is adopted in this inverter. As a result, the modulation ratio M becomes the only control variable to regulate the output voltage/current and the control is simplified. The THD of the proposed inverter output can remain low throughout the entire input voltage range and load power range. This paper presents the topology derivation procedure, operation principle, and steady-state characteristics of the proposed inverter. To validate the effectiveness of theory, experimental results of a 400 W hardware prototype, where the output voltage frequency is at 500 Hz, are reported.

Qin, M, Jin, D, Lei, K, Gabrys, B & Musial-Gabrys, K 2018, 'Adaptive community detection incorporating topology and content in social networks✰', Knowledge-Based Systems, vol. 161, pp. 342-356.
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© 2018 In social network analysis, community detection is a basic step to understand the structure and function of networks. Some conventional community detection methods may have limited performance because they merely focus on the networks’ topological structure. Besides topology, content information is another significant aspect of social networks. Although some state-of-the-art methods started to combine these two aspects of information for the sake of the improvement of community partitioning, they often assume that topology and content carry similar information. In fact, for some examples of social networks, the hidden characteristics of content may unexpectedly mismatch with topology. To better cope with such situations, we introduce a novel community detection method under the framework of non-negative matrix factorization (NMF). Our proposed method integrates topology as well as content of networks and has an adaptive parameter (with two variations) to effectively control the contribution of content with respect to the identified mismatch degree. Based on the disjoint community partition result, we also introduce an additional overlapping community discovery algorithm, so that our new method can meet the application requirements of both disjoint and overlapping community detection. The case study using real social networks shows that our new method can simultaneously obtain the community structures and their corresponding semantic description, which is helpful to understand the semantics of communities. Related performance evaluations on both artificial and real networks further indicate that our method outperforms some state-of-the-art methods while exhibiting more robust behavior when the mismatch between topology and content is observed.

Qin, P, Chen, S & Guo, YJ 2018, 'Recent Advances in Reconfigurable Antennas at University of Technology Sydney', Journal of Communications and Information Networks, vol. 3, no. 1, pp. 15-20.
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Qiu, N, Gao, Y, Fang, J, Sun, G & Kim, NH 2018, 'Topological design of multi-cell hexagonal tubes under axial and lateral loading cases using a modified particle swarm algorithm', Applied Mathematical Modelling, vol. 53, pp. 567-583.
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© 2017 Elsevier Inc. Multi-cell structures have widely been studied due to their excellent energy absorption ability. However, few systematic studies have been conducted on the topological design of cross-sectional configurations of thin-walled tubes. To make full use of the material, topology optimization of multi-cell hexagonal tubes was conducted under both axial compression and lateral bending loadings. A binary particle swarm optimization (PSO) was enhanced by introducing the mass constraint factor to guide the movement of particles, which could improve the success rate of obtaining the global optimum. It was found that the optimum designs under the axial load placed the material outward to strengthen the interaction between the outer and inner walls and created more partitions between the inside rib walls. While under the lateral load, all the optimum designs have diagonally-connected elements to resist local deformation, and the material was also placed outward to increase the moment of inertia and thus to resist the global deformation. For the multiple loading cases, the final optimal designs are similar to the compression designs or combined designs from the two loading cases.

Qiu, N, Gao, Y, Fang, J, Sun, G, Li, Q & Kim, NH 2018, 'Crashworthiness optimization with uncertainty from surrogate model and numerical error', Thin-Walled Structures, vol. 129, pp. 457-472.
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© 2018 Elsevier Ltd Due to the expensive cost of full-scale tests, more and more designs rely on simulation. For highly nonlinear crash simulation, numerical uncertainty is an inherent by-product, which refers to the oscillation of results when the simulation is repeated at the same design or the design variables are slightly changed. This oscillation directly influences the quality and reliability of the optimal design. This paper shows how these issues can be addressed by proposing a simple uncertainty quantification method for numerical uncertainty (noise) and surrogate model uncertainty (error) in the optimization process. Three engineering problems, a tube crush example, an automotive front-rail crush example and a multi-cell structure crush example, are used to illustrate this method. Firstly, the level of numerical uncertainty is quantified in terms of noise frequency and amplitude, and the convergence study of these two criteria is employed to determine an appropriate data size to describe numerical noise. Secondly, an estimation method considering both numerical noise and surrogate model error is proposed based on the prediction variance of the polynomial response surface. Finally, the tube and front rail structures are optimized according to the proposed uncertainty quantification method. It was found that by considering the two sources of uncertainty, the optimal designs are more reliable than the deterministic solutions.

Qiu, N, Park, C, Gao, Y, Fang, J, Sun, G & Kim, NH 2018, 'Sensitivity-Based Parameter Calibration and Model Validation Under Model Error', Journal of Mechanical Design, vol. 140, no. 1, pp. 1-9.
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In calibrating model parameters, it is important to include the model discrepancy term in order to capture missing physics in simulation, which can result from numerical, measurement, and modeling errors. Ignoring the discrepancy may lead to biased calibration parameters and predictions, even with an increasing number of observations. In this paper, a simple yet efficient calibration method is proposed based on sensitivity information when the simulation model has a model error and/or numerical error but only a small number of observations are available. The sensitivity-based calibration method captures the trend of observation data by matching the slope of simulation predictions and observations at different designs and then utilizing a constant value to compensate for the model discrepancy. The sensitivity-based calibration is compared with the conventional least squares calibration method and Bayesian calibration method in terms of parameter estimation and model prediction accuracies. A cantilever beam example, as well as a honeycomb tube crush example, is used to illustrate the calibration process of these three methods. It turned out that the sensitivity-based method has a similar performance with the Bayesian calibration method and performs much better than the conventional method in parameter estimation and prediction accuracy.

Qu, Y, Yu, S, Gao, L, Zhou, W & Peng, S 2018, 'A Hybrid Privacy Protection Scheme in Cyber-Physical Social Networks', IEEE Transactions on Computational Social Systems, vol. 5, no. 3, pp. 773-784.
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© 2014 IEEE. The rapid proliferation of smart mobile devices has significantly enhanced the popularization of the cyber-physical social network, where users actively publish data with sensitive information. Adversaries can easily obtain these data and launch continuous attacks to breach privacy. However, existing works only focus on either location privacy or identity privacy with a static adversary. This results in privacy leakage and possible further damage. Motivated by this, we propose a hybrid privacy-preserving scheme, which considers both location and identity privacy against a dynamic adversary. We study the privacy protection problem as the tradeoff between the users aiming at maximizing data utility with high-level privacy protection while adversaries possessing the opposite goal. We first establish a game-based Markov decision process model, in which the user and the adversary are regarded as two players in a dynamic multistage zero-sum game. To acquire the best strategy for users, we employ a modified state-action-reward-state-action reinforcement learning algorithm. Iteration times decrease because of cardinality reduction from n to 2, which accelerates the convergence process. Our extensive experiments on real-world data sets demonstrate the efficiency and feasibility of the propose method.

Qu, Y, Yu, S, Zhou, W, Peng, S, Wang, G & Xiao, K 2018, 'Privacy of Things: Emerging Challenges and Opportunities in Wireless Internet of Things', IEEE Wireless Communications, vol. 25, no. 6, pp. 91-97.
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© 2002-2012 IEEE. The proliferation of wireless devices and appliances is facilitating the rapid development of the Internet of Things (IoT). Numerous state-of-the-art applications are being used in, for example, smart cities, autonomous vehicles, and biocomputing. With the popularization of IoT, new challenges are emerging with respect to privacy issues. In this article, we first summarize privacy constraints and primary attacks based on new features of IoT. Then we present three case studies to demonstrate principal vulnerabilities and classify existing protection schemes. Built on this analysis, we identify three key challenges: a lack of theoretical foundation, the trade-off optimization between privacy and data utility, and system isomerism over-complexity and high scalability. Finally, we illustrate possible promising future directions and potential solutions to the emerging challenges facing wireless IoT scenarios. We aim to assist interested readers in investigating the unexplored parts of this promising domain.

Quadeer, M, Tomamichel, M & Ferrie, C 2018, 'Minimax quantum state estimation under Bregman divergence', Quantum, vol. 3, p. 126.
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We investigate minimax estimators for quantum state tomography under generalBregman divergences. First, generalizing the work of Komaki et al.$\href{http://dx.doi.org/10.3390/e19110618}{\textrm{[Entropy 19, 618 (2017)]}}$for relative entropy, we find that given any estimator for a quantum state,there always exists a sequence of Bayes estimators that asymptotically performat least as well as the given estimator, on any state. Second, we show thatthere always exists a sequence of priors for which the corresponding sequenceof Bayes estimators is asymptotically minimax (i.e. it minimizes the worst-caserisk). Third, by re-formulating Holevo's theorem for the covariant stateestimation problem in terms of estimators, we find that any covariantmeasurement is, in fact, minimax (i.e. it minimizes the worst-case risk).Moreover, we find that a measurement is minimax if it is only covariant under aunitary 2-design. Lastly, in an attempt to understand the problem of findingminimax measurements for general state estimation, we study the qubit case indetail and find that every spherical 2-design is a minimax measurement.

Qumer Gill, A, Loumish, A, Riyat, I & Han, S 2018, 'DevOps for information management systems', VINE Journal of Information and Knowledge Management Systems, vol. 48, no. 1, pp. 122-139.
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PurposeDevelopment and operations (DevOps) is complex in nature. Organizations are unsure how to effectively establish a DevOps capability for the continuous delivery of information management systems. This paper aims to compile and analyze DevOps by applying the well-known systematic literature review (SLR) approach. This review is intended to provide a knowledge base to support the informed, effective and less risky adoption of DevOps for information management systems.Design/methodology/approachIn this qualitative research study, the SLR method was applied to identify 3,790 papers, of which, 32 relevant papers were selected and reviewed.FindingsThe results are organized using the well-known ISO/IEC 24744 metamodel elements: people (roles), process, technology and artifacts. In total 11 major roles, 6 processes, 23 technologies, 5 artifacts and 7 challenges (including 6 corresponding solutions) were found. DevOps engineer is becoming a newly identified role. Continuous delivery pipeline and continuous improvement are the most highlighted major DevOps processes. Build system technology is becoming the key focus of DevOps. Finally, major challenges are around people and culture and the misunderstanding of DevOps. Potential research areas are: DevOps analytics, artifacts and tool–chain integration.Research limitations/implicationsThe research findings will serve as a resource for both practitioners and researchers who have interest in the research and adoption of DevOps for information management systems.Journal of Environmental Chemical Engineering, vol. 6, no. 5, pp. 5771-5794.
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Carbon capture and storage (CCS) community has been struggling over the past few decades to demonstrate the economic feasibility of CO2 sequestration. Nevertheless, in practice, it has only proven feasible under conditions with a market for the recovered CO2, such as in the beverage industry or enhanced oil/gas recovery. The research community and industry are progressively converging to a conclusion that CO2 sequestration has severe limitations for the value proposition. Alternatively, creating diverse demand markets and revenue streams for the recovered almost-pure CO2 may prevail over CO2 sequestration option and improve the economic feasibility of this climate change mitigation approach. As such, research in the carbon capture and management field is seen to be shifting towards CO2 utilization, directly and indirectly, in energy and chemical industries. In this paper, we have critically reviewed the literature on carbon capture, conversion, and utilization routes and assessed the progress in the research and developments in this direction. Both physical and chemical CO2 utilization pathways are studied and the principles of key routes are identified. The literature is also probed in addressing the process integration scenarios and the performance assessment benchmarks.

Ragazzon, MRP, Ruppert, MG, Harcombe, DM, Fleming, AJ & Gravdahl, JT 2018, 'Lyapunov Estimator for High-Speed Demodulation in Dynamic Mode Atomic Force Microscopy', IEEE Transactions on Control Systems Technology, vol. 26, no. 2, pp. 765-772.
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Rahman, MS, Hossain, MJ, Lu, J & Pota, HR 2018, 'A Need-Based Distributed Coordination Strategy for EV Storages in a Commercial Hybrid AC/DC Microgrid With an Improved Interlinking Converter Control Topology', IEEE Transactions on Energy Conversion, vol. 33, no. 3, pp. 1372-1383.
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Rahman, S, Quin, P, Walsh, T, Vidal-Calleja, T, McPhee, MJ, Toohey, E & Alempijevic, A 2018, 'Preliminary estimation of fat depth in the lamb short loin using a hyperspectral camera', Animal Production Science, vol. 58, no. 8, pp. 1488-1488.
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The objectives of the present study were to describe the approach used for classifying surface tissue, and for estimating fat depth in lamb short loins and validating the approach. Fat versus non-fat pixels were classified and then used to estimate the fat depth for each pixel in the hyperspectral image. Estimated reflectance, instead of image intensity or radiance, was used as the input feature for classification. The relationship between reflectance and the fat/non-fat classification label was learnt using support vector machines. Gaussian processes were used to learn regression for fat depth as a function of reflectance. Data to train and test the machine learning algorithms was collected by scanning 16 short loins. The near-infrared hyperspectral camera captured lines of data of the side of the short loin (i.e. with the subcutaneous fat facing the camera). Advanced single-lens reflex camera took photos of the same cuts from above, such that a ground truth of fat depth could be semi-automatically extracted and associated with the hyperspectral data. A subset of the data was used to train the machine learning model, and to test it. The results of classifying pixels as either fat or non-fat achieved a 96% accuracy. Fat depths of up to 12 mm were estimated, with an R2 of 0.59, a mean absolute bias of 1.72 mm and root mean square error of 2.34 mm. The techniques developed and validated in the present study will be used to estimate fat coverage to predict total fat, and, subsequently, lean meat yield in the carcass.

Rahmati, O, Naghibi, SA, Shahabi, H, Bui, DT, Pradhan, B, Azareh, A, Rafiei-Sardooi, E, Samani, AN & Melesse, AM 2018, 'Groundwater spring potential modelling: Comprising the capability and robustness of three different modeling approaches', Journal of Hydrology, vol. 565, pp. 248-261.
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© 2018 Elsevier B.V. Sustainable water resources management in arid and semi-arid areas needs robust models, which allow accurate and reliable predictive modeling. This issue has motivated the researchers to develop hybrid models that offer solutions on modelling problems and accurate predictions of groundwater potential zonation. For this purpose, this research aims to investigate the capability and robustness of a novel hybrid model, namely the logistic model tree (LMT) and compares it with state-of-the-art models such as the support vector machine and C4.5 models that locate potential zones for groundwater springs. A spring location dataset consisting of 359 springs was provided by field surveys and national reports and from which three different sample data sets (S1–S3) were randomly prepared (70% for training and 30% for validation). Additionally, 16 spring-related factors were analyzed using regression logistic analysis to find which factors play a significant role in spring occurrence. Twelve significant geo-environmental and morphometric factors were identified and applied in all models. The accuracy of models was evaluated by three different threshold-dependent and –Independent methods including efficiency (E), true skill statistic (TSS), and area under the receiver operating characteristics curve (AUC-ROC) methods. Results showed that the LMT model had the highest accuracy performance for all three validation datasets (Emean = 0.860, TSSmean = 0.718, AUC-ROCmean = 0.904); although a slight sensitivity to change in input data was sometimes observed for this model. Furthermore, the findings showed that relative slope position (RSP) was the most important factor followed by distance from faults and lithology.

Rahnema, H, Hashemi Jokar, M & Khabbaz, H 2018, 'Predicting the Effective Stress Parameter of Unsaturated Soils Using Adaptive Neuro-Fuzzy Inference System', Scientia Iranica, vol. 0, no. 0, pp. 0-0.
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Rajabi Asadabadi, M, Saberi, M & Chang, E 2018, 'Letter: The concept of stratification and future applications', Applied Soft Computing, vol. 66, pp. 292-296.
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© 2018 Elsevier B.V. The main purpose of this letter is to draw attention to a recent concept, namely Concept of Stratification (CST) developed by Zadeh [1]. CST describes a system that transitions through a number of states in order to arrive at a desired state. CST is a problem-solving approach, which is easy while effective. Therefore, CST seems very likely to emerge in coming years as a major interest area in areas such as soft computing, Artificial Intelligence (AI), robotics, Natural Language Processing (NLP), and big data. In this expository letter, the advantages and the main shortcoming of CST are reviewed. The concept is explained and areas that the concept is likely to be applied are discussed. Considering the generality of the original CST proposed by Zadeh, it is possible to consider different versions for CST to be applied in future studies. Hence, versions of CST including fuzzy CST, a 3DCST, and multiple systems and multiple CSTs are presented. This work is a first step in a vast range of applications of CST. Researchers, especially those applying soft computing tools such as fuzzy sets theory and granulation, are encouraged to examine the capability of CST in addressing significant real-world problems.

Rajput, A, Iqbal, MA & Wu, C 2018, 'Prestressed concrete targets under high rate of loading', International Journal of Protective Structures, vol. 9, no. 3, pp. 362-376.
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Prestressed concrete is highly being preferred as material for construction in the case of strategic and relevant structures such as, for instance, nuclear containments, armor deposits, shelters, bridges, and military bunkers. It is highly durable, fire and corrosion resistant, and non-porous. In order to study the influence of prestressing on the mechanics of deformation, energy absorption capacity, and failure modes of concrete targets, finite element simulations have been carried out using hard steel bullets and compared with the experiments carried out by the authors earlier. Prestressed concrete targets of plan size 450 mm × 450 mm and thickness of 80 mm were impacted by 0.5-kg hard steel projectiles. The concrete was designed to obtain an unconfined compressive strength of 48 MPa. An initial stress of 10% magnitude of compressive strength was induced by 4-mm-diameter high-tensile-strength (1700 MPa) steel wires in prestressed concrete targets. A grid of 8-mm-diameter steel bars was inserted in the reinforced and prestressed concrete targets to enable the straight comparison between these concretes. The prestressing in concrete has been found to be effective in reducing the volume of scabbed material as well as the ballistic resistance of prestressed concrete targets. The ballistic limit of prestressed concrete with 10% induced stress was found to be, respectively, 14% higher than that of the plain concrete target and 10.2% higher than the reinforced concrete. Failure modes predicted through finite element simulations were found in agreement with that of the actual results.

Ramakrishna, VAS, Chamoli, U, Viglione, LL, Tsafnat, N & Diwan, AD 2018, 'Mild (not severe) disc degeneration is implicated in the progression of bilateral L5 spondylolysis to spondylolisthesis', BMC Musculoskeletal Disorders, vol. 19, no. 1.
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BACKGROUND:Spondylolytic (or lytic) spondylolisthesis is often associated with disc degeneration at the index-level; however, it is not clear if disc degeneration is the cause or the consequence of lytic spondylolisthesis. The main objective of this computed tomography based finite element modelling study was to examine the role of different grades of disc degeneration in the progression of a bilateral L5-lytic defect to spondylolisthesis. METHODS:High-resolution computed tomography data of the lumbosacral spine from an anonymised healthy male subject (26 years old) were segmented to build a 3D-computational model of an INTACT L1-S1 spine. The INTACT model was manipulated to generate four more models representing a bilateral L5-lytic defect and the following states of the L5-S1 disc: nil degeneration (NOR LYTIC), mild degeneration (M-DEG LYTIC), mild degeneration with 50% disc height collapse (M-DEG-COL LYTIC), and severe degeneration with 50% disc height collapse(S-COL LYTIC). The models were imported into a finite element modelling software for pre-processing, running nonlinear-static solves, and post-processing of the results. RESULTS:Compared with the baseline INTACT model, M-DEG LYTIC model experienced the greatest increase in kinematics (Fx range of motion: 73% ↑, Fx intervertebral translation: 53%↑), shear stresses in the annulus (Fx anteroposterior: 163%↑, Fx posteroanterior: 31%↑), and strain in the iliolumbar ligament (Fx: 90%↑). The S-COL LYTIC model experienced a decrease in mobility (Fx range of motion: 48%↓, Fx intervertebral translation: 69%↓) and an increase in normal stresses in the annulus (Fx Tensile: 170%↑; Fx Compressive: 397%↑). No significant difference in results was noted between M-DEG-COL LYTIC and S-COL LYTIC models. CONCLUSIONS:In the presence of a bilateral L5 spondylolytic defect, a mildly degenerate index-level disc experienced greater intervertebral motions and shear stresses compared with a severely degenerate index-level disc in ...

Ramakrishna, VAS, Chamoli, U, Viglione, LL, Tsafnat, N & Diwan, AD 2018, 'The Role of Sacral Slope in the Progression of a Bilateral Spondylolytic Defect at L5 to Spondylolisthesis: A Biomechanical Investigation Using Finite Element Analysis', Global Spine Journal, vol. 8, no. 5, pp. 460-470.
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Study Design: A biomechanical study using finite element analysis. Objectives: The main objective of this study was to investigate the role of sacral slope in the progression of a L5 bilateral spondylolytic defect to spondylolisthesis. Methods: A 3-dimensional model of lumbosacral spine was built using computed tomography (CT) data procured from an anonymized healthy male subject. The segmented CT data was manipulated to generate 3 more models representing L5 bilateral spondylolytic defect with normal sacral slope (SS), sacral slope increased by 10° (SS+10), and sacral slope decreased by 10° (SS-10). The 3D models were imported into finite element modelling software Strand7 for preprocessing, running nonlinear static solves, and postprocessing of the results. Results: Directional biomechanical instabilities were induced in the lumbosacral spine as a result of changes in the L5-S1 disc shape secondary to the changes in sacral slope. Compared with the normal L5 lytic model, wedging of the L5-S1 disc (SS+10) resulted in a significantly greater range of motion in flexion (18% ↑) but extension motion characteristics were similar. Conversely, flattening of the L5-S1 disc (SS-10) resulted in a significantly greater range of motion in extension (16% ↑) but flexion motion characteristics were similar to that of the normal L5 lytic model. Conclusions: Variations in sacral slope while preserving the L5-S1 mid-disc height and orientation of the L5 vertebra resulted in variations in the L5-S1 disc shape. The results suggest that for such extremities in the L5-S1 disc shape different pathomechanisms exist for the progression of the L5 lytic defect to spondylolisthesis.

Rana, MM, Li, L & Su, SW 2018, 'Cyber attack protection and control of microgrids', IEEE/CAA Journal of Automatica Sinica, vol. 5, no. 2, pp. 602-609.
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© 2014 Chinese Association of Automation. Recently, the smart grid has been considered as a next-generation power system to modernize the traditional grid to improve its security, connectivity, efficiency and sustainability. Unfortunately, the smart grid is susceptible to malicious cyber attacks, which can create serious technical, economical, social and control problems in power network operations. In contrast to the traditional cyber attack minimization techniques, this paper proposes a recursive systematic convolutional U+0028 RSC U+0029 code and Kalman filter U+0028 KF U+0029 based method in the context of smart grids. Specifically, the proposed RSC code is used to add redundancy in the microgrid states, and the log maximum a-posterior is used to recover the state information, which is affected by random noises and cyber attacks. Once the estimated states are obtained by KF algorithm, a semidefinite programming based optimal feedback controller is proposed to regulate the system states, so that the power system can operate properly. Test results show that the proposed approach can accurately mitigate the cyber attacks and properly estimate and control the system states.

Rana, MM, Li, L, Su, SW & Choi, BJ 2018, 'Modelling the Interconnected Synchronous Generators and its State Estimations', IEEE Access, vol. 6, pp. 36198-36207.
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© 2018 IEEE. In contrast to the traditional centralized power system state estimation approaches, this paper investigates the optimal filtering problem for distributed dynamic systems. Particularly, the interconnected synchronous generators are modeled as a state-space linear equation where sensors are deployed to obtain measurements. As the synchronous generator states are unknown, the estimation is required to know the operating conditions of large-scale power networks. Availability of the system states gives the designer an accurate picture of power networks to avoid blackouts. Basically, the proposed algorithm is based on the minimization of the mean squared estimation error, and the optimal gain is determined by exchanging information with their neighboring estimators. Afterward, the convergence of the developed algorithm is proved so that it can be applied to real-time applications in modern smart grids. Simulation results demonstrate the efficacy of the developed algorithm.

Rana, MM, Li, L, Su, SW & Xiang, W 2018, 'Consensus-Based Smart Grid State Estimation Algorithm', IEEE Transactions on Industrial Informatics, vol. 14, no. 8, pp. 3368-3375.
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© 2005-2012 IEEE. The distribution power subsystems are usually interconnected to each other, so the design of the interconnected optimal filtering algorithm for distributed state estimation is a challenging task. Driven by this motivation, this paper proposes a novel consensus filter based dynamic state estimation algorithm with its convergence analysis for modern power systems. The novelty of the scheme is that the algorithm is designed based on the mean squared error and semidefinite programming approaches. Specifically, the optimal local gain is computed after minimizing the mean squared error between the true and estimated states. The consensus gain is determined by a convex optimization process with a given suboptimal local gain. Furthermore, the convergence of the proposed scheme is analyzed after stacking all the estimation error dynamics. The Laplacian operator is used to represent the interconnected filter structure as a compact error dynamic for deriving the convergence condition of the algorithm. The developed approach is verified by using the renewable microgrid. It shows that the distributed scheme being explored is effective as it takes only 0.00004 seconds to properly estimate the system states and does not need to transmit the remote sensing signals to the central estimator.

Ranjbar-Zahedani, M, Keshavarzi, A, Khabbaz, H & Ball, J 2018, 'Protecting bridge piers against local scour using a flow-diversion structure', Proceedings of the Institution of Civil Engineers - Water Management, vol. 171, no. 5, pp. 271-280.
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Previous studies indicate that local scour is a leading cause of most waterway bridge failures during flood events. Using armouring countermeasures such as riprap and gabions is a conventional way of reducing scour around bridge piers, but is very costly and time consuming. As an alternative, a flow-diversion structure is proposed that has a triangular prismatic shape with dimensions much smaller than the actual pier and should be installed upstream of the pier. To assess its performance, experiments were conducted under clear-water scour conditions. After achieving equilibrium bed conditions, the bed profile was measured and the maximum scour depth and volume of the scour hole were determined for each experimental test. The results indicated that the clear distance between the pier and the countermeasure to achieve the maximum reduction in local scour was 1·5 times the pier diameter. For this condition, the proposed countermeasure reduced the maximum scour depth by 38% and the volume of the scour hole was decreased by around 61%. To determine the influence of the countermeasure on flow field around the pier, three-dimensional velocity components were measured at grid points using a micro-acoustic Doppler velocity meter. Analysis of the results indicated that the proposed structure could change both the magnitude and direction of the velocity components upstream of the pier and consequently induce a significant reduction in local scour depth and volume around the pier.

Ranji-Burachaloo, H, Fu, Q, Gurr, PA, Dunstan, DE & Qiao, GG 2018, 'Improved Fenton Therapy Using Cancer Cell Hydrogen Peroxide', Australian Journal of Chemistry, vol. 71, no. 10, pp. 826-826.
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Fenton cancer therapy as a new methodology for the treatment of tumour cells is largely restricted owing to the low stability, high aggregation, and poor selectivity of reported nanoparticles. In this study, an improved approach for the selective destruction of cancer cells is reported. Metal–organic framework (MOF) nanoparticles were synthesized and reduced via a hydrothermal method, and then PEGylated through the surface-initiated atom transfer radical polymerization (SI-ATRP) reaction to produce a PEGylated reduced MOF (P@rMOF). The ratio of PEG to nanoparticles was used to optimize the size and aggregation of the nanoparticles, with 2P@rMOF (2 : 1 mass ratio) having the smallest hydrodynamic diameter. The nanoparticles were further conjugated with folic acid for cell targeting. In vitro cell uptake experiments demonstrated that the internalization of 2P@rMOF-FA nanoparticles into cancer cells (HeLa) was almost 3-fold that of normal cells (NIH-3T3). In the presence of 2P@rMOF-FA, the HeLa cell viability decreased dramatically to 22 %, whereas the NIH-3T3 cell viability remained higher than 80 % after 24 h incubation. The selectivity index for 2P@rMOF-FA is 4.48, which is significantly higher than those reported in the literature for similar strategies. This work thus demonstrates the most stable and selective nanoparticle system for the treatment of cancer cells using the cell’s own H2O2.

Rao, P, Chen, Q, Nimbalkar, S & Liu, Y 2018, 'Effect of water and salinity on soil behaviour under lightning', Environmental Geotechnics, vol. 5, no. 1, pp. 56-62.
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The east coast of China, in particular Shanghai, is frequently exposed to lightning, and the resulting annual loss approaches US$30 million. All kinds of protection devices transfer the lightning current and the energy into the ground. In this study, the characteristics of the typical soft soil in Shanghai with different values of water content and salinity under the action of lightning shock have been analysed by an impulse current generator and a self-designed test equipment. The test results show that the current waveform from the impact of lightning in soils has a steep rise and a slow fall. At the same lightning intensity, higher water content or salinity leads to (a) shorter peak time, (b) larger peak current waveform, (c) quicker release speed and (d) larger lightning impulse response. The test results are valuable in guiding the design and the reformation of lightning protection and grounding systems.

Rao, T, Xu, M & Liu, H 2018, 'Generating affective maps for images', Multimedia Tools and Applications, vol. 77, no. 13, pp. 17247-17267.
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© 2017, Springer Science+Business Media, LLC. Affective image analysis, which estimates humans’ emotion reflection on images, has attracted increasing attention. Most of the existing methods focus on developing efficient visual features according to theoretical and empirical concepts, and extract these features from an image as a whole. However, analyzing emotion from an entire image, can only extract the dominant emotion conveyed by the whole image, which ignores the affective differences existing among different regions within the image. This may reduce the performance of emotion recognition, and limit the range of possible applications. In this paper, we are the first to propose the concept of affective map, by which image emotion can be represented at region-level. In an affective map, the value of each pixel represents the probability of the pixel belonging to a certain emotion category. Two popular application exemplars, i.e. affective image classification and visual saliency computing, are explored to prove the effectiveness of the proposed affective map. Analyzing detailed image emotion at a region-level, the accuracy of affective image classification has been improved 5.1% on average. The Area Under the Curve (AUC) of visual saliency detection has been improved 15% on average.

Ratiko, R, Samudera, SA, Hindami, R, Siahaan, AT, Naldi, L, Safitri, DH, Mahlia, DTMI & Nasruddin, IN 2018, 'Optimization of Dry Storage for Spent Fuel from G.A. Siwabessy Nuclear Research Reactor', International Journal of Technology, vol. 9, no. 1, pp. 55-55.
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© IJTech 2018. This study proposes a method of optimizing the dry storage design for nuclear-spent fuel from the G.A. Siwabessy research reactor at National Nuclear Energy Agency of Indonesia (BATAN). After several years in a spent fuel pool storage (wet storage), nuclear spent fuel is often moved to dry storage. Some advantages of dry storage compared with wet storage are that there is no generation of liquid waste, no need for a complex and expensive purification system, less corrosion concerns and that dry storage is easier to transport if in the future the storage needs to be sent to the another repository or to the final disposal. In both wet and dry storage, the decay heat of spent fuel must be cooled to a safe temperature to prevent cracking of the spent fuel cladding from where hazardous radioactive nuclides could be released and harm humans and the environment. Three optimization scenarios including the thermal safety single-objective, the economic single-objective and the multi-objective optimizations are obtained. The optimum values of temperature and cost for three optimization scenarios are 317.8K (44.7°C) and 11638.1 US$ for the optimized single-objective thermal safety method, 337.1K (64.0°C) and 6345.2 US$ for the optimized single-objective cost method and 325.1K (52.0°C) and 8037.4 US$ for the optimized multi-objective method, respectively.

Rawat, S & Kant Mittal, R 2018, 'Optimization of Eccentrically Loaded Reinforced-Concrete Isolated Footings', Practice Periodical on Structural Design and Construction, vol. 23, no. 2.
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Raza, A, Khan, MU, Tahir, FA, Hussain, R & Sharawi, MS 2018, 'A 2‐element meandered‐line slot‐based frequency reconfigurable MIMO antenna system', Microwave and Optical Technology Letters, vol. 60, no. 11, pp. 2794-2801.
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AbstractA dual‐band frequency reconfigurable multiple‐input multiple‐output (MIMO) antenna system is presented. The design consists of two slot‐based antenna elements made on an FR4 board and occupies an area of 50 × 100 mm2. The antenna operates in two bands. Further, a varactor diode is integrated across the slot to achieve the frequency reconfiguration. The antenna can be reconfigured to operate in both bands from 1.35‐1.62 GHz and 1.95‐2.2 GHz with minimum −6 dB bandwidth of 50 MHz. A defected ground structure (DGS) between the antenna elements is used to improve the isolation. With compact size and low envelope correlation coefficient (ECC), the design is suitable for long‐term evolution (LTE) systems and cognitive radio (CR) enabled platforms.

Ren, G, Cao, Y, Wen, S, Huang, T & Zeng, Z 2018, 'A modified Elman neural network with a new learning rate scheme', Neurocomputing, vol. 286, pp. 11-18.
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Elman neural network (ENN) is one of recurrent neural networks (RNNs). Comparing to traditional neural networks, ENN has additional inputs from the hidden layer, which forms a new layer–the context layer. So the standard back-propagation (BP) algorithm used in ENN is called Elman back-propagation algorithm (EBP). ENN can be applied to solve prediction problems of discrete time sequence. However, the EBP algorithm suffers from low convergence speed and poor generalization performance. To solve this problem, a new learning rate scheme is proposed, the convergence of new proposed scheme is proved. Furthermore, the contrast experiment is utilized to demonstrate the effectiveness of the proposed scheme from the aspects of convergence speed and consumption time with some popular schemes such as the original ENN, and PSO–ENN which uses PSO algorithm to search the best structure of ENN. The experience shows that the modified method proposed in this paper works best.

Ren, W, Wen, S, Tawfik, SA, Su, QP, Lin, G, Ju, LA, Ford, MJ, Ghodke, H, van Oijen, AM & Jin, D 2018, 'Anisotropic functionalization of upconversion nanoparticles', Chemical Science, vol. 9, no. 18, pp. 4352-4358.
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Ligand competition directs heterogeneous bio-chemistry surface and self-assembly for upconversion nanoparticles.

Ren, Z, Dong, D, Li, H & Chen, C 2018, 'Self-Paced Prioritized Curriculum Learning With Coverage Penalty in Deep Reinforcement Learning', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 6, pp. 2216-2226.
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Resseguier, N, Rosso-Delsemme, N, Beltran Anzola, A, Baumstarck, K, Milien, V, Ardillon, L, Bayart, S, Berger, C, Bertrand, M-A, Biron-Andreani, C, Borel-Derlon, A, Castet, S, Chamouni, P, Claeyssens Donadel, S, De Raucourt, E, Desprez, D, Falaise, C, Frotscher, B, Gay, V, Goudemand, J, Gruel, Y, Guillet, B, Harroche, A, Hassoun, A, Huguenin, Y, Lambert, T, Lebreton, A, Lienhart, A, Martin, M, Meunier, S, Monpoux, F, Mourey, G, Negrier, C, Nguyen, P, Nyombe, P, Oudot, C, Pan-Petesch, B, Polack, B, Rafowicz, A, Rauch, A, Rivaud, D, Schneider, P, Spiegel, A, Stoven, C, Tardy, B, Trossaërt, M, Valentin, J-B, Vanderbecken, S, Volot, F, Voyer-Ebrard, A, Wibaut, B, Leroy, T, Sannie, T, Chambost, H & Auquier, P 2018, 'Determinants of adherence and consequences of the transition from adolescence to adulthood among young people with severe haemophilia (TRANSHEMO): study protocol for a multicentric French national observational cross-sectional study', BMJ Open, vol. 8, no. 7, pp. e022409-e022409.
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IntroductionSevere haemophilia is a rare disease characterised by spontaneous bleeding from early childhood, which may lead to various complications, especially in joints. It is nowadays possible to avoid these complications thanks to substitutive therapies for which the issue of adherence is major. The transition from adolescence to adulthood in young people with severe haemophilia is a critical period as it is associated with a high risk of lack of adherence to healthcare, which might have serious consequences on daily activities and on quality of life.Methods and analysisWe present the protocol for a cross-sectional, observational, multicentric study to assess the differences between adolescents and young adults with severe haemophilia in France through the transition process, especially on adherence to healthcare. This study is based on a mixed methods design, with two complementary and consecutive phases, comparing data from a group of adolescents (aged 14–17 years) with those from a group of young adults (aged 20–29 years). The quantitative phase focuses on the determinants (medical, organisational, sociodemographic and social and psychosocial and behavioural factors) of adherence to healthcare (considered as a marker of the success of transition). The qualitative phase explores participants’ views in more depth to explain and refine the results from the quantitative phase. Eligible patients are contacted by the various Haemophilia Treatment Centres participating in the French national registry FranceCoag.Ethics and disseminationThe study was approved by the French Ethics Committee and by the French National Agency for Medicines and Health Products Safety (number: 2016-A01034-47). Study findings will be disseminated to the scientific and medical community in peer-reviewed journals ...

Reyhani, A, Nothling, MD, Ranji‐Burachaloo, H, McKenzie, TG, Fu, Q, Tan, S, Bryant, G & Qiao, GG 2018, 'Blood‐Catalyzed RAFT Polymerization', Angewandte Chemie, vol. 130, no. 32, pp. 10445-10449.
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AbstractThe use of hemoglobin (Hb) contained within red blood cells to drive a controlled radical polymerization via a reversible addition‐fragmentation chain transfer (RAFT) process is reported for the first time. No pre‐treatment of the Hb or cells was required prior to their use as polymerization catalysts, indicating the potential for synthetic engineering in complex biological microenvironments without the need for ex vivo techniques. Owing to the naturally occurring prevalence of the reagents employed in the catalytic system (Hb and hydrogen peroxide), this approach may facilitate the development of new strategies for in vivo cell engineering with synthetic macromolecules.

Reyhani, A, Nothling, MD, Ranji‐Burachaloo, H, McKenzie, TG, Fu, Q, Tan, S, Bryant, G & Qiao, GG 2018, 'Blood‐Catalyzed RAFT Polymerization', Angewandte Chemie International Edition, vol. 57, no. 32, pp. 10288-10292.
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AbstractThe use of hemoglobin (Hb) contained within red blood cells to drive a controlled radical polymerization via a reversible addition‐fragmentation chain transfer (RAFT) process is reported for the first time. No pre‐treatment of the Hb or cells was required prior to their use as polymerization catalysts, indicating the potential for synthetic engineering in complex biological microenvironments without the need for ex vivo techniques. Owing to the naturally occurring prevalence of the reagents employed in the catalytic system (Hb and hydrogen peroxide), this approach may facilitate the development of new strategies for in vivo cell engineering with synthetic macromolecules.

Reza, CMFS & Lu, DD 2018, 'Design and implementation of a packeted DC power system using a modified power packet structure', IET Power Electronics, vol. 11, no. 9, pp. 1603-1610.
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Recently, energy internet is introduced aiming to improve power system reliability, security and efficiency through advanced information and power electronic technologies. Power packet (PP) distribution system which integrates information transfer into electric power transfer is a potential candidate for energy internet implementation. It can reduce stand‐by power, eliminate voltage conversion stage in the traditional power distribution system, and actively control the load demand intelligently from the source side. This paper improves three areas of the existing PP distribution system, namely (i) a systematic approach to selecting the energy buffer based on the payload, identification bits, the load resistance and bit rate; (ii) a new algorithm to transfer PPs using a modified PP structure to the targeted loads with reduced footer bit, hence it can reduce more than 50% of the switching loss and information overhead; (iii) a simplified algorithm for a mixer to generate PPs according to multiple load requests. Experimental results of the improved packeted DC power system are reported.

Rifai, A, Tran, N, Lau, DW, Elbourne, A, Zhan, H, Stacey, AD, Mayes, ELH, Sarker, A, Ivanova, EP, Crawford, RJ, Tran, PA, Gibson, BC, Greentree, AD, Pirogova, E & Fox, K 2018, 'Polycrystalline Diamond Coating of Additively Manufactured Titanium for Biomedical Applications', ACS Applied Materials & Interfaces, vol. 10, no. 10, pp. 8474-8484.
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Rizeei, HM, Azeez, OS, Pradhan, B & Khamees, HH 2018, 'Assessment of groundwater nitrate contamination hazard in a semi-arid region by using integrated parametric IPNOA and data-driven logistic regression models', Environmental Monitoring and Assessment, vol. 190, no. 11.
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Groundwater hazard assessments involve many activities dealing with the impacts of pollution on groundwater, such as human health studies and environment modelling. Nitrate contamination is considered a hazard to human health, environment and ecosystem. In groundwater management, the hazard should be assessed before any action can be taken, particularly for groundwater pollution and water quality. Thus, pollution due to the presence of nitrate poses considerable hazard to drinking water, and excessive nutrient loads deteriorate the ecosystem. The parametric IPNOA model is one of the well-known methods used for evaluating nitrate content. However, it cannot predict the effect of soil and land use/land cover (LULC) types on calculations relying on parametric well samples. Therefore, in this study, the parametric model was trained and integrated with the multivariate data-driven model with different levels of information to assess groundwater nitrate contamination in Saladin, Iraq. The IPNOA model was developed with 185 different well samples and contributing parameters. Then, the IPNOA model was integrated with the logistic regression (LR) model to predict the nitrate contamination levels. Geographic information system techniques were also used to assess the spatial prediction of nitrate contamination. High-resolution SPOT-5 satellite images with 5 m spatial resolution were processed by object-based image analysis and support vector machine algorithm to extract LULC. Mapping of potential areas of nitrate contamination was examined using receiver operating characteristic assessment. Results indicated that the optimised LR-IPNOA model was more accurate in determining and analysing the nitrate hazard concentration than the standalone IPNOA model. This method can be easily replicated in other areas that have similar climatic condition. Therefore, stakeholders in planning and environmental decision makers could benefit immensely from the proposed method of this research...

Rizeei, HM, Pradhan, B & Saharkhiz, MA 2018, 'Surface runoff prediction regarding LULC and climate dynamics using coupled LTM, optimized ARIMA, and GIS-based SCS-CN models in tropical region', Arabian Journal of Geosciences, vol. 11, no. 3.
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© 2018, Saudi Society for Geosciences. The effects of climate and land use/land cover (LULC) dynamics have directly affected the surface runoff and flooding events. Hence, current study proposes a full-packaged model to monitor the changes in surface runoff in addition to forecast of the future surface runoff based on LULC and precipitation variations. On one hand, six different LULC classes were extracted from Spot-5 satellite image. Conjointly, land transformation model (LTM) was used to detect the LULC pixel changes from 2000 to 2010 as well as predict the 2020 ones. On the other hand, the time series-autoregressive integrated moving average (ARIMA) model was applied to forecast the amount of rainfall in 2020. The ARIMA parameters were calibrated and fitted by latest Taguchi method. To simulate the maximum probable surface runoff, distributed soil conservation service-curve number (SCS-CN) model was applied. The comparison results showed that firstly, deforestation and urbanization have been occurred upon the given time, and they are anticipated to increase as well. Secondly, the amount of rainfall has non-stationary declined since 2000 till 2015 and this trend is estimated to continue by 2020. Thirdly, due to damaging changes in LULC, the surface runoff has been also increased till 2010 and it is forecasted to gradually exceed by 2020. Generally, model calibrations and accuracy assessments have been indicated, using distributed-GIS-based SCS-CN model in combination with the LTM and ARIMA models are an efficient and reliable approach for detecting, monitoring, and forecasting surface runoff.

Rizeei, HM, Shafri, HZM, Mohamoud, MA, Pradhan, B & Kalantar, B 2018, 'Oil Palm Counting and Age Estimation from WorldView-3 Imagery and LiDAR Data Using an Integrated OBIA Height Model and Regression Analysis', Journal of Sensors, vol. 2018, pp. 1-13.
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The current study proposes a new method for oil palm age estimation and counting from Worldview-3 satellite image and light detection and range (LiDAR) airborne imagery. A support vector machine algorithm (SVM) of object-based image analysis (OBIA) was implemented for oil palm counting. The sensitivity analysis was conducted on four SVM kernel types with associated segmentation parameters to obtain the optimal crown coverage delineation. Extracting tree’s crown was integrated with height model and multiregression methods to accurately estimate the age of trees. The multiregression model with multikernel sizes was examined to achieve the most optimized model for age estimation. Applied models were trained and examined over five different oil palm plantations. The results of oil palm counting had an overall accuracy of 98.80%, while the overall accuracy of age estimation showed 84.91%, over all blocks. The relationship between tree’s height and age was significant which supports the polynomial regression function (PRF) model with a 3×3 kernel size for under 10–12-year-old oil palm trees, while exponential regression function (ERF) is more fitted for older trees (i.e., 22 years old). Overall, recent remote sensing dataset and machine learning techniques are useful in monitoring and detecting oil palm plantation to maximize productivity.

Robson, EN, Wijayaratna, KP & Dixit, VV 2018, 'A review of computable general equilibrium models for transport and their applications in appraisal', Transportation Research Part A: Policy and Practice, vol. 116, pp. 31-53.
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© 2018 Elsevier Ltd In the transport planning process, decision makers require reliable and informative appraisals to facilitate comparisons and determine if a proposal is worthwhile to society. The cost–benefit analysis is the most common form of appraisal, where benefits are primarily measured from the change in consumer surplus in the transport market. However, these benefits will only reflect maximum social welfare if markets operate perfectly competitively and without any market failures. There may be significant uncaptured impacts, known as wider economic impacts, which agencies are beginning to incorporate in appraisals using ad-hoc methods. Computable general equilibrium (CGE) models are an increasingly popular method for assessing the economic impact of transport, including both direct and wider economic impacts, as they can determine the distribution of impacts among every market and agent in the economy by simulating the behaviour of households, firms and others from microeconomic first principles. Aside from their traditional role estimating changes in macroeconomic variables, CGE models can provide a measure of welfare that guarantees no double counting and accounts for nth order effects. This paper reviews the full range of CGE models that have been applied to transport issues and discusses their role in transport appraisal. CGE models for transport have been developed in urban, regional and environmental economics as well as other fields, and each field has applied its own theory, assumptions and practices to represent the relationships between transport and the economy relevant to the field. This paper also discusses the general role of CGE modelling in transport appraisal, as well as theoretical and practical concerns regarding CGE modelling practice.

Rocha, CGD, Anzanello, MJ & Gerchman, M 2018, 'Method to Assess the Match between Clients’ Input and Decoupling Points in Customized Building Projects', Journal of Construction Engineering and Management, vol. 144, no. 5, pp. 04018018-04018018.
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Rogers, S, McCloy, RA, Parker, BL, Gallego-Ortega, D, Law, AMK, Chin, VT, Conway, JRW, Fey, D, Millar, EKA, O’Toole, S, Deng, N, Swarbrick, A, Chastain, PD, Cesare, AJ, Timpson, P, Caldon, CE, Croucher, DR, James, DE, Watkins, DN & Burgess, A 2018, 'MASTL overexpression promotes chromosome instability and metastasis in breast cancer', Oncogene, vol. 37, no. 33, pp. 4518-4533.
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MASTL kinase is essential for correct progression through mitosis, with loss of MASTL causing chromosome segregation errors, mitotic collapse and failure of cytokinesis. However, in cancer MASTL is most commonly amplified and overexpressed. This correlates with increased chromosome instability in breast cancer and poor patient survival in breast, ovarian and lung cancer. Global phosphoproteomic analysis of immortalised breast MCF10A cells engineered to overexpressed MASTL revealed disruption to desmosomes, actin cytoskeleton, PI3K/AKT/mTOR and p38 stress kinase signalling pathways. Notably, these pathways were also disrupted in patient samples that overexpress MASTL. In MCF10A cells, these alterations corresponded with a loss of contact inhibition and partial epithelial-mesenchymal transition, which disrupted migration and allowed cells to proliferate uncontrollably in 3D culture. Furthermore, MASTL overexpression increased aberrant mitotic divisions resulting in increased micronuclei formation. Mathematical modelling indicated that this delay was due to continued inhibition of PP2A-B55, which delayed timely mitotic exit. This corresponded with an increase in DNA damage and delayed transit through interphase. There were no significant alterations to replication kinetics upon MASTL overexpression, however, inhibition of p38 kinase rescued the interphase delay, suggesting the delay was a G2 DNA damage checkpoint response. Importantly, knockdown of MASTL, reduced cell proliferation, prevented invasion and metastasis of MDA-MB-231 breast cancer cells both in vitro and in vivo, indicating the potential of future therapies that target MASTL. Taken together, these results suggest that MASTL overexpression contributes to chromosome instability and metastasis, thereby decreasing breast cancer patient survival.

Romero-Hall, E, Aldemir, T, Colorado-Resa, J, Dickson-Deane, C, Watson, GS & Sadaf, A 2018, 'Undisclosed stories of instructional design female scholars in academia', Women's Studies International Forum, vol. 71, pp. 19-28.
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Roobavannan, M, van Emmerik, THM, Elshafei, Y, Kandasamy, J, Sanderson, MR, Vigneswaran, S, Pande, S & Sivapalan, M 2018, 'Norms and values in sociohydrological models', Hydrology and Earth System Sciences, vol. 22, no. 2, pp. 1337-1349.
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Abstract. Sustainable water resources management relies on understanding how societiesand water systems coevolve. Many place-based sociohydrology (SH) modelingstudies use proxies, such as environmental degradation, to capture keyelements of the social component of system dynamics. Parameters of assumedrelationships between environmental degradation and the human response to itare usually obtained through calibration. Since these relationships are notyet underpinned by social-science theories, confidence in the predictivepower of such place-based sociohydrologic models remains low. Thegeneralizability of SH models therefore requires major advances inincorporating more realistic relationships, underpinned by appropriatehydrological and social-science data and theories. The latter is a criticalinput, since human culture – especially values and norms arising from it –influences behavior and the consequences of behaviors. This paper reviews akey social-science theory that links cultural factors to environmentaldecision-making, assesses how to better incorporate social-science insightsto enhance SH models, and raises important questions to be addressed inmoving forward. This is done in the context of recent progress insociohydrological studies and the gaps that remain to be filled. The paperconcludes with a discussion of challenges and opportunities in terms ofgeneralization of SH models and the use of available data to allow futureprediction and model transfer to ungauged basins.

Rossi, MJ, Ares, JO, Jobbágy, EG, Vivoni, ER, Vervoort, RW, Schreiner-McGraw, AP & Saco, PM 2018, 'Vegetation and terrain drivers of infiltration depth along a semiarid hillslope', Science of The Total Environment, vol. 644, pp. 1399-1408.
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Rouzbehi, K, Heidary Yazdi, SS & Shariati Moghadam, N 2018, 'Power Flow Control in Multi-Terminal HVDC Grids Using a Serial-Parallel DC Power Flow Controller', IEEE Access, vol. 6, pp. 56934-56944.
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Rufangura, P & Sabah, C 2018, 'Perfect metamaterial absorber for applications in sustainable and high-efficiency solar cells', Journal of Nanophotonics, vol. 12, no. 02, pp. 1-1.
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The current state of energy is characterized by complex challenges in production processes and environmental issues. With the world population continuing to multiply faster and the globalization process, additional energy production is needed to meet future demands. Solar energy is one of the best sustainable energy resources, which is expected to play a vital role in this scenario. One of the best techniques to harvest this resource is through solar photovoltaic technology, which produces electricity directly from solar radiation. But, one of the problems still persisting is its low efficiency. To harness this technology, this problem needs to be addressed. Metamaterial (MTM) technology has enabled the creation of advanced devices for various applications. Solar cell technology is one of the fields to benefit from this technology. MTM perfect absorber can be used in solar cells to improve their absorption. Multiple-bands MTM absorber for next generation high-efficiency solar cells is proposed. The design gives a nearly perfect absorption (99.94%) with a bandwidth of 23.4% in visible spectrum. In addition, the geometric flexibility of a proposed design causes its absorption rate to be insensitive of polarization angles and angles of incident electromagnetic radiations.

Saberi, M, Theobald, M, Hussain, OK, Chang, E & Hussain, FK 2018, 'Interactive feature selection for efficient customer recognition in contact centers: Dealing with common names', Expert Systems with Applications, vol. 113, pp. 356-376.
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© 2018 Elsevier Ltd We propose an interactive decision-making framework to assist a Customer Service Representative (CSR) in the efficient and effective recognition of customer records in a database with many ambiguous entries. Our proposed framework consists of three integrated modules. The first module focuses on the detection and resolution of duplicate records to improve effectiveness and efficiency in customer recognition. The second module determines the level of ambiguity in recognizing an individual customer when there are multiple records with the same name. The third module recommends the series of feature-related questions that the CSR should ask the customer to enable rapid recognition, based on that level of ambiguity. In the first module, the F-Swoosh approach for duplicate detection is used, and in the second module a dynamic programming-based technique is used to determine the level of ambiguity within the customer database for a given name. In the third module, Levenshtein edit distance is used for feature selection in combination with weights based on the Inverse Document Frequency (IDF) of terms. The algorithm that requires the minimum number of questions to be put to the customer to achieve recognition is the algorithm that is chosen. We evaluate the proposed framework on a synthetic dataset and demonstrate how it assists the CSR to rapidly recognize the correct customer.

Saco, PM, Moreno-de las Heras, M, Keesstra, S, Baartman, J, Yetemen, O & Rodríguez, JF 2018, 'Vegetation and soil degradation in drylands: Non linear feedbacks and early warning signals', Current Opinion in Environmental Science & Health, vol. 5, pp. 67-72.
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Sadr, N, Jayawardhana, M, Pham, TT, Tang, R, Balaei, AT & de Chazal, P 2018, 'A low-complexity algorithm for detection of atrial fibrillation using an ECG', Physiological Measurement, vol. 39, no. 6, pp. 064003-064003.
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We present a method for automatic processing of single-lead electrocardiogram (ECG) with duration of up to 60 s for the detection of atrial fibrillation (AF). The method categorises an ECG recording into one of four categories: normal, AF, other and noisy rhythm. For training the classification model, 8528 scored ECG signals were used; for independent performance assessment, 3658 scored ECG signals.Our method was based on features derived from RR interbeat intervals. The features included time domain, frequency domain and distribution features. We assessed the performance of three different classifiers (linear and quadratic discriminant analysis, and quadratic neural network (QNN)) on the training set using 100-fold cross-validation. The QNN was selected as the highest performing classifier, and a further performance assessment on the test data made.On the test set, our method achieved an F1 score for the normal, AF, other and noisy classes of 0.90, 0.75, 0.68 and 0.32, respectively. The overall F1 score was 0.78.The computational cost of our algorithm is low as all features are derived from RR intervals and are processed by a single hidden layer neural network. This makes it potentially suitable for low-power devices.

Saeidian, B, Mesgari, MS, Pradhan, B & Ghodousi, M 2018, 'Optimized Location-Allocation of Earthquake Relief Centers Using PSO and ACO, Complemented by GIS, Clustering, and TOPSIS', ISPRS International Journal of Geo-Information, vol. 7, no. 8, pp. 292-292.
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After an earthquake, it is required to establish temporary relief centers in order to help the victims. Selection of proper sites for these centers has a significant effect on the processes of urban disaster management. In this paper, the location and allocation of relief centers in district 1 of Tehran are carried out using Geospatial Information System (GIS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision model, a simple clustering method and the two meta-heuristic algorithms of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). First, using TOPSIS, the proposed clustering method and GIS analysis tools, sites satisfying initial conditions with adequate distribution in the area are chosen. Then, the selection of proper centers and the allocation of parcels to them are modelled as a location/allocation problem, which is solved using the meta-heuristic optimization algorithms. Also, in this research, PSO and ACO are compared using different criteria. The implementation results show the general adequacy of TOPSIS, the clustering method, and the optimization algorithms. This is an appropriate approach to solve such complex site selection and allocation problems. In view of the assessment results, the PSO finds better answers, converges faster, and shows higher consistency than the ACO.

Safavi-Naeini, M, Chacon, A, Guatelli, S, Franklin, DR, Bambery, K, Gregoire, M-C & Rosenfeld, A 2018, 'Opportunistic dose amplification for proton and carbon ion therapy via capture of internally generated thermal neutrons', Scientific Reports, vol. 8, no. 1.
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AbstractThis paper presents Neutron Capture Enhanced Particle Therapy (NCEPT), a method for enhancing the radiation dose delivered to a tumour relative to surrounding healthy tissues during proton and carbon ion therapy by capturing thermal neutrons produced inside the treatment volume during irradiation. NCEPT utilises extant and in-development boron-10 and gadolinium-157-based drugs from the related field of neutron capture therapy. Using Monte Carlo simulations, we demonstrate that a typical proton or carbon ion therapy treatment plan generates an approximately uniform thermal neutron field within the target volume, centred around the beam path. The tissue concentrations of neutron capture agents required to obtain an arbitrary 10% increase in biological effective dose are estimated for realistic treatment plans, and compared to concentrations previously reported in the literature. We conclude that the proposed method is theoretically feasible, and can provide a worthwhile improvement in the dose delivered to the tumour relative to healthy tissue with readily achievable concentrations of neutron capture enhancement drugs.

Sahebi, S, Shon, HK, Phuntsho, S & Ramavandi, B 2018, 'Fabricating robust thin film composite membranes reinforced on woven mesh backing fabric support for pressure assisted and forward osmosis: A dataset', Data in Brief, vol. 21, pp. 364-370.
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© 2018 The Authors The data presented in this paper are produced as part of the original research article entitled “Thin-film composite membrane on a compacted woven backing fabric for pressure assisted osmosis” (Sahebi et al., 2017). This article describes how to fabricate a defect free membrane for forward osmosis (FO) and pressure assisted osmosis (PAO) on the woven mesh backing fabric support. Casting polymer on backing fabric support may limit the interfacial polyemirization due to wrinkled membrane surface. This paper presents data obtained from two different backing fabrics used as support for fabrication of thin film composite FO membrane. Backing fabric support were woven polyester mesh with different opening size. The data include the characterization of the intrinsic properties of the membrane samples, SEM and their performance under FO process. The structural parameters (S value) of the substrate were computed from thickness and porosity of the substrates. Thin film composite (TFC) membrane achieved a water flux of 8.1 L m2 h−1 in FO process and 37 L m2 h−1 using 0.5 M NaCl as draw solution (DS) and deionised (DI) water as the feed solution (FS) when applied hydraulic pressure was 10 bar.

Sais, D, Zhang, X, Marques, TM, Rose, B, Khoury, S, Hill, M, Deutsch, F, Lyons, JG, Gama-Carvalho, M & Tran, N 2018, 'Human papillomavirus 16 E6 modulates the expression of miR-496 in oropharyngeal cancer', Virology, vol. 521, pp. 149-157.
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© 2018 Human papillomavirus (HPV), notably type 16, is a risk factor for up to 75% of oropharyngeal squamous cell carcinomas (SCC). It has been demonstrated that small non-coding RNAs known as microRNAs play a vital role in the cellular transformation process. In this study, we used an LNA array to further investigate the impact of HPV16 on the expression of microRNAs in oropharyngeal (tonsillar) cancer. A number of miRNAs were found to be deregulated, with miR-496 showing a four-fold decrease. Over-expression of the high risk E6 oncoprotein down-regulated miR-496, impacting upon the post-transcriptional control of the transcription factor E2F2. These HPV specific miRNAs were integrated with the HPV16 interactome to identify possible mechanistic pathways. These analyses provide insights into novel molecular interactions between HPV16 and miRNAs in oropharyngeal cancers.

Sajedi-Hosseini, F, Malekian, A, Choubin, B, Rahmati, O, Cipullo, S, Coulon, F & Pradhan, B 2018, 'A novel machine learning-based approach for the risk assessment of nitrate groundwater contamination', Science of The Total Environment, vol. 644, pp. 954-962.
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© 2018 Elsevier B.V. This study aimed to develop a novel framework for risk assessment of nitrate groundwater contamination by integrating chemical and statistical analysis for an arid region. A standard method was applied for assessing the vulnerability of groundwater to nitrate pollution in Lenjanat plain, Iran. Nitrate concentration were collected from 102 wells of the plain and used to provide pollution occurrence and probability maps. Three machine learning models including boosted regression trees (BRT), multivariate discriminant analysis (MDA), and support vector machine (SVM) were used for the probability of groundwater pollution occurrence. Afterwards, an ensemble modeling approach was applied for production of the groundwater pollution occurrence probability map. Validation of the models was carried out using area under the receiver operating characteristic curve method (AUC); values above 80% were selected to contribute in ensembling process. Results indicated that accuracy for the three models ranged from 0.81 to 0.87, therefore all models were considered for ensemble modeling process. The resultant groundwater pollution risk (produced by vulnerability, pollution, and probability maps) indicated that the central regions of the plain have high and very high risk of nitrate pollution further confirmed by the exiting landuse map. The findings may provide very helpful information in decision making for groundwater pollution risk management especially in semi-arid regions.

Salari, Z, Vakhshouri, B & Nejadi, S 2018, 'Analytical review of the mix design of fiber reinforced high strength self-compacting concrete', Journal of Building Engineering, vol. 20, pp. 264-276.
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© 2018 Elsevier Ltd Despite application of fiber reinforced concrete, high strength concrete and self-compacting concrete in the construction industry in the last decades, the investigations about combination of these types of concrete in Fiber Reinforced High-Strength Self-Compacting Concrete (FRHSSCC) is very rare in the literature. This study reviews a wide range of experimental data of the mix design in terms of the components and their proportions and the compressive strength of FRHSSCC in the last 12 years. The applied coarse and fine aggregates, chemical and mineral admixtures, fibers, cement, water, powder components and the ratios of water to cement and water to binder are broadly analyzed and evaluated. In addition, the compressive strength of the FRHSSCC mixtures are evaluated. The relationship between the compressive strength with water to cement and water to binder ratios in the mixture, water content, fine and coarse aggregates and the powder content is also discussed and compared in the case studies. Considerable variety of the mix designs with different components and proportions to achieve FRHSSCC without the mixing problems is evident in the collected case studies.

Saleh, A, Far, H & Mok, L 2018, 'Effects of different support conditions on experimental bending strength of thin walled cold formed steel storage upright frames', Journal of Constructional Steel Research, vol. 150, pp. 1-6.
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© 2018 Elsevier Ltd Design computations of industrial storage racks in accordance with current industry standards rely in part on laboratory testing. One of these tests is for determining the bending strength of upright sections. When testing the bending strength about the axis of symmetry of the upright, a four-point bending test of the assembled upright frame is mandated. The test arrangement prescribed by the standard must permit free twisting of the section at the supports, while the applied loads and their reactions for each upright may be applied in the plane of the section's shear centre. A test arrangement that provides free twisting of the upright section at the supports is more complex and difficult to set up compared with a simple support. This paper examines if the condition of free twisting at supports is necessary in the case of shear centre loading, especially that relaxing this particular code requirement would lead to a simpler test arrangement. Laboratory testing of two sets of upright frames, loaded through the upright's shear centre but with each set having a different support condition indicated that free twisting at the supports had no effect on the bending capacity of the upright members tested. The paper outlines the test setup and reports the results in form of characteristic load deformation curves of the tested specimen.

Samaei, SM, Gato-Trinidad, S & Altaee, A 2018, 'The application of pressure-driven ceramic membrane technology for the treatment of industrial wastewaters – A review', Separation and Purification Technology, vol. 200, pp. 198-220.
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© 2018 Elsevier B.V. This paper presents a review of the previous laboratory analysis and case studies on the application of the pressure-driven ceramic membrane technology for treatment of industrial wastewaters. Ceramic membranes has attracted remarkable interests in recent decades for industrial wastewater treatment because of their superior characteristic such as high fluxes, reliable working lifetime under aggressive operating conditions and ease of cleaning. The literature review revealed that the efficiency of this technology has been proven in a wide variety of wastewaters from different industries and activities including pulp and paper, textile, pharmaceutical, petrochemical, food and mining. However, there are still challenges and questions for this technology that need to be addressed in future researches such as investment cost optimisation by introducing new fabrication technologies, selectivity, permeability and packing densities improvement, fouling minimisation and proposing scale up based on experimental research results.

Samanta, M, Punetha, P & Sharma, M 2018, 'Effect of roughness on interface shear behavior of sand with steel and concrete surface', Geomechanics and Engineering, vol. 14, no. 4, pp. 387-398.
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The present study evaluates the interface shear strength between sand and different construction materials, namely steel and concrete, using direct shear test apparatus. The influence of surface roughness, mean size of sand particles, relative density of sand and size of the direct shear box on the interface shear behavior of sand with steel and concrete has been investigated. Test results show that the surface roughness of the construction materials significantly influences the interface shear strength. The peak and residual interface friction angles increase rapidly up to a particular value of surface roughness (critical surface roughness), beyond which the effect becomes negligible. At critical surface roughness, the peak and residual friction angles of the interfaces are 85-92% of the peak and residual internal friction angles of the sand. The particle size of sand (for morphologically identical sands) significantly influences the value of critical surface roughness. For the different roughness considered in the present study, both the peak and residual interaction coefficients lie in the range of 0.3-1. Moreover, the peak and residual interaction coefficients for all the interfaces considered are nearly identical, irrespective of the size of the direct shear box. The constitutive modeling of different interfaces followed the experimental investigation and it successfully predicted the pre-peak, peak and post peak interface shear response with reasonable accuracy. Moreover, the predicted stress-displacement relationship of different interfaces is in good agreement with the experimental results. The findings of the present study may also be applicable to other non-yielding interfaces having a similar range of roughness and sand properties.

Samanta, M, Punetha, P & Sharma, M 2018, 'Influence of surface texture on sand–steel interface strength response', Géotechnique Letters, vol. 8, no. 1, pp. 40-48.
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The surface texture of the interface material plays a significant role in the shear behaviour of soil–continuum interface. This study investigates the influence of surface texture of steel on the shear behaviour of sand–steel interface using different types of steel counterfaces with distinct texturing patterns. The patterns include concentric circular asperities, square-tiled surfaces with equally spaced individual asperities and ruled ribbed asperities oriented parallel, perpendicular and at an angle to the shear direction. The results show that the texturing pattern of the steel counterface significantly affects the shear strength of the sand–steel interface. The peak and residual interface friction angles for the sand–steel interfaces with different texturing patterns (with identical asperity height and spacing) varied from 26·6° to 37·5° and 14·2° to 28·7°, respectively. Moreover, the surface with ruled ribs/asperities inclined at right angle to the shear direction shows the maximum interface shear strength among all the texturing patterns tested. The findings presented herein are imperative for a realistic assessment of the performance of geotechnical structures involving soil–steel interaction.

Samaras, E & Johnston, A 2018, 'Fleeting Film: Using Story to Seek Archival Permanence in the Transitory and Globalized Digital Visual Effects Industry', Preservation, Digital Technology & Culture, vol. 47, no. 1, pp. 12-22.
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AbstractArchiving is a long-standing vocation, founded on principles such as provenance, original order, truth, evidence, preservation and permanence. A far cry from the visual spectacle and movable feast of film visual effects (VFX)—a transitory and globalized industry of disposable firms, ever-advancing technologies and a roving workforce which craft digital animations and seamless effects for the big screen. In this paper we utilize the concept of “story” as a premise to bring together the seemingly different vocations of archival science and film VFX. Through an exploration of digital film production and archival practice under the context of storytelling, we aim to highlight the need for archivists to work with the VFX industry to ensure evidence of this culturally significant aspect of filmmaking and cinema discourse is preserved into the future. As well present the argument that archives are more than collections of historical evidence. Archives are story—and archivists are storytellers.

Sameen, MI, Pradhan, B & Aziz, OS 2018, 'Classification of Very High Resolution Aerial Photos Using Spectral-Spatial Convolutional Neural Networks', Journal of Sensors, vol. 2018, pp. 1-12.
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Classification of aerial photographs relying purely on spectral content is a challenging topic in remote sensing. A convolutional neural network (CNN) was developed to classify aerial photographs into seven land cover classes such as building, grassland, dense vegetation, waterbody, barren land, road, and shadow. The classifier utilized spectral and spatial contents of the data to maximize the accuracy of the classification process. CNN was trained from scratch with manually created ground truth samples. The architecture of the network comprised of a single convolution layer of 32 filters and a kernel size of 3 × 3, pooling size of 2 × 2, batch normalization, dropout, and a dense layer with Softmax activation. The design of the architecture and its hyperparameters were selected via sensitivity analysis and validation accuracy. The results showed that the proposed model could be effective for classifying the aerial photographs. The overall accuracy and Kappa coefficient of the best model were 0.973 and 0.967, respectively. In addition, the sensitivity analysis suggested that the use of dropout and batch normalization technique in CNN is essential to improve the generalization performance of the model. The CNN model without the techniques above achieved the worse performance, with an overall accuracy and Kappa of 0.932 and 0.922, respectively. This research shows that CNN-based models are robust for land cover classification using aerial photographs. However, the architecture and hyperparameters of these models should be carefully selected and optimized.

Sampson, E, Chen, F, Dellenback, S, Novosad, S & Oguchi, T 2018, 'Guest Editorial: Selected Papers from the 25th ITS World Congress Copenhagen 2018', IET Intelligent Transport Systems, vol. 12, no. 9, pp. 995-997.
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Sandi, SG, Rodríguez, JF, Saintilan, N, Riccardi, G & Saco, PM 2018, 'Rising tides, rising gates: The complex ecogeomorphic response of coastal wetlands to sea-level rise and human interventions', Advances in Water Resources, vol. 114, pp. 135-148.
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Saputra, YM, Hoang, DT, Nguyen, DN & Dutkiewicz, E 2018, 'A Novel Mobile Edge Network Architecture with Joint Caching-Delivering and Horizontal Cooperation', IEEE Transactions on Mobile Computing, vol. 20, no. 1, pp. 19-31.
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Mobile edge caching/computing has been emerging as a promising paradigm toprovide new services (e.g., ultra-high rate, ultra-reliable, and/or low-latencycommunications) in future wireless networks. In this paper, we introduce anovel mobile edge caching network architecture that leverages the optimal jointcaching-delivering with horizontal cooperation among mobile edge nodes (MENs),namely JOCAD. Under this architecture, MENs cooperate with each other in bothcaching and delivering contents, aiming to simultaneously minimize the totalaverage delay for the mobile users and mitigate the network traffic on thebackhaul link. Extensive simulations demonstrate that the proposed solutionscan reduce the total average delay for the whole network up to 40% comparedwith the most frequency-of-access policy, and up to 25% compared with locallyoptimal caching policy (i.e., without collaboration). Furthermore, the proposedsolutions also increase the cache hit rate for the network by four times,thereby dramatically reducing the traffic load on the backhaul network.

Saputra, YM, Hoang, DT, Nguyen, DN, Dutkiewicz, E, Niyato, D & Kim, DI 2018, 'Distributed Deep Learning at the Edge: A Novel Proactive and Cooperative Caching Framework for Mobile Edge Networks', IEEE Wireless Communications Letters, vol. 8, no. 4, pp. 1-1.
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This letter proposes two novel proactive cooperative caching approaches usingdeep learning (DL) to predict users' content demand in a mobile edge cachingnetwork. In the first approach, a (central) content server takesresponsibilities to collect information from all mobile edge nodes (MENs) inthe network and then performs our proposed deep learning (DL) algorithm topredict the content demand for the whole network. However, such a centralizedapproach may disclose the private information because MENs have to share theirlocal users' data with the content server. Thus, in the second approach, wepropose a novel distributed deep learning (DDL) based framework. The DDL allowsMENs in the network to collaborate and exchange information to reduce the errorof content demand prediction without revealing the private information ofmobile users. Through simulation results, we show that our proposed approachescan enhance the accuracy by reducing the root mean squared error (RMSE) up to33.7% and reduce the service delay by 36.1% compared with other machinelearning algorithms.

Sarker, A, Tran, N, Rifai, A, Elambasseril, J, Brandt, M, Williams, R, Leary, M & Fox, K 2018, 'Angle defines attachment: Switching the biological response to titanium interfaces by modifying the inclination angle during selective laser melting', Materials & Design, vol. 154, pp. 326-339.
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Satija, S, Prince, Gupta, R, Mahajan, S, Sharma, N, Khurana, N, Kalsi, V, Duggal, N, Singh, A & Mehta, M 2018, 'Chromatographic fingerprinting, antioxidant, and anti-inflammatory potential of Dioscorea villosa (Wild Yam) leaves', International Journal of Green Pharmacy, vol. 12, no. 2, pp. 102-106.
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Context: Free radicals have been implicated in a wide range diversity of diseases and ailments, and therefore, the compounds having the ability to scavenge these free radicals are under extensive investigation, of which Dioscorea species have been actively involved. Objective: The current study assessed the anti-inflammatory and antioxidant potential of standardized leaf extracts of Dioscorea villosa. Material and Methods: Anti-inflammatory activity was carried out using carrageenan-induced paw edema assay, and antioxidant activity was evaluated using 1,1-diphenyl-2-picrylhydrazyl radical scavenging assay. Chromatographic fingerprinting of the crude methanolic extract was carried out using high-performance liquid chromatography (HPLC) whereby diosgenin was used as a standard marker compound. Results: Among all the crude successive extracts, methanolic extract showed significant anti-inflammatory activity in comparison with the standard whereby the extract showed maximum inhibition of paw edema after 3 h of carrageenan injection. The aqueous extract showed noticeable antioxidant activity with the half maximal inhibitory concentration of 21.36 μg/ml. Discussion: The preliminary phytochemical screening showed the presence of flavonoids and tannins that may be responsible for the observed effect. In addition, the presence of steroids marks toward the observed anti-inflammatory activity. In addition, the extract showed noticeable levels of diosgenin, which were marked and quantified using HPLC. Conclusion: The results strongly support the ethnobotanical use of the plant.

Scheltema, MJ, Chang, JI, Böhm, M, van den Bos, W, Blazevski, A, Gielchinsky, I, Kalsbeek, AMF, van Leeuwen, PJ, Nguyen, TV, de Reijke, TM, Siriwardana, AR, Thompson, JE, de la Rosette, JJ & Stricker, PD 2018, 'Pair-matched patient-reported quality of life and early oncological control following focal irreversible electroporation versus robot-assisted radical prostatectomy', World Journal of Urology, vol. 36, no. 9, pp. 1383-1389.
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PURPOSE:The design, conduct and completion of randomized trials for curative prostate cancer (PCa) treatments are challenging. To evaluate the effect of robot-assisted radical prostatectomy (RARP) versus focal irreversible electroporation (IRE) on patient-reported quality of life (QoL) and early oncological control using propensity-scored matching. METHODS:Patients with T1c-cT2b significant PCa (high-volume ISUP 1 or any 2/3) who received unifocal IRE were pair-matched to patients who received nerve-sparing RARP. Patient-reported outcomes were prospectively assessed using the Expanded Prostate Cancer Index Composite (EPIC), AUA symptom score and Short Form of Health Survey (SF-12) physical and mental components. Oncological failure was defined as biochemical recurrence (RARP) or positive follow-up biopsies (IRE). Generalized mixed-effect models were used to compare IRE and RARP. RESULTS:50 IRE patients were matched to 50 RARP patients by propensity score. IRE was significantly superior to RARP in preserving pad-free continence (UC) and erections sufficient for intercourse (ESI). The absolute differences were 44, 21, 13, 14% for UC and 32, 46, 27, 22% for ESI at 1.5, 3, 6, and 12 months, respectively. The EPIC summary scores showed no statistically significant differences. Urinary symptoms were reduced for IRE and RARP patients at 12 months, although IRE patient initially had more complaints. IRE patients experienced more early oncological failure than RARP patients. CONCLUSIONS:These data demonstrated the superior preservation of UC and ESI with IRE compared to RARP up to 12 months after treatment. Long-term oncological data are warranted to provide ultimate proof for or against focal therapy.

Schmitt, J, Wiegand, M & Deuse, J 2018, 'Qualitätsbasierte Auftrags-zuordnung', Zeitschrift für wirtschaftlichen Fabrikbetrieb, vol. 113, no. 4, pp. 191-194.
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Kurzfassung Die Gewährleistung durchgängiger Qualität ist für Unternehmen ein wesentlicher Wettbewerbsfaktor. Die Qualitätsanforderungen des Kunden an ein Produkt können dabei sehr unterschiedlich sein. Im Rahmen dieses Fachbeitrags wird ein Konzept zur optimalen Zuordnung von Zwischenprodukten zu Kundenaufträgen aus dem Auftragsbestand auf Basis von Qualitätsprognosen vorgestellt. Ziel des Konzepts ist die Reduzierung von Ausschuss und Lieferterminabweichungen.

Schönbach, C, Li, J, Ma, L, Horton, P, Sjaugi, MF & Ranganathan, S 2018, 'A bioinformatics potpourri', BMC Genomics, vol. 19, no. S1.
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Seibers, ZD, Le, TP, Lee, Y, Gomez, ED & Kilbey, SM 2018, 'Impact of Low Molecular Weight Poly(3-hexylthiophene)s as Additives in Organic Photovoltaic Devices', ACS Applied Materials & Interfaces, vol. 10, no. 3, pp. 2752-2761.
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Seo, DH, Pineda, S, Woo, YC, Xie, M, Murdock, AT, Ang, EYM, Jiao, Y, Park, MJ, Lim, SI, Lawn, M, Borghi, FF, Han, ZJ, Gray, S, Millar, G, Du, A, Shon, HK, Ng, TY & Ostrikov, K 2018, 'Anti-fouling graphene-based membranes for effective water desalination', Nature Communications, vol. 9, no. 1.
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AbstractThe inability of membranes to handle a wide spectrum of pollutants is an important unsolved problem for water treatment. Here we demonstrate water desalination via a membrane distillation process using a graphene membrane where water permeation is enabled by nanochannels of multilayer, mismatched, partially overlapping graphene grains. Graphene films derived from renewable oil exhibit significantly superior retention of water vapour flux and salt rejection rates, and a superior antifouling capability under a mixture of saline water containing contaminants such as oils and surfactants, compared to commercial distillation membranes. Moreover, real-world applicability of our membrane is demonstrated by processing sea water from Sydney Harbour over 72 h with macroscale membrane size of 4 cm2, processing ~0.5 L per day. Numerical simulations show that the channels between the mismatched grains serve as an effective water permeation route. Our research will pave the way for large-scale graphene-based antifouling membranes for diverse water treatment applications.

Setiadi, H, Krismanto, AU, Mithulananthan, N & Hossain, MJ 2018, 'Modal interaction of power systems with high penetration of renewable energy and BES systems', International Journal of Electrical Power & Energy Systems, vol. 97, pp. 385-395.
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Integration of renewable energy sources (RESs) at transmission level is getting popular in the recent years. RESs have advantages of generating clean and environmentally friendly electricity. However, due to the uncertainty and less inertia characteristic of the RESs based power plant, it can bring negative impacts on small signal stability which is also known as low-frequency oscillatory stability. Hence, utilizing an additional device, such as battery energy storage (BES) in power system with high penetration of RESs is inevitable. BES system could provide additional active power to the grid to overcome the shortfall energy from RESs. Conversely, BES installation may also introduce negative impact on system dynamic in terms of possible interaction with other elements of the power system. Therefore, proper gain control setting of BES is required to avoid undesirable interaction and make sure system stability. This paper investigates the impact of gain variation in BES controller to oscillatory stability and modal interaction on the power system. Eigenvalue trajectories, participation factor and time domain simulation of the critical modes are thoroughly investigated. Influence of the capacity of BES and its location on damping ratio of weak modes is also examined in the paper. Moreover, the mitigation of modal interaction occurrence through BES gain tuning using metaheuristic algorithms is proposed in this paper. From the simulation results, it was found that increasing BES's gain controller could lead to the interaction events. It was also reported that the proposed tuning method is feasible to mitigate the occurrence of modal interaction.

Shafaghat, A, Khabbaz, H, Moravej, S & Shafaghat, A 2018, 'Effect of footing shape on bearing capacity and settlement of closely spaced footings on sandy soil', International Journal of Geotechnical and Geological Engineering, vol. 12, no. 11.

Shahsavari, M, Golpayegani, AH, Saberi, M & Hussain, FK 2018, 'Recruiting the K-most influential prospective workers for crowdsourcing platforms', Service Oriented Computing and Applications, vol. 12, no. 3-4, pp. 247-257.
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© 2018, Springer-Verlag London Ltd., part of Springer Nature. Viral marketing is widely used by businesses to achieve their marketing objectives using social media. In this work, we propose a customized crowdsourcing approach for viral marketing which aims at efficient marketing based on information propagation through a social network. We term this approach the social community-based crowdsourcing platform and integrate it with an information diffusion model to find the most efficient crowd workers. We propose an intelligent viral marketing framework (IVMF) comprising two modules to achieve this end. The first module identifies the K-most influential users in a given social network for the platform using a novel linear threshold diffusion model. The proposed model considers the different propagation behaviors of the network users in relation to different contexts. Being able to consider multiple topics in the information propagation model as opposed to only one topic makes our model more applicable to a diverse population base. Additionally, the proposed content-based improved greedy (CBIG) algorithm enhances the basic greedy algorithm by decreasing the total amount of computations required in the greedy algorithm (the total influence propagation of a unique node in any step of the greedy algorithm). The highest computational cost of the basic greedy algorithm is incurred on computing the total influence propagation of each node. The results of the experiments reveal that the number of iterations in our CBIG algorithm is much less than the basic greedy algorithm, while the precision in choosing the K influential nodes in a social network is close to the greedy algorithm. The second module of the IVMF framework, the multi-objective integer optimization model, is used to determine which social network should be targeted for viral marketing, taking into account the marketing budget. The overall IVMF framework can be used to select a social network and rec...

Shahzad Iqbal, M & Esselle, KP 2018, 'Pulse‐preserving characteristics and effective isotropically radiated power spectra of a new ultrawideband dielectric resonator antenna', IET Microwaves, Antennas & Propagation, vol. 12, no. 7, pp. 1231-1238.
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A dielectric resonator antenna (DRA) with a full ground plane and an ultrawideband (UWB) operating bandwidth of 3.1–11.6 GHz is presented. Good return loss over a wide bandwidth is achieved, while the full ground plane directs most of the radiation into the upper hemisphere, significantly reducing undesirable radiation to the lower hemisphere. The measured results confirm a 10‐dB return‐loss bandwidth of 115%. Time‐domain characteristics and effective isotropically radiated power (EIRP) spectra of the antenna are investigated for several types of UWB input pulses. The correlations between the input pulses and the radiated pulses in many directions were found to be excellent when the antenna is excited by a linearly chirped Gaussian pulse or a fifth‐order Gaussian pulse. Nevertheless, EIRP spectrum calculations indicate that none of those pulses efficiently fill the Federal Communication Commission UWB mask when applied to this DRA. Hence, a third‐order Rayleigh pulse is introduced and tuned to make efficient use of the allowed spectrum limits. Further improvement of pulse performance is investigated by varying antenna design parameters. This DRA is suitable for both impulse radio UWB systems and carrier‐based UWB systems.

Shannon, A, Miteva, B, Sotirova, E, Atanassov, K & Kim, T 2018, 'A generalized net model of information flow within a school', Advanced Studies in Contemporary Mathematics (Kyungshang), vol. 28, no. 4, pp. 699-706.
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A generalized net is used to construct a model which describes the organization of the processes for information exchange among the different units within a school. The model can be applied for both the analysis and the optimization of the flow of information.

Shannon, RM, Macquart, J-P, Bannister, KW, Ekers, RD, James, CW, Osłowski, S, Qiu, H, Sammons, M, Hotan, AW, Voronkov, MA, Beresford, RJ, Brothers, M, Brown, AJ, Bunton, JD, Chippendale, AP, Haskins, C, Leach, M, Marquarding, M, McConnell, D, Pilawa, MA, Sadler, EM, Troup, ER, Tuthill, J, Whiting, MT, Allison, JR, Anderson, CS, Bell, ME, Collier, JD, Gürkan, G, Heald, G & Riseley, CJ 2018, 'The dispersion–brightness relation for fast radio bursts from a wide-field survey', Nature, vol. 562, no. 7727, pp. 386-390.
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Shao, R, Wu, C, Liu, Z, Su, Y, Liu, J, Chen, G & Xu, S 2018, 'Penetration resistance of ultra-high-strength concrete protected with layers of high-toughness and lightweight energy absorption materials', Composite Structures, vol. 185, pp. 807-820.
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© 2017 Elsevier Ltd Aluminium foam has advantages of excellent shock absorption, cyclic utilization, and lightweight. Ultra-high-molecular-weight polyethylene (UHMWPE) fibre has a low density, a high specific strength, a high modulus and a great capability in energy absorption. Steel wire mesh has high toughness and elongation properties and a good effect on energy absorption. In the present study, UHMWPE fibre, steel wire mesh and aluminium foam were used to protect ultra-high-strength concrete (UHSC) targets to resist DT300 high-strength alloy-steel projectile penetration with striking velocities from 550 m/s to 800 m/s. High-speed impact tests on normal-strength concrete (NSC) targets were also conducted for comparison. Testing results including the failure mode, depth of penetration (DOP), crater dimensions and damage area of protected concrete targets, indicate that the new composite material protective cover has an outstanding performance in the shock wave absorption, especially in reducing the crack propagation and debris spatter of protected UHSC targets, as well as increasing the deviation angles of projectile terminal ballistic trajectories. It is a successful demonstration of anti-penetration properties research for new concrete composite structures.

Sharafi, P, Mortazavi, M, Samali, B & Ronagh, H 2018, 'Interlocking system for enhancing the integrity of multi-storey modular buildings', Automation in Construction, vol. 85, pp. 263-272.
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Maintaining the structural integrity against severe loading conditions and accidental loads is one of the primary concerns when designing multi-storey modular buildings. Connections between the modular units play a central role in providing integrity in modular buildings. This paper describes the development of an innovative interlocking system for improving the integrity of multi-storey modular buildings. The concept of Modular Integrating System (MIS) and the procedure used to develop an efficient interlocking system, which can be widely used in the construction of modular buildings, is investigated. MIS is a patented joining system including a set of interlocking connections and the method of assembly of modular units that provides a high level of integrity that prevents accidental disassembly and stress concentrations at the points of attachments in case of extreme loading occurrence. The creative easy to install, self-fit and self-locking mechanism of this system can also considerably facilitate the automated assembly of modular buildings and provide an effective solution for controlling construction tolerance. The robustness provided by the proposed system is demonstrated through numerical and experimental analysis.

Sharafi, P, Mortazavi, M, Usefi, N, Kildashti, K, Ronagh, H & Samali, B 2018, 'Lateral force resisting systems in lightweight steel frames: Recent research advances', Thin-Walled Structures, vol. 130, pp. 231-253.
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Lightweight Steel Frames (LSF) made by framing thin gauge cold-formed steel (CFS) into different structural elements such as walls, trusses and joists are commonplace in Australia and many parts of the world. The great progress in the knowledge of CFS structures achieved in the past two decades, together with the modern design and fabrication methods supported by progressively improved specifications, have equipped the industry of the lightweight steel construction with tools and confidence to play an important part in the future of building construction. Despite the ever-increasing demand on the use of cold formed steel (CFS) framing into more complex and taller structures, the lateral load resistance capacity of lightweight steel frames has proven to be a major hindrance and a major concern. This paper reviews and summarises the research developments made in the area of lateral load resistance capacity of lightweight steel frames (LSF) as published in leading journals and codes’ provisions in the area. Research advances in conventional systems such as shear walls clad with face sheathings and LSF strap-braced wall systems in addition to other less conventional systems such as special bolted moment frames are reviewed here, and the solutions for improving the lateral performance of these systems are classified.

Sharafi, P, Rashidi, M, Samali, B, Ronagh, H & Mortazavi, M 2018, 'Identification of Factors and Decision Analysis of the Level of Modularization in Building Construction', Journal of Architectural Engineering, vol. 24, no. 2, pp. 04018010-04018010.
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In the majority of ordinary housing development projects, instead of using complex multicriteria decision-making systems, companies still rely on expert knowledge, checklists, or similar tools to decide on an appropriate level of modularization. Generally, in these types of projects the level of modularization is mainly driven by site constraints, such as accessibility and harsh weather conditions. Because of the lack of appropriate decision support tools, it is very hard for decision makers to include factors, such as lifecycle costs, quality, productivity, efficiency, and design complexity, into their decision, even if they are willing to do so. Simple decision support tools are required to provide practical assistance to the decision makers to adopt an appropriate level of modularization for such projects. This study, as a part of a broad ongoing research project on the optimum level of modularization in building construction, has compiled the expert knowledge for decision support that enables the decision makers to perform an easy initial feasibility study on the use of an appropriate level of modularization in their construction projects. First, a list of critical decision-making criteria is created. These criteria are obtained from an extensive literature review, qualitative survey questionnaires, and semistructured interviews with researchers and professionals in the construction industry as well as modular manufacturers. Then, using the results, a simple multicriteria decision analysis (MCDA) approach is developed as a practical decision support system to facilitate the decision-making process for selecting appropriate construction systems as well as determining the proper level of modularization for building construction projects. The validation of the study is demonstrated through a local actual case study.

Shariati, N, Scott, JR, Schreurs, D & Ghorbani, K 2018, 'Multitone Excitation Analysis in RF Energy Harvesters—Considerations and Limitations', IEEE Internet of Things Journal, vol. 5, no. 4, pp. 2804-2816.
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© 2018 IEEE. The effect of multitone excitation on the dc response of a voltage-doubler radio frequency energy harvester is analyzed. Theoretical analysis as well as frequency and time domain (TD) simulations were conducted to clarify the findings. Measurements were also carried out to validate the results. The measured, simulations and theoretical results are in good agreement. This paper focuses on evaluating the performance of a voltage doubler rectifier under multitone excitation (input power is the same in the single-tone and multitone case). Based on TD and harmonic balance simulations, theoretical and measurement analyses, it is evident that the application of multiple tones simultaneously within the matched frequency band and with the same average available power results in a lower average output dc power when compared with the single-tone case with the same input power. This trend is evident over a broad low input power range of −50 to −10 dBm (0.01–100 µW).

Sharifian, A, Fathi Sasansara, S, Ghadi, MJ, Ghavidel, S, Li, L & Zhang, J 2018, 'Dynamic performance improvement of an ultra-lift Luo DC–DC converter by using a type-2 fuzzy neural controller', Computers & Electrical Engineering, vol. 69, pp. 171-182.
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© 2018 Due to the uncertainty associated with the structure and electrical elements of DC–DC converters and the nonlinear performance of these modules, designing an effective controller is highly complicated and also technically challenging. This paper employs a new control approach based on type-2 fuzzy neural controller (T2FNC) in order to improve the dynamic response of an ultra-lift Luo DC–DC converter under different operational conditions. The proposed controller can rapidly stabilize the output voltage of converter to expected values by tuning the converter switching duty cycle. This controller can tackle the uncertainties associated with the structure of converters, measured control signals and measuring devices. Moreover, a new intelligent method based on firefly algorithm is applied to tune the parameters of T2FNC. In order to demonstrate the effectiveness of the proposed control approach, the proposed controller is compared to PI and fuzzy controllers under different operational conditions. Results validate efficiency of proposed T2FNC.

Sharifian, A, Ghadi, MJ, Ghavidel, S, Li, L & Zhang, J 2018, 'A new method based on Type-2 fuzzy neural network for accurate wind power forecasting under uncertain data', Renewable Energy, vol. 120, pp. 220-230.
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© 2017 Elsevier Ltd Nowadays, due to some environmental restrictions and decrease of fossil fuel sources, renewable energy sources and specifically wind power plants have a major part of energy generation in the industrial countries. To this end, the accurate forecasting of wind power is considered as an important and influential factor for the management and planning of power systems. In this paper, a novel intelligent method is proposed to provide an accurate forecast of the medium-term and long-term wind power by using the uncertain data from an online supervisory control and data acquisition (SCADA) system and the numerical weather prediction (NWP). This new method is based on the particle swarm optimization (PSO) algorithm and applied to train the Type-2 fuzzy neural network (T2FNN) which is called T2FNN-PSO. The presented method combines both of fuzzy system's expert knowledge and the neural network's learning capability for accurate forecasting of the wind power. In addition, the T2FNN-PSO can appropriately handle the uncertainties associated with the measured parameters from SCADA system, the numerical weather prediction and measuring tools. The proposed method is applied on a case study of a real wind farm. The obtained simulation results validate effectiveness and applicability of the proposed method for a practical solution to an accurate wind power forecasting in a power system control center.

Sharwood, LN, Adams, S, Blaszkow, T & Eager, D 2018, 'Increasing injuries as trampoline parks expand within Australia: a call for mandatory standards', Australian and New Zealand Journal of Public Health, vol. 42, no. 2, pp. 153-156.
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© 2018 The Authors Objective: To quantify an apparent increase in indoor trampoline park related injuries in children and young people across Australia, and to understand the implications for current regulatory standards. Methods: Retrospective analyses of three state-based Injury Surveillance databases, identifying children and adolescents presenting to emergency departments between the years 2005 and 2017, who had sustained injuries during trampolining activity at an indoor trampoline park. Results: Across the three datasets, 487 cases were identified. No cases were recorded prior to 2012, the year the first indoor trampoline park opened. At least half occurred among those aged 10–14 years. In Victoria, 58% were male, with 52% in Queensland and 60% in Western Australia being male, respectively. Hospital admission rates in these states were 15%, 11.7% and 14.5%, respectively. The most frequent injury types were dislocations, sprains and strains, followed by fractures, with some head and spinal injuries. Conclusions: Across several states in Australia, the incidence of indoor trampoline park related injuries is concerning, as these venues are increasing in number. Some injuries can be serious and result in lifelong disability for children or adolescents. Implications for public health: National safety standards that apply to indoor trampoline park operators are not currently mandatory; injury prevention efforts would be assisted if such standards were mandatory.

She, Z, Wu, L, Wang, Q, Gao, M, Jin, C, Zhao, Y, Zhao, L & Guo, L 2018, 'Salinity effect on simultaneous nitrification and denitrification, microbial characteristics in a hybrid sequencing batch biofilm reactor', Bioprocess and Biosystems Engineering, vol. 41, no. 1, pp. 65-75.
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Shen, J, Hung, C-C, Beydoun, G, Li, Y & Guo, WW 2018, 'Data-Centric Intelligent Computing: Preface.', Int. J. Comput. Intell. Syst., vol. 11, no. 1, pp. 616-617.
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Shen, S, Huang, L, Zhou, H, Yu, S, Fan, E & Cao, Q 2018, 'Multistage Signaling Game-Based Optimal Detection Strategies for Suppressing Malware Diffusion in Fog-Cloud-Based IoT Networks', IEEE Internet of Things Journal, vol. 5, no. 2, pp. 1043-1054.
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© 2018 IEEE. We consider the Internet of Things (IoT) with malware diffusion and seek optimal malware detection strategies for preserving the privacy of smart objects in IoT networks and suppressing malware diffusion. To this end, we propose a malware detection infrastructure realized by an intrusion detection system (IDS) with cloud and fog computing to overcome the IDS deployment problem in smart objects due to their limited resources and heterogeneous subnetworks. We then employ a signaling game to disclose interactions between smart objects and the corresponding fog node because of malware uncertainty in smart objects. To minimize privacy leakage of smart objects, we also develop optimal strategies that maximize malware detection probability by theoretically computing the perfect Bayesian equilibrium of the game. Moreover, we analyze the factors influencing the optimal probability of a malicious smart object diffusing malware, and factors influencing the performance of a fog node in determining an infected smart object. Finally, we present a framework to demonstrate a potential and practical application of suppressing malware diffusion in IoT networks.

Shen, X, Liu, W, Tsang, IW, Sun, Q-S & Ong, Y-S 2018, 'Multilabel Prediction via Cross-View Search', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 9, pp. 4324-4338.
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© 2012 IEEE. Embedding methods have shown promising performance in multilabel prediction, as they are able to discover the label dependence. However, most methods ignore the correlations between the input and output, such that their learned embeddings are not well aligned, which leads to degradation in prediction performance. This paper presents a formulation for multilabel learning, from the perspective of cross-view learning, that explores the correlations between the input and the output. The proposed method, called Co-Embedding (CoE), jointly learns a semantic common subspace and view-specific mappings within one framework. The semantic similarity structure among the embeddings is further preserved, ensuring that close embeddings share similar labels. Additionally, CoE conducts multilabel prediction through the cross-view k nearest neighborhood (k NN) search among the learned embeddings, which significantly reduces computational costs compared with conventional decoding schemes. A hashing-based model, i.e., Co-Hashing (CoH), is further proposed. CoH is based on CoE, and imposes the binary constraint on continuous latent embeddings. CoH aims to generate compact binary representations to improve the prediction efficiency by benefiting from the efficient k NN search of multiple labels in the Hamming space. Extensive experiments on various real-world data sets demonstrate the superiority of the proposed methods over the state of the arts in terms of both prediction accuracy and efficiency.

Sheng, Z, Tuan, HD, Duong, TQ & Poor, HV 2018, 'Beamforming Optimization for Physical Layer Security in MISO Wireless Networks', IEEE Transactions on Signal Processing, vol. 66, no. 14, pp. 3710-3723.
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© 1991-2012 IEEE. A wireless network of multiple transmitter-user pairs overheard by an eavesdropper, where the transmitters are equipped with multiple antennas, while the users and eavesdropper are equipped with a single antenna, is considered. At different levels of wireless channel knowledge, the problem of interest is beamforming to optimize the users' quality-of-service (QoS) in terms of their secrecy throughputs or maximize the network's energy efficiency under users' QoS. All these problems are seen as very difficult optimization problems with many nonconvex constraints and nonlinear equality constraints in beamforming vectors. The paper develops path-following computational procedures of low complexity and rapid convergence for the optimal beamforming solution. Their practicability is demonstrated through numerical examples.

Sheng, Z, Tuan, HD, Duong, TQ & Poor, HV 2018, 'Outage-Aware Secure Beamforming in MISO Wireless Interference Networks', IEEE Signal Processing Letters, vol. 25, no. 7, pp. 956-960.
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Sheng, Z, Tuan, HD, Duong, TQ, Poor, HV & Fang, Y 2018, 'Low-Latency Multiuser Two-Way Wireless Relaying for Spectral and Energy Efficiencies', IEEE Transactions on Signal Processing, vol. 66, no. 16, pp. 4362-4376.
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Sheng, Z, Tuan, HD, Nasir, AA, Duong, TQ & Poor, HV 2018, 'Power Allocation for Energy Efficiency and Secrecy of Wireless Interference Networks', IEEE Transactions on Wireless Communications, vol. 17, no. 6, pp. 3737-3751.
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© 2002-2012 IEEE. Considering a multi-user interference network with an eavesdropper, this paper aims at the power allocation to optimize the worst secrecy throughput among the network links or the secure energy efficiency in terms of achieved secrecy throughput per Joule under link security requirements. Three scenarios for the access of channel state information are considered: the perfect channel state information; partial channel state information with channels from the transmitters to the eavesdropper exponentially distributed; and not perfectly known channels between the transmitters and the users with exponentially distributed errors. The paper develops various path-following procedures of low complexity and rapid convergence for the optimal power allocation. Their effectiveness and viability are illustrated through numerical examples. The power allocation schemes are shown to achieve both high secrecy throughput and energy efficiency.

Sheu, A, Chan, Y, Ferguson, A, Bakhtyari, MB, Hawke, W, White, C, Chan, YF, Bertolino, PJ, Woon, HG, Palendira, U, Sierro, F & Lau, SM 2018, 'A proinflammatory CD4+ T cell phenotype in gestational diabetes mellitus', Diabetologia, vol. 61, no. 7, pp. 1633-1643.
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SHI, G, ZHU, LIN & WEI, D 2018, 'A NEW PREDICTION APPROACH FOR THE STRUCTURAL FATIGUE LIFE BASED ON MULTI-FACTOR CORRECTION', Surface Review and Letters, vol. 25, no. 05, pp. 1850095-1850095.
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As the phenomenon of fatigue damage is a common failure mode of equipment, the reliability evaluation and life prediction have become a hot-spot. The precise prediction of fatigue life in the initiation stage has become necessary. The common prediction study for structural fatigue life takes less influence factors into consideration. The common prediction results of fatigue life cannot be quantitatively corrected by the influence factors at the same time. This paper presents a research on the prediction approach for structural fatigue life based on the multi-factor correction. The influence of some factors on the fatigue life was analyzed and the prediction approach for structural fatigue life based on multi-factor correction was raised. Then the fatigue life of axle housing was predicted by using the corrected approach, as the case study. Moreover, the result predicted by the local stress–strain approach and the experimental data were used to verify the accuracy of the corrected approach. It can be clearly demonstrated by the results that the corrected prediction approach can be used to achieve the precision fatigue life for engineering structures. Further, it is also a prediction approach endowed with engineering application prospects.

Shi, L & Miro, JV 2018, 'Towards optimised and reconstructable sampling inspection of pipe integrity for improved efficiency of non-destructive testing', Water Supply, vol. 18, no. 2, pp. 515-523.
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Abstract This work proposes a sampling inspection framework for point measurement non-destructive testing of pipelines to improve its time and cost efficiencies. Remaining pipe wall thickness data from limited dense inspection are modelled with spatial statistics approaches. The spatial dependence in the available data and some subjective requirements provide a reference for selecting a most efficient sampling inspection scheme. With the learned model and the selected sampling scheme, the effort of inspecting the residual part of the same pipeline or cohort will be significantly reduced from dense inspection to sampling inspection, and the full information can be reconstructed from samples while maintaining a reasonable accuracy. The recovered thickness map can be used as an equivalent measure to the dense inspection for subsequent structural analysis for failure risk estimation or remaining life assessment.

Shi, X, Ngo, HH, Sang, L, Jin, P, Wang, XC & Wang, G 2018, 'Functional evaluation of pollutant transformation in sediment from combined sewer system', Environmental Pollution, vol. 238, pp. 85-93.
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© 2018 Elsevier Ltd In this study, a pilot combined sewer system was constructed to characterize the pollutant transformation in sewer sediment. The results showed that particulate contaminants deposited from sewage could be transformed into dissolved matter by distinct pollutant transformation pathways. Although the oxidation-reduction potential (ORP) was varied from −80 mV to −340 mV in different region of the sediment, the fermentation was the dominant process in all regions of the sediment, which induced hydrolysis and decomposition of particulate contaminants. As a result, the accumulation of dissolved organic matter and the variation of ORP values along the sediment depth led to the depth-dependent reproduction characteristics of methanogens and sulfate-reducing bacteria, which were existed in the middle and deep layer of the sediment respectively. However, the diversity of nitrifying and polyphosphate-accumulating bacteria was low in sewer sediment and those microbial communities showed a non-significant correlation with nitrogen and phosphorus contaminants, which indicated that the enrichment of nitrogen and phosphorus contaminants was mainly caused by physical deposition process. Thus, this study proposed a promising pathway to evaluate pollutant transformation and can help provide theoretical foundation for urban sewer improvement.

Shi, X, Zhu, S, Ni, YQ & Li, J 2018, 'Vibration suppression in high-speed trains with negative stiffness dampers', Smart Structures and Systems, vol. 21, no. 5, pp. 653-668.
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This work proposes and investigates re-centering negative stiffness dampers (NSDs) for vibration suppression in high-speed trains. The merit of the negative stiffness feature is demonstrated by active controllers on a high-speed train. This merit inspires the replacement of active controllers with re-centering NSDs, which are more reliable and robust than active controllers. The proposed damper design consists of a passive magnetic negative stiffness spring and a semi-active positioning shaft for re-centering function. The former produces negative stiffness control forces, and the latter prevents the amplification of quasi-static spring deflection. Numerical investigations verify that the proposed re-centering NSD can improve ride comfort significantly without amplifying spring deflection.

Shi, Y, Tuan, HD, Apkarian, P & Savkin, AV 2018, 'Global optimal power flow over large-scale power transmission networks', Systems & Control Letters, vol. 118, pp. 16-21.
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© 2018 Elsevier B.V. Optimal power flow (OPF) over power transmission networks poses challenging large-scale nonlinear optimization problems, which involve a large number of quadratic equality and indefinite quadratic inequality constraints. These computationally intractable constraints are often expressed by linear constraints plus matrix additional rank-one constraints on the outer products of the voltage vectors. The existing convex relaxation technique, which drops the difficult rank-one constraints for tractable computation, cannot yield even a feasible point. We address these computationally difficult problems by an iterative procedure, which generates a sequence of improved points that converges to a rank-one solution. Each iteration calls a semi-definite program. Intensive simulations for the OPF problems over networks with a few thousands of buses are provided to demonstrate the efficiency of our approach. The suboptimal values of the OPF problems found by our computational procedure turn out to be the global optimal value with computational tolerance less than 0.01%.

Shibuya, M, Park, MJ, Lim, S, Phuntsho, S, Matsuyama, H & Shon, HK 2018, 'Novel CA/PVDF nanofiber supports strategically designed via coaxial electrospinning for high performance thin-film composite forward osmosis membranes for desalination', Desalination, vol. 445, pp. 63-74.
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© 2018 Elsevier B.V. This study introduces a novel electrospun nanofiber mat fabricated via coaxial electrospinning as a support for high performance thin-film composite (TFC) forward osmosis (FO) membrane. This method produces a dual layer composite nanofiber support consisted of a polyvinylidene fluoride (PVDF) core layer and a cellulose acetate (CA) sheath layer, which provide mechanical stability and hydrophilicity, respectively. The CA sheath layer aims to cover the hydrophobic core layer and improve its hydrophilicity. The TFC FO membrane with coaxial electrospun CA/PVDF support layer not only showed high improvement in water flux due to improved hydrophilicity, but also exhibited comparable mechanical strength with pure PVDF nanofiber support. After FO operation using 0.5 M NaCl as draw solution and deionized water as feed solution, the coaxial electrospun CA/PVDF composite based TFC-FO membrane achieved the following: water flux of 31.2 L m−2 h−1, remarkably lower specific reverse salt flux of 0.03 g L−1, and low structural parameter of 190 μm. Coaxial electrospinning is therefore a promising approach to fabricate high performance FO membrane whose support exhibits high porosity, mechanical stability, and hydrophilicity.

Shiozaki, T & Dissanayake, G 2018, 'Eliminating Scale Drift in Monocular SLAM Using Depth From Defocus', IEEE Robotics and Automation Letters, vol. 3, no. 1, pp. 581-587.
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This letter presents a novel approach to correct errors caused by accumulated scale drift in monocular SLAM. It is shown that the metric scale can be estimated using information gathered through monocular SLAM and image blur due to defocus. A nonlinear least squares optimization problem is formulated to integrate depth estimates from defocus to monocular SLAM. An algorithm to process the output keyframe and feature location estimates generated by a monocular SLAM algorithm to correct for scale drift at selected local regions of the environment is presented. The proposed algorithm is experimentally evaluated by processing the output of ORB-SLAM to obtain accurate metric scale maps from a monocular camera without any prior knowledge about the scene.

Shirzadi, A, Soliamani, K, Habibnejhad, M, Kavian, A, Chapi, K, Shahabi, H, Chen, W, Khosravi, K, Thai Pham, B, Pradhan, B, Ahmad, A, Bin Ahmad, B & Tien Bui, D 2018, 'Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping', Sensors, vol. 18, no. 11, pp. 3777-3777.
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The main objective of this research was to introduce a novel machine learning algorithm of alternating decision tree (ADTree) based on the multiboost (MB), bagging (BA), rotation forest (RF) and random subspace (RS) ensemble algorithms under two scenarios of different sample sizes and raster resolutions for spatial prediction of shallow landslides around Bijar City, Kurdistan Province, Iran. The evaluation of modeling process was checked by some statistical measures and area under the receiver operating characteristic curve (AUROC). Results show that, for combination of sample sizes of 60%/40% and 70%/30% with a raster resolution of 10 m, the RS model, while, for 80%/20% and 90%/10% with a raster resolution of 20 m, the MB model obtained a high goodness-of-fit and prediction accuracy. The RS-ADTree and MB-ADTree ensemble models outperformed the ADTree model in two scenarios. Overall, MB-ADTree in sample size of 80%/20% with a resolution of 20 m (area under the curve (AUC) = 0.942) and sample size of 60%/40% with a resolution of 10 m (AUC = 0.845) had the highest and lowest prediction accuracy, respectively. The findings confirm that the newly proposed models are very promising alternative tools to assist planners and decision makers in the task of managing landslide prone areas.

Shu, L, Chiemchaisri, C, Nghiem, LD & Jegatheesan, JV 2018, 'Challenges in Environmental Science and Engineering, CESE-2017: 11–15 Nov. 2017, Kunming, China', Bioresource Technology, vol. 263, pp. 679-680.
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Siahaan, F, Indraratna, B, Ngo, NT, Rujikiatkamjorn, C & Heitor, A 2018, 'Influence of Particle Gradation and Shape on the Performance of Stone Columns in Soft Clay', Geotechnical Testing Journal, vol. 41, no. 6, pp. 1076-1091.
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Abstract A stone column typically consists of particles whose influence has largely been overlooked in design practice in terms of stress transfer, pattern of deformation, and intrusion of fines (clogging). This article presents an experimental study on the load-deformation behavior of a model stone column installed in soft clay with a particular emphasis on the influence of particle gradation and shape under undrained loading. The results show that particle gradation and shape have a significant influence on the load-deformation behavior and the extent of fines intrusion into the stone columns. Relatively well-graded particle sizes favor the development of higher peak shear stresses accompanied by lateral bulging, whereas more uniform grading results in the development of distinct shear planes and smaller peak shear stresses. Deformed columns were also examined using computed tomography, and the porosity profiles at the end of the test were determined using micrographs. Maximum porosity typically occurred in the zone of extreme lateral deformation, with the results suggesting that the extent of fines intrusion was influenced by particle morphology.

Sick, N, Bröring, S & Figgemeier, E 2018, 'Start-ups as technology life cycle indicator for the early stage of application: An analysis of the battery value chain', Journal of Cleaner Production, vol. 201, pp. 325-333.
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© 2018 Elsevier Ltd Insights from battery research and development (R&D) need to be transferred into industrial application to create innovations and thus foster e.g. electro mobility. In terms of battery technology transfer, the early phase of application is particularly challenging due to the close intertwining between R&D and application. Therefore, the present study introduces start-ups as an additional indicator to capture the transition from science to industry within the technology life cycle. The findings show that despite highly dynamic R&D activities, technology transfer is only taking place on a very limited level. Surprisingly, start-ups focus on incremental improvements of existing technologies instead of introducing radical breakthrough-technologies. An analysis of the battery value chain reveals that opportunities for start-ups are rather located downstream in the value chain when integrating cells to battery systems and developing applications relying on innovative battery technologies. The findings contribute to the area of technology life cycle analysis explicitly using start-up companies as additional indicator for the critical transfer step from R&D to application. In a similar vein, technology forecasting literature, which is to date mainly focused on R&D, is expanded by a more application-centred perspective that allows identifying transfer opportunities along the technology value chain.

Siddiqi, MWU, Tu, C & Lee, JE-Y 2018, 'Effect of mode order, resonator length, curvature, and electrode coverage on enhancing the performance of biconvex resonators', Journal of Micromechanics and Microengineering, vol. 28, no. 9, pp. 094002-094002.
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Siedelhofer, C, Schallow, J, Wolf, P, Mayer, S & Deuse, J 2018, 'Simulationsbasierte Rekonfigurationsplanung flexibler Montagesysteme', Zeitschrift für wirtschaftlichen Fabrikbetrieb, vol. 113, no. 4, pp. 216-219.
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Kurzfassung Die Rekonfiguration flexibler Montagesysteme erfolgt in immer kürzeren Zyklen, was zu einem erhöhten Planungsaufwand führt. Zur Unterstützung der Montageplanung und Erhöhung der Planungs-qualität wird eine Planungssystematik für die Rekonfiguration entwickelt. Die Planungsmethode basiert auf einem integrierten, digitalen Planungswerkzeug, welches ein PLM-System und ein Simulationswerkzeug konsistent verknüpft.

Siksnelyte, I, Zavadskas, EK, Streimikiene, D & Sharma, D 2018, 'An Overview of Multi-Criteria Decision-Making Methods in Dealing with Sustainable Energy Development Issues', Energies, vol. 11, no. 10, pp. 2754-2754.
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The measurement of sustainability is actively used today as one of the main preventative instruments in order to reduce the decline of the environment. Sustainable decision-making in solving energy issues can be supported and contradictory effects can be evaluated by scientific achievements of multi-criteria decision-making (MCDM) techniques. The main goal of this paper is to overview the application of decision-making methods in dealing with sustainable energy development issues. In this study, 105 published papers from the Web of Science Core Collection (WSCC) database are selected and reviewed, from 2004 to 2017, related to energy sustainability issues and MCDM methods. All the selected papers were categorized into 9 fields by the application area and into 10 fields by the used method. After the categorization of the scientific articles and detailed analysis, SWOT analysis of MCDM approaches in dealing with sustainable energy development issues is provided. The widespread application and use of MCDM methods confirm that MCDM methods can help decision-makers in solving energy sustainability problems and are highly popular and used in practice.

Sili, I 2018, 'PARAMETERS OF THE IMPULSE GENERATOR BASED ON IMPATT DIODES FOR THE POTATO`S PESTS EXTERMINATION PURPOSE', Scientific bulletin of the Tavria Agrotechnological State University, vol. 8, no. 2.
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Silitonga, AS, Masjuki, HH, Ong, HC, Sebayang, AH, Dharma, S, Kusumo, F, Siswantoro, J, Milano, J, Daud, K, Mahlia, TMI, Chen, W-H & Sugiyanto, B 2018, 'Evaluation of the engine performance and exhaust emissions of biodiesel-bioethanol-diesel blends using kernel-based extreme learning machine', Energy, vol. 159, pp. 1075-1087.
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© 2018 Elsevier Ltd It is known that biodiesel and bioethanol are viable alternative fuels to replace diesel for compression ignition engines. In this study, an experimental investigation is carried out to evaluate the performance and exhaust emissions of a single cylinder diesel engine fuelled with biodiesel-bioethanol-diesel blends. The engine performance parameters evaluated are the brake specific fuel consumption and brake thermal efficiency whereas the exhaust emission parameters evaluated are carbon monoxide, nitrogen oxide, and smoke opacity. Kernel-based extreme learning machine is used to predict the engine performance and exhaust emission parameters of the fuel blends at full throttle conditions. Based on the experimental results, the brake specific fuel consumption is lower while the brake thermal efficiency is higher for the biodiesel-bioethanol-diesel blends. The carbon monoxide emissions and smoke opacity are also lower for these fuel blends. The mean absolute percentage error of the brake specific fuel consumption, brake thermal efficiency, carbon monoxide, nitrogen oxide, and smoke opacity is 1.363, 1.482, 4.597, 2.224, and 2.090%, respectively. Thus, it can be concluded that K-ELM is a reliable method to estimate the engine performance and exhaust emission parameters of a single cylinder compression ignition engine fuelled with biodiesel-bioethanol-diesel blends to reduce fuel consumption and exhaust emissions.

Simorangkir, RBVB, Kiourti, A & Esselle, KP 2018, 'UWB Wearable Antenna With a Full Ground Plane Based on PDMS-Embedded Conductive Fabric', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 3, pp. 493-496.
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A new flexible ultrawideband (UWB) antenna is presented for wearable applications in the 3.7-10.3 GHz band, which is highly tolerant to human body loading and physical deformation. The antenna exhibits a footprint of 80 mm × 67 mm and is based on a simple microstrip structure with two modified arc-shaped patches as the main radiator. A full ground plane is maintained on the opposite side of the substrate to suppress antenna loading from the underlying biological tissues and back radiation directed toward the human body. For enhanced flexibility and robustness, the proposed antenna is realized using conductive fabric embedded into polydimethylsiloxane polymer. Promising simulation and experimental results are presented for free-space and in-vitro wearable scenarios. To our knowledge, this is the first UWB antenna with a full ground plane that is concurrently highly tolerant to harsh operating conditions, such as those encountered in wearable applications.

Simorangkir, RBVB, Yang, Y, Esselle, KP & Zeb, BA 2018, 'A Method to Realize Robust Flexible Electronically Tunable Antennas Using Polymer-Embedded Conductive Fabric', IEEE Transactions on Antennas and Propagation, vol. 66, no. 1, pp. 50-58.
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© 1963-2012 IEEE. A new approach to realize robust, flexible, and electronically tunable wearable antennas is presented. Conductive fabric is used to form the conducting parts of the antenna on a polydimethylsiloxane (PDMS) substrate. Then the antenna and the lumped (active and passive) elements, required for electronic tuning and RF choking, are fully encapsulated with additional layers of PDMS. As a concept demonstration, a new frequency-reconfigurable antenna has been designed and fabricated. The details of the prototype manufacturing process are described. Two UWB human muscle equivalent phantoms were also fabricated for testing purposes. Furthermore, the antenna was subjected to several investigations on its RF performance (both in free space and on a flat phantom) and mechanical stability. The latter includes bending tests on several locations on a human-body shaped phantom and washing in a household washing machine. Good agreement between predicted and experimental results (both in free space and on the phantom) is observed, validating the proposed concept. The tests demonstrated that lumped components and other antenna parts remained intact and in working order even under extreme bending (to a bending radius of 28 mm) and after washing, thus maintaining the overall antenna performance including good frequency reconfigurability from 2.3 to 2.68 GHz. To the best of our knowledge, all these features have never been demonstrated in previously published electronically tunable antennas.

Simorangkir, RBVB, Yang, Y, Hashmi, RM, Bjorninen, T, Esselle, KP & Ukkonen, L 2018, 'Polydimethylsiloxane-Embedded Conductive Fabric: Characterization and Application for Realization of Robust Passive and Active Flexible Wearable Antennas', IEEE Access, vol. 6, pp. 48102-48112.
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© 2013 IEEE. We present our study on polydimethylsiloxane (PDMS)-embedded conductive fabric, which we propose as a simple yet effective solution to the challenging issue of poor PDMS-metal adhesion, allowing for a relatively easy realization of robust flexible antennas for wearable applications. The method combines the use of conductive fabric as a radiator with PDMS, which acts as the substrate and a protective encapsulation simultaneously. For the first time, a holistic study on the mechanical and electrical properties of the proposed combination of materials is presented thoroughly using a number of fabricated samples. As concept demonstrations, a microstrip patch and a reconfigurable patch antenna are fabricated using the proposed technique to validate the idea. The inclusion of a PDMS-ceramic composite as part of the antenna's substrate, which leads to over 50% reduction in the size compared with a pure PDMS, is also demonstrated to showcase further the versatility of the proposed technique. The fabricated antennas are tested in several wearable scenarios and consistent performance including reconfigurability is obtained even after the antennas are exposed to harsh environments, i.e., extreme bending and machine-washing.

Singh, A, Mukhtar, HM, Satija, S & Mehta, M 2018, 'DEVELOPMENT OF QUALITATIVE PHARMACOGNOSTIC AND HIGH-PERFORMANCE THIN-LAYER CHROMATOGRAPHIC FINGERPRINTING OF MORPHOLOGICAL SIMILAR SPECIES OF GENUS FICUS', Asian Journal of Pharmaceutical and Clinical Research, vol. 11, no. 7, pp. 444-444.
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Objective: Ficus deltoidea (FD) and Ficus benjamina (FB), popularly known as “jack tree/mas cotek” and “pimpri/java fig,” respectively, in India and are used in folk medicine to treat the wound, ulcers, diabetes, microbial infections, and inflammatory disorders. Such therapeutic claims have also been justified in the literature by their rich chemical diversity. Both the plant species are morphologically similar and used unauthentically as the traditional medicinal product. Although these plants are sold in the local market by a traditional medicinal healer, we did not find any authenticated data on its quality.Methods: In the present study, quality standards of both the plant drugs have been developed and compared by performing morphological, microscopical, physicochemical, phytochemical, and high-performance thin-layer chromatographic (HPTLC) analysis. using CAMAG Linomat 5 instrument (Kindly delete the bold matter).Results: It was revealed that both the plant species have similar pharmacognostic features with some differences in type of stomata, presence of marked midrib, arrangement of the cell, cell structures, and meristele. HPTLC data revealed that the primary component in FD leaves (FDL) and FB leaves (FBL) extracts was found at Rf 0.67 and 0.37 with the respective peak area of 35.61% and 34.71%. The peaks at Rf 0.17 and 0.27 can be appeared as the chemical marker to highlight the quality of FDL, whereas peaks at Rf 0.87 and 0.95 can be considered to identify and chemically standardize the FBL.Conclusion: This study highlighted essential characters which contribute to the standardization, identification, and authentication of plant drugs.

Singh, AK, Chen, H-T, Cheng, Y-F, King, J-T, Ko, L-W, Gramann, K & Lin, C-T 2018, 'Visual Appearance Modulates Prediction Error in Virtual Reality', IEEE Access, vol. 6, pp. 24617-24624.
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© 2013 IEEE. Different rendering styles induce different levels of agency and user behaviors in virtual reality environments. We applied an electroencephalogram-based approach to investigate how the rendering style of the users' hands affects behavioral and cognitive responses. To this end, we introduced prediction errors due to cognitive conflicts during a 3-D object selection task by manipulating the selection distance of the target object. The results showed that, for participants with high behavioral inhibition scores, the amplitude of the negative event-related potential at approximately 50-250 ms correlated with the realism of the virtual hands. Concurring with the uncanny valley theory, these findings suggest that the more realistic the representation of the user's hand is, the more sensitive the user becomes toward subtle errors, such as tracking inaccuracies.

Singh, AK, Lv, Z, Rho, S, Singh, SK, Chang, X & Puech, W 2018, 'IEEE Access Special Section Editorial: Information Security Solutions for Telemedicine Applications', IEEE Access, vol. 6, pp. 79005-79009.
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Singh, SK, Taylor, RW, Rahman, MM & Pradhan, B 2018, 'Developing robust arsenic awareness prediction models using machine learning algorithms', Journal of Environmental Management, vol. 211, pp. 125-137.
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© 2018 Elsevier Ltd Arsenic awareness plays a vital role in ensuring the sustainability of arsenic mitigation technologies. Thus far, however, few studies have dealt with the sustainability of such technologies and its associated socioeconomic dimensions. As a result, arsenic awareness prediction has not yet been fully conceptualized. Accordingly, this study evaluated arsenic awareness among arsenic-affected communities in rural India, using a structured questionnaire to record socioeconomic, demographic, and other sociobehavioral factors with an eye to assessing their association with and influence on arsenic awareness. First a logistic regression model was applied and its results compared with those produced by six state-of-the-art machine-learning algorithms (Support Vector Machine [SVM], Kernel-SVM, Decision Tree [DT], k-Nearest Neighbor [k-NN], Naïve Bayes [NB], and Random Forests [RF]) as measured by their accuracy at predicting arsenic awareness. Most (63%) of the surveyed population was found to be arsenic-aware. Significant arsenic awareness predictors were divided into three types: (1) socioeconomic factors: caste, education level, and occupation; (2) water and sanitation behavior factors: number of family members involved in water collection, distance traveled and time spent for water collection, places for defecation, and materials used for handwashing after defecation; and (3) social capital and trust factors: presence of anganwadi and people's trust in other community members, NGOs, and private agencies. Moreover, individuals' having higher social network positively contributed to arsenic awareness in the communities. Results indicated that both the SVM and the RF algorithms outperformed at overall prediction of arsenic awareness—a nonlinear classification problem. Lower-caste, less educated, and unemployed members of the population were found to be the most vulnerable, requiring immediate arsenic mitigation. To this end, local social inst...

Sioutis, M, Long, Z & Li, S 2018, 'Leveraging Variable Elimination for Efficiently Reasoning about Qualitative Constraints', International Journal on Artificial Intelligence Tools, vol. 27, no. 04, pp. 1860001-1860001.
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We introduce, study, and evaluate a novel algorithm in the context of qualitative constraint-based spatial and temporal reasoning that is based on the idea of variable elimination, a simple and general exact inference approach in probabilistic graphical models. Given a qualitative constraint network [Formula: see text], our algorithm utilizes a particular directional local consistency, which we denote by [Formula: see text]-consistency, in order to efficiently decide the satisfiability of [Formula: see text]. Our discussion is restricted to distributive subclasses of relations, i.e., sets of relations closed under converse, intersection, and weak composition and for which weak composition distributes over non-empty intersections for all of their relations. We demonstrate that enforcing [Formula: see text]-consistency in a given qualitative constraint network defined over a distributive subclass of relations allows us to decide its satisfiability, and obtain similar useful results for the problems of minimal labelling and redundancy. Further, we present a generic method that allows extracting a scenario from a satisfiable network, i.e., an atomic satisfiable subnetwork of that network, in a very simple and effective manner. The experimentation that we have conducted with random and real-world qualitative constraint networks defined over a distributive subclass of relations of the Region Connection Calculus and the Interval Algebra, shows that our approach exhibits unparalleled performance against state-of-the-art approaches for checking the satisfiability of such constraint networks.

Siwakoti, YP & Blaabjerg, F 2018, 'Common-Ground-Type Transformerless Inverters for Single-Phase Solar Photovoltaic Systems.', IEEE Trans. Ind. Electron., vol. 65, no. 3, pp. 2100-2111.
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© 1982-2012 IEEE. This paper proposes a family of novel flying capacitor transformerless inverters for single-phase photovoltaic (PV) systems. Each of the new topologies proposed is based on a flying capacitor principle and requires only four power switches and/or diodes, one capacitor, and a small filter at the output stage. A simple unipolar sinusoidal pulse width modulation technique is used to modulate the inverter to minimize the switching loss, output current ripple, and the filter requirements. In general, the main advantages of the new inverter topologies are: 1) the negative polarity of the PV is directly connected to the grid, and therefore, no leakage current; 2) reactive power compensation capability; and 3) the output ac voltage peak is equal to the input dc voltage (unlike neutral-point-clamped and derivative topologies, which requires twice the magnitude of the peak ac voltage). A complete description of the operating principle with modulation techniques, design guidelines, and comprehensive comparisons is presented to reveal the properties and limitations of each topology in detail. Finally, experimental results of 1-kVA prototypes are presented to prove the concept and theoretical analysis of the proposed inverter family for practical applications.

Sofela, S, Sahloul, S, Rafeie, M, Kwon, T, Han, J, Warkiani, ME & Song, Y-A 2018, 'High-throughput sorting of eggs for synchronization ofC. elegansin a microfluidic spiral chip', Lab on a Chip, vol. 18, no. 4, pp. 679-687.
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High-throughput isolation ofC. eleganseggs from a mixed worm population in a spiral chip using inertial microfluidics.

Solanes, JE, Gracia, L, Muñoz-Benavent, P, Esparza, A, Valls Miro, J & Tornero, J 2018, 'Adaptive robust control and admittance control for contact-driven robotic surface conditioning', Robotics and Computer-Integrated Manufacturing, vol. 54, pp. 115-132.
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© 2018 Elsevier Ltd This work presents a hybrid position/force control of robots for surface contact conditioning tasks such as polishing, profiling, deburring, etc. The robot force control is designed using sliding mode ideas to benefit from robustness. On the one hand, a set of equality constraints are defined to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. On the other hand, inequality constraints are defined to adapt the tool position to unmodeled features present in the surface, e.g., a protruding window frame. Conventional and non-conventional sliding mode controls are used to fulfill the equality and inequality constraints, respectively. Furthermore, in order to deal with sudden changes of the material stiffness, which are forwarded to the robot tool and can produce instability and bad performance, adaptive switching gain laws are considered not only for the conventional sliding mode control but also for the non-conventional sliding mode control. A lower priority tracking controller is also defined to follow the desired reference trajectory on the target surface. Moreover, the classical admittance control typically used in force control tasks is adapted for the proposed surface contact application in order to experimentally compare the performance of both control approaches. The effectiveness of the proposed method is substantiated by experimental results using a redundant 7R manipulator, whereas its advantages over the classical admittance control approach are experimentally shown.

Solanes, JE, Gracia, L, Muñoz-Benavent, P, Valls Miro, J, Carmichael, MG & Tornero, J 2018, 'Human–robot collaboration for safe object transportation using force feedback', Robotics and Autonomous Systems, vol. 107, pp. 196-208.
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© 2018 Elsevier B.V. This work presents an approach based on multi-task, non-conventional sliding mode control and admittance control for human–robot collaboration aimed at handling applications using force feedback. The proposed robot controller is based on three tasks with different priority levels in order to cooperatively perform the safe transportation of an object with a human operator. In particular, a high-priority task is developed using non-conventional sliding mode control to guarantee safe reference parameters imposed by the task, e.g., keeping a load at a desired orientation (to prevent spill out in the case of liquids, or to reduce undue stresses that may compromise fragile items). Moreover, a second task based on a hybrid admittance control algorithm is used for the human operator to guide the robot by means of a force sensor located at the robot tool. Finally, a third low-priority task is considered for redundant robots in order to use the remaining degrees of freedom of the robot to achieve a pre-set secondary goal (e.g., singularity avoidance, remaining close to a homing configuration for increased safety, etc.) by means of the gradient projection method. The main advantages of the proposed method are robustness and low computational cost. The applicability and effectiveness of the proposed approach are substantiated by experimental results using a redundant 7R manipulator: the Sawyer collaborative robot.

Solanes, JE, Gracia, L, Muñoz-Benavent, P, Valls Miro, J, Girbés, V & Tornero, J 2018, 'Human-robot cooperation for robust surface treatment using non-conventional sliding mode control', ISA Transactions, vol. 80, pp. 528-541.
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© 2018 ISA This work presents a human-robot closely collaborative solution to cooperatively perform surface treatment tasks such as polishing, grinding, deburring, etc. The method considers two force sensors attached to the manipulator end-effector and tool: one sensor is used to properly accomplish the surface treatment task, while the second one is used by the operator to guide the robot tool. The proposed scheme is based on task priority and adaptive non-conventional sliding mode control. The applicability of the proposed approach is substantiated by experimental results using a redundant 7R manipulator: the Sawyer cobot.

Soldani, D, Guo, YJ, Barani, B, Mogensen, P, I, C-L & Das, SK 2018, '5G for Ultra-Reliable Low-Latency Communications', IEEE Network, vol. 32, no. 2, pp. 6-7.
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© 2018 IEEE. The articles in this special section focus on fifth generation (5G) mobile communication for ultra-reliable low-latency communications. With the expected superior performance to the current generation of mobile networks, 5G systems are poised to support new and diverse usage scenarios and applications, thus enriching the lives of citizens and the productivity of industry and public sectors. The widely accepted scenarios for 5G include enhanced mobile broadband (eMBB), addressing human-centric use cases for access to multimedia content, services and data; ultra-reliable low-latency communications (URLLC) with strict requirements, especially in terms of latency and reliability; and massive machine type communications (mMTC) for a very large number of connected devices typically transmitting a relatively low volume of non-delay-sensitive data. The articles in this section present the most relevant scenarios, prominent research outcomes, and state-of-the-art advances of 5G systems for URLLC achieving the Third Generation Partnership Project (3GPP) targets on latency and reliability requirements to successfully deliver delay-sensitive information. In 3GPP, the performance target for control plane latency is 10 ms, and for user plane latency it is 0.5 ms for downlink and uplink directions, separately.

Song, H, Guo, T, Zhao, Z, Wei, Y, Luo, H, Weng, W, Zhang, R, Zhong, M, Chen, C, Su, J & Shen, W 2018, 'Biocompatible PEGylated Gold nanorods function As cytokinesis inhibitors to suppress angiogenesis', Biomaterials, vol. 178, pp. 23-35.
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Song, J, Wang, J & Lu, H 2018, 'A novel combined model based on advanced optimization algorithm for short-term wind speed forecasting', Applied Energy, vol. 215, pp. 643-658.
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© 2018 Elsevier Ltd Short-term wind speed forecasting has a significant influence on enhancing the operation efficiency and increasing the economic benefits of wind power generation systems. A substantial number of wind speed forecasting models, which are aimed at improving the forecasting performance, have been proposed. However, some conventional forecasting models do not consider the necessity and importance of data preprocessing. Moreover, they neglect the limitations of individual forecasting models, leading to poor forecasting accuracy. In this study, a novel model combining a data preprocessing technique, forecasting algorithms, an advanced optimization algorithm, and no negative constraint theory is developed. This combined model successfully overcomes some limitations of the individual forecasting models and effectively improves the forecasting accuracy. To estimate the effectiveness of the proposed combined model, 10-min wind speed data from the wind farm in Peng Lai, China are used as case studies. The experiment results demonstrate that the developed combined model is definitely superior compared to all other conventional models. Furthermore, it can be used as an effective technique for smart grid planning.

Song, J, Wang, J, Zhao, L, Huang, S & Dissanayake, G 2018, 'Dynamic Reconstruction of Deformable Soft-Tissue With Stereo Scope in Minimal Invasive Surgery', IEEE Robotics and Automation Letters, vol. 3, no. 1, pp. 155-162.
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© 2016 IEEE. In minimal invasive surgery, it is important to rebuild and visualize the latest deformed shape of soft-tissue surfaces to mitigate tissue damages. This letter proposes an innovative Simultaneous localization and mapping (SLAM) algorithm for deformable dense reconstruction of surfaces using a sequence of images from a stereoscope. We introduce a warping field based on the embedded deformation nodes with three-dimensional (3-D) shapes recovered from consecutive pairs of stereo images. The warping field is estimated by deforming the last updated model to the current live model. Our SLAM system can incrementally build a live model by progressively fusing new observations with vivid accurate texture; estimate the deformed shape of unobserved region with the principle as-rigid-as-possible; show the consecutive shape of models; and estimate the current relative pose between the soft-tissue and the scope. In-vivo experiments with publicly available datasets demonstrate that the 3-D models can be incrementally built for different soft-tissues with different deformations from sequences of stereo images obtained by laparoscopes. Results show the potential clinical application of our SLAM system for providing surgeon useful shape and texture information in minimal invasive surgery.

Song, J, Wang, J, Zhao, L, Huang, S & Dissanayake, G 2018, 'MIS-SLAM: Real-Time Large-Scale Dense Deformable SLAM System in Minimal Invasive Surgery Based on Heterogeneous Computing', IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 4068-4075.
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© 2016 IEEE. Real-time simultaneous localization and dense mapping is very helpful for providing virtual reality and augmented reality for surgeons or even surgical robots. In this letter, we propose MIS-SLAM: A complete real-time large-scale dense deformable SLAM system with stereoscope in minimal invasive surgery (MIS) based on heterogeneous computing by making full use of CPU and GPU. Idled CPU is used to perform ORB-SLAM for providing robust global pose. Strategies are taken to integrate modules from CPU and GPU. We solved the key problem raised in the previous work, that is, fast movement of scope and blurry images make the scope tracking fail. Benefiting from improved localization, MIS-SLAM can achieve large-scale scope localizing and dense mapping in real time. It transforms and deforms current model and incrementally fuses new observation while keeping vivid texture. In-vivo experiments conducted on publicly available datasets presented in the form of videos demonstrate the feasibility and practicality of MIS-SLAM for potential clinical purpose.

Song, X, Luo, W, Hai, FI, Price, WE, Guo, W, Ngo, HH & Nghiem, LD 2018, 'Resource recovery from wastewater by anaerobic membrane bioreactors: Opportunities and challenges', Bioresource Technology, vol. 270, pp. 669-677.
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© 2018 This review examines the potential of anaerobic membrane bioreactor (AnMBR) to serve as the core technology for simultaneous recovery of clean water, energy, and nutrient from wastewater. The potential is significant as AnMBR treatment can remove a board range of trace organic contaminants relevant to water reuse, convert organics in wastewater to biogas for subsequent energy production, and liberate nutrients to soluble forms (e.g. ammonia and phosphorus) for subsequent recovery for fertilizer production. Yet, there remain several significant challenges to the further development of AnMBR. These challenges evolve around the dilute nature of municipal wastewater, which entails the need for pre-concentrating wastewater prior to AnMBR, and hence, issues related to salinity build-up, accumulation of substances, membrane fouling, and membrane stability. Strategies to address these challenges are proposed and discussed. A road map for further research is also provided to guide future AnMBR development toward resource recovery.

Song, X, Luo, W, McDonald, J, Khan, SJ, Hai, FI, Guo, W, Ngo, HH & Nghiem, LD 2018, 'Effects of sulphur on the performance of an anaerobic membrane bioreactor: Biological stability, trace organic contaminant removal, and membrane fouling', Bioresource Technology, vol. 250, pp. 171-177.
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© 2017 This study investigated the impact of sulphur content on the performance of an anaerobic membrane bioreactor (AnMBR) with an emphasis on the biological stability, contaminant removal, and membrane fouling. Removal of 38 trace organic contaminants (TrOCs) that are ubiquitously present in municipal wastewater by AnMBR was evaluated. Results show that basic biological performance of AnMBR regarding biomass growth and the removal of chemical oxygen demand (COD) was not affected by sulphur addition when the influent COD/SO42− ratio was maintained higher than 10. Nevertheless, the content of hydrogen sulphate in the produced biogas increased significantly and membrane fouling was exacerbated with sulphur addition. Moreover, the increase in sulphur content considerably affected the removal of some hydrophilic TrOCs and their residuals in the sludge phase during AnMBR operation. By contrast, no significant impact on the removal of hydrophobic TrOCs was noted with sulphur addition to AnMBR.

Song, X, Luo, W, McDonald, J, Khan, SJ, Hai, FI, Price, WE & Nghiem, LD 2018, 'An anaerobic membrane bioreactor – membrane distillation hybrid system for energy recovery and water reuse: Removal performance of organic carbon, nutrients, and trace organic contaminants', Science of The Total Environment, vol. 628-629, pp. 358-365.
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© 2018 In this study, a direct contact membrane distillation (MD) unit was integrated with an anaerobic membrane bioreactor (AnMBR) to simultaneously recover energy and produce high quality water for reuse from wastewater. Results show that AnMBR could produce 0.3–0.5 L/g CODadded biogas with a stable methane content of approximately 65%. By integrating MD with AnMBR, bulk organic matter and phosphate were almost completely removed. The removal of the 26 selected trace organic contaminants by AnMBR was compound specific, but the MD process could complement AnMBR removal, leading to an overall efficiency from 76% to complete removal by the integrated system. The results also show that, due to complete retention, organic matter (such as humic-like and protein-like substances) and inorganic salts accumulated in the MD feed solution and therefore resulted in significant fouling of the MD unit. As a result, the water flux of the MD process decreased continuously. Nevertheless, membrane pore wetting was not observed throughout the operation.

Song, Y-C, Kim, M, Shon, H, Jegatheesan, V & Kim, S 2018, 'Modeling methane production in anaerobic forward osmosis bioreactor using a modified anaerobic digestion model No. 1', Bioresource Technology, vol. 264, pp. 211-218.
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Sornalingam, K, McDonagh, A, Zhou, JL, Johir, MAH & Ahmed, MB 2018, 'Photocatalysis of estrone in water and wastewater: Comparison between Au-TiO2 nanocomposite and TiO2, and degradation by-products', Science of The Total Environment, vol. 610-611, pp. 521-530.
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© 2017 Elsevier B.V. Gold-modified TiO2 (Au-TiO2) photocatalysts were utilised for the degradation of estrone (E1), a major endocrine disrupting chemical in water and wastewater. Au-TiO2 catalysts were synthesised by a deposition-precipitation method with gold loadings of 0–8% (wt%). The Au-TiO2 nanocomposite exhibited superior activity compared to P25 TiO2 under UVA (λ = 365 nm), cool white (λ > 420 nm) and green (λ = 523 nm) light emitting diodes (LEDs), for treating 1 mg l− 1 of E1. The 4 wt% Au loading was found to produce the best photocatalytic activity with a rate constant of 2.44 ± 0.36 h− 1, compared to 0.06 ± 0.01 h− 1 for P25 TiO2, under visible light. In total 4 by-products were identified, one from negative ionization mode (m/z = 269) and three from positive ionization mode (m/z = 287) during photocatalysis, which were also degraded with time by Au-TiO2. For different water matrices, the photodegradation rate of E1 decreased in the order: ultrapure water > synthetic wastewater ≈ wastewater effluent from membrane bio-reactor. Overall, 4 wt% Au-TiO2 demonstrated superior performance compared to P25 TiO2 in water and wastewater.

Soudagar, MEM, Nik-Ghazali, N-N, Abul Kalam, M, Badruddin, IA, Banapurmath, NR & Akram, N 2018, 'The effect of nano-additives in diesel-biodiesel fuel blends: A comprehensive review on stability, engine performance and emission characteristics', Energy Conversion and Management, vol. 178, pp. 146-177.
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Srivastava, K, Kumar, A, Kanaujia, BK, Dwari, S, Verma, AK, Esselle, KP & Mittra, R 2018, 'Integrated GSM‐UWB Fibonacci‐type antennas with single, dual, and triple notched bands', IET Microwaves, Antennas & Propagation, vol. 12, no. 6, pp. 1004-1012.
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This study presents four integrated Fibonacci‐type Global System for Mobile (GSM) ultra‐wideband (UWB) antennas with single, dual, and triple band‐notched characteristics. These antennas have been designed to control potential interference in Wi‐Max and WLAN bands. The antenna operates in the 900 MHz GSM band and also in the 3.2–11.9 GHz extended UWB band. The 900 MHz operating band can be further tuned to get the antenna to operate in a specific GSM band. Triple notches have been created at frequencies within several bands, such as 3.4 GHz Wi‐Max (3.06–3.54 GHz), 4.23 GHz WLAN (3.59–4.86 GHz), and 6.35 GHz (5.93–7.15 GHz) with voltage standing wave ratio (VSWR) levels of 7.9, 11.3, and 7, respectively. These notch bands are also tuneable to some extent. The measured gain varies from −1.92 to 10.2 dBi. Measured radiation patterns of the antenna are also presented to validate its performance. The integrated antenna has a radiation efficiency in the range of 78–98% in the UWB and 98% in the GSM band. The fidelity factor in time domain varies between 0.76 and 0.84, depending on the orientation of the antenna. This research confirms that the Fibonacci monopole can be used as a multiband antenna in GSM and UWB bands.

Stefen, H, Hassanzadeh-Barforoushi, A, Brettle, M, Fok, S, Suchowerska, AK, Tedla, N, Barber, T, Warkiani, ME & Fath, T 2018, 'A Novel Microfluidic Device-Based Neurite Outgrowth Inhibition Assay Reveals the Neurite Outgrowth-Promoting Activity of Tropomyosin Tpm3.1 in Hippocampal Neurons', Cellular and Molecular Neurobiology, vol. 38, no. 8, pp. 1557-1563.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Overcoming neurite inhibition is integral for restoring neuronal connectivity after CNS injury. Actin dynamics are critical for neurite growth cone formation and extension. The tropomyosin family of proteins is a regarded as master regulator of actin dynamics. This study investigates tropomyosin isoform 3.1 (Tpm3.1) as a potential candidate for overcoming an inhibitory substrate, as it is known to influence neurite branching and outgrowth. We designed a microfluidic device that enables neurons to be grown adjacent to an inhibitory substrate, Nogo-66. Results show that neurons, overexpressing hTpm3.1, have an increased propensity to overcome Nogo-66 inhibition. We propose Tpm3.1 as a potential target for promoting neurite growth in an inhibitory environment in the central nervous system.

Stender, M, Tiedemann, M, Hoffmann, N & Oberst, S 2018, 'Impact of an irregular friction formulation on dynamics of a minimal model for brake squeal', Mechanical Systems and Signal Processing, vol. 107, pp. 439-451.
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Friction-induced vibrations are of major concern in the design of reliable, efficient and comfortable technical systems. Well-known examples for systems susceptible to self-excitation can be found in fluid structure interaction, disk brake squeal, rotor dynamics, hip implants noise and many more. While damping elements and amplitude reduction are well-understood in linear systems, nonlinear systems and especially self-excited dynamics still constitute a challenge for damping element design. Additionally, complex dynamical systems exhibit deterministic chaotic cores which add severe sensitivity to initial conditions to the system response. Especially the complex friction interface dynamics remain a challenging task for measurements and modeling. Today, mostly simple and regular friction models are investigated in the field of self-excited brake system vibrations. This work aims at investigating the effect of high-frequency irregular interface dynamics on the nonlinear dynamical response of a self-excited structure. Special focus is put on the characterization of the system response time series. A low-dimensional minimal model is studied which features self-excitation, gyroscopic effects and friction-induced damping. Additionally, the employed friction formulation exhibits temperature as inner variable and superposed chaotic fluctuations governed by a Lorenz attractor. The time scale of the irregular fluctuations is chosen one order smaller than the overall system dynamics. The influence of those fluctuations on the structural response is studied in various ways, i.e. in time domain and by means of recurrence analysis. The separate time scales are studied in detail and regimes of dynamic interactions are identified. The results of the irregular friction formulation indicate dynamic interactions on multiple time scales, which trigger larger vibration amplitudes as compared to regular friction formulations conventionally studied in the field of friction-induced vibr...

Stewart, MG 2018, 'Reliability-based load factor design model for explosive blast loading', Structural Safety, vol. 71, pp. 13-23.
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The risk of damage to infrastructure and people is affected by airblast variability. Reliability-based design allows the decision-maker to select the level of reliability for a specific blast loading scenario. Reliability-based load factors are calculated where the nominal load is multiplied by the load factor to ensure that the actual load is equal to the reliability level. A design model for predicting reliability-based load factors is developed where model error, explosive mass and stand-off distance are random variables, and calculated reliability-based design load factors (RBDF) are independent of explosive mass, net equivalent quantity, angle of incidence, temperature or pressure. Hence, a design model describing reliability-based load factors are presented for reliability levels of 0.05 to 0.99, and for coefficients of variation of explosive mass and range each varying from 0.0 to 0.3. The paper then shows the significant effect that range and explosive mass variability have on RBDFs, and how this affects structural design and damage predictions for reinforced concrete columns and glazing.

Stewart, MG & Mueller, J 2018, 'Risk and economic assessment of U.S. aviation security for passenger-borne bomb attacks', Journal of Transportation Security, vol. 11, no. 3-4, pp. 117-136.
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A systems reliability analysis is developed that includes 18 layers of security that might disrupt a terrorist organisation undeterred and intent on downing an airliner with a passenger-borne bomb. Overall, they reduce the risk that such an attack would be successful by 93%. The odds that a lone wolf will be successful in such an attack are considerably lower. This level of risk reduction is very robust: security remains high even when the disruption rates that make it up are varied considerably. The same model is used to explore the risk reduction of aviation security measures in other western countries and in Israel. The benefit-to-cost ratio is then calculated for most of the security measures. It considers the costs and the risk reduction of the layer, the losses from a successful terrorist attack, and the attack probability. It is found that the Joint Terrorism Task Force (JTTF) and police, PreCheck, Visible Intermodal Protection Response (VIPR) teams, and canines pass a cost-benefit assessment. However, it finds that air marshals and behavior detection officers, at a combined cost of nearly $1.3 billion per year, fail to be cost-effective. Accordingly, there are likely to be spending reductions that could be made with little or no consequent reduction in security.

Stewart, MG, Ginger, JD, Henderson, DJ & Ryan, PC 2018, 'Fragility and climate impact assessment of contemporary housing roof sheeting failure due to extreme wind', Engineering Structures, vol. 171, pp. 464-475.
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The paper describes a risk analysis of the economic impact of damage to metal roofing of a typical contemporary (new) Australian house subject to extreme wind loading. The failure modes considered are roof cladding and batten-to-truss connection failures, with the effect of defective construction also considered. Monte-Carlo simulation and structural reliability methods are used to stochastically model spatially varying pressure coefficients, roof component failure, and load re-distribution across the roof. This spatial reliability analysis enables fragility curves to be developed that relate likelihood and extent of roof cover loss to gust wind speed. The annual economic risk is up to 0.3% of house replacement value. A typical house with construction defects increases economic risk more than sixfold when compared to the defect-free house. There is a 10% chance that a changing climate will increase expected losses for houses in Brisbane and Melbourne by 6–18% over the next 50 years.

Su, H, Macquart, JP, Hurley-Walker, N, McClure-Griffiths, NM, Jackson, CA, Tingay, SJ, Tian, WW, Gaensler, BM, McKinley, B, Kapińska, AD, Hindson, L, Hancock, P, Wayth, RB, Staveley-Smith, L, Morgan, J, Johnston-Hollitt, M, Lenc, E, Bell, ME, Callingham, JR, Dwarkanath, KS, For, B-Q, Offringa, AR, Procopio, P, Wu, C & Zheng, Q 2018, 'Galactic synchrotron distribution derived from 152 H ii region absorption features in the full GLEAM survey', Monthly Notices of the Royal Astronomical Society, vol. 479, no. 3, pp. 4041-4055.
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© 2018 The Author(s) Published by Oxford University Press on behalf of The Royal Astronomical Society. We derive the synchrotron distribution in the Milky Way disc from H II region absorption observations over -40° < l < 40° at six frequencies of 76.2, 83.8, 91.5, 99.2, 106.9, and 114.6 MHz with the GaLactic and Extragalactic All-sky Murchison widefield array survey (GLEAM). We develop a new method of emissivity calculation by taking advantage of the Haslam et al. (1981) map and known spectral indices, which enable us to simultaneously derive the emissivity and the optical depth of H II regions at each frequency. We show our derived synchrotron emissivities based on 152 absorption features of H II regions using both the method previously adopted in the literature and our improved method. We derive the synchrotron emissivity from H II regions to the Galactic edge along the line of sight and, for the first time, derive the emissivity from H II regions to the Sun. These results provide direct information on the distribution of the Galactic magnetic field and cosmic ray electrons for future modelling.

Su, QP & Ju, LA 2018, 'Biophysical nanotools for single-molecule dynamics', Biophysical Reviews, vol. 10, no. 5, pp. 1349-1357.
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The focus of the cell biology field is now shifting from characterizing cellular activities to organelle and molecular behaviors. This process accompanies the development of new biophysical visualization techniques that offer high spatial and temporal resolutions with ultra-sensitivity and low cell toxicity. They allow the biology research community to observe dynamic behaviors from scales of single molecules, organelles, cells to organoids, and even live animal tissues. In this review, we summarize these biophysical techniques into two major classes: the mechanical nanotools like dynamic force spectroscopy (DFS) and the optical nanotools like single-molecule and super-resolution microscopy. We also discuss their applications in elucidating molecular dynamics and functionally mapping of interactions between inter-cellular networks and intra-cellular components, which is key to understanding cellular processes such as adhesion, trafficking, inheritance, and division.

Sui, Y, Fan, X, Zhou, H & Xue, J 2018, 'Loop-Oriented Pointer Analysis for Automatic SIMD Vectorization', ACM Transactions on Embedded Computing Systems, vol. 17, no. 2, pp. 1-31.
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Compiler-based vectorization represents a promising solution to automatically generate code that makes efficient use of modern CPUs with SIMD extensions. Two main auto-vectorization techniques, superword-level parallelism vectorization (SLP) and loop-level vectorization (LLV), require precise dependence analysis on arrays and structs to vectorize isomorphic scalar instructions (in the case of SLP) and reduce dynamic dependence checks at runtime (in the case of LLV). The alias analyses used in modern vectorizing compilers are either intra-procedural (without tracking inter-procedural data-flows) or inter-procedural (by using field-sensitive models, which are too imprecise in handling arrays and structs). This article proposes an inter-procedural L oop-oriented P ointer A nalysis for C, called L pa , for analyzing arrays and structs to support aggressive SLP and LLV optimizations effectively. Unlike field-insensitive solutions that pre-allocate objects for each memory allocation site, our approach uses a lazy memory model to generate access-based location sets based on how structs and arrays are accessed. L pa can precisely analyze arrays and nested aggregate structures to enable SIMD optimizations for large programs. By separating the location set generation as an independent concern from the rest of the pointer analysis, L pa is designed so that existing points-to resolution algorithms (e.g., flow-insensitive and flow-sensitive pointer analysis) can be reused easily. We have implemented L pa fully i...

Sui, Y, Yan, H, Zheng, Z, Zhang, Y & Xue, J 2018, 'Parallel construction of interprocedural memory SSA form', Journal of Systems and Software, vol. 146, pp. 186-195.
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© 2018 Elsevier Inc. Interprocedural memory SSA form, which provides a sparse data-flow representation for indirect memory operations, paves the way for many advanced program analyses. Any performance improvement for memory SSA construction benefits for a wide range of clients (e.g., bug detection and compiler optimisations). However, its construction is much more expensive than that for scalar-based SSA form. The memory objects distinguished at a pointer dereference significantly increases the number of variables that need to be put on SSA form, resulting in considerable analysis overhead when analyzing large programs (e.g., millions of lines of code). This paper presents PARSSA, a fully parameterised approach for parallel construction of interprocedural memory SSA form by utilising multi-core computing resources. PARSSA partitions whole-program memory objects into uniquely identified memory regions. The indirect memory accesses in a function are fully parameterised using partitioned memory regions, so that the memory SSA construction of a parameterised function is readily parallelised. We implemented PARSSA in LLVM using Intel Threading Building Block (TBB) for creating parallel tasks. We evaluated PARSSA using 15 large applications. PARSSA achieves up to 6.9 × speedup against the sequential version on an 8-core machine.

Sulecio de Alvarez, M & Dickson-Deane, C 2018, 'Avoiding Educational Technology Pitfalls for Inclusion and Equity', TechTrends, vol. 62, no. 4, pp. 345-353.
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© 2018, Association for Educational Communications & Technology. The integration of technology in learning, from a cultural perspective, continues to be of concern to many. The concerns include understanding the use of tools in meaningful ways, designing learning experiences where learners retain agency in learning, avoiding unintended consequences in learning, and reconciling perspectives to allow natural learning to flourish. The purpose of this article is to encourage a healthy discussion regarding how designs may be created considering common cultural belief systems. The discussions presented will challenge how learning has been understood in the past, how it is being understood now, and how it may be designed, with thought to how contextually-cultured learning pathways can be achieved.

Sullivan, AL, Surawski, NC, Crawford, D, Hurley, RJ, Volkova, L, Weston, CJ & Meyer, CP 2018, 'Effect of woody debris on the rate of spread of surface fires in forest fuels in a combustion wind tunnel', Forest Ecology and Management, vol. 424, pp. 236-245.
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© 2018 The treatment of the contribution of woody debris (WD, such as branches or small logs >6–50 mm diameter) to the rate of forward spread of a fire in current operational forest fire spread models is inconsistent. Some models do not take into account this fuel at all (i.e. only consider the combustion of fine fuels (⩽6 mm diameter)), while others incorporate effects based on little or no data. An experimental programme utilising a large combustion wind tunnel investigated the effect of WD on the spread of fires burning through forest litter (surface fuel) beds of 1.0 kg m-2. Fires spreading with (heading) and against (backing) the wind were investigated. Three treatments of WD load (0.2, 0.6 and 1.2 kg m-2) and a control (0 kg m-2) were studied using a single constant wind speed (1.0 m s-1) and a narrow range of fine and woody fuel moisture contents (10.0–12.7% and 9.2–11.6% oven-dry weight, respectively) determined by ambient conditions. Presence of WD was found to approximately halve the overall rate of spread of heading fires relative to when no WD was present, regardless of the level of treatment. No effect of WD on rate of spread was found for backing fires. Potential explanations of these findings and implications for the use of operational forest fire spread models are explored, as are future research needs.

Sun, F, Hou, F, Zhou, H, Liu, B, Chen, J & Gui, L 2018, 'Equilibriums in the Mobile-Virtual-Network-Operator-Oriented Data Offloading', IEEE Transactions on Vehicular Technology, vol. 67, no. 2, pp. 1622-1634.
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Sun, G, Liu, T, Fang, J, Steven, GP & Li, Q 2018, 'Configurational optimization of multi-cell topologies for multiple oblique loads', Structural and Multidisciplinary Optimization, vol. 57, no. 2, pp. 469-488.
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© 2017, Springer-Verlag GmbH Germany. Multi-cell thin-walled structures exhibit significant advantages in maximizing energy absorption and minimizing mass during vehicle crashes. Since the topological distribution of wall members has an appreciable effect on the crashworthiness, their design signifies an important area of research. As a major energy absorber, multi-cell tubes are more commonly encounter oblique loading in real life. Thus, this study aimed to optimize multi-cell cross-sectional configuration of tubal structures for multiple oblique loading cases. An integer coded genetic algorithm (ICGA) is introduced here to optimize topological distribution of multi-celled web members for single/multiple oblique impacting conditions. Specifically, material distribution in a form of allocating web wall thickness, starting from zero, is considered as design variables and maximization of energy absorption (EA) as the design objective under the predefined peak crushing force and structural mass constraints. The optimization allows generating uniform or non-uniform thickness distribution in different web wall configurations to maximize usage efficiency of material. Compared with the baseline structure, the optimized configurations largely improved the energy absorption in both single and multiple load cases. The examples demonstrate that the proposed ICGA-based design method not only provides a useful approach to searching for novel crashworthy structures in a systematic fashion, but also develops a series of novel multi-cell topologies for multiple oblique loading cases.

Sun, G, Zhang, H, Fang, J, Li, G & Li, Q 2018, 'A new multi-objective discrete robust optimization algorithm for engineering design', Applied Mathematical Modelling, vol. 53, pp. 602-621.
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© 2017 Elsevier Inc. This paper proposes a novel multi-objective discrete robust optimization (MODRO) algorithm for design of engineering structures involving uncertainties. In the present MODRO procedure, grey relational analysis (GRA), coupled with principal component analysis (PCA), was used as a multicriteria decision making model for converting multiple conflicting objectives into one unified cost function. The optimization process was iterated using the successive Taguchi approach to avoid the limitation that the conventional Taguchi method fails to deal with a large number of design variables and design levels. The proposed method was first verified by a mathematical benchmark example and a ten-bar truss design problem; and then it was applied to a more sophisticated design case of full scale vehicle structure for crashworthiness criteria. The results showed that the algorithm is able to achieve an optimal design in a fairly efficient manner attributable to its integration with the multicriteria decision making model. Note that the optimal design can be directly used in practical applications without further design selection. In addition, it was found that the optimum is close to the corresponding Pareto frontier generated from the other approaches, such as the non-dominated sorting genetic algorithm II (NSGA-II), but can be more robust as a result of introduction of the Taguchi method. Due to its independence on metamodeling techniques, the proposed algorithm could be fairly promising for engineering design problems of high dimensionality.

Sun, H-H, Zhu, H, Ding, C & Guo, YJ 2018, 'Wideband Planarized Dual-Linearly-Polarized Dipole Antenna and Its Integration for Dual-Circularly-Polarized Radiation', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 12, pp. 2289-2293.
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© 2002-2011 IEEE. A planarized dual-linearly-polarized (dual-LP) antenna and an integrated dual-circularly-polarized (dual-CP) antenna are proposed in this letter. For the dual-LP antenna, two groups of dipoles are fed by two balun-included feed networks to achieve ±45° polarizations. The feed networks and the radiators are printed on two sides of a substrate, forming a fully planar structure. Taking advantage of its planar configuration, the dual-LP antenna is further integrated with a wideband coupler to realize dual-CP radiation. The coupler is bent and squeezed into the space between the radiators and the reflector, leading to a compact structure. Both the dual-LP antenna and the dual-CP antenna have very stable radiation performances across a wide operating band >66%.

Sun, J, Ni, B-J, Sharma, KR, Wang, Q, Hu, S & Yuan, Z 2018, 'Modelling the long-term effect of wastewater compositions on maximum sulfide and methane production rates of sewer biofilm', Water Research, vol. 129, pp. 58-65.
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© 2017 Elsevier Ltd Reliable modelling of sulfide and methane production in sewer systems is required for efficient sewer emission management. Wastewater compositions affect sulfide and methane production kinetics through both its short-term variation influencing the substrate availability to sewer biofilms, and its long-term variation affecting the sewer biofilm structure. While the short-term effect is well considered in existing sewer models with the use of Monod or half-order equations, the long-term effect has not been explicitly considered in current sewer models suitable for network modelling. In this study, the long-term effect of wastewater compositions on sulfide and methane production activities in rising main sewers was investigated. A detailed biofilm model was firstly developed, and then calibrated and validated using experimental data measured during the entire biofilm development period of a laboratory sewer reactor. Based on scenario simulations using the detailed biofilm model, empirical equations describing the long-term effect of sulfate and sCOD (soluble chemical oxygen demand) concentrations on kH2S (the maximum sulfide production rate of sewer biofilm) and kCH4 (the maximum methane production rate of sewer biofilm) were proposed. These equations require further verification in future studies before their potential integration into network-wide sewer models.

Sun, X, Shen, Y, Wang, S, Lei, G, Yang, Z & Han, S 2018, 'Core Losses Analysis of a Novel 16/10 Segmented Rotor Switched Reluctance BSG Motor for HEVs Using Nonlinear Lumped Parameter Equivalent Circuit Model', IEEE/ASME Transactions on Mechatronics, vol. 23, no. 2, pp. 747-757.
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© 1996-2012 IEEE. In this paper, a new nonlinear lumped parameter equivalent circuit model is proposed to calculate the core losses of a novel 16/10 segmented rotor switched reluctance motor (SSRM) for belt-driven starter generators. The model investigates the hysteresis, eddy current and anomalous losses by using the method of energy conservation. Four parameters are introduced in the proposed model to consider the effects of saturation and leakage flux in SSRM. They are the incremental leakage inductance, the incremental equivalent winding resistance, the incremental magnetizing inductance, and the incremental equivalent core-loss resistance. This model can overcome the hysteresis effects of winding resistance and leakage inductance on the current, and improve the accuracy of the parameters. To illustrate the advantages of the proposed model, an experiment platform is developed. Experimental results show that the proposed model can significantly improve the calculation accuracy of core losses of the SSRM. The accuracy is better than the conventional Epstein frame method. The proposed core-loss model and analysis method can be applied to other kinds of switched reluctance motors.

Sun, Y, Zhang, W, Wang, B, Xu, X, Chou, J, Shimoni, O, Ung, AT & Jin, D 2018, 'A supramolecular self-assembly strategy for upconversion nanoparticle bioconjugation', Chemical Communications, vol. 54, no. 31, pp. 3851-3854.
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An efficient surface modification and bioconjugation strategy for upconversion nanoparticles is reported via supramolecular host–guest self-assembly.

Suñer, S, Gowland, N, Craven, R, Joffe, R, Emami, N & Tipper, JL 2018, 'Ultrahigh molecular weight polyethylene/graphene oxide nanocomposites: Wear characterization and biological response to wear particles', Journal of Biomedical Materials Research Part B: Applied Biomaterials, vol. 106, no. 1, pp. 183-190.
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AbstractIn the field of total joint replacements, polymer nanocomposites are being investigated as alternatives to ultrahigh molecular weight polyethylene (UHMWPE) for acetabular cup bearings. The objective of this study was to investigate the wear performance and biocompatibility of UHMWPE/graphene oxide (GO) nanocomposites. This study revealed that low concentrations of GO nanoparticles (0.5 wt %) do not significantly alter the wear performance of UHMWPE. In contrast, the addition of higher concentrations (2 wt %) led to a significant reduction in wear. In terms of biocompatibility, UHMWPE/GO wear particles did not show any adverse effects on L929 fibroblast and PBMNC viability at any of the concentrations tested over time. Moreover, the addition of GO to a UHMWPE matrix did not significantly affect the inflammatory response to wear particles. Further work is required to optimize the manufacturing processes to improve the mechanical properties of the nanocomposites and additional biocompatibility testing should be performed to understand the potential clinical application of these materials. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 183–190, 2018.

Suseno, Y, Laurell, C & Sick, N 2018, 'Assessing value creation in digital innovation ecosystems: A Social Media Analytics approach', The Journal of Strategic Information Systems, vol. 27, no. 4, pp. 335-349.
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Sutton, GJ, Zeng, J, Liu, RP, Ni, W, Nguyen, DN, Jayawickrama, BA, Huang, X, Abolhasan, M & Zhang, Z 2018, 'Enabling Ultra-Reliable and Low-Latency Communications through Unlicensed Spectrum', IEEE Network, vol. 32, no. 2, pp. 70-77.
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© 2018 IEEE. In this article, we aim to address the question of how to exploit the unlicensed spectrum to achieve URLLC. Potential URLLC PHY mechanisms are reviewed and then compared via simulations to demonstrate their potential benefits to URLLC. Although a number of important PHY techniques help with URLLC, the PHY layer exhibits an intrinsic trade-off between latency and reliability, posed by limited and unstable wireless channels. We then explore MAC mechanisms and discuss multi-channel strategies for achieving low-latency LTE unlicensed band access. We demonstrate, via simulations, that the periods without access to the unlicensed band can be substantially reduced by maintaining channel access processes on multiple unlicensed channels, choosing the channels intelligently, and implementing RTS/CTS.

Syed, MS, Rafeie, M, Vandamme, D, Asadnia, M, Henderson, R, Taylor, RA & Warkiani, ME 2018, 'Selective separation of microalgae cells using inertial microfluidics', Bioresource Technology, vol. 252, pp. 91-99.
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© 2017 Elsevier Ltd Microalgae represent the most promising new source of biomass for the world's growing demands. However, the biomass productivity and quality is significantly decreased by the presence of bacteria or other invading microalgae species in the cultures. We therefore report a low-cost spiral-microchannel that can effectively separate and purify Tetraselmis suecica (lipid-rich microalgae) cultures from Phaeodactylum tricornutum (invasive diatom). Fluorescent polystyrene-microbeads of 6 μm and 10 μm diameters were first used as surrogate particles to optimize the microchannel design by mimicking the microalgae cell behaviour. Using the optimum flowrate, up to 95% of the P. tricornutum cells were separated from the culture without affecting the cell viability. This study shows, for the first time, the potential of inertial microfluidics to sort microalgae species with minimal size difference. Additionally, this approach can also be applied as a pre-sorting technique for water quality analysis.

Szemes, M, Greenhough, A, Melegh, Z, Malik, S, Yuksel, A, Catchpoole, D, Gallacher, K, Kollareddy, M, Park, JH & Malik, K 2018, 'Wnt Signalling Drives Context-Dependent Differentiation or Proliferation in Neuroblastoma', Neoplasia, vol. 20, no. 4, pp. 335-350.
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Neuroblastoma is one of the commonest and deadliest solid tumours of childhood, and is thought to result from disrupted differentiation of the developing sympathoadrenergic lineage of the neural crest. Neuroblastoma exhibits intra- and intertumoural heterogeneity, with high risk tumours characterised by poor differentiation, which can be attributable to MYCN-mediated repression of genes involved in neuronal differentiation. MYCN is known to co-operate with oncogenic signalling pathways such as Alk, Akt and MEK/ERK signalling, and, together with c-MYC has been shown to be activated by Wnt signalling in various tissues. However, our previous work demonstrated that Wnt3a/Rspo2 treatment of some neuroblastoma cell lines can, paradoxically, decrease c-MYC and MYCN proteins. This prompted us to define the neuroblastoma-specific Wnt3a/Rspo2-driven transcriptome using RNA sequencing, and characterise the accompanying changes in cell biology. Here we report the identification of ninety Wnt target genes, and show that Wnt signalling is upstream of numerous transcription factors and signalling pathways in neuroblastoma. Using live-cell imaging, we show that Wnt signalling can drive differentiation of SK-N-BE(2)-C and SH-SY5Y cell-lines, but, conversely, proliferation of SK-N-AS cells. We show that cell-lines that differentiate show induction of pro-differentiation BMP4 and EPAS1 proteins, which is not apparent in the SK-N-AS cells. In contrast, SK-N-AS cells show increased CCND1, phosphorylated RB and E2F1 in response to Wnt3a/Rspo2, consistent with their proliferative response, and these proteins are not increased in differentiating lines. By meta-analysis of the expression of our 90 genes in primary tumour gene expression databases, we demonstrate discrete expression patterns of our Wnt genes in patient cohorts with different prognosis. Furthermore our analysis reveals interconnectivity within subsets of our Wnt genes, with one subset comprised of novel putative...

Taghizadeh, S, Hossain, MJ & Lu, J 2018, 'Enhanced orthogonal signal generator for a single‐phase grid‐connected converter', IET Power Electronics, vol. 11, no. 15, pp. 2563-2572.
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This study presents a new orthogonal signal generation (OSG) technique for the control system of a single‐phase grid‐connected voltage‐source converter (VSC). The existing methods mostly suffer from delay, rely on the system parameters, or require multiple inputs. Among them, the second‐order generalised integrator (SOGI) excludes the drawbacks of the other methods and shows better steady‐state and dynamic response. The proposed OSG method here includes the advantages of the SOGI technique while demonstrating superior dynamic response and higher disturbance rejection capability. It is structurally simple without adding complexity to the control system. The proposed method is implemented in a DQ‐frame current controller and its feasibility and reliability are verified through mathematical analysis, simulation, and experimental results.

Taghizadeh, S, Hossain, MJ, Lu, J & Water, W 2018, 'A unified multi-functional on-board EV charger for power-quality control in household networks', Applied Energy, vol. 215, pp. 186-201.
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This paper presents a feasible and reliable unified control system for a single-phase 4.5 kVA on-board multifunctional electric-vehicle (EV) charger that is connected to a low-voltage household network. Based on the proposed control system, the EV charger can operate as both a single-phase four-quadrant static synchronous compensator (STATCOM) and an active power filter (APF). The proposed EV charger can simultaneously perform four functions: charging/discharging the electric-vehicle's (EV's) battery; reactive power compensation; voltage regulation; and, harmonic reduction, which are important concerns of the existing power grid. Accordingly, it can enhance the building s voltage profile, power quality, and reliability, which makes the proposed method a complete solution for low-voltage household networks. The stress on the EV battery is also reduced, which can enhance its lifetime. A stability analysis of the proposed unified control system is provided in this paper. The simulation results, with two loads, static and dynamic, confirm the efficacy and reliability of the proposed system. The performance of the designed unified control system is also validated by experimental results.

Tahmassebi, A & Gandomi, AH 2018, 'Building energy consumption forecast using multi-objective genetic programming', Measurement, vol. 118, pp. 164-171.
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A multi-objective genetic programming (MOGP) technique with multiple genes is proposed to formulate the energy performance of residential buildings. Here, it is assumed that loads have linear relation in terms of genes. On this basis, an equation is developed by MOGP method to predict both heating and cooling loads. The proposed evolutionary approach optimizes the most significant predictor input variables in the model for both accuracy and complexity, while simultaneously solving the unknown parameters of the model. In the proposed energy performance model, relative compactness has the most and orientation the least contribution. The proposed MOGP model is simple and has a high degree of accuracy. The results show that MOGP is a suitable tool to generate solid models for complex nonlinear systems with capability of solving big data problems via parallel algorithms.

Tahmassebi, A, Gandomi, AH, Schulte, MHJ, Goudriaan, AE, Foo, SY & Meyer-Baese, A 2018, 'Optimized Naive‐Bayes and Decision Tree Approaches for fMRI Smoking Cessation Classification', Complexity, vol. 2018, no. 1, pp. 1-24.
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This paper aims at developing new theory‐driven biomarkers by implementing and evaluating novel techniques from resting‐state scans that can be used in relapse prediction for nicotine‐dependent patients and future treatment efficacy. Two classes of patients were studied. One class took the drug N‐acetylcysteine and the other class took a placebo. Then, the patients underwent a double‐blind smoking cessation treatment and the resting‐state fMRI scans of their brains before and after treatment were recorded. The scientific research goal of this study was to interpret the fMRI connectivity maps based on machine learning algorithms to predict the patient who will relapse and the one who will not. In this regard, the feature matrix was extracted from the image slices of brain employing voxel selection schemes and data reduction algorithms. Then, the feature matrix was fed into the machine learning classifiers including optimized CART decision tree and Naive‐Bayes classifier with standard and optimized implementation employing 10‐fold cross‐validation. Out of all the data reduction techniques and the machine learning algorithms employed, the best accuracy was obtained using the singular value decomposition along with the optimized Naive‐Bayes classifier. This gave an accuracy of 93% with sensitivity‐specificity of 99% which suggests that the relapse in nicotine‐dependent patients can be predicted based on the resting‐state fMRI images. The use of these approaches may result in clinical applications in the future.

Tai, P, Indraratna, B & Rujikiatkamjorn, C 2018, 'Experimental simulation and mathematical modelling of clogging in stone column', Canadian Geotechnical Journal, vol. 55, no. 3, pp. 427-436.
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In this paper, time-dependent clogging is studied considering a unit cell consisting of a single stone column interacting with the surrounding soft clay. Clogging is assessed quantitatively and the corresponding void space of the column is determined using computed tomography. It is observed that the extent of clogging is substantial in the upper part of the column, but diminishes rapidly with depth. The soil properties in the clogged zone are determined indirectly through additional tests of clay–aggregates mixtures with various clay fractions. An equal strain consolidation model based on the principle of unit cell analysis is developed to capture both the initial and time-dependent clogging. The model accounts for a reduction in permeability and an increase in compressibility of the column. This current model, as expected, offers identical results to some previous studies if clogging is ignored, while the comparison with other selected models demonstrates the influence that clogging of the stone column can have on the consolidation of the surrounding soil. Furthermore, load–settlement predictions from the proposed “equal strain” model are also compared with the consolidation response of a previously developed “free strain” model.

Takalkar, M, Xu, M, Wu, Q & Chaczko, Z 2018, 'A survey: facial micro-expression recognition', Multimedia Tools and Applications, vol. 77, no. 15, pp. 19301-19325.
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© 2017, Springer Science+Business Media, LLC. Facial expression recognition plays a crucial role in a wide range of applications of psychotherapy, security systems, marketing, commerce and much more. Detecting a macro-expression, which is a direct representation of an ‘emotion,’ is a relatively straight-forward task. Playing a pivotal role as macro-expressions, micro-expressions are more accurate indicators of a train of thought or even subtle, passive or involuntary thoughts. Compared to macro-expressions, identifying micro-expressions is a much more challenging research question because their time spans are narrowed down to a fraction of a second, and can only be defined using a broader classification scale. This paper is an all-inclusive survey-cum-analysis of the various micro-expression recognition techniques. We analyze the general framework for micro-expression recognition system by decomposing the pipeline into fundamental components, namely face detecting, pre-processing, facial feature detection and extraction, datasets, and classification. We discuss the role of these elements and highlight the models and new trends that are followed in their design. Moreover, we provide an extensive analysis of micro-expression recognition systems by comparing their performance. We also discuss the new deep learning features that can, in the near future, replace the hand-crafted features for facial micro-expression recognition. This survey has been developed, focusing on the methodologies applied, databases used, performance regarding recognition accuracy and comparing these to distil the gaps in the efficiencies, future scope, and research potentials. Through this survey, we intend to look into this problem and develop a comprehensive and efficient recognition scheme. This study allows us to identify open issues and to determine future directions for designing real-world micro-expression recognition systems.

Takeuchi, H, Tanaka, H, Nghiem, LD & Fujioka, T 2018, 'Emerging investigators series: a steric pore-flow model to predict the transport of small and uncharged solutes through a reverse osmosis membrane', Environmental Science: Water Research & Technology, vol. 4, no. 4, pp. 493-504.
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This study proposed a new approach to apply the steric pore-flow model to predict the rejection of eight N-nitrosamines and seven VOCs that are of great concern in potable water reuse through an RO membrane.

Tan, SX, Ong, HC, Lim, S & Pang, YL 2018, 'In situ reactive extraction of Jatropha curcas L. seeds assisted by ultrasound: Preliminary studies', Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 40, no. 14, pp. 1772-1779.
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Tang, CY, Yang, Z, Guo, H, Wen, JJ, Nghiem, LD & Cornelissen, E 2018, 'Potable Water Reuse through Advanced Membrane Technology', Environmental Science & Technology, vol. 52, no. 18, pp. 10215-10223.
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© 2018 American Chemical Society. Recycling water from municipal wastewater offers a reliable and sustainable solution to cities and regions facing shortage of water supply. Places including California and Singapore have developed advanced water reuse programs as an integral part of their water management strategy. Membrane technology, particularly reverse osmosis, has been playing a key role in producing high quality recycled water. This feature paper highlights the current status and future perspectives of advanced membrane processes to meet potable water reuse. Recent advances in membrane materials and process configurations are presented and opportunities and challenges are identified in the context of water reuse.

Tang, G, Huang, J, Sheng, D & Sloan, SW 2018, 'Stability analysis of unsaturated soil slopes under random rainfall patterns', Engineering Geology, vol. 245, pp. 322-332.
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The significance of rainfall pattern in the assessment of rainfall-induced landslide is widely recognized. However, much work so far is limited to several simplified typical rainfall patterns. In this study, the random rainfall pattern (RRP) is introduced and generated using random cascade model based on the rainfall event characterized by average rainfall intensity and duration. The stability of unsaturated slope considering RRPs is studied from three perspectives: deterministic analysis by means of safety factor under different generated RRPs, probabilistic analysis through conditional failure probability considering the diversity of generated RRPs based on Monte Carlo method and risk assessment analysis by introducing annual failure probability (AFP) considering also the occurrence frequencies of rainfall events. Three typical rainfall patterns are introduced for comparison analysis. The results show that slope stability is sensitive to the RRP and is strongly depend on the temporal distribution of rainfall intensity in RRP. High likelihood of slope failure may occur considering the variety of RRPs even though the slope is in a stable state in terms of deterministic analysis. The AFP considering RRPs increases rapidly with increasing rainfall duration and is significantly different from those under typical rainfall patterns. The findings lead to the conclusion that RRPs should be considered in the estimation of unsaturated slope stability.

Tang, J, Wang, XC, Hu, Y, Pu, Y, Huang, J, Hao Ngo, H, Zeng, Y & Li, Y 2018, 'Nitrogen removal enhancement using lactic acid fermentation products from food waste as external carbon sources: Performance and microbial communities', Bioresource Technology, vol. 256, pp. 259-268.
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Tang, Z-E, Lim, S, Pang, Y-L, Ong, H-C & Lee, K-T 2018, 'Synthesis of biomass as heterogeneous catalyst for application in biodiesel production: State of the art and fundamental review', RENEWABLE & SUSTAINABLE ENERGY REVIEWS, vol. 92, no. C, pp. 235-253.
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Biodiesel is gaining attention as a remedy for the increasing demand of fossil fuels which is depleting rapidly. Commercial homogeneous catalysts in the biodiesel production industry are facing challenges such as separation difficulties and severe corrosion which will lead to the increment of production and maintenance cost. Herein, this paper focuses on the comprehensive review of literature reported on the usage of biomass as the precursor for the catalyst used in biodiesel production. Compared to other commercial catalysts, the usage of biomass as catalyst precursor possesses several advantages such as abundantly available, cheaper raw materials, reusable, non-toxic and biodegradable. Carbon material synthesized from biomass which acts as the efficient support for active sites due to its high porosity and surface area characteristic has been studied widely. The latest development of biomass derived basic, acidic and magnetic heterogeneous catalyst through several state of the art synthesis pathways starting from the synthesis of the supporting material (carbon) until the functionalization process to form the complete catalyst was reviewed. Apart from direct sulfonation using sulfuric acid, sulfonation by reduction and arylation were less hazardous and provided comparable active sites activity. Most biomass based catalysts exhibited good catalytic performance by providing high biodiesel yield of above 80% at optimum conditions. Besides that, various kinetic models developed from the reaction kinetic study catalyzed by biomass based catalyst were also reviewed as a preparatory stage for the scaled-up commercialization process of the studied catalyst in the biodiesel production sector. This catalyst could assist to lower the activation energy required for the reactions and thus enables higher reaction rate to reach equilibrium. Continuous research on producing high performing biomass based catalyst with minimum resources is needed in order to achieve th...

Tapas, M, Brenner, J, Vessalas, K, Thomas, P & Sirivivatnanon, V 2018, 'Effect of Limestone Content in Cement on Alkali-Silica Reaction Using Accelerated Mortar Bar Test', Concrete in Australia, vol. 44, no. 2, pp. 41-47.
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This paper reports the effect of interground limestone content on Alkali Silica Reaction (ASR) in binder systems with and without supplementary cementitious materials (SCMs) using commercial Portland cement (Type GP) with no limestone addition and a masonry cement with 17% limestone. The results show that increasing cement limestone content up to 17% has no adverse effect on expansion of mortar bars containing reactive greywacke aggregate tested using Australian Standard AS 1141.60.1. The high limestone content of 17% also appears to stabilise the Accelerated Mortar Bar Test (AMBT) expansion after 14 days of immersion in 1M NaOH 80 oC. This is possibly because of the formation of monocarboaluminate as detected by X-Ray Diffraction (XRD), resulting from the reaction of limestone with the aluminate phases in the cement, which may lead to reduced porosity in the mortar as well as the reduced amount of portlandite in the hydrated masonry cement as confirmed by Thermogravimetric Analysis (TGA). Moreover, it was found that the limestone content had no detrimental effect on the efficacy of SCMs to suppress ASR as shown in the expansion of the accelerated mortar bar tests.

Taranto, P, Pollock, FA, Milz, S, Tomamichel, M & Modi, K 2018, 'Quantum Markov Order', Phys. Rev. Lett., vol. 122, no. 14, p. 140401.
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We formally extend the notion of Markov order to open quantum processes byaccounting for the instruments used to probe the system of interest atdifferent times. Our description recovers the classical Markov order propertyin the appropriate limit: when the stochastic process is classical and theinstruments are non-invasive, \emph{i.e.}, restricted to orthogonal, projectivemeasurements. We then prove that there do not exist non-Markovian quantumprocesses that have finite Markov order with respect to all possibleinstruments; the same process exhibits distinct memory effects with respect todifferent probing instruments. This naturally leads to a relaxed definition ofquantum Markov order with respect to specified sequences of instruments. Thememory effects captured by different choices of instruments vary dramatically,providing a rich landscape for future exploration.

Tavakoli, J & Costi, JJ 2018, 'A method for visualization and isolation of elastic fibres in annulus fibrosus of the disc', Materials Science and Engineering: C, vol. 93, pp. 299-304.
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A simple and cost effective protocol for visualization and isolation of the elastic fibres network in the annulus fibrosus (AF) of the disc is explained, to provide other researchers a method that can be applied in disc ultra-structural analysis, biomechanical assessment of elastic fibre and tissue engineered scaffold fabrication. This protocol is developed based on simultaneous sonication and alkali digestion of tissue that eliminates all matrix constituents except for elastic fibres, which is applicable for different species including human. Thin samples harvested from ovine, bovine, porcine and human, which are commonly used in disc research, were exposed to 0.5 M sodium hydroxide solution along with sonication (25 kHz) in distilled water for defined periods of time at room temperature. Post heat treatment removed collagen fibres via the gelatinization process, for visualization of elastic fibres.

Tavakoli, J & Costi, JJ 2018, 'New findings confirm the viscoelastic behaviour of the inter-lamellar matrix of the disc annulus fibrosus in radial and circumferential directions of loading', Acta Biomaterialia, vol. 71, pp. 411-419.
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While few studies have improved our understanding of composition and organization of elastic fibres in the inter-lamellar matrix (ILM), its clinical relevance is not fully understood. Moreover, no studies have measured the direct tensile and shear failure and viscoelastic properties of the ILM. Therefore, the aim of this study was, for the first time, to measure the viscoelastic and failure properties of the ILM in both the tension and shear directions of loading. Using an ovine model, isolated ILM samples were stretched to 40% of their initial length at three strain rates of 0.1%s-1 (slow), 1%s-1 (medium) and 10%s-1 (fast) and a ramp test to failure was performed at a strain rate of 10%s-1. The findings from this study identified that the stiffness of the ILM was significantly larger at faster strain rates, and energy absorption significantly smaller, compared to slower strain rates, and the viscoelastic and failure properties were not significantly different under tension and shear loading. We found a strain rate dependent response of the ILM during dynamic loading, particularly at the fastest rate. The ILM demonstrated a significantly higher capability for energy absorption at slow strain rates compared to medium and fast strain rates. A significant increase in modulus was found in both loading directions and all strain rates, having a trend of larger modulus in tension and at faster strain rates. The finding of no significant difference in failure properties in both loading directions, was consistent with our previous ultra-structural studies that revealed a well-organized (±45°) elastic fibre orientation in the ILM. The results from this study can be used to develop and validate finite element models of the AF at the tissue scale, as well as providing new strategies for fabricating tissue engineered scaffolds. STATEMENT OF SIGNIFICANCE: While few studies have improved our understanding of composition and organization of elastic fibres in the inter-...

Tavakoli, J & Costi, JJ 2018, 'New insights into the viscoelastic and failure mechanical properties of the elastic fiber network of the inter-lamellar matrix in the annulus fibrosus of the disc', Acta Biomaterialia, vol. 77, pp. 292-300.
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The mechanical role of elastic fibers in the inter-lamellar matrix (ILM) is unknown; however, it has been suggested that they play a role in providing structural integrity to the annulus fibrosus (AF). Therefore, the aim of this study was to measure the viscoelastic and failure properties of the elastic fiber network in the ILM of ovine discs under both tension and shear directions of loading. Utilizing a technique, isolated elastic fibers within the ILM from ovine discs were stretched to 40% of their initial length at three strain rates of 0.1% s-1 (slow), 1% s-1 (medium) and 10% s-1 (fast), followed by a ramp test to failure at 10% s-1. A significant strain-rate dependent response was found, particularly at the fastest rate for phase angle and normalized stiffness (p < 0.001). The elastic fibers in the ILM demonstrated a significantly higher capability for energy absorption at slow compared to medium and fast strain rates (p < 0.001). These finding suggests that the elastic fiber network of the ILM exhibits nonlinear elastic behavior. When tested to failure, a significantly higher normalized failure force was found in tension compared to shear loading (p = 0.011), which is consistent with the orthotropic structure of elastic fibers in the ILM. The results of this study confirmed the mechanical contribution of the elastic fiber network to the ILM and the structural integrity of the AF. This research serves as a foundation for future studies to investigate the relationship between degeneration and ILM mechanical properties. STATEMENT OF SIGNIFICANCE: The mechanical role of elastic fibres in the inter-lamellar matrix (ILM) of the disc is unknown. The viscoelastic and failure properties of the elastic fibre network in the ILM in both tension and shear directions of loading was measured for the first time. We found a strain-rate dependent response for the elastic fibres in the ILM. The elastic fibres in the ILM demonstrated a significantly higher capabilit...

Tavakoli, J & Costi, JJ 2018, 'Ultrastructural organization of elastic fibres in the partition boundaries of the annulus fibrosus within the intervertebral disc', Acta Biomaterialia, vol. 68, pp. 67-77.
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The relationship between elastic fibre disorders and disc degeneration, aging and progression of spine deformity have been discussed in a small number of studies. However, the clinical relevance of elastic fibres in the annulus fibrosus (AF) of the disc is poorly understood. Ultrastructural visualization of elastic fibres is an important step towards understanding their structure-function relationship. In our previous studies, a novel technique for visualization of elastic fibres across the AF was presented and their ultrastructural organization in intra- and inter-lamellar regions was compared. Using the same novel technique in the present study, the ultrastructural organization of elastic fibres in the partition boundaries (PBs), which are located between adjacent collagen bundles, is presented for the first time. Visualization of elastic fibres in the PBs in control and partially digested (digested) samples was compared, and their orientation in two different cutting planes (transverse and oblique) were discussed. The ultrastructural analysis revealed that elastic fibres in PBs were a well-organized dense and complex network having different size and shape. Adjacent collagen bundles in a cross section (CS) lamella appear to be connected to each other, where elastic fibres in the PBs were merged in parallel or penetrated into the collagen bundles. There was no significant difference in directional coherency coefficient of elastic fibres between the two different cutting planes (p = .35). The present study revealed that a continuous network of elastic fibres may provide disc integrity by connecting adjacent bundles of CS lamellae together. Compared to our previous studies, the density of the elastic fibre network in PBs was lower, and fibre orientation was similar to the intra-lamellar space and inter-lamellar matrix. STATEMENT OF SIGNIFICANCE: A detailed ultrastructural study in the partition boundaries of the annulus fibrosus within the disc revealed...

Tavakoli, J & Khosroshahi, ME 2018, 'Surface morphology characterization of laser-induced titanium implants: lesson to enhance osseointegration process', Biomedical Engineering Letters, vol. 8, no. 3, pp. 249-257.
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The surface properties of implant are responsible to provide mechanical stability by creating an intimate bond between the bone and implant; hence, play a major role on osseointegration process. The current study was aimed to measure surface characteristics of titanium modified by a pulsed Nd:YAG laser. The results of this study revealed an optimum density of laser energy (140 Jcm-2), at which improvement of osteointegration process was seen. Significant differences were found between arithmetical mean height (Ra), root mean square deviation (Rq) and texture orientation, all were lower for 140 Jcm-2 samples compared to untreated one. Also it was identified that the surface segments were more uniformly distributed with a more Gaussian distribution for treated samples at 140 Jcm-2. The distribution of texture orientation at high laser density (250 and 300 Jcm-2) were approximately similar to untreated sample. The skewness index that indicates how peaks and valleys are distributed throughout the surface showed a positive value for laser treated samples, compared to untreated one. The surface characterization revealed that Kurtosis index, which tells us how high or flat the surface profile is, for treated sample at 140 Jcm-2 was marginally close to 3 indicating flat peaks and valleys in the surface profile.

Tavakoli, J, Amin, DB, Freeman, BJC & Costi, JJ 2018, 'The Biomechanics of the Inter-Lamellar Matrix and the Lamellae During Progression to Lumbar Disc Herniation: Which is the Weakest Structure?', Annals of Biomedical Engineering, vol. 46, no. 9, pp. 1280-1291.
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While microstructural observations have improved our understanding of possible pathways of herniation progression, no studies have measured the mechanical failure properties of the inter-lamellar matrix (ILM), nor of the adjacent lamellae during progression to herniation. The aim of this study was to employ multiscale, biomechanical and microstructural techniques to evaluate the effects of progressive induced herniation on the ILM and lamellae in control, pre-herniated and herniated discs (N = 7), using 2 year-old ovine spines. Pre-herniated and herniated (experimental) groups were subjected to macroscopic compression while held in flexion (13°), before micro-mechanical testing. Micro-tensile testing of the ILM and the lamella from anterior and posterolateral regions was performed in radial and circumferential directions to measure failure stress, modulus, and toughness in all three groups. The failure stress of the ILM was significantly lower for both experimental groups compared to control in each of radial and circumferential loading directions in the posterolateral region (p < 0.032). Within each experimental group in both loading directions, the ILM failure stress was significantly lower by 36% (pre-herniation), and 59% (herniation), compared to the lamella (p < 0.029). In pre-herniated compared to control discs, microstructural imaging revealed significant tissue stretching and change in orientation (p < 0.003), resulting in a loss of distinction between respective lamellae and ILM boundaries.

Tavakoli, J, Mirzaei, S & Tang, Y 2018, 'Cost-Effective Double-Layer Hydrogel Composites for Wound Dressing Applications', Polymers, vol. 10, no. 3, pp. 305-305.
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Although poly vinyl alcohol-poly acrylic acid (PVA-PAA) composites have been widely used for biomedical applications, their incorporation into double-layer assembled thin films has been limited because the interfacial binding materials negatively influence the water uptake capacity of PVA. To minimize the effect of interfacial binding, a simple method for the fabrication of a double-layered PVA-PAA hydrogel was introduced, and its biomedical properties were evaluated in this study. Our results revealed that the addition of PAA layers on the surface of PVA significantly increased the swelling properties. Compared to PVA, the equilibrium swelling ratio of the PVA-PAA hydrogel increased (p = 0.035) and its water vapour permeability significantly decreased (p = 0.04). Statistical analysis revealed that an increase in pH value from 7 to 10 as well as the addition of PAA at pH = 7 significantly increased the adhesion force (p < 0.04). The mechanical properties—including ultimate tensile strength, modulus, and elongation at break—remained approximately untouched compared to PVA. A significant increase in biocompatibility was found after day 7 (p = 0.016). A higher release rate for tetracycline was found at pH = 8 compared to neutral pH.

Tavassoli, H, Alhosseini, SN, Tay, A, Chan, PPY, Weng Oh, SK & Warkiani, ME 2018, 'Large-scale production of stem cells utilizing microcarriers: A biomaterials engineering perspective from academic research to commercialized products', Biomaterials, vol. 181, pp. 333-346.
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© 2018 Elsevier Ltd Human stem cells, including pluripotent, embryonic and mesenchymal, stem cells play pivotal roles in cell-based therapies. Over the past decades, various methods for expansion and differentiation of stem cells have been developed to satisfy the burgeoning clinical demands. One of the most widely endorsed technologies for producing large cell quantities is using microcarriers (MCs) in bioreactor culture systems. In this review, we focus on microcarriers properties that can manipulate the expansion and fate of stem cells. Here, we provide an overview of commercially available MCs and focus on novel stimulus responsive MCs controlled by temperature, pH and field changes. Different features of MCs including composition, surface coating, morphology, geometry/size, surface functionalization, charge and mechanical properties, and their cellular effects are also highlighted. We then conclude with current challenges and outlook on this promising technology.

Tavassoli, H, Javadpour, J, Taheri, M, Mehrjou, M, Koushki, N, Arianpour, F, Majidi, M, Izadi-Mobarakeh, J, Negahdari, B, Chan, P, Ebrahimi Warkiani, M & Bonakdar, S 2018, 'Incorporation of Nanoalumina Improves Mechanical Properties and Osteogenesis of Hydroxyapatite Bioceramics', ACS Biomaterials Science & Engineering, vol. 4, no. 4, pp. 1324-1336.
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© 2018 American Chemical Society. A handful of work focused on improving the intrinsic low mechanical properties of hydroxyapatite (HA) by various reinforcing agents. However, the big challenge regarding improving mechanical properties is maintaining bioactivity. To address this issue, we report fabrication of apatite-based composites by incorporation of alumina nanoparticles (n-Al2O3). Although numerous studies have used micron or submicron alumina for reinforcing hydroxyapatite, only few reports are available about the use of n-Al2O3. In this study, spark plasma sintering (SPS) method was utilized to develop HA-nAl2O3 dense bodies. Compared to the conventional sintering, decomposition of HA and formation of calcium aluminates phases are restricted using SPS. Moreover, n-Al2O3 acts as a bioactive agent while its conventional form is an inert bioceramics. The addition of n-Al2O3 resulted in 40% improvement in hardness along with a 110% increase in fracture toughness, while attaining nearly full dense bodies. The in vitro characterization of nanocomposite demonstrated improved bone-specific cell function markers as evidenced by cell attachment and proliferation, alkaline phosphatase activity, calcium and collagen detection and nitric oxide production. Specifically, gene expression analysis demonstrated that introduction of n-Al2O3 in HA matrix resulted in accelerated osteogenic differentiation of osteoblast and mesenchymal stem cells, as expression of Runx-2 and OSP showed 2.5 and 19.6 fold increase after 2 weeks (p < 0.05). Moreover, protein adsorption analysis showed enhanced adsorption of plasma proteins to HA-nAl2O3 sample compared to HA. These findings suggest that HA-nAl2O3 could be a prospective candidate for orthopedic applications due to its improved mechanical and osteogenic properties.

Taylor, RA, Hjerrild, N, Duhaini, N, Pickford, M & Mesgari, S 2018, 'Stability testing of silver nanodisc suspensions for solar applications', Applied Surface Science, vol. 455, pp. 465-475.
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© 2018 Elsevier B.V. In solar and optical applications, nanofluids can be exposed to intense light, high temperature, and variable pH levels. Over time these forces can destabilize particle suspensions by altering particle morphology, breaking functional groups, and inducing agglomeration. Since UV exposure has been a critical unknown for nanoparticle suspension stability in solar and optical applications, a modified ISO standard UV accelerated lifetime test method was developed and applied herein. Aqueous formulations of protective silica shells over silver nanodiscs (relative to unprotected silver) were investigated as indicative non-spherical nanoparticles that might be expected to survive these perturbations. As such, the dispersion stability of these suspensions was investigated before and after exposure to elevated temperature, UV light, and pH levels. Dispersion stability was determined using a few techniques – changes in spectral transmission, zeta potential, and particle size distribution via nanoparticle tracking analysis. A protective shell of silica deposited via a modified Stöber (using tetraethyl-orthosilicate – TEOS) method was found to provide stability against temperature, UV, and pH exposure, whereas uncoated silver nanoparticles or those with a shell grown using a sodium silicate silica source were considered relatively unstable. The TEOS silica shells also exhibited a beneficial UV curing effect, which can be explained by increased crosslinking throughout UV exposure.

Teng, JD, Shan, F, Zhang, S & Tong, J 2018, 'New method for calculating soil surface evaporation considering effect of wind speed', Yantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering, vol. 40, no. 1, pp. 100-107.
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Soil surface evaporation is one of the main processes in the soil-atmosphere interaction. Since it is highly related to meteorological factors and soil properties, the determination of evaporation from soil surface remains a challenge, and the key point is to determine the critial water content where the evaporation changes from constant rate stage into falling rate stage. To investigate the effect of wind speed on soil evaporation, a climate control apparatus is newly developed, with a feature of completely controlling air temperature, relative humidity and wind speed. 12 climatic conditions are applied to 3 kinds of soil specimens to carry out the evaporation tests. The results show that a lower aerodynamic resistance always leads to a higher critical water content, only the water content cannot allow an accurate estimation, and the additional variables accounting for soil texture and wind speed must be included as well. Moreover, a simple approach to parameterizing the evaporation is presented by using the water content of top 1-cm layer as a variable and considering the effect of soil texture and wind speed.

Teoh, YH, Masjuki, HH, How, HG, Kalam, MA, Yu, KH & Alabdulkarem, A 2018, 'Effect of two-stage injection dwell angle on engine combustion and performance characteristics of a common-rail diesel engine fueled with coconut oil methyl esters-diesel fuel blends', Fuel, vol. 234, pp. 227-237.
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Thaib, R, Rizal, S, Hamdani, Mahlia, TMI & Pambudi, NA 2018, 'Experimental analysis of using beeswax as phase change materials for limiting temperature rise in building integrated photovoltaics', Case Studies in Thermal Engineering, vol. 12, pp. 223-227.
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© 2018 The Authors. Indonesia has the potential of saving from 10% to 30% of energy in the commercial sector which consists of trade, hotels, restaurants, finances, government agencies, schools, hospitals, and communications. By simultaneously serving as building envelope material and power generator, BIPV systems can represent savings in the cost of materials and electricity. It reduce the use of fossil fuels and emission of ozone depleting gases, and also add architectural interest to buildings. However, the temperature rise poses a challenge for BIPV, given that it manifests itself in electrical efficiency and overheating. The experiments present in this study aim at understanding the behavior of the PV-PCM systems in realistic outdoor uncontrolled conditions to determine how effective they are. In addition, the PV-PCM systems were tried in the low latitude and hot climate of Banda Aceh, Indonesia. Experiments were conducted outdoors at the Engineering Faculty in Syiah Kuala University, located in Banda Aceh, Indonesia (05:57 N, 95.37 E). In this study, both paraffin wax and beeswax were used as a phase change material. The final results showed that the electrical efficiency of PV panels without PCM is ranged between 6.1% and 6.5%. While for PV panels with PCM the efficiency is ranged at 7.0-7.8%. This proved that the process of water cooling is capable of increasing the efficiency of PV panels.

Thakur, CS, Wang, R, Hamilton, TJ, Etienne-Cummings, R, Tapson, J & van Schaik, A 2018, 'An Analogue Neuromorphic Co-Processor That Utilizes Device Mismatch for Learning Applications', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 4, pp. 1174-1184.
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© 2004-2012 IEEE. As the integrated circuit (IC) technology advances into smaller nanometre feature sizes, a fixed-error noise known as device mismatch is introduced owing to the dissimilarity between transistors, and this degrades the accuracy of analog circuits. In this paper, we present an analog co-processor that uses this fixed-pattern noise to its advantage to perform complex computation. This circuit is an extension of our previously published trainable analogue block (TAB) framework and uses multiple inputs that substantially increase functionality. We present measurement results of our two-input analogue co-processor built using a 130-nm process technology and show its learning capabilities for regression and classification tasks. We also show that the co-processor, comprised of 100 neurons, is a low-power system with a power dissipation of only 1.1μ W. The IC fabrication process contributes to randomness and variability in ICs, and we show that random device mismatch is favorable for the learning capability of our system as it causes variability among the neuronal tuning curves. The low-power capability of our framework makes it suitable for use in various battery-powered applications ranging from biomedical to military as a front-end analog co-processor.

Thiyagarajan, K, Kodagoda, S, Ranasinghe, R, Vitanage, D & Iori, G 2018, 'Robust sensing suite for measuring temporal dynamics of surface temperature in sewers', Scientific Reports, vol. 8, no. 1.
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AbstractSewerage systems are paramount underground infrastructure assets for any nation. In most cities, they are old and have been exposed to significant microbial induced corrosion. It is a serious global problem as they pose threats to public health and economic repercussions to water utilities. For managing sewer assets efficaciously, it is vital to predict the rate of corrosion. Predictive models of sewer corrosion incorporate concrete surface temperature measurements as an observation. However, currently, it has not been fully utilized due to unavailability of a proven sensor. This study reports the feasibility of infrared radiometer for measuring the surface temperature dynamics in the aggressive sewer conditions. The infrared sensor was comprehensively evaluated in the laboratory at different environmental conditions. Then, the sensor suite was deployed in a Sydney based sewer for three months to perform continuous measurements of surface temperature variations. The field study revealed the suitability of the developed sensor suite for non-contact surface temperature measurements in hostile sewer conditions. Further, the accuracy of the sensor measurements was improved by calibrating the sensor with emissivity coefficient of the sewer concrete. Overall, this study will ameliorate the present sewer corrosion monitoring capabilities by providing new data to models predicting sewer corrosion.

Thiyagarajan, K, Kodagoda, S, Van Nguyen, L & Ranasinghe, R 2018, 'Sensor Failure Detection and Faulty Data Accommodation Approach for Instrumented Wastewater Infrastructures', IEEE Access, vol. 6, no. 1, pp. 56562-56574.
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© 2013 IEEE. In wastewater industry, real-time sensing of surface temperature variations on concrete sewer pipes is paramount in assessing the rate of microbial-induced corrosion. However, the sensing systems are prone to failures due to the aggressively corrosive environmental conditions inside sewer assets. Therefore, reliable sensing in such infrastructures is vital for water utilities to enact efficient wastewater management. In this context, this paper presents a sensor failure detection and faulty data accommodation (SFDFDA) approach that aids to digitally monitor the health conditions of the sewer monitoring sensors. The SFDFDA approach embraces seasonal autoregressive integrated moving average model with a statistical hypothesis testing technique for enabling temporal forecasting of sensor variable. Then, it identifies and isolates anomalies in a continuous stream of sensor data whilst detecting early sensor failure. Finally, the SFDFDA approach provides reliable estimates of sensor data in the event of sensor failure or during the scheduled maintenance period of sewer monitoring systems. The SFDFDA approach was evaluated by using the surface temperature data sourced from the instrumented wastewater infrastructure and the results have demonstrated the effectiveness of the SFDFDA approach and its applicability to surface temperature monitoring sensor suites.

Thomas, D & Ding, G 2018, 'Comparing the performance of brick and timber in residential buildings – The case of Australia', Energy and Buildings, vol. 159, pp. 136-147.
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© 2017 Elsevier B.V. There is currently a limited use of timber products in residential development in Australia due to the dominance of heavy materials such as concrete, steel and brick. This dominant use of heavy materials is a reversal of the traditional material choice that was based predominantly on timber products. Technological advances and efficiencies drove the change to heavy materials to use in residential construction. The emerging issue with this reliance on heavy materials is the impact of their use on the environment. The carbon impact and problem of finite resource depletion associated with concrete, steel and bricks need to be addressed due to the increasing pressure from national and international requirements and legislations. The construction industry needs to reduce its negative impact on the environment and the renewable nature of timber presents a material solution to the problem. Timber from sustainably managed forests and plantations can be utilised as lumber or manufactured into engineered products for residential development. This paper examines the benefits of timber used in building envelopes when compared with conventional high-density materials such as brick and concrete when construction is designed with equivalent thermal performance. Multiple case studies were used to demonstrate the reduced life cycle energy and costs, and the time of construction benefits of timber when used as an alternative to heavy materials. Results revealed that Life cycle energy and time of construction showed noticeable differences between timber construction and heavy materials and cost showing marginal differences.

Tian, H, Li, W, Ogunbona, PO & Wang, L 2018, 'Detection and Separation of Smoke From Single Image Frames', IEEE Transactions on Image Processing, vol. 27, no. 3, pp. 1164-1177.
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© 2017 IEEE. This paper proposes novel methods for detecting and separating smoke from a single image frame. Specifically, an image formation model is derived based on the atmospheric scattering models. The separation of a frame into quasi-smoke and quasi-background components is formulated as convex optimization that solves a sparse representation problem using dual dictionaries for the smoke and background components, respectively. A novel feature is constructed as a concatenation of the respective sparse coefficients for detection. In addition, a method based on the concept of image matting is developed to separate the true smoke and background components from the smoke detection results. Extensive experiments on detection were conducted and the results showed that the proposed feature significantly outperforms existing features for smoke detection. In particular, the proposed method is able to differentiate smoke from other challenging objects (e.g. fog/haze, cloud, and so on) with similar visual appearance in a gray-scale frame. Experiments on smoke separation also demonstrated that the proposed separation method can effectively estimate/separate the true smoke and background components.

Tien Bui, D, Shahabi, H, Shirzadi, A, Chapi, K, Pradhan, B, Chen, W, Khosravi, K, Panahi, M, Bin Ahmad, B & Saro, L 2018, 'Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms', Sensors, vol. 18, no. 8, pp. 2464-2464.
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In this study, land subsidence susceptibility was assessed for a study area in South Korea by using four machine learning models including Bayesian Logistic Regression (BLR), Support Vector Machine (SVM), Logistic Model Tree (LMT) and Alternate Decision Tree (ADTree). Eight conditioning factors were distinguished as the most important affecting factors on land subsidence of Jeong-am area, including slope angle, distance to drift, drift density, geology, distance to lineament, lineament density, land use and rock-mass rating (RMR) were applied to modelling. About 24 previously occurred land subsidence were surveyed and used as training dataset (70% of data) and validation dataset (30% of data) in the modelling process. Each studied model generated a land subsidence susceptibility map (LSSM). The maps were verified using several appropriate tools including statistical indices, the area under the receiver operating characteristic (AUROC) and success rate (SR) and prediction rate (PR) curves. The results of this study indicated that the BLR model produced LSSM with higher acceptable accuracy and reliability compared to the other applied models, even though the other models also had reasonable results.

To, AWK, Paul, G & Liu, D 2018, 'A comprehensive approach to real-time fault diagnosis during automatic grit-blasting operation by autonomous industrial robots', Robotics and Computer-Integrated Manufacturing, vol. 49, pp. 13-23.
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© 2017 Elsevier Ltd This paper presents a comprehensive approach to diagnose for faults that may occur during a robotic grit-blasting operation. The approach proposes the use of information collected from multiple sensors (RGB-D camera, audio and pressure transducers) to detect for 1) the real-time position of the grit-blasting spot and 2) the real-time state within the blasting line (i.e. compressed air only). The outcome of this approach will enable a grit-blasting robot to autonomous diagnose for faults and take corrective actions during the blasting operation. Experiments are conducted in a laboratory and in a grit-blasting chamber during real grit-blasting to demonstrate the proposed approach. Accuracy of 95% and above has been achieved in the experiments.

To, VHP, Nguyen, TV, Vigneswaran, S, Bustamante, H, Higgins, M & van Rys, D 2018, 'Novel methodologies for determining a suitable polymer for effective sludge dewatering', Journal of Environmental Chemical Engineering, vol. 6, no. 4, pp. 4206-4214.
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© 2018 Elsevier Ltd. All rights reserved. Understanding the interactions between sludge particles and polymers during sludge dewatering is necessary to: firstly, maximize dewatered cake solids content; and secondly, minimize polymer demand. In this study, two scientific methodologies, namely the 'y-intercept' concept and Higgins modified centrifugal technique (Higgins MCT) were used to identify the optimum polymer demand and type for effective conditioning and dewatering. Results from the 'y-intercept' concept show that a large amount of polymer required during conditioning of anaerobically digested sludge (ADS) is mainly due to neutralization of soluble biopolymers. In contrast, conditioning of aerobically digested sludge (AEDS) and waste activated sludge (WAS) is mostly controlled by a polymer bridging mechanism. The results indicated that, in order to achieve maximum dewatering performance with minimum conditioning polymer requirement, high charge density polymers are suitable for ADS while branched (or cross-linked) polymers can be used for AEDS and WAS. The new lab-scale technique, Higgins MCT, was successfully implemented for measuring cake solids content achievable by centrifuge and determining the optimum polymer demand (OPD). The Higgins MCT also helped to understand the relationship between digestion, conditioning and dewatering.

Tomc, E & Vassallo, AM 2018, 'Community electricity and storage central management for multi-dwelling developments: An analysis of operating options', International Journal of Sustainable Energy Planning and Management, vol. 17, no. 3, pp. 15-30.
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A combination of PV, storage and energy management in multi-dwelling developments can be very effective in utilising load diversity and reducing grid dependence. Sharing PV and electricity storage resources within a community renewable energy network (CREN) via an energy management system (EMS) shifts the peak individual loads to times that the grid considers off-peak periods – i.e. night time – so managed off-peak charging and a retail plan with the lowest off-peak pricing affords the community savings in the order of 95.5% compared to the traditional individual grid connection. The balancing performed by the EMS eliminates the paradox of concomitant demand and supply from/to grid that occurs when some of the individual systems in the community have available charge while others do not. The optimisation of off-peak charging avoids 54% of redundant charge which is a financial gain in jurisdictions where feed-in tariffs are much lower than supply charges. Even though this study focuses on an Australian case study it provides a tool that allows the performance of the same analysis for other specific sites and load profiles.

Tong, C-X, Burton, GJ, Zhang, S & Sheng, D 2018, 'A simple particle-size distribution model for granular materials', Canadian Geotechnical Journal, vol. 55, no. 2, pp. 246-257.
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Particle-size distribution (PSD) is a fundamental soil property that plays an important role in soil classification and soil hydromechanical behaviour. A continuous mathematical model representing the PSD curve facilitates the quantification of particle breakage, which often takes place when granular soils are compressed or sheared. This paper proposes a simple and continuous PSD model for granular soils involving particle breakage. The model has two parameters and is able to represent different types of continuous PSD curves. It is found that one model parameter is closely related to the coefficient of nonuniformity (Cu) and the coefficient of curvature (Cc), while the other represents a characteristic particle diameter. A database of 53 granular soils with 154 varying PSD curves is analyzed to evaluate the performance of the proposed PSD model, as well as that of three other PSD models in the literature. The results show that the proposed model has improved overall performance and captures the typical trends in PSD evolution during particle breakage. In addition, the proposed model is also used for assessing the internal stability of 27 widely graded soils.

Torpy, F, Clements, N, Pollinger, M, Dengel, A, Mulvihill, I, He, C & Irga, P 2018, 'Testing the single-pass VOC removal efficiency of an active green wall using methyl ethyl ketone (MEK)', Air Quality, Atmosphere & Health, vol. 11, no. 2, pp. 163-170.
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© 2017, The Author(s). In recent years, research into the efficacy of indoor air biofiltration mechanisms, notably living green walls, has become more prevalent. Whilst green walls are often utilised within the built environment for their biophilic effects, there is little evidence demonstrating the efficacy of active green wall biofiltration for the removal of volatile organic compounds (VOCs) at concentrations found within an interior environment. The current work describes a novel approach to quantifying the VOC removal effectiveness by an active living green wall, which uses a mechanical system to force air through the substrate and plant foliage. After developing a single-pass efficiency protocol to understand the immediate effects of the system, the active green wall was installed into a 30-m3 chamber representative of a single room and presented with the contaminant 2-butanone (methyl ethyl ketone; MEK), a VOC commonly found in interior environments through its use in textile and plastic manufacture. Chamber inlet levels of MEK remained steady at 33.91 ± 0.541 ppbv. Utilising a forced-air system to draw the contaminated air through a green wall based on a soil-less growing medium containing activated carbon, the combined effects of substrate media and botanical component within the biofiltration system showed statistically significant VOC reduction, averaging 57% single-pass removal efficiency over multiple test procedures. These results indicate a high level of VOC removal efficiency for the active green wall biofilter tested and provide evidence that active biofiltration may aid in reducing exposure to VOCs in the indoor environment.

Torpy, FR, Pettit, T & Irga, PJ 2018, 'Applied Horticultural Biotechnology for the Mitigation of Indoor Air Pollution', Journal of People, Plants, and Environment, vol. 21, no. 6, pp. 445-460.
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Exposure to indoor air pollution is an emerging world-wide problem, with growing evidence that it is a major cause of morbidity worldwide. Whilst most indoor air pollutants are of outdoor origin, these combine with a range of indoor sourced pollutants that may lead to high pollutant levels indoors. The pollutants of greatest concern are volatile organic compounds (VOCs) and particulate matter (PM), both of which are associated with a range of serious health problems. Whilst current buildings usually use ventilation with outdoor air to remove these pollutants, botanical systems are gaining recognition as an effective alternative. Whilst many years research has shown that traditional potted plants and their substrates are capable of removing VOCs effectively, they are inefficient at removing PM, and are limited in their pollutant removal rates by the need for pollutants to diffuse to the active pollutant removal components of these systems. Active botanical biofiltration, using green wall systems combined with mechanical fans to increase pollutant exposure to the plants and substrate, show greatly increased rates of pollutant removal for both VOCs, PM and also carbon dioxide (CO2). A developing body of research indicates that these systems can outperform existing technologies for indoor air pollutant removal, although further research is required before their use will become widespread. Whilst it is known that plant species selection and substrate characteristics can affect the performance of active botanical systems, optimal characteristics are yet to be identified. Once this research has been completed, it is proposed that active botanical biofiltration will provide a cheap and low energy use alternative to mechanical ventilations systems for the maintenance of indoor environmental quality.

Tran, HN, Lee, C-K, Nguyen, TV & Chao, H-P 2018, 'Saccharide-derived microporous spherical biochar prepared from hydrothermal carbonization and different pyrolysis temperatures: synthesis, characterization, and application in water treatment', Environmental Technology, vol. 39, no. 21, pp. 2747-2760.
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© 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group. Three saccharides (glucose, sucrose, and xylose) were used as pure precursors for synthesizing spherical biochars (GB, SB, and XB), respectively. The two-stage synthesis process comprised: (1) the hydrothermal carbonization of saccharides to produce spherical hydrochar’ and (2) pyrolysis of the hydrochar at different temperatures from 300°C to 1200°C. The results demonstrated that the pyrolysis temperatures insignificantly affected the spherical morphology and surface chemistry of biochar. The biochar’ isoelectric point ranged from 2.64 to 3.90 (abundant oxygen-containing functionalities). The Brunauer–Emmett–Teller (BET)-specific surface areas (SBET) and total pore volumes (Vtotal) of biochar increased with the increasing pyrolysis temperatures. The highest SBET and Vtotal were obtained at a pyrolysis temperature of 900°C for GB (775 m2/g and 0.392 cm3/g), 500°C for SB (410 m2/g and 0.212 cm3/g), and 600°C for XB (426 m2/g and 0.225 cm3/g), respectively. The spherical biochar was a microporous material with approximately 71–98% micropore volume. X-ray diffraction results indicated that the biochar’ structure was predominantly amorphous. The spherical biochar possessed the graphite structure when the pyrolysis temperature was higher than 600°C. The adsorption capacity of GB depended strongly on the pyrolysis temperature. The maximum Langmuir adsorption capacities ((Formula presented.)) of 900GB exhibited the following selective order: phenol (2.332 mmol/g) > Pb2+ (1.052 mmol/g) > Cu2+ (0.825 mmol/g) > methylene green 5 (0.426 mmol/g) > acid red 1 (0.076 mmol/g). This study provides a simple method to prepare spherical biochar–a new and potential adsorbent for adsorbing heavy metals and aromatic contaminants.

Tran, T & Ha, QP 2018, 'Perturbed cooperative-state feedback strategy for model predictive networked control of interconnected systems', ISA Transactions, vol. 72, pp. 110-121.
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© 2017 ISA A perturbed cooperative-state feedback (PSF) strategy is presented for the control of interconnected systems in this paper. The subsystems of an interconnected system can exchange data via the communication network that has multiple connection topologies. The PSF strategy can resolve both issues, the sensor data losses and the communication network breaks, thanks to the two components of the control including a cooperative-state feedback and a perturbation variable, e.g., ui=Kijxj+wi. The PSF is implemented in a decentralized model predictive control scheme with a stability constraint and a non-monotonic storage function (ΔV(x(k))≥0), derived from the dissipative systems theory. Numerical simulation for the automatic generation control problem in power systems is studied to illustrate the effectiveness of the presented PSF strategy.

Tran, T, Bliuc, D, Hansen, L, Abrahamsen, B, van den Bergh, J, Eisman, JA, van Geel, T, Geusens, P, Vestergaard, P, Nguyen, TV & Center, JR 2018, 'Persistence of Excess Mortality Following Individual Nonhip Fractures: A Relative Survival Analysis', The Journal of Clinical Endocrinology & Metabolism, vol. 103, no. 9, pp. 3205-3214.
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© 2018 Endocrine Society. Context: Little is known about long-term excess mortality following fragility nonhip fractures. Objective: The study aimed to determine which fracture was associated with excess mortality and for how long the postfracture excess mortality persisted. Design, Setting, and Patients: This nationwide registry-based follow-up study included all individuals in Denmark aged 50+ years who first experienced fragility fractures in 2001 and were followed up for up to 10 years for their mortality risk. Main Outcome Measure: The contribution of fracture to mortality at precise postfracture time intervals was examined using relative survival analysis, accounting for time-related mortality changes in the background population. Results: There were 21,123 women (aged 72 ± 13 years) and 9481 men (aged 67 ± 12 years) with an incident fragility fracture in 2001, followed by 10,668 and 4745 deaths, respectively. Excess mortality was observed following all proximal and lower leg fractures. The majority of deaths occurred within the first year after fracture, and thereafter excess mortality gradually declined. Hip fractures were associated with the highest excess mortality (33% and 20% at 1 year after fracture in men and women, respectively). One-year excess mortality after fracture of a femur or pelvis was 20% to 25%; vertebrae, 10%; humerus, rib, or clavicle, 5% to 10%; and lower leg, 3%. A significant although smaller excess mortality was still observed until 10 years for hip fractures and ∼5 years after femur, other proximal, and lower leg fractures. Conclusion: This study highlights the important contribution of a wide variety of fragility fractures to long-term excess mortality and thus the potential for benefit from early intervention.

Trianni, A & Thollander, P 2018, 'Guest editorial note', Energy Efficiency, vol. 11, no. 5, pp. 1053-1055.
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Trianni, A, Merigó, JM & Bertoldi, P 2018, 'Ten years of Energy Efficiency: a bibliometric analysis', Energy Efficiency, vol. 11, no. 8, pp. 1917-1939.
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© 2018, Springer Nature B.V. Energy Efficiency is an international journal dedicated to research topics connected to energy with a focus on end-use efficiency issues. In 2018, the journal celebrates its 10th anniversary. In order to mark it and analyze not only how the journal has been performing over the years, but also which are the trends for academic debate and research in this journal, this article presents a bibliometric overview of the publication and citation structure of the journal during period 2008–2017. The study relies on the Web of Science Core Collection and the Scopus database to collect the bibliographic results. Additionally, the work exploits the visualization of similarities (VOS) viewer software to map graphically the bibliographic material. The research analyses the most cited papers and the most popular keywords. Moreover, the paper studies how the journal connects with other international journals and identifies the most productive authors, institutions, and countries. The results indicate that the journal has rapidly grown over the years, obtained a merited position in the scientific community, with contributions from authors all over the world (with Europe as the most productive region). Moreover, the journal has focused so far mainly on energy efficiency issues in close relationship with policies and incentives, corporate energy efficiency, consumer behavior, and demand-side management programs, with both industrial, building and transport sectors widely involved. Our discussion concludes with suggested future research avenues, in particular towards coordinated efforts from different disciplines (technical, economic, and sociopsychological ones) to address the emerging energy efficiency challenges.

Tsai, W-C & van den Hoven, E 2018, 'Memory Probes: Exploring Retrospective User Experience Through Traces of Use on Cherished Objects', INTERNATIONAL JOURNAL OF DESIGN, vol. 12, no. 3, pp. 57-72.

Tur-Porcar, A, Mas-Tur, A, Merigó, JM, Roig-Tierno, N & Watt, J 2018, 'A Bibliometric History of the Journal of Psychology Between 1936 and 2015', The Journal of Psychology, vol. 152, no. 4, pp. 199-225.
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Uddin, MB, Chow, CM & Su, SW 2018, 'Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review', Physiological Measurement, vol. 39, no. 3, pp. 03TR01-03TR01.
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© 2018 Institute of Physics and Engineering in Medicine. Objective: Sleep apnea (SA), a common sleep disorder, can significantly decrease the quality of life, and is closely associated with major health risks such as cardiovascular disease, sudden death, depression, and hypertension. The normal diagnostic process of SA using polysomnography is costly and time consuming. In addition, the accuracy of different classification methods to detect SA varies with the use of different physiological signals. If an effective, reliable, and accurate classification method is developed, then the diagnosis of SA and its associated treatment will be time-efficient and economical. This study aims to systematically review the literature and present an overview of classification methods to detect SA using respiratory and oximetry signals and address the automated detection approach. Approach: Sixty-two included studies revealed the application of single and multiple signals (respiratory and oximetry) for the diagnosis of SA. Main results: Both airflow and oxygen saturation signals alone were effective in detecting SA in the case of binary decision-making, whereas multiple signals were good for multi-class detection. In addition, some machine learning methods were superior to the other classification methods for SA detection using respiratory and oximetry signals. Significance: To deal with the respiratory and oximetry signals, a good choice of classification method as well as the consideration of associated factors would result in high accuracy in the detection of SA. An accurate classification method should provide a high detection rate with an automated (independent of human action) analysis of respiratory and oximetry signals. Future high-quality automated studies using large samples of data from multiple patient groups or record batches are recommended.

Uddin, MN, Techato, K, Taweekun, J, Rahman, MM, Rasul, MG, Mahlia, TMI & Ashrafur, SM 2018, 'An Overview of Recent Developments in Biomass Pyrolysis Technologies', Energies, vol. 11, no. 11, pp. 3115-3115.
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Biomass is a promising sustainable and renewable energy source, due to its high diversity of sources, and as it is profusely obtainable everywhere in the world. It is the third most important fuel source used to generate electricity and for thermal applications, as 50% of the global population depends on biomass. The increase in availability and technological developments of recent years allow the use of biomass as a renewable energy source with low levels of emissions and environmental impacts. Biomass energy can be in the forms of biogas, bio-liquid, and bio-solid fuels. It can be used to replace fossil fuels in the power and transportation sectors. This paper critically reviews the facts and prospects of biomass, the pyrolysis process to obtain bio-oil, the impact of different pyrolysis technology (for example, temperature and speed of pyrolysis process), and the impact of various reactors. The paper also discusses different pyrolysis products, their yields, and factors affecting biomass products, including the present status of the pyrolysis process and future challenges. This study concluded that the characteristics of pyrolysis products depend on the biomass used, and what the pyrolysis product, such as bio-oil, can contribute to the local economy. Finally, more research, along with government subsidies and technology transfer, is needed to tackle the future challenges of the development of pyrolysis technology.

Ulapane, N, Alempijevic, A, Valls Miro, J & Vidal-Calleja, T 2018, 'Non-destructive evaluation of ferromagnetic material thickness using Pulsed Eddy Current sensor detector coil voltage decay rate', NDT & E International, vol. 100, pp. 108-114.
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© 2018 Elsevier Ltd A ferromagnetic material thickness quantification method based on the decay rate of the Pulsed Eddy Current sensor detector coil voltage is proposed. An expression for the decay rate is derived and the relationship between the decay rate and material thickness is established. Pipe wall thickness estimation is done with a developed circular sensor incorporating the proposed method, and results are evaluated through destructive testing. The decay rate feature has a unique attribute of being lowly dependent on properties such as sensor shape and size, and lift-off, enabling the method to be usable with any detector coil-based sensor. A case study on using the proposed method with a commercial sensor is also presented to demonstrate its versatility.

Usman, M, Yang, N, Jan, MA, He, X, Xu, M & Lam, K-M 2018, 'A Joint Framework for QoS and QoE for Video Transmission over Wireless Multimedia Sensor Networks', IEEE Transactions on Mobile Computing, vol. 17, no. 4, pp. 746-759.
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© 2002-2012 IEEE. With the emergence of Wireless Multimedia Sensor Networks (WMSNs), the distribution of multimedia contents have now become a reality. Without proper management, the transmission of multimedia data over WMSNs affects the performance of networks due to excessive packet-drop. The existing studies on Quality of Service (QoS) mostly deal with simple Wireless Sensor Networks (WSNs) and as such do not account for an increasing number of sensor nodes and an increasing volume of data. In this paper, we propose a novel framework to support QoS in WMSNs along with a light-weight Error Concealment (EC) scheme. The EC schemes play a vital role to enhance Quality of Experience (QoE) by maintaining an acceptable quality at the receiving ends. The main objectives of the proposed framework are to maximize the network throughput and to cover-up the effects produced by dropped video packets. To control the data-rate, Scalable High efficiency Video Coding (SHVC) is applied at multimedia sensor nodes with variable Quantization Parameters (QPs). Multi-path routing is exploited to support real-time video transmission. Experimental results show that the proposed framework can efficiently adjust large volumes of video data under certain network distortions and can effectively conceal lost video frames by producing better objective measurements.

Vahedian, A, Shrestha, R & Crews, K 2018, 'Analysis of externally bonded Carbon Fibre Reinforced Polymers sheet to timber interface', Composite Structures, vol. 191, pp. 239-250.
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Vahedian, A, Shrestha, R & Crews, K 2018, 'Bond strength model for externally bonded FRP-to-timber interface', Composite Structures, vol. 200, pp. 328-339.
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Vakhshouri, B & Nejadi, S 2018, 'Effect of fiber reinforcing on instantaneous deflection of self-compacting concrete one-way slabs under early-age loading', Structural Engineering and Mechanics, vol. 67, no. 2, pp. 155-163.
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The Early-age construction loading and changing properties of concrete, especially in the multi-story structures can affect the slab deflection, significantly. Based on previously conducted experiment on eight simply-supported one-way slabs this paper investigates the effect of concrete type, fiber type and content, loading value, cracking moment, ultimate moment and applied moment on the instantaneous deflection of Self-Compacting Concrete (SCC) slabs. Two distinct loading levels equal to 30% and 40% of the ultimate capacity of the slab section were applied on the slabs at the age of 14 days. A wide range of the existing models of the effective moment of inertia which are mainly developed for conventional concrete elements, were investigated. Comparison of the experimental deflection values with predictions of the existing models shows considerable differences between the recorded and estimated instantaneous deflection of SCC slabs. Calculated elastic deflection of slabs at the ages of 14 and 28 days were also compared with the experimental deflection of slabs. Based on sensitivity analysis of the effective parameters, a new model is proposed and verified to predict the effective moment of inertia in SCC slabs with and without fiber reinforcing under two different loading levels at the age of 14 days.

Vakhshouri, B & Nejadi, S 2018, 'Instantaneous deflection of self-compacting and lightweight concrete slabs at early-age', Engineering Solid Mechanics, vol. 6, no. 2, pp. 143-154.
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© 2018 Growing Science Ltd. All rights reserved. This paper describes laboratory tests on twelve simply-supported one-way slabs including four lightweight concrete slabs in this study and previously conducted experiments on eight self-compacting reinforced concrete slabs subjected to loading at the age of 14 days. All slab were identical by dimensions of 3.8 m long supported on 3.5 m span, 400 mm wide, and 161 mm deep with 4N12 bars at an effective depth of 136 mm providing a reinforcement ratio of 0.008. After seven days moist-curing, the specimens were removed from the formworks and subjected to different values of the uniformly distributed loading including the self-weight of slabs. The mid-span deflection of slabs was recorded immediately after putting the loading blocks on the slabs. Despite close values of the compressive strength of the mixtures, the obtained results validate the effect of the concrete type on the instantaneous deflection of slabs. A wide range of existing models of the effective stiffness of reinforced concrete section were investigated to predict the instantaneous deflection of slabs. Majority of the models are developed for conventional concrete. Comparing the predicted and experimental results of mid-span deflection confirmed that the existing models are inadequate for lightly reinforced specimens such as slabs. New models are proposed and verified to predict the effective moment of inertia in the slabs with and without fiber reinforcing concretes.

Vakhshouri, B & Nejadi, S 2018, 'Prediction of compressive strength of self-compacting concrete by ANFIS models', Neurocomputing, vol. 280, pp. 13-22.
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© 2017 Elsevier Ltd. Many studies predict the compressive strength of conventional concrete from hardened characteristics; however, in the case of self-compacting concrete, these investigations are very rare. There is no study to predict the compressive strength of self-compacting concrete from mixture proportions and slump flow. This paper designs ANFIS models to establish relationship between the compressive strength as output, and slump flow and mixture proportions as input in eighteen combinations of input parameters. The applied dada is taken from 55 previously conducted experimental studies. Effect of each parameter on the compressive strength and its importance level in the developed model has been investigated. Based on the error size in each combination analysis, weighting factor and importance level of each parameter is evaluated to apply the correction factors to get the most optimized relationship. Obtained results indicate that the model including all input data (slump flow and mixture proportions) gives the best prediction of the compressive strength. Excluding the slump flow from combinations affects the prediction of compressive strength, considerably. However it's not as much as the effect of the maximum aggregate size and aggregate volume in the mixture design. In addition, different values of powder volume, aggregate volume and paste content in the mixture reveal different ascending and descending effects on the compressive strength.

Vakhshouri, B & Nejadi, S 2018, 'Review on the mixture design and mechanical properties of the lightweight concrete containing expanded polystyrene beads', Australian Journal of Structural Engineering, vol. 19, no. 1, pp. 1-23.
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© 2017, © 2017 Engineers Australia. Lightweight concrete containing expanded polystyrene beads (EPS-LWC) is frequently used in different structural and non-structural applications, since it was first developed about 60 years ago. However, effect of new materials and admixtures to improve its performance and strength are not investigated properly. A wide range of investigations about EPS-LWC since 1976, including the experimental data are evaluated. The collected data contain the information of curing methods, type of fine and coarse aggregates, mineral fillers, chemical admixtures and fibres in each experiment. In addition, the mixture proportions including the size and volume of EPS beads, density and compressive strength of the concrete are presented. Mechanical properties of EPS-LWC from 154 mixture design in 55 experimental programmes are also assessed. Utilising the experimental data, new models are developed and verified by the existing models of the mechanical properties of concrete. The existing models of the mechanical properties of LWC are also compared with those of the convention concrete.

Vakhshouri, B & Nejadi, S 2018, 'Sensitivity of concrete properties to compressive strength', Proceedings of the Institution of Civil Engineers - Engineering and Computational Mechanics, vol. 171, no. 1, pp. 29-44.
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Concrete is generally classified by compressive strength (CS) grade, which signifies the characteristic strength required. Other mechanical parameters of concrete are expressed in terms of the CS. Depending on design objectives, economic issues and available materials, normal-strength concrete, high-strength concrete (HSC) or ultra-high-strength concrete (UHSC) might be used in design and construction. Due to the non-linear nature of concrete, there is no proportional relation between properties of concrete, even in corresponding characteristics in different types of concrete. Although design codes and experimental investigations define different limits for HSC and UHSC and present relations for properties of various concrete classes, predicted values are sometimes significantly imprecise. This study broadly presents equations to estimate modulus of elasticity, splitting tensile strength and modulus of rupture for different CS classifications and validates them by comparing with empirical relations and international design codes' formulae.

Vakhshouri, B & Nejadi, S 2018, 'Size effect and age factor in mechanical properties of BST Light Weight Concrete', Construction and Building Materials, vol. 177, pp. 63-71.
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© 2018 Elsevier Ltd Replacement of whole or part of normal aggregates with Expanded Polystyrene (EPS) beads in the concrete mix is a reliable method to produce Light Weight Concrete (LWC) with considerable advantages. Due to modification effect on mechanical properties of LWC, it is important to examine whether all the assumed hypotheses about conventional concrete also are applicable for LWC structures. Based on an experimental program, this study investigates the effects of specimen size and shape on the compressive and tensile strength of this type of LWC. In this regard, cylinder specimens with 75 × 150, 100 × 200 and 150 × 300 mm dimensions and cube specimens with 100 and 150 mm dimensions were cast and cured in laboratory conditions. Compressive and tensile strengths were tested after 3, 7, 14, 21, 28, 56 and 91 days. The correlation factor between the compressive strength, tensile strength and the shape and size of specimens is evaluated also.

Valdes-Mora, F, Handler, K, Law, AMK, Salomon, R, Oakes, SR, Ormandy, CJ & Gallego-Ortega, D 2018, 'Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology', Frontiers in Immunology, vol. 9.
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Valenzuela-Fernández, L, Merigó, JM & Nicolas, C 2018, 'The most influential countries in market orientation', International Journal of Engineering Business Management, vol. 10, pp. 184797901775148-184797901775148.
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The purpose of this article is to analyze the most productive and influential countries engaging in market orientation (MO) research between 1990 and 2016. This article shows the general trajectories of these countries, the relationships among them, and their research in the area of MO by analyzing results on citations and publications. The article uses applied bibliometric techniques on available information found in the Web of Science. The results show that the 10 leading countries produce more than 70% of total publications, where the United States leads in all indicators, followed by the United Kingdom and China. Furthermore, although there has been a steady increase in overall number of publications, this trend is not shared evenly among different nations.

Valenzuela-Fernández, L, Nicolas, C & Merigo, JM 2018, 'Overview of the leading countries in marketing research between 1990 and 2014', American Journal of Business, vol. 33, no. 4, pp. 134-156.
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PurposeThe purpose of this paper is to present a general overview of the most influential countries according to their scientific contributions in marketing for the 1990–2014 period. In this bibliometric-based research, the authors generate a ranking of the 50 most influential nations according to the H-index and citations per paper, co-authorship, citation analysis and bibliographic coupling. The study provides a map that identifies the networks of researchers between countries.Design/methodology/approachThe method used is bibliometric analysis. The relevant research in marketing was extracted from Web of Science Database Core Collection, during the 1990–2014 period; 29,947 published articles in 50 countries were obtained. The investigation used: H-index as the first criterion in creating the country ranking, number of articles (TP) as a proxy for the productivity of each country, the average citation per article (C/P) and the number of citations (TC) to express the influence of a country’s articles. In addition, the study adopts VOSviewer software to identify the collaboration networks of researchers between countries and the links between countries.FindingsThe results reveal a general level that 54 percent of countries have a category H-index greater than 20. In turn, the authors see a steady increase in the number of publications over the five-year periods. The first ten countries account for over 80 percent of all publications of the sample. The USA is presented here as the leader in all indicators and highlights the important role that China has been developing.Research limitations/implicat...

Valls Miro, J, Ulapane, N, Shi, L, Hunt, D & Behrens, M 2018, 'Robotic pipeline wall thickness evaluation for dense nondestructive testing inspection', Journal of Field Robotics, vol. 35, no. 8, pp. 1293-1310.
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AbstractThis paper addresses automated mapping of the remaining wall thickness of metallic pipelines in the field by means of an inspection robot equipped with nondestructive testing (NDT) sensing. Set in the context of condition assessment of critical infrastructure, the integrity of arbitrary sections in the conduit is derived with a bespoke robot kinematic configuration that allows dense pipe wall thickness discrimination in circumferential and longitudinal direction via NDT sensing with guaranteed sensing lift‐off (offset of the sensor from pipe wall) to the pipe wall, an essential barrier to overcome in cement‐lined water pipelines. A tailored covariance function for pipeline cylindrical structures within the context of a Gaussian Processes has also been developed to regress missing sensor data incurred by a sampling strategy folllowed in the field to speed up the inspection times, given the slow response of the pulsed eddy current electromagnetic sensor proposed. The data gathered represent not only a visual understanding of the condition of the pipe for asset managers, but also constitute a quantative input to a remaining‐life calculation that defines the likelihood of the pipeline for future renewal or repair. Results are presented from deployment of the robotic device on a series of pipeline inspections which demonstrate the feasibility of the device and sensing configuration to provide meaningful 2.5D geometric maps.

van Geel, TACM, Bliuc, D, Geusens, PPM, Center, JR, Dinant, G-J, Tran, T, van den Bergh, JPW, McLellan, AR & Eisman, JA 2018, 'Reduced mortality and subsequent fracture risk associated with oral bisphosphonate recommendation in a fracture liaison service setting: A prospective cohort study', PLOS ONE, vol. 13, no. 6, pp. e0198006-e0198006.
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OBJECTIVE: Osteoporotic fragility fractures, that are common in men and women, signal increased risk of future fractures and of premature mortality. Less than one-third of postmenopausal women and fewer men are prescribed active treatments to reduce fracture risk. Therefore, in this study the association of oral bisphosphonate recommendation with subsequent fracture and mortality over eight years in a fracture liaison service setting was analysed. MATERIALS AND METHODS: In this prospective cohort study, 5011 men and women aged >50 years, who sustained a clinical fracture, accepted the invitation to attend the fracture liaison service of the West Glasgow health service between 1999 and 2007. These patients were fully assessed and all were recommended calcium and vitamin D. Based on pre-defined fracture risk criteria, 2534 (50.7%) patients were additionally also recommended oral bisphosphonates. Mortality and subsequent fracture risk were the pre-defined outcomes analysed using Cox proportional hazard models. RESULTS: Those recommended bisphosphonates were more often female (82.9 vs. 72.4%), were older (73.4 vs. 64.4 years), had lower bone mineral density T-score (-3.1 vs. -1.5) and more had sustained hip fractures (21.7 vs. 6.2%; p < 0.001). After adjustments, patients recommended bisphosphonates had lower subsequent fracture risk (Hazard Ratio (HR): 0.60; 95% confidence interval (CI): 0.49-0.73) and lower mortality risk (HR: 0.79, 95%CI: 0.64-0.97). CONCLUSION: Of the patients, who are fully assessed after a fracture at the fracture liaison service, those with higher fracture risk and a recommendation for bisphosphonates had worse baseline characteristics. However, after adjusting for these differences, those recommended bisphosphonate treatment had a substantially lower risk for subsequent fragility fracture and lower risk for mortality. These community-based data indicate the adverse public health outcomes and mortality impacts of the current low trea...

Van, HT, Nguyen, TMP, Thao, VT, Vu, XH, Nguyen, TV & Nguyen, LH 2018, 'Applying Activated Carbon Derived from Coconut Shell Loaded by Silver Nanoparticles to Remove Methylene Blue in Aqueous Solution', Water, Air, & Soil Pollution, vol. 229, no. 12.
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© 2018, Springer Nature Switzerland AG. This study developed a new adsorbent, specifically activated carbon-loaded silver nanoparticles (AgNPs-AC) by coating the silver nanoparticles (AgNPs) onto activated carbon (AC). The obtained AgNPs-AC were characterized by scanning electron microscopy (SEM), energy-dispersive spectrometry (EDS), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET). The ability of AgNPs-AC to remove methylene blue (MB) was evaluated using different experimental factors, these being pH solution, contact time, adsorbent dose, and initial MB concentration. Results indicated that the highest adsorption capacity of MB onto AgNPs-AC was obtained when the AC was loaded onto AgNPs at the impregnation ratio of 0.5% w/w for AC and AgNPs. The best conditions in which AgNPs-AC could remove MB were as follows: pH 10, contact time lasting 120 min, and adsorbent dose being 250 mg/25 mL solution. In this scenario, the maximum adsorption capacity of MB onto AgNPs-AC was 172.22 mg/g. The adsorption isothermal equilibrium was well described by the Langmuir, Freundlich and Sips models. The Sips equations had the highest correlation coefficient value (R2 = 0.935). The pseudo-first-order and pseudo-second-order kinetic models agree well with the dynamic behavior of the adsorption of dye MB on AgNPs-AC.

Varisco, M, Deuse, J, Johnsson, C, Nöhring, F, Schiraldi, MM & Wöstmann, R 2018, 'From production planning flows to manufacturing operation management KPIs: linking ISO18828 & ISO22400 standards', IFAC-PapersOnLine, vol. 51, no. 11, pp. 25-30.
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© 2018 International standards are playing a key role in leading and shaping the smart manufacturing landscape. The integration and consistency among different standards is therefore essential to effectively support industrial automation evolution and to ensure their applicability. This paper focuses on the ISO18828 and ISO22400 standards, related to the production planning process and manufacturing, consequential phases in product lifecycle. In this paper the connections between the information related to production planning process (ISO18828) and the KPI main basic elements in manufacturing operation management (ISO22400) are analysed. The analysis aims at supporting the standards’ users, underlining the aspects that should be taken into account in order to consolidate and improve the considered lifecycle phases.

Viardot, A, Purtell, L, Nguyen, TV & Campbell, LV 2018, 'Relative Contributions of Lean and Fat Mass to Bone Mineral Density: Insight From Prader-Willi Syndrome', Frontiers in Endocrinology, vol. 9, no. AUG.
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© 2018 Viardot, Purtell, Nguyen and Campbell. Context: Low bone mineral density (BMD) is the most important risk factor for fragility fracture. Body weight is a simple screening predictor of difference in BMD between individuals. However, it is not clear which component of body weight, lean (LM), or fat mass (FM), is associated with BMD. People with the genetic disorder of Prader-Willi syndrome (PWS) uniquely have a reduced LM despite increased FM. Objective: We sought to define the individual impact of LM and FM on BMD by investigating subjects with and without PWS. Design, Setting and Participants: This cross-sectional study was conducted at the Clinical Research Facility of the Garvan Institute of Medical Research, with PWS and control participants recruited from a specialized PWS clinic and from the general public by advertisement, respectively. The study involved 11 adults with PWS, who were age- and sex-matched with 12 obese individuals (Obese group) and 10 lean individuals (Lean group). Main Outcome Measures: Whole body BMD was measured by dual-energy X-ray absorptiometry. Total body FM and LM were derived from the whole body scan. Differences in BMD between groups were assessed by the analysis of covariance model, taking into account the effects of LM and FM. Results: The PWS group had significantly shorter height than the lean and obese groups. As expected, there was no significant difference in FM between the Obese and PWS group, and no significant difference in LM between the Lean and PWS group. However, obese individuals had greater LM than lean individuals. BMD in lean individuals was significantly lower than in PWS individuals (1.13 g/cm2 vs. 1.21 g/cm2, p < 0.05) and obese individuals (1.13 g/cm2 vs. 1.25 g/cm2, p < 0.05). After adjusting for both LM and FM, there was no significant difference in BMD between groups, and the only significant predictor of BMD was LM. Conclusions: These data from the human genetic model Prader-Willi syndrome...

Vijayan, MK, Chitambar, E & Hsieh, M-H 2018, 'One-shot assisted concentration of coherence', Journal of Physics A: Mathematical and Theoretical 51.41 (2018): 414001, vol. 51, no. 41.
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We find one-shot bounds for concentration of maximally coherent states in theso called assisted scenario. In this setting, Bob is restricted to performingincoherent operations on his quantum system, however he is assisted by Alice,who holds a purification of Bob's state and can send classical data to him. Wefurther show that in the asymptotic limit our one-shot bounds recover thepreviously computed rate of asymptotic assisted concentration.

Vo Hoang Nhat, P, Ngo, HH, Guo, WS, Chang, SW, Nguyen, DD, Nguyen, PD, Bui, XT, Zhang, XB & Guo, JB 2018, 'Can algae-based technologies be an affordable green process for biofuel production and wastewater remediation?', Bioresource Technology, vol. 256, pp. 491-501.
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© 2018 Elsevier Ltd Algae is a well-known organism that its characteristic is prominent for biofuel production and wastewater remediation. This critical review aims to present the applicability of algae with in-depth discussion regarding three key aspects: (i) characterization of algae for its applications; (ii) the technical approaches and their strengths and drawbacks; and (iii) future perspectives of algae-based technologies. The process optimization and combinations with other chemical and biological processes have generated efficiency, in which bio-oil yield is up to 41.1%. Through life cycle assessment, algae bio-energy achieves high energy return than fossil fuel. Thus, the algae-based technologies can reasonably be considered as green approaches. Although selling price of algae bio-oil is still high (about $2 L−1) compared to fossil fuel's price of $1 L−1, it is expected that the algae bio-oil's price will become acceptable in the next coming decades and potentially dominate 75% of the market.

Vo, K, Pham, T, Nguyen, DN, Kha, HH & Dutkiewicz, E 2018, 'Subject-Independent ERP-Based Brain–Computer Interfaces', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, no. 4, pp. 719-728.
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Brain–computer interfaces (BCIs) are desirable for people to express their thoughts, especially those with profound disabilities in communication. The classification of brain patterns for each different subject requires an extensively time-consuming learning stage specific to that person, in order to reach satisfactory accuracy performance. The training session could also be infeasible for disabled patients as they may not fully understand the training instructions. In this paper, we propose a unified classification scheme based on ensemble classifier, dynamic stopping, and adaptive learning. We apply this scheme on the P300-based BCI, with the subjectindependent manner, where no learning session is required for new experimental users. According to our theoretical analysis and empirical results, the harmonized integration of these three methods can significantly boost up the average accuracy from 75.00% to 91.26%, while at the same time reduce the average spelling time from 12.62 to 6.78 iterations, approximately to two-fold faster. The experiments were conducted on a large public dataset which had been used in other related studies. Direct comparisons between our work with the others’ are also reported in details.

Vo, N-S, Duong, TQ, Tuan, HD & Kortun, A 2018, 'Optimal Video Streaming in Dense 5G Networks With D2D Communications', IEEE Access, vol. 6, pp. 209-223.
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© 2017 IEEE. Mobile video traffic and mobile devices have now outpaced other data traffic and fixed devices. Global service providers are attempting to propose new mobile infrastructures and solutions for high performance of video streaming services, i.e., high quality of experience (QoE) at high resource efficiency. Although device-to-device (D2D) communications have been an emerging technique that is anticipated to provide a massive number of mobile users with advanced services in 5G networks, the management of resource and co-channel interference between D2D pairs, i.e., helper-requester pairs, and cellular users (CUs) is challenging. In this paper, we design an optimal rate allocation and description distribution for high performance video streaming, particularly, achieving high QoE at high energy efficiency while limiting co-channel interference over D2D communications in 5G networks. To this end, we allocate optimal encoding rates to different layers of a video segment and then packetize the video segment into multiple descriptions with embedded forward error correction before transmission. Simultaneously, the optimal numbers of descriptions are distributed to D2D helpers and base stations in a cooperative scheme for transmitting to the D2D requesters. The optimal results are efficiently in correspondence with intra-popularity of different segments of a video characterized by requesters' behavior, characteristic of lossy wireless channels, channel state information of D2D requesters, and constraints on remaining energy of D2D helpers and target signal to interference plus noise ratio of CUs. Simulation results demonstrate the benefits of our proposed solution in terms of high performance video streaming.

Vo, T-D-H, Bui, X-T, Nguyen, D-D, Nguyen, V-T, Ngo, H-H, Guo, W, Nguyen, P-D, Nguyen, C-N & Lin, C 2018, 'Wastewater treatment and biomass growth of eight plants for shallow bed wetland roofs', Bioresource Technology, vol. 247, pp. 992-998.
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© 2017 Elsevier Ltd Wetland roof (WR) could bring many advantages for tropical cities such as thermal benefits, flood control, green coverage and domestic wastewater treatment. This study investigates wastewater treatment and biomass growth of eight local plants in shallow bed WRs. Results showed that removal rates of WRs were 21–28 kg COD ha−1 day−1, 9–13 kg TN ha−1 day−1 and 0.5–0.9 kg TP ha−1 day−1, respectively. The plants generated more biomass at lower hydraulic loading rate (HLR). Dry biomass growth was 0.4–28.1 g day−1 for average HLR of 247–403 m3 ha−1 day−1. Green leaf area of the plants was ranging as high as 67–99 m2 leaves per m2 of WR. In general, the descent order of Kyllinga brevifoliaRottb (WR8), Cyperus javanicus Houtt (WR5) and Imperata cylindrical (WR4) was suggested as effective vegetations in WR conditions in terms of wastewater treatment, dry biomass growth and green coverage ratio.

Voinov, A, Jenni, K, Gray, S, Kolagani, N, Glynn, PD, Bommel, P, Prell, C, Zellner, M, Paolisso, M, Jordan, R, Sterling, E, Schmitt Olabisi, L, Giabbanelli, PJ, Sun, Z, Le Page, C, Elsawah, S, BenDor, TK, Hubacek, K, Laursen, BK, Jetter, A, Basco-Carrera, L, Singer, A, Young, L, Brunacini, J & Smajgl, A 2018, 'Tools and methods in participatory modeling: Selecting the right tool for the job', Environmental Modelling & Software, vol. 109, pp. 232-255.
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© 2018 Elsevier Ltd Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process.

Voinov, AA, Çöltekin, A, Chen, M & Beydoun, G 2018, 'Virtual geographic environments in socio-environmental modeling: a fancy distraction or a key to communication?', Int. J. Digit. Earth, vol. 11, no. 4, pp. 408-419.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group. Modeling and simulation are recognized as effective tools for management and decision support across various disciplines; however, poor communication of results to the end users is a major obstacle for properly using and understanding model output. Visualizations can play an essential role in making modeling results accessible for management and decision-making. Virtual reality (VR) and virtual geographic environments (VGEs) are popular and potentially very rewarding ways to visualize socio-environmental models. However, there is a fundamental conflict between abstraction and realism: models are goal-driven, and created to simplify reality and to focus on certain crucial aspects of the system; VR, in the meanwhile, by definition, attempts to replicate reality as closely as possible. This elevated realism may add to the complexity curse in modeling, and the message might be diluted by too many (background) details. This is also connected to information overload and cognitive load. Moreover, modeling is always associated with the treatment of uncertainty–something difficult to present in VR. In this paper, we examine the use of VR and, specifically, VGEs in socio-environmental modeling, and discuss how VGEs and simulation modeling can be married in a mutually beneficial way that makes VGEs more effective for users, while enhancing simulation models.

Volpin, F, Chekli, L, Phuntsho, S, Cho, J, Ghaffour, N, Vrouwenvelder, JS & Kyong Shon, H 2018, 'Simultaneous phosphorous and nitrogen recovery from source-separated urine: A novel application for fertiliser drawn forward osmosis', Chemosphere, vol. 203, pp. 482-489.
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© 2018 Elsevier Ltd Re-thinking our approach to dealing with waste is one of the major challenges in achieving a more sustainable society. However, it could also generate numerous opportunities. Specifically, in the context of wastewater, nutrients, energy and water could be mined from it. Because of its exceptionally high nitrogen (N) and phosphorous (P) concentration, human urine is particularly suitable to be processed for fertiliser production. In the present study, forward osmosis (FO) was employed to mine the P and N from human urine. Two Mg2+-fertilisers, i.e. MgSO4 and Mg(NO3)2 were selected as draw solution (DS) to dewater synthetic non-hydrolysed urine. In this process, the Mg2+ reverse salt flux (RSF) were used to recover P as struvite. Simultaneously, the urea was recovered in the DS as it is poorly rejected by the FO membrane. The results showed that, after concentrating the urine by 60%, about 40% of the P and 50% of the N were recovered. XRD and SEM – EDX analysis confirmed that P was precipitated as mineral struvite. If successfully tested on real urine, this process could be applied to treat the urine collected in urban areas e.g., high-rise building. After the filtration, the solid struvite could be sold for inland applications whereas the diluted fertiliser used for direct fertigation of green walls, parks or for urban farming. Finally, reduction in the load of N, P to the downstream wastewater treatment plant would also ensure a more sustainable urban water cycle.

Volpin, F, Fons, E, Chekli, L, Kim, JE, Jang, A & Shon, HK 2018, 'Hybrid forward osmosis-reverse osmosis for wastewater reuse and seawater desalination: Understanding the optimal feed solution to minimise fouling', Process Safety and Environmental Protection, vol. 117, pp. 523-532.
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© 2018 Institution of Chemical Engineers To enhance the seawater desalination energy efficiency forward osmosis – reverse osmosis (FO-RO) hybrid system has recently been developed. In this process, the FO “pre-treatment” step is designed to use seawater (SW) as draw solution to filter the wastewater (WW) while reducing the seawater osmotic pressure. Thereby reducing the operating pressure of the RO to desalinate the diluted SW. However, membrane fouling is a major issue that needs to be addressed. Proper selection of suitable WWs is necessary before proceeding with large-scale FO-RO desalination plants. In this study, long-term experiments were carried out, using state-of-the-art FO membrane, using real WW and SW solutions. A combination of water flux modelling and membrane characterisation were used to assess the degree of membrane fouling and the impact on the process performance. Initial water flux as high as 22.5 Lm−2 h−1 was observed when using secondary effluent. It was also found that secondary effluent causes negligible flux decline. On the other hand, biologically treated wastewater and primary effluent caused mild and severe flux decline respectively (25% and 50% of flux decline after 80 hours, compared to no-fouling conditions). Ammonia leakage to the diluted seawater was also measured, concluding that, if biologically treated wastewater is used as feed, the final NH4+ concentration in the draw is likely to be negligible.

Volpin, F, Gonzales, RR, Lim, S, Pathak, N, Phuntsho, S & Shon, HK 2018, 'GreenPRO: A novel fertiliser-driven osmotic power generation process for fertigation', Desalination, vol. 447, pp. 158-166.
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© 2018 This study introduces and describes GreenPRO, a novel concept involving fertiliser-driven osmotic energy generation via pressure retarded osmosis (PRO). The potential of GreenPRO was proposed for three objectives: (a) power generation, (b) water pressurisation for fertiliser-based irrigation, and (c) water treatment, as a holistic water-energy-food nexus process. Three pure agricultural fertilisers and two commercial blended fertiliser solutions were used as the draw solution and irrigation water as feed to test this concept for power generation. Theoretical thermodynamic simulation of the maximum extractable Gibbs energy, was first performed. After which, a series of bench-scale experiments were conducted to obtain realistic extractable energy data. The results showed that concentrated fertilisers potentially have 11 times higher energy than seawater. Even after accounting for the irreversibility losses due to constant pressure operation, the investigated pure fertilisers were found to have between 2.5 and 4.6 Wh/kg of energy. The outcomes from the flux and power density modelling were then validated with real experimental data. This study has successfully demonstrated that concentrated fertilisers can release a substantial amount of chemical potential energy when diluted for fertigation. This energy could be harnessed by transforming it into electric energy or pressure energy via PRO.

Vu, MT, Ansari, AJ, Hai, FI & Nghiem, LD 2018, 'Performance of a seawater-driven forward osmosis process for pre-concentrating digested sludge centrate: organic enrichment and membrane fouling', Environmental Science: Water Research & Technology, vol. 4, no. 7, pp. 1047-1056.
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This study demonstrated the potential of seawater-driven forward osmosis for enriching organic matter in digested sludge centrate.

Wagner, M, Hectors, S, Bane, O, Gordic, S, Kennedy, P, Besa, C, Schiano, TD, Thung, S, Fischman, A & Taouli, B 2018, 'Noninvasive prediction of portal pressure with MR elastography and DCE‐MRI of the liver and spleen: Preliminary results', Journal of Magnetic Resonance Imaging, vol. 48, no. 4, pp. 1091-1103.
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BackgroundPortal hypertension (PH), defined by hepatic venous pressure gradient (HVPG) ≥5 mmHg and clinically significant PH, defined by HVPG ≥10 mmHg, are complications of chronic liver disease.PurposeTo assess the diagnostic performance of MR elastography (MRE) and dynamic contrast‐enhanced MRI (DCE‐MRI) of the liver and spleen for the prediction of PH and clinically significant PH, in comparison with a qualitative PH imaging scoring system.Study TypeIRB‐approved prospective study.PopulationIn all, 34 patients with chronic liver disease who underwent HVPG measurement.Field Strength/Sequence1.5/3T examination including 2D‐GRE MRE (n = 33) and DCE‐MRI of the liver/spleen (n = 28).AssessmentLiver and spleen stiffness were calculated from elastogram maps. DCE‐MRI was analyzed using model‐free parameters and pharmacokinetic modeling. Two observers calculated qualitative PH imaging scores based on routine images.Statistical TestsImaging parameters were correlated with HVPG. Receiver operating characteristic (ROC) analysis was performed for prediction of PH and clinically significant PH.ResultsThere were significant correlations between DCE‐MRI parameters (liver time‐to‐peak, r = 0.517 / P = 0.006, liver distribution volume, r = 0.494 / P = 0.009, liver upslope, r = –0.567 / P

Wakefield, J, Frawley, JK, Tyler, J & Dyson, LE 2018, 'The impact of an iPad-supported annotation and sharing technology on university students' learning', Computers & Education, vol. 122, pp. 243-259.
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Waldron, KJ 2018, 'Bernard Roth: The early days of the design division at Stanford, and the beginnings of research in robotics', Mechanism and Machine Theory, vol. 125, pp. 45-51.
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© 2017 This paper comprises a review of Bernard Roth's technical contributions and contributions to his professional community. Particular attention is paid to his role in the establishment of the unique design program of the Department of Mechanical Engineering at Stanford University. Another theme is the creation of one of the very first research programs in digitally controlled robotics in the Stanford Artificial Intelligence Laboratory. No review of Roth's career would be complete without touching on the numerous fundamental contributions to research in linkages and robotics. At the same time it is not possible in a work on this type to examine every one of his publications and other contributions. We have endeavored to select the most important, but that is, of course, a personal judgment.

Walker, RTR & Indraratna, B 2018, 'Moving Loads on a Viscoelastic Foundation with Special Reference to Railway Transition Zones', International Journal of Geomechanics, vol. 18, no. 11, pp. 04018145-04018145.
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Walsh, P, Saleh, A & Far, H 2018, 'Evaluation of structural systems in slender high-rise buildings', Australian Journal of Structural Engineering, vol. 19, no. 2, pp. 105-117.
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With the rapid population growth and scarcity of developable space, especially in large cities, there is a need for increased density in both commercial and residential housing, and hence a strong demand to maximise floor space by constructing not only tall, but also slender buildings. This study considers different structural systems available for constructing slender high-rise buildings and evaluates their feasibility in terms of the lateral deformation being one of the key governing design criteria for very tall buildings. To examine the performance of different structural systems in buildings of varying height and floorplan, this study applies finite element analyses in a parametric study to compare nine different building configurations under static loading with heights varying from 80m to 460m. The study shows that buildings with square footprints can achieve greater heights over rectangular footprints with the same area and that multiple towers when connected structurally at one or more levels can achieve even greater heights.

Wan, Y, Chen, L, Xu, G, Zhao, Z, Tang, J & Wu, J 2018, 'SCSMiner: mining social coding sites for software developer recommendation with relevance propagation', World Wide Web, vol. 21, no. 6, pp. 1523-1543.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. With the advent of social coding sites, software development has entered a new era of collaborative work. Social coding sites (e.g., GitHub) can integrate social networking and distributed version control in a unified platform to facilitate collaborative developments over the world. One unique characteristic of such sites is that the past development experiences of developers provided on the sites convey the implicit metrics of developer’s programming capability and expertise, which can be applied in many areas, such as software developer recruitment for IT corporations. Motivated by this intuition, we aim to develop a framework to effectively locate the developers with right coding skills. To achieve this goal, we devise a generativ e probabilistic expert ranking model upon which a consistency among projects is incorporated as graph regularization to enhance the expert ranking and a perspective of relevance propagation illustration is introduced. For evaluation, StackOverflow is leveraged to complement the ground truth of expert. Finally, a prototype system, SCSMiner, which provides expert search service based on a real-world dataset crawled from GitHub is implemented and demonstrated.

Wan, Y, Xu, G, Chen, L, Zhao, Z & Wu, J 2018, 'Exploiting cross-source knowledge for warming up community question answering services', Neurocomputing, vol. 320, pp. 25-34.
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© 2018 Elsevier B.V. Community Question Answering (CQA) services such as Yahoo! Answers, Quora and StackOverflow are collaborative platforms where users can share and exchange their knowledge explicitly by asking and answering questions. One essential task in CQA is learning topical expertise of users, which may benefit many applications such as question routing and best answers identification. One limitation of existing related works is that they only consider the warm-start users who have posted many questions or answers, while ignoring cold-start users who have few posts. In this paper, we aim to exploit knowledge from cross sources such as GitHub and StackOverflow to build up the richer views of expertise for better CQA. Inspired by the idea of Bayesian co-training, we propose a topical expertise model from the perspective of multi-view learning. Specifically, we incorporate the consistency existing among multiple views into a unified probabilistic graphic model. Comprehensive experiments on two real-world datasets demonstrate the performance of our proposed model with the comparison of some state-of-the-art ones.

Wang, C, Chi, C-H, She, Z, Cao, L & Stantic, B 2018, 'Coupled Clustering Ensemble by Exploring Data Interdependence', ACM Transactions on Knowledge Discovery from Data, vol. 12, no. 6, pp. 1-38.
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Clustering ensembles combine multiple partitions of data into a single clustering solution. It is an effective technique for improving the quality of clustering results. Current clustering ensemble algorithms are usually built on the pairwise agreements between clusterings that focus on the similarity via consensus functions, between data objects that induce similarity measures from partitions and re-cluster objects, and between clusters that collapse groups of clusters into meta-clusters. In most of those models, there is a strong assumption on IIDness (i.e., independent and identical distribution), which states that base clusterings perform independently of one another and all objects are also independent. In the real world, however, objects are generally likely related to each other through features that are either explicit or even implicit. There is also latent but definite relationship among intermediate base clusterings because they are derived from the same set of data. All these demand a further investigation of clustering ensembles that explores the interdependence characteristics of data. To solve this problem, a new coupled clustering ensemble (CCE) framework that works on the interdependence nature of objects and intermediate base clusterings is proposed in this article. The main idea is to model the coupling relationship between objects by aggregating the similarity of base clusterings, and the interactive relationship among objects by addressing their neighborhood domains. Once these interdependence relationships are discovered, they will act as critical supplements to clustering ensembles. We verified our proposed framework by using three types of consensus function: clustering-based, object-based, and cluster-based. Substantial experiments on multiple synthetic and real-life benchmark datasets indicate thatCCEcan effectively capture the implicit interdependence relationships a...

Wang, C, Gao, B, Zhao, P, Yue, Q, Shon, HK & Yang, S 2018, 'The forward osmosis application: using the secondary effluent as makeup water for cooling water dilution', Desalination and Water Treatment, vol. 105, pp. 1-10.
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© 2018 Desalination Publications. All rights reserved. This study evaluated the feasibility of using the secondary effluent as makeup water for cooling water. The secondary effluent and the simulated cooling water were used as feed solution (FS) and draw solution (DS) in FO process. Ammonium bicarbonate was added into the simulated cooling water to promote the osmotic pressure. The tests were studied under different membrane orientations, temperatures and flow rates using both TFC-FO and CTA-FO membranes, and determined in terms of water flux, the permeate recovery and membrane fouling. The considerable permeate recovery (18.9% at 20 h) and reversible membrane fouling indicated that the feasibility of using FO for cooling water reuse. CTA- and TFC-PRO modes had higher initial water flux, but more significant flux decline compared to CTA- and TFC-FO modes. The optimal conditions were determined to be 25°C and 17.0 cm/s in which the water flux was highest. The results showed that water flux did not increase with the temperature when it was above than 30°C. The same situation occurred at the cross flow velocity above than 17 cm/s. The fouling of TFC membrane was serious after running 20 h, but it could be cleaned well by 1 h simple surface flushing and the water flux could restore nearly 93.8%.

Wang, C-T, Huang, Y-S, Sangeetha, T, Chen, Y-M, Chong, W-T, Ong, H-C, Zhao, F & Yan, W-M 2018, 'Novel bufferless photosynthetic microbial fuel cell (PMFCs) for enhanced electrochemical performance', Bioresource Technology, vol. 255, pp. 83-87.
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Wang, D, Deng, S & Xu, G 2018, 'Sequence-based context-aware music recommendation', Information Retrieval Journal, vol. 21, no. 2-3, pp. 230-252.
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© 2017, Springer Science+Business Media, LLC. Contextual factors greatly affect users’ preferences for music, so they can benefit music recommendation and music retrieval. However, how to acquire and utilize the contextual information is still facing challenges. This paper proposes a novel approach for context-aware music recommendation, which infers users’ preferences for music, and then recommends music pieces that fit their real-time requirements. Specifically, the proposed approach first learns the low dimensional representations of music pieces from users’ music listening sequences using neural network models. Based on the learned representations, it then infers and models users’ general and contextual preferences for music from users’ historical listening records. Finally, music pieces in accordance with user’s preferences are recommended to the target user. Extensive experiments are conducted on real world datasets to compare the proposed method with other state-of-the-art recommendation methods. The results demonstrate that the proposed method significantly outperforms those baselines, especially on sparse data.

Wang, D, Deng, S, Zhang, X & Xu, G 2018, 'Learning to embed music and metadata for context-aware music recommendation', World Wide Web, vol. 21, no. 5, pp. 1399-1423.
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© 2017, Springer Science+Business Media, LLC, part of Springer Nature. Contextual factors greatly influence users’ musical preferences, so they are beneficial remarkably to music recommendation and retrieval tasks. However, it still needs to be studied how to obtain and utilize the contextual information. In this paper, we propose a context-aware music recommendation approach, which can recommend music pieces appropriate for users’ contextual preferences for music. In analogy to matrix factorization methods for collaborative filtering, the proposed approach does not require music pieces to be represented by features ahead, but it can learn the representations from users’ historical listening records. Specifically, the proposed approach first learns music pieces’ embeddings (feature vectors in low-dimension continuous space) from music listening records and corresponding metadata. Then it infers and models users’ global and contextual preferences for music from their listening records with the learned embeddings. Finally, it recommends appropriate music pieces according to the target user’s preferences to satisfy her/his real-time requirements. Experimental evaluations on a real-world dataset show that the proposed approach outperforms baseline methods in terms of precision, recall, F1 score, and hitrate. Especially, our approach has better performance on sparse datasets.

Wang, D, Duan, Y, Yang, Q, Liu, Y, Ni, B-J, Wang, Q, Zeng, G, Li, X & Yuan, Z 2018, 'Free ammonia enhances dark fermentative hydrogen production from waste activated sludge', Water Research, vol. 133, pp. 272-281.
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© 2018 Elsevier Ltd Ammonium and/or free ammonia (the unionized form of ammonium) are generally thought to inhibit the activities of microbes involved in anaerobic digestion of waste activated sludge. It was found in this work, however, that the presence of ammonium (NH4+-N) largely enhanced dark fermentative hydrogen production from alkaline pretreated-sludge. With the increase of initial NH4+-N level from 36 to 266 mg/L, the maximal hydrogen production from alkaline (pH 9.5) pretreated-sludge increased from 7.3 to 15.6 mL per gram volatile suspended solids (VSS) under the standard condition. Further increase of NH4+-N to 308 mg/L caused a slight decrease of hydrogen yield (15.0 mL/g VSS). Experimental results demonstrated that free ammonia instead of NH4+-N was the true contributor to the enhancement of hydrogen production. It was found that the presence of free ammonia facilitated the releases of both extracellular and intracellular constituents, which thereby provided more substrates for subsequent hydrogen production. The free ammonia at the tested levels (i.e., 0–444 mg/L) did not affect acetogenesis significantly. Although free ammonia inhibited all other bio-processes, its inhibition to the hydrogen consumption processes (i.e., homoacetogenesis, methanogenesis, and sulfate-reducing process) was much severer than that to the hydrolysis and acidogenesis processes. Further investigations with enzyme analyses showed that free ammonia posed slight impacts on protease, butyrate kinase, acetate kinase, CoA-transferase, and [FeFe] hydrogenase activities but largely suppressed the activities of coenzyme F420, carbon monoxide dehydrogenase, and adenylyl sulfate reductase, which were consistent with the chemical analyses performed above.

Wang, D, He, C, Wu, C & Zhang, Y 2018, 'Mechanical behaviors of tension and relaxation of tongue and soft palate: Experimental and analytical modeling', Journal of Theoretical Biology, vol. 459, pp. 142-153.
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© 2018 This study is to characterize mechanical properties of uniaxial tension and stress relaxation responses of muscle tissues of tongue and soft palate. Uniaxial tension test and stress relaxation test on 39 fresh tissue samples from four five-month-old boars (65 ± 15 kg) are conducted. Firstly, the rationality of the samples’ dimension design and experimenal data measurement is validated by one-way ANOVA F-type test. Mechanical properties, including stress-strain relationship and stress relaxation characteristic, are then investigated in details to show the nonlinear behaviors of the tissue samples clearly. Finally, a constitutive model of representing the mechanical properties is formulated within the nonlinear integral representation framework proposed by Pinkin and Rogers, and corresponding material parameters are fitted to the experimental data based on the Levenberg-Marquardt minimization algorithm. The results of the fitting comparison prove that the formulated constitutive model can capture the observed nonlinear behaviors of the muscle tissue samples in both the axial tension and stress relaxation experiments.

Wang, D, Liu, B, Liu, X, Xu, Q, Yang, Q, Liu, Y, Zeng, G, Li, X & Ni, B-J 2018, 'How does free ammonia-based sludge pretreatment improve methane production from anaerobic digestion of waste activated sludge', Chemosphere, vol. 206, pp. 491-501.
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© 2018 Elsevier Ltd Previous studies reported that free ammonia (FA) pretreatment could improve methane production from anaerobic digestion of waste activated sludge (WAS) effectively. However, details of how FA pretreatment improves methane production are poorly understood. This study therefore aims to reveal the underlying mechanisms of FA pretreatment affecting anaerobic digestion of WAS through a series of batch tests using either real sludge or synthetic media as the digestion substrates at different pH values. At pH 8.5 level, with an increase of FA level from 18.5 to 92.5 mg/L (i.e., NH+ 4-N: 100–500 mg/L; pH 8.5) the maximum methane yield varied between 194.0 ± 3.9 and 196.9 ± 7.7 mL/g of VSS (25 °C, 1 atm). At pH 9.5 or 10 level, however, with an increase of initial FA level from 103.2 to 516.2 mg/L, the maximal methane yield increased linearly. The mechanism studies revealed that FA pretreatment at high levels not only accelerated the disintegration of WAS but also enhanced the biodegradability of WAS. Although pH in the digesters was adjusted to 7.0 ± 0.1, the high levels of NH+ 4-N added or released led to substantial levels of residual FA ranging from 4.4 to 11.6 mg/L. It was found that this level of FA inhibited homoacetogenesis and methanogenesis significantly, though hydrolysis, acidogenesis, and acetogenesis processes were unaffected largely. Further analyses showed that the inhibition constant of FA to substrate degradation was in the sequence of dextran > glucose > hydrogen > acetate, indicating the methanogenesis process was more sensitive to FA.

Wang, D, Liu, X, Zeng, G, Zhao, J, Liu, Y, Wang, Q, Chen, F, Li, X & Yang, Q 2018, 'Understanding the impact of cationic polyacrylamide on anaerobic digestion of waste activated sludge', Water Research, vol. 130, pp. 281-290.
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© 2017 Elsevier Ltd Previous investigations showed that cationic polyacrylamide (cPAM), a flocculant widely used in wastewater pretreatment and waste activated sludge dewatering, deteriorated methane production during anaerobic digestion of sludge. However, details of how cPAM affects methane production are poorly understood, hindering deep control of sludge anaerobic digestion systems. In this study, the mechanisms of cPAM affecting sludge anaerobic digestion were investigated in batch and long-term tests using either real sludge or synthetic wastewaters as the digestion substrates. Experimental results showed that the presence of cPAM not only slowed the process of anaerobic digestion but also decreased methane yield. The maximal methane yield decreased from 139.1 to 86.7 mL/g of volatile suspended solids (i.e., 1861.5 to 1187.0 mL/L) with the cPAM level increasing from 0 to 12 g/kg of total suspended solids (i.e., 0–236.7 mg/L), whereas the corresponding digestion time increased from 22 to 26 d. Mechanism explorations revealed that the addition of cPAM significantly restrained the sludge solubilization, hydrolysis, acidogenesis, and methanogenesis processes. It was found that ∼46% of cAPM was degraded in the anaerobic digestion, and the degradation products significantly affected methane production. Although the theoretically biochemical methane potential of cPAM is higher than that of protein and carbohydrate, only 6.7% of the degraded cPAM was transformed to the final product, methane. Acrylamide, acrylic acid, and polyacrylic acid were found to be the main degradation metabolites, and their amount accounted for ∼50% of the degraded cPAM. Further investigations showed that polyacrylic acid inhibited all the solubilization, hydrolysis, acidogenesis, and methanogenesis processes while acrylamide and acrylic acid inhibited the methanogenesis significantly.

Wang, D, Shuai, K, Xu, Q, Liu, X, Li, Y, Liu, Y, Wang, Q, Li, X, Zeng, G & Yang, Q 2018, 'Enhanced short-chain fatty acids production from waste activated sludge by combining calcium peroxide with free ammonia pretreatment', Bioresource Technology, vol. 262, pp. 114-123.
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© 2018 Elsevier Ltd This study reported a new low-cost and high-efficient combined method of CaO2 + free ammonia (FA) pretreatment for sludge anaerobic fermentation. Experimental results showed that the optimal short-chain fatty acids (SCFA) yield of 338.6 mg COD/g VSS was achieved when waste activated sludge (WAS) was pretreated with 0.05 g/g VSS of CaO2 + 180 mg/L of FA for 3 d, which was 2.5-fold of that from CaO2 pretreatment and 1.5-fold of that from FA pretreatment. The mechanism investigations exhibited that the CaO2 + FA could provided more biodegradable substrates, this combination accelerated the disintegration of sludge cells, which thereby providing more organics for subsequent SCFA production. It was also found that the combination of CaO2 and FA inhibited the specific activities of hydrolytic microbes, SCFA producers, and methanogens to some extents, but its inhibition to methanogens was much severer than that to the other two types of microbes.

Wang, H, Huang, S, Yang, G & Dissanayake, G 2018, 'Comparison of two different objective functions in 2D point feature SLAM', Automatica, vol. 97, pp. 172-181.
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© 2018 Elsevier Ltd This paper compares two different objective functions in 2D point feature Simultaneous Localization and Mapping (SLAM). It is shown that the objective function can have a significant impact on the convergence of the iterative optimization techniques used in SLAM. When Frobenius norm is adopted for the error term of the orientation part of odometry, the SLAM problem has much better convergence properties, as compared with that using the angle difference as the error term. For one-step case, we have proved that there is one and only one minimum to the SLAM problem, and strong duality always holds. For two-step case, strong duality always holds except when three very special conditions hold simultaneously (which happens with probability zero), thus the global optimal solution to primal SLAM problem can be obtained by solving the corresponding Lagrangian dual problem in most cases. Further, for arbitrary m-step cases, we also show using examples that much better convergence results can be obtained. Simulation examples are given to demonstrate the different convergence properties using two different objective functions.

Wang, H, Wu, J, Zhu, X, Chen, Y & Zhang, C 2018, 'Time-Variant Graph Classification', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, no. 8, pp. 1-14.
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IEEE Graphs are commonly used to represent objects, such as images and text, for pattern classification. In a dynamic world, an object may continuously evolve over time, and so does the graph extracted from the underlying object. These changes in graph structure with respect to the temporal order present a new representation of the graph, in which an object corresponds to a set of time-variant graphs. In this paper, we formulate a novel time-variant graph classification task and propose a new graph feature, called a graph-shapelet pattern, for learning and classifying time-variant graphs. Graph-shapelet patterns are compact and discriminative graph transformation subsequences. A graph-shapelet pattern can be regarded as a graphical extension of a shapelet--a class of discriminative features designed for vector-based temporal data classification. To discover graph-shapelet patterns, we propose to convert a time-variant graph sequence into time-series data and use the discovered shapelets to find graph transformation subsequences as graph-shapelet patterns. By converting each graph-shapelet pattern into a unique tokenized graph transformation sequence, we can measure the similarity between two graph-shapelet patterns and therefore classify time-variant graphs. Experiments on both synthetic and real-world data demonstrate the superior performance of the proposed algorithms.

Wang, J, Du, P, Lu, H, Yang, W & Niu, T 2018, 'An improved grey model optimized by multi-objective ant lion optimization algorithm for annual electricity consumption forecasting', Applied Soft Computing, vol. 72, pp. 321-337.
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© 2018 Elsevier B.V. Accurate and stable annual electricity consumption forecasting play vital role in modern social and economic development through providing effective planning and guaranteeing a reliable supply of sustainable electricity. However, establishing a robust method to improve prediction accuracy and stability simultaneously of electricity consumption forecasting has been proven to be a highly challenging task. Most previous researches only pay more attention to enhance prediction accuracy, which usually ignore the significant of forecasting stability, despite its importance to the effectiveness of forecasting models. Considering the characteristics of annual power consumption data as well as one criterion i.e. accuracy or stability is insufficient, in this study a novel hybrid forecasting model based on an improved grey forecasting mode optimized by multi-objective ant lion optimization algorithm is successfully developed, which can not only be utilized to dynamic choose the best input training sets, but also obtain satisfactory forecasting results with high accuracy and strong ability. Case studies of annual power consumption datasets from several regions in China are utilized as illustrative examples to estimate the effectiveness and efficiency of the proposed hybrid forecasting model. Finally, experimental results indicated that the proposed forecasting model is superior to the comparison models.

Wang, J, Li, H & Lu, H 2018, 'Application of a novel early warning system based on fuzzy time series in urban air quality forecasting in China', Applied Soft Computing, vol. 71, pp. 783-799.
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© 2018 Elsevier B.V. With atmospheric environmental pollution becoming increasingly serious, developing an early warning system for air quality forecasting is vital to monitoring and controlling air quality. However, considering the large fluctuations in the concentration of pollutants, most previous studies have focused on enhancing accuracy, while few have addressed the stability and uncertainty analysis, which may lead to insufficient results. Therefore, a novel early warning system based on fuzzy time series was successfully developed that includes three modules: deterministic prediction module, uncertainty analysis module, and assessment module. In this system, a hybrid model combining the fuzzy time series forecasting technique and data reprocessing approaches was constructed to forecast the major air pollutants. Moreover, an uncertainty analysis was generated to further analyze and explore the uncertainties involved in future air quality forecasting. Finally, an assessment module proved the effectiveness of the developed model. The experimental results reveal that the proposed model outperforms the comparison models and baselines, and both the accuracy and the stability of the developed system are remarkable. Therefore, fuzzy logic is a better option in air quality forecasting and the developed system will be a useful tool for analyzing and monitoring air pollution.

Wang, J, Niu, T, Lu, H, Guo, Z, Yang, W & Du, P 2018, 'An analysis-forecast system for uncertainty modeling of wind speed: A case study of large-scale wind farms', Applied Energy, vol. 211, pp. 492-512.
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© 2017 Elsevier Ltd The uncertainty analysis and modeling of wind speed, which has an essential influence on wind power systems, is consistently considered a challenging task. However, most investigations thus far were focused mainly on point forecasts, which in reality cannot facilitate quantitative characterization of the endogenous uncertainty involved. An analysis-forecast system that includes an analysis module and a forecast module and can provide appropriate scenarios for the dispatching and scheduling of a power system is devised in this study; this system superior to those presented in previous studies. In order to qualitatively and quantitatively investigate the uncertainty of wind speed, recurrence analysis techniques are effectively developed for application in the analysis module. Furthermore, in order to quantify the uncertainty accurately, a novel architecture aimed at uncertainty mining is devised for the forecast module, where a non-parametric model optimized by an improved multi-objective water cycle algorithm is considered a predictor for producing intervals for each mode component after feature selection. The results of extensive in-depth experiments show that the devised system is not only superior to the considered benchmark models, but also has good potential practical applications in wind power systems.

Wang, J, Zhao, L, Zhang, A, Huang, Y, Tavakoli, J & Tang, Y 2018, 'Novel Bacterial Cellulose/Gelatin Hydrogels as 3D Scaffolds for Tumor Cell Culture', Polymers, vol. 10, no. 6, pp. 581-581.
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Three-dimensional (3D) cells in vitro culture are becoming increasingly popular in cancer research because some important signals are lost when cells are cultured in a two-dimensional (2D) substrate. In this work, bacterial cellulose (BC)/gelatin hydrogels were successfully synthesized and were investigated as scaffolds for cancer cells in vitro culture to simulate tumor microenvironment. Their properties and ability to support normal growth of cancer cells were evaluated. In particular, the human breast cancer cell line (MDA-MD-231) was seeded into BC/gelatin scaffolds to investigate their potential in 3D cell in vitro culture. MTT proliferation assay, scanning electron microscopy, hematoxylin and eosin staining and immunofluorescence were used to determine cell proliferation, morphology, adhesion, infiltration, and receptor expression. The in vitro MDA-MD-231 cell culture results demonstrated that cells cultured on the BC/gelatin scaffolds had significant adhesion, proliferation, ingrowth and differentiation. More importantly, MDA-MD-231 cells cultured in BC/gelatin scaffolds retained triple-negative receptor expression, demonstrating that BC/gelatin scaffolds could be used as ideal in vitro culture scaffolds for tumor cells.

Wang, L, Bao, X, Chen, H & Cao, L 2018, 'Effective lossless condensed representation and discovery of spatial co-location patterns', Information Sciences, vol. 436-437, pp. 197-213.
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© 2018 Elsevier Inc. A spatial co-location pattern is a set of spatial features frequently co-occuring in nearby geographic spaces. Similar to closed frequent itemset mining, closed co-location pattern (CCP) mining was proposed for losslessly condensing large collections of prevalent co-location patterns. However, the state-of-the-art condensation methods in mining CCP are inspired by closed frequent itemset mining and do not consider the intrinsic characteristics of spatial co-locations, e.g., the participation index and ratio in spatial feature interactions, thus causing serious containment issues in CCP mining. In this paper, we propose a novel lossless condensed representation of prevalent co-location patterns, Super Participation Index-closed (SPI-closed) co-location. An efficient SPI-closed Miner is also proposed to effectively capture the nature of spatial co-location patterns, alongside the development of three additional pruning strategies to make the SPI-closed Miner efficient. This method captures richer feature interactions in spatial co-locations and solves the containment issues in existing CCP methods. A performance evaluation conducted on both synthetic and real-life data sets shows that SPI-closed Miner reduces the number of CCPs by up to 50%, and runs much faster than the baseline CCP mining algorithm described in the literature.

Wang, M, Liu, Y, Su, D, Liao, Y, Shi, L, Xu, J & Valls Miro, J 2018, 'Accurate and Real-Time 3-D Tracking for the Following Robots by Fusing Vision and Ultrasonar Information', IEEE/ASME Transactions on Mechatronics, vol. 23, no. 3, pp. 997-1006.
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© 1996-2012 IEEE. Acquiring the accurate three-dimensional (3-D) position of a target person around a robot provides valuable information that is applicable to a wide range of robotic tasks, especially for promoting the intelligent manufacturing processes of industries. This paper presents a real-time robotic 3-D human tracking system that combines a monocular camera with an ultrasonic sensor by an extended Kalman filter (EKF). The proposed system consists of three submodules: a monocular camera sensor tracking module, an ultrasonic sensor tracking module, and the multisensor fusion algorithm. An improved visual tracking algorithm is presented to provide 2-D partial location estimation. The algorithm is designed to overcome severe occlusions, scale variation, target missing, and achieve robust redetection. The scale accuracy is further enhanced by the estimated 3-D information. An ultrasonic sensor array is employed to provide the range information from the target person to the robot, and time of flight is used for the 2-D partial location estimation. EKF is adopted to sequentially process multiple, heterogeneous measurements arriving in an asynchronous order from the vision sensor, and the ultrasonic sensor separately. In the experiments, the proposed tracking system is tested in both a simulation platform and actual mobile robot for various indoor and outdoor scenes. The experimental results show the persuasive performance of the 3-D tracking system in terms of both the accuracy and robustness.

Wang, N, Li, H-W, Ding, C, Shi, L-Y, Jia, H-Z, Ren, Z-D & Zhao, Z-Y 2018, 'A Double-Voltage-Controlled Effective Thermal Conductivity Model of Graphene for Thermoelectric Cooling', IEEE Transactions on Electron Devices, vol. 65, no. 3, pp. 1185-1191.
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© 1963-2012 IEEE. Graphene provides a new opportunity for thermoelectric study based on its unique heat transfer behavior controllable by a gate voltage. In this paper, an effective thermal conductivity model of graphene for thermoelectric cooling is proposed. The model is based on a double-voltage-control mechanism. According to the law of Fourier heat conduction, an effective thermal conductivity model of the proposed thermoelectric cooling device is derived taking a tunable external voltage into account. Then, a gate voltage is used which can change graphene's thermoelectric characteristics. To verify the correctness and effectiveness of the proposed model, a circuit simulation model using HSPICE is built based on the thermoelectric duality. The simulation results from HSPICE and the calculated results from the mathematic model show good agreements with each other. This paper provides a novel precisely controlling method for thermoelectric cooling.

Wang, Q, Song, K, Hao, X, Wei, J, Pijuan, M, van Loosdrecht, MCM & Zhao, H 2018, 'Evaluating death and activity decay of Anammox bacteria during anaerobic and aerobic starvation', Chemosphere, vol. 201, pp. 25-31.
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© 2018 Elsevier Ltd The decreased activity (i.e. decay) of anaerobic ammonium oxidation (Anammox) bacteria during starvation can be attributed to death (i.e. decrease in the amount of viable bacteria) and activity decay (i.e. decrease in the specific activity of viable bacteria). Although they are crucial for the operation of the Anammox process, they have never been comprehensively investigated. This study for the first time experimentally assessed death and activity decay of the Anammox bacteria during 84 days’ starvation stress based on ammonium removal rate, Live/Dead staining and fluorescence in-situ hybridization. The anaerobic and aerobic decay rates of Anammox bacteria were determined as 0.015 ± 0.001 d−1 and 0.028 ± 0.001 d−1, respectively, indicating Anammox bacteria would lose their activity more quickly in the aerobic starvation than in the anaerobic starvation. The anaerobic and aerobic death rates of Anammox bacteria were measured at 0.011 ± 0.001 d−1 and 0.025 ± 0.001 d−1, respectively, while their anaerobic and aerobic activity decay rates were determined at 0.004 ± 0.001 d−1 and 0.003 ± 0.001 d−1, respectively. Further analysis revealed that death accounted for 73 ± 4% and 89 ± 5% of the decreased activity of Anammox bacteria during anaerobic and aerobic starvations, and activity decay was only responsible for 27 ± 4% and 11 ± 5% of the decreased Anammox activity, respectively, over the same starvation periods. These deeply shed light on the response of Anammox bacteria to the starvation stress, which would facilitate operation and optimization of the Anammox process.

Wang, Q, Sun, J, Song, K, Zhou, X, Wei, W, Wang, D, Xie, G-J, Gong, Y & Zhou, B 2018, 'Combined zero valent iron and hydrogen peroxide conditioning significantly enhances the dewaterability of anaerobic digestate', Journal of Environmental Sciences, vol. 67, pp. 378-386.
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© 2017 The importance of enhancing sludge dewaterability is increasing due to the considerable impact of excess sludge volume on disposal costs and on overall sludge management. This study presents an innovative approach to enhance dewaterability of anaerobic digestate (AD) harvested from a wastewater treatment plant. The combination of zero valent iron (ZVI, 0–4.0 g/g total solids (TS)) and hydrogen peroxide (HP, 0–90 mg/g TS) under pH 3.0 significantly enhanced the AD dewaterability. The largest enhancement of AD dewaterability was achieved at 18 mg HP/g TS and 2.0 g ZVI/g TS, with the capillary suction time reduced by up to 90%. Economic analysis suggested that the proposed HP and ZVI treatment has more economic benefits in comparison with the classical Fenton reaction process. The destruction of extracellular polymeric substances and cells as well as the decrease of particle size were supposed to contribute to the enhanced AD dewaterability by HP + ZVI conditioning.

Wang, Q, Wei, W, Liu, S, Yan, M, Song, K, Mai, J, Sun, J, Ni, B-J & Gong, Y 2018, 'Free Ammonia Pretreatment Improves Degradation of Secondary Sludge During Aerobic Digestion', ACS Sustainable Chemistry & Engineering, vol. 6, no. 1, pp. 1105-1111.
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Aerobic digestion is commonly used to achieve secondary sludge reduction in the small-size wastewater treatment plants. Nevertheless, secondary sludge degradation is usually restricted by the slow hydrolysis rate and low degradable percentage of secondary sludge. Here, we present an innovative approach using pretreatment of free ammonia (FA, i.e. NH3), a renewable chemical from wastewater, to improve the degradation of secondary sludge during aerobic digestion. The secondary sludge was degraded by 36 ± 4% (volatile solids (VS) basis) within 15 days of aerobic digestion while being pretreated at 300 mg NH3-N/L (pH 9.0; total ammonia nitrogen = 800 mg N/L) for 24 h, whereas only 23 ± 3% (VS basis) of the secondary sludge without FA pretreatment was degraded over the same period. Similarly, the production of inorganic nitrogen also increased from 27 ± 2 to 38 ± 2 mg N/g VS after implementing FA pretreatment, corroborating the idea that degradation of secondary sludge was effectively improved by FA pretreatment. Further analysis by model revealed that the improved hydrolysis rate and increased degradable percentage of secondary sludge were responsible for the enhanced sludge degradation in aerobic digestion. It was also found that FA pretreatment would produce an aerobic digestate with a better stability and dewaterability, as indicated by the lower degradable percentage of digestate and the decrease of capillary suction time from 38 ± 1 to 34 ± 1 s, respectively. Economic analysis indicates that the FA pretreatment approach would be economically favorable when the sludge transport and disposal cost is higher than $40/wet tone.

Wang, Q, Ye, X, Wang, S, Sloan, SW & Sheng, D 2018, 'Use of photo-based 3D photogrammetry in analysing the results of laboratory pressure grouting tests', Acta Geotechnica, vol. 13, no. 5, pp. 1129-1140.
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This paper presents a non-destructive, low-cost, photo-based, 3D reconstruction technique for characterizing geo-materials with irregular shapes of a relatively large size. After being validated against two traditional volume measurement methods, namely the vernier caliper method and the fluid displacement method for regular and irregular shapes, respectively, 3D photogrammetry was used to analyse the grout bulbs formed in laboratory pressure grouting tests. The reconstructed 3D mesh model of the sample provides accurate and detailed 3D vertex data, which allowed the volume, densification efficiency and bleeding behaviour of the grout bulbs to be analysed. Comparing the bulb section views at different grouting pressures also offers an intuitive observation of the grout development and propagation process. Moreover, the 3D vertex data and surface area included in the model are of great importance in validating numerical predictions of the pressure grouting process and analysing the interface shear resistance of grouted soil nails or anchors. Compared to existing approaches, the new 3D photogrammetry method possesses several key advantages: (a) it does not require expensive, specialized equipment; (b) samples are not destroyed or modified during testing; (c) it allows to reconstruct objects of various scales and (d) the software is public domain. Therefore, the adoption of this 3D photogrammetry method will facilitate research in the pressure grouting process and can be extended to other problems in geotechnical engineering.

Wang, S, Kodagoda, S, Shi, L & Dai, X 2018, 'Two-Stage Road Terrain Identification Approach for Land Vehicles Using Feature-Based and Markov Random Field Algorithm', IEEE Intelligent Systems, vol. 33, no. 1, pp. 29-39.
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© 2001-2011 IEEE. Road terrain identification is one of the important tasks for driving assistant systems or autonomous land vehicles. It plays a key role in improving driving strategy and enhancing fuel efficiency. In this paper, a two-stage approach using multiple sensors is presented. In the first stage, a feature-based identification approach is performed using an accelerometer, a camera, and downward-looking and forward-looking laser range finders (LRFs). This produces four classification label sequences. In the second stage, a majority vote is implemented for each label sequences to match them into synchronized road patches. Then a Markov Random Field (MRF) model is designed to generate the final optimized identification results to improve the forward-looking LRF. This approach enables the vehicle to observe the upcoming road terrain before moving onto it by fusing all the classification results using an MRF algorithm. The experiments show this approach improved the terrain identification accuracy and robustness significantly for some familiar road terrains.

Wang, S, Wu, W, Peng, C, He, X & Cui, D 2018, 'Numerical integration and FE implementation of a hypoplastic constitutive model', Acta Geotechnica, vol. 13, no. 6, pp. 1265-1281.
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Wang, S, Wu, W, Yin, Z, Peng, C & He, X 2018, 'Modelling the time‐dependent behaviour of granular material with hypoplasticity', International Journal for Numerical and Analytical Methods in Geomechanics, vol. 42, no. 12, pp. 1331-1345.
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SummaryThis paper presents a constitutive model for time‐dependent behaviour of granular material. The model consists of 2 parts representing the inviscid and viscous behaviour of granular materials. The inviscid part is a rate‐independent hypoplastic constitutive model. The viscous part is represented by a rheological model, which contains a high‐order term denoting the strain acceleration. The proposed model is validated by simulating some element tests on granular soils. Our model is able to model not only the non‐isotach behaviour but also the 3 creep stages, namely, primary, secondary, and tertiary creep, in a unified way.

Wang, T, Lu, J & Zhang, G 2018, 'Two-Stage Fuzzy Multiple Kernel Learning Based on Hilbert–Schmidt Independence Criterion', IEEE Transactions on Fuzzy Systems, vol. 26, no. 6, pp. 3703-3714.
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© 1993-2012 IEEE. Multiple kernel learning (MKL) is a principled approach to kernel combination and selection for a variety of learning tasks, such as classification, clustering, and dimensionality reduction. In this paper, we develop a novel fuzzy multiple kernel learning model based on the Hilbert-Schmidt independence criterion (HSIC) for classification, which we call HSIC-FMKL. In this model, we first propose an HSIC Lasso-based MKL formulation, which not only has a clear statistical interpretation that minimum redundant kernels with maximum dependence on output labels are found and combined, but also enables the global optimal solution to be computed efficiently by solving a Lasso optimization problem. Since the traditional support vector machine (SVM) is sensitive to outliers or noises in the dataset, fuzzy SVM (FSVM) is used to select the prediction hypothesis once the optimal kernel has been obtained. The main advantage of FSVM is that we can associate a fuzzy membership with each data point such that these data points can have different effects on the training of the learning machine. We propose a new fuzzy membership function using a heuristic strategy based on the HSIC. The proposed HSIC-FMKL is a two-stage kernel learning approach and the HSIC is applied in both stages. We perform extensive experiments on real-world datasets from the UCI benchmark repository and the application domain of computational biology which validate the superiority of the proposed model in terms of prediction accuracy.

Wang, TQ & Huang, X 2018, 'Fractional Reverse Polarity Optical OFDM for High Speed Dimmable Visible Light Communications', IEEE Transactions on Communications, vol. 66, no. 4, pp. 1565-1578.
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© 1972-2012 IEEE. In this paper, fractional reverse polarity optical orthogonal frequency division multiplexing (FRPO-OFDM) is studied to enable dimming compatible visible light communications. The scheme combines a layered asymmetrically clipped optical OFDM (ACO-OFDM) sequence with an information-carrying brightness control sequence (BCS) in the form of M -ary pulse position modulation. We derive the expressions of the FRPO-OFDM signal and its achievable brightness level, and develop an effective detector which can recover information from both sequences based on maximum likelihood detection. We show that when the detector is to be implemented, the use of multi-layer ACO-OFDM imposes strong periodicity on the BCS, which leads to a trade-off between spectral efficiency and brightness resolution for dimming control. It is shown that high spectral efficiency can be achieved with practical dimming requirements. Simulation results show that the extra information carried by the BCS can be decoded with extremely low bit error rate and thus has negligible impacts on the demodulation of the ACO-OFDM signal, when the system nonlinearity is not dominating.

Wang, TQ, Li, H & Huang, X 2018, 'Interference Cancellation for Layered Asymmetrically Clipped Optical OFDM With Application to Optical Receiver Design', Journal of Lightwave Technology, vol. 36, no. 11, pp. 2100-2113.
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© 1983-2012 IEEE. In this paper, we study a novel two-stage receiver to demodulate layered asymmetrically clipped optical orthogonal frequency division multiplexing for intensity modulation direct detection based visible light communications. Designed for avoiding the error propagation of the conventional receiver, the first stage of the receiver is a soft interference cancellation (SIC) module which evaluates the minimum mean square error (MMSE) estimates of the signals in different layers. For this stage, we derive the exact formula of the MMSE estimator, and compare the achieved mean square error and bit error rate (BER) with those of the existing simplified SIC receiver. We show that the estimation error in a layer has negligible impact on the design of estimators in the subsequent layers. Using the outputs of the SIC module, the second stage performs noise clipping to suppress the additive noise. For this stage, we present two schemes, the SIC-based iterative noise clipping (SIC-INC) and the SIC-based direct noise clipping (SIC-DNC). The simulation results show that SIC-INC can achieve BERs similar to those of the SIC-based diversity combining receiver with optimum combining coefficients. It is also shown that SIC-DNC outperforms the existing advanced receivers by up to 0.8 dB at the BER of 10{-4}.

Wang, W, Hoang, DT, Niyato, D, Wang, P & Kim, DI 2018, 'Stackelberg Game for Distributed Time Scheduling in RF-Powered Backscatter Cognitive Radio Networks', IEEE Transactions on Wireless Communications, vol. 17, no. 8, pp. 5606-5622.
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© 2002-2012 IEEE. In this paper, we study the transmission strategy adaptation problem in an RF-powered cognitive radio network, in which hybrid secondary users are able to switch between the harvest-then-transmit mode and the ambient backscatter mode for their communication with the secondary gateway. In the network, a monetary incentive is introduced for managing the interference caused by the secondary transmission with imperfect channel sensing. The sensing-pricing-transmitting process of the secondary gateway and the transmitters is modeled as a single-leader-multi-follower Stackelberg game. Furthermore, the follower sub-game among the secondary transmitters is modeled as a generalized Nash equilibrium problem with shared constraints. Based on our theoretical discoveries regarding the properties of equilibria in the follower sub-game and the Stackelberg game, we propose a distributed, iterative strategy searching scheme that guarantees the convergence to the Stackelberg equilibrium. The numerical simulations show that the proposed hybrid transmission scheme always outperforms the schemes with fixed transmission modes. Furthermore, the simulations reveal that the adopted hybrid scheme is able to achieve a higher throughput than the sum of the throughput obtained from the schemes with fixed transmission modes.

Wang, W, Laengle, S, Merigó, JM, Yu, D, Herrera-Viedma, E, Cobo, MJ & Bouchon-Meunier, B 2018, 'A Bibliometric Analysis of the First Twenty-Five Years of the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems', International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 26, no. 02, pp. 169-193.
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Since the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems published its first issue in 1993, it has made important contributions to the research field of computer science. In this study, based on the dataset of the publications published in this journal between 1993 and 2016 retrieved from Web of Science, a general overview of this journal is performed using bibliometric methods and visualized networks. First, the productive and influential publications, authors, institutions, countries/territories, and supraregions are analysed based on the total number of citations, publications, and different citation thresholds. Second, network visualization analysis is applied to illustrate the links and connections between terms by using the VOSviewer software. Moreover, the most cited journals and common author keywords of three continents, including North America, Europe, and Asia, are also presented. This paper will hopefully help researchers understand the research patterns of this journal.

Wang, W, Wu, C & Li, J 2018, 'Numerical Simulation of Hybrid FRP-Concrete-Steel Double-Skin Tubular Columns under Close-Range Blast Loading', Journal of Composites for Construction, vol. 22, no. 5, pp. 04018036-04018036.
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© 2018 American Society of Civil Engineers. Hybrid fiber-reinforced polymer (FRP)-concrete-steel double-skin tubular columns (DSTCs) are a new form of composite columns that consist of an outer FRP tube and an inner steel tube, with the space between them filled with concrete. Although many studies have been conducted on the hybrid DSTCs, no studies have been conducted on their behavior under blast loading. This study presents the results of a numerical study on the behavior of hybrid DSTCs under close-in blast loading. Numerical models of hybrid DSTCs are developed using finite-element code LS-DYNA, and the reliability of the developed models are validated with available testing results. With the validated models, numerical simulations are carried out to investigate the structural responses of hybrid DSTCs under blast loading. The simulation results indicate that the hybrid DSTCs behave in a ductile manner under blast loading. The outer FRP tube can effectively provide confinement to the infilled concrete, and the inner steel tube plays a key role in resisting the blast loading. Detailed parametric analyses are conducted to investigate the influences of different parameters on the blast behavior of hybrid DSTCs. The blast resistance capacities of the hybrid DSTCs, concrete-filled steel tubes (CFSTs), and concrete-filled double-skin steel tubes (CFDSTs) are compared and discussed based on the simulation results.

Wang, W, Wu, C, Liu, Z & Si, H 2018, 'Compressive behavior of ultra-high performance fiber-reinforced concrete (UHPFRC) confined with FRP', Composite Structures, vol. 204, pp. 419-437.
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© 2018 Elsevier Ltd This study presents the results of an experimental program on the compressive behavior of fiber reinforced polymer (FRP) confined ultra-high performance fiber-reinforced concrete (UHPFRC). A total of 38 specimens were prepared and tested under axial compression. In addition to FRP confined UHPFRC, FRP confined ultra-high performance concrete without fiber addition (UHPC), high strength concrete (HSC), and normal strength concrete (NSC) were also tested to investigate their comparative performances. The test results indicate that the FRP confined UHPFRC can exhibit ductile behavior if sufficient FRP confinement is provided. However, due to their ultra-high strength as well as the unique microstructure, FRP confined UHPFRC is likely to exhibit more brittle behavior than FRP confined NSC and HSC. Compared to FRP confined NSC and HSC, the confinement efficiency is less for FRP confined UHPFRC. Sudden stress reduction or stress fluctuations are observed shortly after the initial peak stress (axial stress at the first peak point) for FRP confined UHPFRC. Based on the confinement level, the stress-strain behavior of FRP confined UHPFRC may experience a second ascending branch or a continuous descending branch after the sudden stress reduction or stress fluctuations. The influences of FRP layers, FRP types, and fiber addition on the compressive behavior of FRP confined UHPFRC are observed to be significant. Moreover, existing stress-strain models available for FRP confined UHPFRC are evaluated by using a database collected in this study.

Wang, X, Cui, H, Gong, G, Fu, Z, Zhou, J, Gu, J, Yin, Y & Feng, D 2018, 'Computational delineation and quantitative heterogeneity analysis of lung tumor on 18F-FDG PET for radiation dose-escalation', Scientific Reports, vol. 8, no. 1.
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AbstractQuantitative measurement and analysis of tumor metabolic activities could provide a more optimal solution to personalized accurate dose painting. We collected PET images of 58 lung cancer patients, in which the tumor exhibits heterogeneous FDG uptake. We design an automated delineation and quantitative heterogeneity measurement of the lung tumor for dose-escalation. For tumor delineation, our algorithm firstly separates the tumor from its adjacent high-uptake tissues using 3D projection masks; then the tumor boundary is delineated with our stopping criterion of joint gradient and intensity affinities. For dose-escalation, tumor sub-volumes with low, moderate and high metabolic activities are extracted and measured. Based on our quantitative heterogeneity measurement, a sub-volume oriented dose-escalation plan is implemented in intensity modulated radiation therapy (IMRT) planning system. With respect to manual tumor delineations by two radiation oncologists, the paired t-test demonstrated our model outperformed the other computational methods in comparison (p < 0.05) and reduced the variability between inter-observers. Compared to standard uniform dose prescription, the dosimetry results demonstrated that the dose-escalation plan statistically boosted the dose delivered to high metabolic tumor sub-volumes (p < 0.05). Meanwhile, the doses received by organs-at-risk (OAR) including the heart, ipsilateral lung and contralateral lung were not statistically different (p > 0.05).

Wang, X, Huang, C, Yao, L, Benatallah, B & Dong, M 2018, 'A Survey on Expert Recommendation in Community Question Answering', Journal of Computer Science and Technology, vol. 33, no. 4, pp. 625-653.
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Wang, X, Xu, C, Zhao, G & Yu, S 2018, 'Tuna: An Efficient and Practical Scheme for Wireless Access Point in 5G Networks Virtualization', IEEE Communications Letters, vol. 22, no. 4, pp. 748-751.
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© 1997-2012 IEEE. Recently, network function virtualization (NFV) has been widely used in 5G innovation. However, with the implementation of NFV, virtualized wireless access point has suffered a significant performance degradation. In this letter, we propose an efficient packet processing scheme (Tuna) to improve the performance of wireless network virtualization. Specifically, we locate management frame into user space for virtualization, and place control and data frame in kernel space to reduce packet processing delay. Moreover, hostapd and network address translation are modified to accelerate packet processing. We implemented the prototype of the proposed scheme, and the experimental results demonstrate that Tuna can improve both delay and throughput dramatically.

Wang, X, Xu, C, Zhao, G, Xie, K & Yu, S 2018, 'Efficient Performance Monitoring for Ubiquitous Virtual Networks Based on Matrix Completion', IEEE Access, vol. 6, pp. 14524-14536.
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© 2013 IEEE. Inspired by the concept of software-defined network and network function virtualization, vast virtual networks are generated to isolate and share wireless resources for different network operators. To achieve fine-grained resource control and scheduling among virtual networks (VNs), network performance monitoring is essential. However, due to limitation of hardware, real-time performance monitoring is impossible for a complete virtual network. In this paper, taking advantage of the low-rank characteristic of 90 virtual access points (VAPs) measurement data, we propose an intelligent measurement scheme, namely, adaptive and sequential sampling based on matrix completion (MC), which exploits from the MC to construct the complete data of VN performance from a partial direct monitoring data. First, to construct the initial measurement matrix, we propose a sampling correction model based on dispersion and coverage. Second, a stopping condition for the sequential sampling is introduced, based on the stopping condition, the sampling process for a period can stop without waiting for the matrix reconstruction to reach certain of accuracy level. Finally, the sampled VAPs are determined by referring the back-forth completed matrixes' normalized mean absolute error. The experiments show that our approach can achieve a constant network perception and maintain a relatively low error rate with a small sampling rate.

Wang, X, Zhang, Q, Ren, J, Xu, S, Wang, S & Yu, S 2018, 'Toward efficient parallel routing optimization for large-scale SDN networks using GPGPU', Journal of Network and Computer Applications, vol. 113, pp. 1-13.
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Routing optimization is an efficient way to improve network performance and guarantee the QoS requirements of users. However, with the rapid growth of network size and traffic demands, the routing optimization of SDN networks with centralized control plane is facing the scalability issue. To overcome the scalability issue, we aim to speed up the routing optimization process in large networks by utilizing the massive parallel computation capability of GPU. In this paper, we develop an efficient Lagrangian Relaxation based Parallel Routing Optimization Algorithm (LR-PROA). LR-PROA first decomposes the routing optimization problem into a set of path calculation problems for the traffic demands by relaxing the link capacity constraints, then the path calculation tasks are dispatched to GPU and executed concurrently on GPU. In order to achieve high degree of parallelism, LR-PROA also parallelizes the path calculation process for each traffic demand. Furthermore, to improve the convergence speed, LR-PROA uses efficient methods to adjust the calculated paths for a part of traffic demands and set the step size of subgradient algorithm for solving the Lagrangian dual problem in each iteration. Our evaluations on synthetic network topologies verify that LR-PROA has good optimization performance as well as superior calculation time efficiency. In our simulations, LR-PROA is up to tens of times faster than benchmark algorithms in large networks.

Wang, Y, Dong, D, Qi, B, Zhang, J, Petersen, IR & Yonezawa, H 2018, 'A Quantum Hamiltonian Identification Algorithm: Computational Complexity and Error Analysis', IEEE Transactions on Automatic Control, vol. 63, no. 5, pp. 1388-1403.
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Wang, Y, Dong, L, Liao, X, Ju, X, Su, SW & Ma, H 2018, 'A Pulse Energy Injection Inverter for the Switch-Mode Inductive Power Transfer System', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 7, pp. 2330-2340.
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IEEE Considering the coupling relationships between transfer power and efficiency in continuous-mode inductive power transfer (IPT) systems, this paper presents a pulse energy injection inverter for IPT systems. With a new topology and parameters tuning, the pulse energy injection IPT system with the proposed inverter can work in switch-mode to decouple transfer power with efficiency. Moreover, the transfer power is only decided by the duty ratio of the semiconductor switch, rather than affected by the transmitting resonator, receiving (Rx) resonator, and load. In this way, the pulse energy injection IPT system holds an operating frequency much lower than the resonant frequency to reduce switch loss and improve transfer efficiency. Experiments verify that the IPT system with proposed inverter maintains a high level efficiency within the middle range and realizes nearly 80 & #x0025; supply to load transfer efficiency even in a weak coupling coefficient (k = 0.044). Finally, experimental analysis implies that the pulse energy injection inverter is suitable for full-range transmission, and high-Q IPT systems with uncertainty in Rx circuits or load.

Wang, Y, Fan, S, Wu, S, Wang, C, Huang, Z & Zhang, L 2018, 'In Situ Synthesis and Unprecedented Electrochemical Performance of Double Carbon Coated Cross-Linked Co₃O₄', ACS Applied Materials & Interfaces, vol. 10, no. 49, pp. 42372-42379.
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© 2018 American Chemical Society. Improving the structural stability and the electron/ion diffusion rate across whole electrode particles is crucial for transition metal oxides as next-generation anodic materials in lithium-ion batteries. Herein, we report a novel structure of double carbon-coated Co 3 O 4 cross-linked composite, where the Co 3 O 4 nanoparticle is in situ covered by nitrogen-doped carbon and further connected by carbon nanotubes (Co 3 O 4 NP@NC@CNTs). This double carbon-coated Co 3 O 4 NP@NC@CNTs framework not only endows a porous structure that can effectively accommodate the volume changes of Co 3 O 4, but also provides multidimensional pathways for electronic/ionic diffusion in and among the Co 3 O 4 NPs. Electrochemical kinetics investigation reveals a decreased energy barrier for electron/ion transport in the Co 3 O 4 NP@NC@CNTs, compared with the single carbon-coated Co 3 O 4 NP@NC. As expected, the Co 3 O 4 NP@NC@CNT electrode exhibits unprecedented lithium storage performance, with a high reversible capacity of 1017 mA h g -1 after 500 cycles at 1 A g -1 , and a very good capacity retention of 75%, even after 5000 cycles at 15 A g -1 . The lithiation/delithiation process of Co 3 O 4 NP@NC@CNTs is dominated by the pseudocapacitive behavior, resulting in excellent rate performance and durable cycle stability.

Wang, Y, He, Q, Ye, D & Yang, Y 2018, 'Formulating Criticality-Based Cost-Effective Fault Tolerance Strategies for Multi-Tenant Service-Based Systems', IEEE Transactions on Software Engineering, vol. 44, no. 3, pp. 291-307.
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Wang, Y, Wang, R, Zhou, Y, Huang, Z, Wang, J & Jiang, L 2018, 'Directional Droplet Propulsion on Gradient Boron Nitride Nanosheet Grid Surface Lubricated with a Vapor Film below the Leidenfrost Temperature', ACS Nano, vol. 12, no. 12, pp. 11995-12003.
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© Copyright 2018 American Chemical Society. Controlled propulsion of liquid droplets on a solid surface offers important applications in various fields, including fog harvesting, heat transfer, microfluidics, and microdevice technologies. The propulsion of the liquid droplet is realized only if the driven force exceeds the resistance force. Sometimes the directional propulsion of droplets only takes place at the Leidenfrost state to achieve enough lubrication for a vapor cushion. The thick vapor cushions levitate liquid droplets to reduce resistance force. However, it is still challenging to reduce the vapor cushion thickness and simultaneously realize the directional droplet's motion, especially below the Leidenfrost temperature. Here, a structurally hydrophobic boron nitride nanosheet (BNNS) grid surface was constructed with a two-direction topographical gradient, i.e., the perpendicular altitude gradient and the horizontal density gradient. The polar nature of the B-N bonds results in intrinsic hydrophilicity of the boron nitride layer, which increases the Leidenfrost point and facilitates wetting even at high temperature. Much thinner vapor-lubricating layers are competent in the droplet's directional motion below the Leidenfrost temperature of the BNNS grid surface because the air gap trapped within boron nitride nanosheet grids acts as a part of the lubrication layer.

Wang, Y, Wang, Z, Jia, W, He, X & Jiang, M 2018, 'Joint Learning of Body and Part Representation for Person Re-Identification', IEEE Access, vol. 6, pp. 44199-44210.
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© 2013 IEEE. Person re-identification (ReID), aiming to identify people among multiple camera views, has attracted an increasing attention due to the potential of application in surveillance security. Large variations in subjects' postures, view angles, and illuminating conditions as well as non-ideal human detection significantly increase the difficulty of person ReID. Learning a robust metric for measuring the similarity between different person images is another under-addressed problem. In this paper, following the recent success of part-based models, in order to generate a discriminative and robust feature representation, we first propose to learn global and weighted local body-part features from pedestrian images. Then, in the training phase, angular loss and part-level classification loss are employed jointly as a similarity measure to train the network, which significantly improves the robustness of the resultant network against feature variance. Experimental results on several benchmark data sets demonstrate that our method outperforms the state-of-the-art methods.

Wang, Y, Zhang, J, Liu, Z, Wu, Q, Zhang, Z & Jia, Y 2018, 'Depth Super-Resolution on RGB-D Video Sequences With Large Displacement 3D Motion', IEEE Transactions on Image Processing, vol. 27, no. 7, pp. 3571-3585.
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© 1992-2012 IEEE. To enhance the resolution and accuracy of depth data, some video-based depth super-resolution methods have been proposed, which utilizes its neighboring depth images in the temporal domain. They often consist of two main stages: motion compensation of temporally neighboring depth images and fusion of compensated depth images. However, large displacement 3D motion often leads to compensation error, and the compensation error is further introduced into the fusion. A video-based depth super-resolution method with novel motion compensation and fusion approaches is proposed in this paper. We claim that 3D nearest neighboring field (NNF) is a better choice than using positions with true motion displacement for depth enhancements. To handle large displacement 3D motion, the compensation stage utilized 3D NNF instead of true motion used in the previous methods. Next, the fusion approach is modeled as a regression problem to predict the super-resolution result efficiently for each depth image by using its compensated depth images. A new deep convolutional neural network architecture is designed for fusion, which is able to employ a large amount of video data for learning the complicated regression function. We comprehensively evaluate our method on various RGB-D video sequences to show its superior performance.

Wang, Y, Zhao, J, Wang, D, Liu, Y, Wang, Q, Ni, B-J, Chen, F, Yang, Q, Li, X, Zeng, G & Yuan, Z 2018, 'Free nitrous acid promotes hydrogen production from dark fermentation of waste activated sludge', Water Research, vol. 145, pp. 113-124.
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© 2018 Elsevier Ltd Simultaneous sludge fermentation and nitrite removal is an effective approach to enhance nutrient removal from low carbon-wastewater. It was found in this work that the presence of nitrite largely promoted hydrogen production from acidic fermentation of waste activated sludge (WAS). The results showed that with an increase of nitrite from 0 to 250 mg/L, the maximal hydrogen yield increased from 8.5 to 15.0 mL/g VSS at pH 5.5 fermentation and 8.1–13.0 mL/g VSS at pH 6 fermentation. However, the maximal hydrogen yield from WAS fermentation at pH 8 remained almost constant (2.9–3.7 mL/g VSS) when nitrite was in the range of 0–250 mg/L. Further analyses revealed that free nitrous acid (FNA) rather than nitrite was the major contributor to the promotion of hydrogen yield. The mechanism investigations showed that FNA not only accelerated the disruption of sludge cells but also promoted the biodegradability of organics released, thereby provided more biodegradable substrates for subsequent hydrogen production. Although FNA inhibited activities of all microbes involved in the anaerobic fermentation, its inhibitions to hydrogen consumers were much severer than those to hydrolytic microorganisms and hydrogen producers. Further investigations with microbial community showed that FNA increased the abundances of hydrogen producers (e.g., Citrobacter sp.) and denitrifiers (e.g., Dechloromonas sp.), but reduced the abundances of hydrogen consumers (e.g., Clostridium_aceticum). This work demonstrated for the first time that FNA in WAS fermentation systems enhanced hydrogen production. The findings obtained expand the application field of FNA and may provide supports for sustainable operation of wastewater treatment plants.

Wang, Y-K, Jung, T-P & Lin, C-T 2018, 'Theta and Alpha Oscillations in Attentional Interaction during Distracted Driving', Frontiers in Behavioral Neuroscience, vol. 12, pp. 3-3.
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© 2018 Wang, Jung and Lin. Performing multiple tasks simultaneously usually affects the behavioral performance as compared with executing the single task. Moreover, processing multiple tasks simultaneously often involve more cognitive demands. Two visual tasks, lane-keeping task and mental calculation, were utilized to assess the brain dynamics through 32-channel electroencephalogram (EEG) recorded from 14 participants. A 400-ms stimulus onset asynchrony (SOA) factor was used to induce distinct levels of attentional requirements. In the dual-task conditions, the deteriorated behavior reflected the divided attention and the overlapping brain resources used. The frontal, parietal and occipital components were decomposed by independent component analysis (ICA) algorithm. The event- and response-related theta and alpha oscillations in selected brain regions were investigated first. The increased theta oscillation in frontal component and decreased alpha oscillations in parietal and occipital components reflect the cognitive demands and attentional requirements as executing the designed tasks. Furthermore, time-varying interactive over-additive (O-Add), additive (Add) and under-additive (U-Add) activations were explored and summarized through the comparison between the summation of the elicited spectral perturbations in two single-task conditions and the spectral perturbations in the dual task. Add and U-Add activations were observed while executing the dual tasks. U-Add theta and alpha activations dominated the posterior region in dual-task situations. Our results show that both deteriorated behaviors and interactive brain activations should be comprehensively considered for evaluating workload or attentional interaction precisely.

Wang, Z & Piccardi, M 2018, 'Minimum-risk temporal alignment of videos', Multimedia Tools and Applications, vol. 77, no. 12, pp. 14891-14906.
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Temporal alignment of videos is an important requirement of tasks such as video comparison, analysis and classification. Most of the approaches proposed to date for video alignment leverage dynamic programming algorithms whose parameters are manually tuned. Conversely, this paper proposes a model that can learn its parameters automatically by minimizing a meaningful loss function over a given training set of videos and alignments. For learning, we exploit the effective framework of structural SVM and we extend it with an original scoring function that suitably scores the alignment of two given videos, and a loss function that quantifies the accuracy of a predicted alignment. The experimental results from four video action datasets show that the proposed model has been able to outperform a baseline and a state-of-the-art algorithm by a large margin in terms of alignment accuracy.

Wang, Z, Wu, S, Huang, Y, Huang, S, Shi, S, Cheng, X & Huang, R 2018, 'Experimental investigation on spray, evaporation and combustion characteristics of ethanol-diesel, water-emulsified diesel and neat diesel fuels', Fuel, vol. 231, pp. 438-448.
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© 2018 This paper explored the spray and combustion characteristics of ethanol-diesel (E10), water-emulsified diesel (W10) and neat diesel (D100), especially micro-explosion of E10 and W10. The experiments were conducted in a constant volume combustion chamber under cold (383 K, 0% O2), evaporating (900 K, 0% O2) and combustion (900 K, 21% O2) conditions. Results showed that the spray expansion capacities of E10 and W10 under cold condition were much weaker than that of D100 due to the larger viscosity of emulsified diesels. Under evaporating condition, the spray volume of E10, W10 and D100 increased by 59%, 34% and 21% respectively comparing with cold spray volume. The higher increasing rates of E10 and W10 were mainly due to the micro-explosion effects of ethanol and water contents. Under combustion condition, the integrated natural flame luminosity (INFL) demonstrated that the ethanol content could accelerate the oxidation of soot, while the water content could prohibit soot generation. Therefore, both ethanol- and water-emulsified diesels could inhibit the soot emission, causing lower final residual soot emission of E10 and W10 than that of D100 by 21% and 39% respectively. Moreover, the flame lift-off length (LOL) and flame spread velocity showed that the effects of micro-explosion in E10 and W10 are different. The micro-explosion in ethanol occurred earlier, which enhanced the reaction rate in upstream flame and reduced the LOL. However, the micro-explosion in W10 occurred later, which enhanced the combustion rate in downstream flame.

Wang, Z, Xiao, F, Ye, N, Wang, R & Yang, P 2018, 'A See-through-Wall System for Device-Free Human Motion Sensing Based on Battery-Free RFID', ACM Transactions on Embedded Computing Systems, vol. 17, no. 1, pp. 1-21.
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A see-through-wall system can be used in life detection, military fields, elderly people surveillance. and gaming. The existing systems are mainly based on military devices, customized signals or pre-deployed sensors inside the room, which are very expensive and inaccessible for general use. Recently, a low-cost RFID technology has gained a lot of attention in this field. Since phase estimates of a battery-free RFID tag collected by a commercial off-the-shelf (COTS) RFID reader are sensitive to external interference, the RFID tag could be regarded as a battery-free sensor that detects reflections off targeted objects. The existing RFID-based system, however, needs to first learn the environment of the empty room beforehand to separate reflections off the tracked target. Besides, it can only track low-speed metal objects with high-positioning accuracy. Since the human body with its complex surface has a weaker ability to reflect radio frequency (RF) signals than metal objects, a battery-free RFID tag can capture only a subset of the reflections off the human body. To address these challenges, a RFID-based human motion sensing technology, called RF-HMS, is presented to track device-free human motion through walls. At first, we construct transfer functions of multipath channel based on phase and RSSI measurements to eliminate device noise and reflections off static objects like walls and furniture without learning the environment of the empty room before. Then a tag planar array is grouped by many battery-free RFID tags to improve the sensing performance. RF-HMS combines reflections from each RFID tag into a reinforced result. On this basis, we extract phase shifts to detect the absence or presence of any moving persons and further derive the reflections off a single moving person to identify his/her forward or backward motion direction. The results show that RF-HMS can effectively detect the absence or presence of moving persons with 100% accuracy...

Wattanapornprom, R, Valerio, DNR, Pansuk, W, Nguyen, TN & Pheinsusom, P 2018, 'Fire Resistance Performance of Reactive Powder Concrete Columns', Engineering Journal, vol. 22, no. 4, pp. 67-82.
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© 2018, Chulalongkorn University. All rights reserved. This paper experimentally explores the fire resistance of reactive powder concrete (RPC) columns with varying steel and polypropylene (PP) fiber content. RPC is a concrete composition with the highest developed compressive strength and is incorporated with steel fibers that can improve the tensile strength and ductility of RPC structures. The fire resistance of RPC structures, however, has been disputed by engineers and researchers. Four columns with different weight contents of fiber were tested in fire for 30 and 60 minutes with a load applied afterwards. Then, the performance of RPC columns in elevated temperature was investigated, focusing on spalling depth, failure mechanism in fiber and residual strength. The results showed that increasing the volume fraction of steel fiber or the presence of PP fiber improves the fire resistance of the columns. However, the columns lost significant cross-sectional area and load capacity. With the knowledge that this research would provide, a better understanding for making decisions could be developed.

Wei, C-S, Lin, Y-P, Wang, Y-T, Lin, C-T & Jung, T-P 2018, 'A subject-transfer framework for obviating inter- and intra-subject variability in EEG-based drowsiness detection', NeuroImage, vol. 174, pp. 407-419.
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© 2018 Inter- and intra-subject variability pose a major challenge to decoding human brain activity in brain-computer interfaces (BCIs) based on non-invasive electroencephalogram (EEG). Conventionally, a time-consuming and laborious training procedure is performed on each new user to collect sufficient individualized data, hindering the applications of BCIs on monitoring brain states (e.g. drowsiness) in real-world settings. This study proposes applying hierarchical clustering to assess the inter- and intra-subject variability within a large-scale dataset of EEG collected in a simulated driving task, and validates the feasibility of transferring EEG-based drowsiness-detection models across subjects. A subject-transfer framework is thus developed for detecting drowsiness based on a large-scale model pool from other subjects and a small amount of alert baseline calibration data from a new user. The model pool ensures the availability of positive model transferring, whereas the alert baseline data serve as a selector of decoding models in the pool. Compared with the conventional within-subject approach, the proposed framework remarkably reduced the required calibration time for a new user by 90% (18.00 min–1.72 ± 0.36 min) without compromising performance (p = 0.0910) when sufficient existing data are available. These findings suggest a practical pathway toward plug-and-play drowsiness detection and can ignite numerous real-world BCI applications.

Wei, C-S, Wang, Y-T, Lin, C-T & Jung, T-P 2018, 'Toward Drowsiness Detection Using Non-hair-Bearing EEG-Based Brain-Computer Interfaces', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, no. 2, pp. 400-406.
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© 2001-2011 IEEE. Drowsy driving is one of the major causes that lead to fatal accidents worldwide. For the past two decades, many studies have explored the feasibility and practicality of drowsiness detection using electroencephalogram (EEG)-based brain-computer interface (BCI) systems. However, on the pathway of transitioning laboratory-oriented BCI into real-world environments, one chief challenge is to obtain high-quality EEG with convenience and long-term wearing comfort. Recently, acquiring EEG from non-hair-bearing (NHB) scalp areas has been proposed as an alternative solution to avoid many of the technical limitations resulted from the interference of hair between electrodes and the skin. Furthermore, our pilot study has shown that informative drowsiness-related EEG features are accessible from the NHB areas. This study extends the previous work to quantitatively evaluate the performance of drowsiness detection using cross-session validation with widely studied machine-learning classifiers. The offline results showed no significant difference between the accuracy of drowsiness detection using the NHB EEG and the whole-scalp EEG across all subjects ( ${p} = \textsf {0.31}$ ). The findings of this study demonstrate the efficacy and practicality of the NHB EEG for drowsiness detection and could catalyze explorations and developments of many other real-world BCI applications.

Wei, D, Ngo, HH, Guo, W, Xu, W, Du, B & Wei, Q 2018, 'Partial nitrification granular sludge reactor as a pretreatment for anaerobic ammonium oxidation (Anammox): Achievement, performance and microbial community', Bioresource Technology, vol. 269, pp. 25-31.
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Partial nitrification granular sludge was successfully cultivated in a sequencing batch reactor as a pretreatment for anaerobic ammonium oxidation (Anammox) through shortening settling time. After 250-days operation, the effluent NH4+-N and NO2--N concentrations were average at 277.5 and 280.5 mg/L with nitrite accumulation rate of 87.8%, making it as an ideal influent for Anammox. Simultaneous free ammonia (FA) and free nitrous acid (FNA) played major inhibitory roles on the activity of nitrite oxidizing bacteria (NOB). The MLSS and SVI30 of partial nitrification reactor were 14.6 g/L and 25.0 mL/g, respectively. Polysaccharide (PS) and protein (PN) amounts in extracellular polymeric substances (EPS) from granular sludge were about 1.3 and 2.8 times higher than from seed sludge. High-throughput pyrosequencing results indicated that Nitrosomonas affiliated to the ammonia oxidizing bacteria (AOB) was the predominant group with a proportion of 24.1% in the partial nitrification system.

Wei, D, Ngo, HH, Guo, W, Xu, W, Du, B, Khan, MS & Wei, Q 2018, 'Biosorption performance evaluation of heavy metal onto aerobic granular sludge-derived biochar in the presence of effluent organic matter via batch and fluorescence approaches', Bioresource Technology, vol. 249, pp. 410-416.
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In present study, the biosorption process of Cu(II) onto aerobic granular sludge-derived biochar was evaluated in the absence and presence of effluent organic matter (EfOM) by using batch and fluorescence approaches. It was found that EfOM gave rise to enhancement of Cu(II) removal efficiency onto biochar, and the sorption data were better fitted with pseudo-second order model and Freundlich equation, in despite of the absence and presence of EfOM. According to excitation-emission matrix (EEM), EfOM was mainly comprised by humic-like substances and fulvic-like substances and their intensities were reduced in the addition of biochar and Cu(II) from batch biosorption process. Synchronous fluorescence spectra coupled to two-dimensional correlation spectroscopy (2D-COS) further implied that a successive fluorescence quenching was observed in various EfOM fractions with the increasing Cu(II) concentration. Moreover, fulvic-like fraction was more susceptibility than other fractions for fluorescence quenching of EfOM.

Wei, F, Costanza, R, Dai, Q, Stoeckl, N, Gu, X, Farber, S, Nie, Y, Kubiszewski, I, Hu, Y, Swaisgood, R, Yang, X, Bruford, M, Chen, Y, Voinov, A, Qi, D, Owen, M, Yan, L, Kenny, DC, Zhang, Z, Hou, R, Jiang, S, Liu, H, Zhan, X, Zhang, L, Yang, B, Zhao, L, Zheng, X, Zhou, W, Wen, Y, Gao, H & Zhang, W 2018, 'The Value of Ecosystem Services from Giant Panda Reserves', Current Biology, vol. 28, no. 13, pp. 2174-2180.e7.
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© 2018 Elsevier Ltd Ecosystem services (the benefits to humans from ecosystems) are estimated globally at $125 trillion/year [1, 2]. Similar assessments at national and regional scales show how these services support our lives [3]. All valuations recognize the role of biodiversity, which continues to decrease around the world in maintaining these services [4, 5]. The giant panda epitomizes the flagship species [6]. Its unrivalled public appeal translates into support for conservation funding and policy, including a tax on foreign visitors to support its conservation [7]. The Chinese government has established a panda reserve system, which today numbers 67 reserves [8, 9]. The biodiversity of these reserves is among the highest in the temperate world [10], covering many of China's endemic species [11]. The panda is thus also an umbrella species [12]—protecting panda habitat also protects other species. Despite the benefits derived from pandas, some journalists have suggested that it would be best to let the panda go extinct. With the recent downlisting of the panda from Endangered to Vulnerable, it is clear that society's investment has started to pay off in terms of panda population recovery [13, 14]. Here, we estimate the value of ecosystem services of the panda and its reserves at between US$2.6 and US$6.9 billion/year in 2010. Protecting the panda as an umbrella species and the habitat that supports it yields roughly 10–27 times the cost of maintaining the current reserves, potentially further motivating expansion of the reserves and other investments in natural capital in China. Wei et al. estimate that the value of ecosystem services of the giant panda and its nature reserves was US$2.6–US$6.9 billion/year in 2010. Protecting the panda and its habitat yields roughly 10–27 times the cost of maintaining the current reserves, potentially motivating expansion of the reserves and other investments in natural capital in China.

Wei, JS, Kuznetsov, IB, Zhang, S, Song, YK, Asgharzadeh, S, Sindiri, S, Wen, X, Patidar, R, Najaraj, S, Walton, A, Guidry Auvil, JM, Gerhard, DS, Yuksel, A, Catchpoole, D, Hewitt, SM, Sondel, PM, Seeger, R, Maris, JM & Khan, J 2018, 'Clinically Relevant Cytotoxic Immune Cell Signatures and Clonal Expansion of T-Cell Receptors in High-Risk MYCN-Not-Amplified Human Neuroblastoma', Clinical Cancer Research, vol. 24, no. 22, pp. 5673-5684.
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Abstract Purpose: High-risk neuroblastoma is an aggressive disease. DNA sequencing studies have revealed a paucity of actionable genomic alterations and a low mutation burden, posing challenges to develop effective novel therapies. We used RNA sequencing (RNA-seq) to investigate the biology of this disease, including a focus on tumor-infiltrating lymphocytes (TIL). Experimental Design: We performed deep RNA-seq on pretreatment diagnostic tumors from 129 high-risk and 21 low- or intermediate-risk patients with neuroblastomas. We used single-sample gene set enrichment analysis to detect gene expression signatures of TILs in tumors and examined their association with clinical and molecular parameters, including patient outcome. The expression profiles of 190 additional pretreatment diagnostic neuroblastomas, a neuroblastoma tissue microarray, and T-cell receptor (TCR) sequencing were used to validate our findings. Results: We found that MYCN-not-amplified (MYCN-NA) tumors had significantly higher cytotoxic TIL signatures compared with MYCN-amplified (MYCN-A) tumors. A reported MYCN activation signature was significantly associated with poor outcome for high-risk patients with MYCN-NA tumors; however, a subgroup of these patients who had elevated activated natural killer (NK) cells, CD8+ T cells, and cytolytic signatures showed improved outcome and expansion of infiltrating TCR clones. Furthermore, we observed upregulation of immune exhaustion marker genes, indicating an immune-suppressive microenvironment in these neuroblastomas. Conclusions: This study provides evidence that RNA signatures of cytotoxic TIL are associated with the presence of activated NK/T cells and improved outcomes in high-risk neuroblastoma patients harboring MYCN-NA tumors. Our findings suggest that these high-risk patients with MYCN-NA neurob...

Wei, W, Cai, Z, Fu, J, Xie, G-J, Li, A, Zhou, X, Ni, B-J, Wang, D & Wang, Q 2018, 'Zero valent iron enhances methane production from primary sludge in anaerobic digestion', Chemical Engineering Journal, vol. 351, pp. 1159-1165.
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© 2018 Elsevier B.V. This study proposed a novel zero valent iron (ZVI) technology to enhance anaerobic methane production from primary sludge in the anaerobic digester and to improve the dewaterability of digested sludge for the first time. Compared to the control test without ZVI, the anaerobic digester with ZVI at all levels (1, 4 and 20 g/L) played a driving role in anaerobic methane production from primary sludge. The maximal biochemical methane production of 439 ± 5 L CH4/kg VS was achieved at ZVI of 4 g/L, while only 345 ± 2 L CH4/kg VS (volatile solids) was produced in the case of no-ZVI dosage, representing a relative increase of 26.9 ± 0.1%. It was also found that ZVI addition would produce an anaerobically digested sludge with a better dewaterability, as indicated by the decrease of the normalized capillary suction time from 100 to 63 ∼ 89 s, respectively. Model based analysis revealed that the enhanced methane production from primary sludge was due to an increase in both hydrolysis rate and biochemical methane potential of primary sludge. Economic analysis demonstrated that ZVI technology was economically favorable.

Wei, W, Li, A, Ma, F, Pi, S, Yang, J, Wang, Q & Ni, B 2018, 'Simultaneous sorption and reduction of Cr(VI) in aquatic system by microbial extracellular polymeric substances from Klebsiella sp. J1', Journal of Chemical Technology & Biotechnology, vol. 93, no. 11, pp. 3152-3159.
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AbstractBACKGROUNDCr(VI) is being increasingly used in a variety of fields, including electroplating, metallurgy, pigment synthesis and leather tanning. The possible application of a microbial extracellular polymeric substance (EPS) from Klebsiella sp. J1 with abundant functional groups in remediating Cr(VI) pollution in water system was demonstrated.RESULTSThe maximum biosorption capacity of EPS for Cr(VI) was found to be 53.3 mg g−1 at an EPS dose of 1.5 g L−1, which was better than the majority of reported biosorbents. The adsorption of EPS for Cr(VI) was a spontaneous and endothermic process. The removal mechanism of Cr(VI) in aquatic environments was explored qualitatively and quantitatively by Zeta‐potential meter, X‐ray photoelectron spectrometer (XPS) as well as Fourier transform infrared spectrometer. The superior Cr(VI) removal performance was attributed mainly to Cr(VI) adsorption on EPS via chelation and ion‐exchange sorption, and the efficient reduction (82.3%) of Cr(VI) to Cr(III) by benzenoid amine (–NH–) on EPS, followed by generated Cr(III) immobilization on the surface of EPS via surface physical sorption and chelation, which might control the reaction rate of Cr(VI) removal process.CONCLUSIONThe removal of Cr(VI) by EPS from Klebsiella sp. J1 was attributed mainly to simultaneous sorption and reduction of Cr(VI) by EPS. The results demonstrated that EPS from Klebsiella sp. J1 has great potential in treating Cr(VI)‐contaminated water. © 2018 Society of Chemical Industry

Wei, W, Li, A, Pi, S, Wang, Q, Zhou, L, Yang, J, Ma, F & Ni, B-J 2018, 'Synthesis of Core–Shell Magnetic Nanocomposite Fe₃O₄@ Microbial Extracellular Polymeric Substances for Simultaneous Redox Sorption and Recovery of Silver Ions as Silver Nanoparticles', ACS Sustainable Chemistry & Engineering, vol. 6, no. 1, pp. 749-756.
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Microbial extracellular polymeric substance (EPS) is a complex high molecular weight compound secreted from many organisms. In this work, magnetic nanocomposite Fe3O4@EPS of Klebsiella sp. J1 were first synthesized for silver ions (Ag+) wastewater remediation, which synergistically combined the advantages of the easy separation property of magnetic Fe3O4 nanoparticles and the superior adsorption capacity of EPS of Klebsiella sp. J1. The physical and chemical properties of Fe3O4@EPS were analyzed comprehensively. Fe3O4@EPS exhibited the well-defined core-shell structure (size 50 nm) with high magnetic (79.01 emu g-1). Batch adsorption experiments revealed that Fe3O4@EPS achieved high Ag+ adsorption capacity (48 mg g-1), which was also much higher than many reported adsorbents. The optimal solution pH for Ag+ adsorption was around 6.0, with the sorption process followed pseudo-second-order kinetics. Ag+ adsorption on Fe3O4@EPS was mainly attributed to the reduction of Ag+ to silver nanoparticles (AgNPs) by benzenoid amine (-NH-), accompanied by the chelation between Ag+ and hydroxyl groups, ion exchange between Ag+ and Mg2+ and K+, and physical electrostatic sorption. The repeated adsorption-desorption experiments showed a good recycle performance of Fe3O4@EPS. This study has great importance for demonstrating magnetic Fe3O4@EPS as potential adsorbent to remove Ag+ from contaminated aquatic systems.

Wei, W, Wang, Q, Zhang, L, Laloo, A, Duan, H, Batstone, DJ & Yuan, Z 2018, 'Free nitrous acid pre-treatment of waste activated sludge enhances volatile solids destruction and improves sludge dewaterability in continuous anaerobic digestion', Water Research, vol. 130, pp. 13-19.
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© 2017 Elsevier Ltd Previous work has demonstrated that pre-treatment of waste activated sludge (WAS) with free nitrous acid (FNA i.e. HNO2) enhances the biodegradability of WAS, identified by a 20–50% increase in specific methane production in biochemical methane potential (BMP) tests. This suggests that FNA pre-treatment would enhance the destruction of volatile solids (VS) in an anaerobic sludge digester, and reduce overall sludge disposal costs, provided that the dewaterability of the digested sludge is not negatively affected. This study experimentally evaluates the impact of FNA pre-treatment on the VS destruction in anaerobic sludge digestion and on the dewaterability of digested sludge, using continuously operated bench-scale anaerobic digesters. Pre-treatment of full-scale WAS for 24 h at an FNA concentration of 1.8 mg NN/L enhanced VS destruction by 17 ± 1% (from 29.2 ± 0.9% to 34.2 ± 1.1%) and increased dewaterability (centrifuge test) from 12.4 ± 0.4% to 14.1 ± 0.4%. Supporting the VS destruction data, methane production increased by 16 ± 1%. Biochemical methane potential tests indicated that the final digestate stability was also improved with a lower potential from FNA treated digestate. Further, a 2.1 ± 0.2 log improvement in pathogen reduction was also achieved. With inorganic solids representing 15–22% of the full-scale WAS used, FNA pre-treatment resulted in a 16–17% reduction in the volume of dewatered sludge for final disposal. This results in significantly reduced costs as assessed by economic analysis.

Wei, W, Zhou, X, Wang, D, Sun, J, Nghiem, LD & Wang, Q 2018, 'Free Ammonia Pretreatment to Enhance Biodegradation of Anaerobically Digested Sludge in Post Aerobic Digestion', ACS Sustainable Chemistry & Engineering, vol. 6, no. 9, pp. 11836-11842.
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Copyright © 2018 American Chemical Society. In wastewater treatment plants (WWTPs), sludge reduction was implemented via sequential anaerobic-aerobic digestion. However, the performance of post aerobic digestion for anaerobically digested sludge (ADS) is limited. Free ammonia (FA)-based pretreatment technology is proposed in this study as an innovative method to enhance the degradation efficiency of post aerobic digestion for ADS. Pretreatment using FA at >440 mg NH3-N/L for 24 h significantly increased ADS solubilization. The highest solubilization was reached at 1030 mg NH3-N/L, which (0.12 mg COD/mg VS) is 6 times that (0.02 mg COD/mg VS) of no treatment. The batch experiments of post aerobic digestion demonstrated unpretreated ADS over the 8 days post aerobic digestion was degraded by 18.4%, whereas 31.3-33.6% of the pretreated ADS with FA at 440-1030 mg NH3-N/L was degraded, representing a relative increase of 70-83%. Accordingly, inorganic nitrogen production increased in a similar way. Model analysis results revealed the enhanced ADS degradation was because of the increase in both hydrolysis rate and degradable percentage of ADS. Capillary suction time (CST) tests demonstrated FA-based pretreatment was able to generate ADS with greater dewaterability, as revealed by the decline of normalized CST from 77 s for ADS without pretreatment to 63-74 s for ADS with FA pretreatment at 65-1030 NH3-N/L, with the best ADS dewaterability at 1030 mg NH3-N/L of FA. Economic assessment showed that this FA pretreatment technology could be economically favorable.

Wei, Z, Wang, Z, Yuan, X, Wu, H & Feng, Z 2018, 'Information density–based energy-limited capacity of ad hoc networks', International Journal of Distributed Sensor Networks, vol. 14, no. 4, pp. 155014771877324-155014771877324.
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In this article, the inhomogeneous energy consumption is characterized by the concept of information density, which is defined as the number of bits per unit time passing through a specific region. With information density, it is possible to derive the energy consumption of each region and determine the energy configuration scheme to maximize the network lifetime. The information density of pure ad hoc network and hybrid ad hoc network is derived. It is discovered that the information density of pure ad hoc network is inhomogeneous and the information density of hybrid ad hoc network is homogeneous, except for the regions near the edge of the entire area. With information density, the energy-limited capacity of pure and hybrid ad hoc networks is derived. The information density introduced in this article provides more insights into the information transfer of ad hoc networks, which may be applied in the energy configuration of ad hoc networks.

Wei, Z, Wu, H, Yuan, X, Huang, S & Feng, Z 2018, 'Achievable Capacity Scaling Laws of Three-Dimensional Wireless Social Networks', IEEE Transactions on Vehicular Technology, vol. 67, no. 3, pp. 2671-2685.
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With the development of aeronautical telecommunication and unmanned aerial vehicles (UAVs), wireless networks will be extended to three-dimensional (3-D) space. Besides, 3-D wireless networks have been widely deployed in battlefields, which consist of aircraft, UAVs, ground troops, and fleets. When nodes in these wireless networks form swarm and cooperate with each other, there will be social behavior among them and 3-D wireless social networks emerge. Although the study of wireless social networks has been initiated, the capacity of 3-D wireless social networks is unknown. In this paper, we derive the achievable capacity of 3-D wireless social networks. It shows that the capacity is a function of the pathloss exponent, the number of nodes, the social group concentration, the contact concentration, and the size of social group. When the social group concentration or the contact concentration exceeds a threshold, the wireless social network is scalable and the capacity of wireless social network is much larger than that of the wireless network without social behavior. Besides, we discover the existence of a singular point for social group concentration and contact concentration, where the network capacity skips to a larger value than the neighborhood. The results reveal the interplay between wireless communication and social connection in 3-D space, which brings an insight into the design of 3-D wireless networks.

Wen, S, Wei, H, Zeng, Z & Huang, T 2018, 'Memristive Fully Convolutional Network: An Accurate Hardware Image-Segmentor in Deep Learning', IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 2, no. 5, pp. 324-334.
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As well known, fully convolutional network (FCN) becomes the state of the art for semantic segmentation in deep learning. Currently, new hardware designs for deep learning have focused on improving the speed and parallelism of processing units. This motivates memristive solutions, in which the memory units (i.e., memristors) have computing capabilities. However, designing a memristive deep learning network is challenging, since memristors work very differently from the traditional CMOS hardware. This paper proposes a complete solution to implement memristive FCN (MFCN). Voltage selectors are firstly utilized to realize max-pooling layers with the detailed MFCN deconvolution hardware circuit by the massively parallel structure, which is effective since the deconvolution kernel and the input feature are similar in size. Then, deconvolution calculation is realized by converting the image into a column matrix and converting the deconvolution kernel into a sparse matrix. Meanwhile, the convolution realization in MFCN is also studied with the traditional sliding window method rather than the large matrix theory to overcome the shortcoming of low efficiency. Moreover, the conductance values of memristors are predetermined in Tensorflow with ex-situ training method. In other words, we train MFCN in software, then download the trained parameters to the simulink system by writing memristor. The effectiveness of the designed MFCN scheme is verified with improved accuracy over some existing machine learning methods. The proposed scheme is also adapt to LFW dataset with three-classification tasks. However, the MFCN training is time consuming as the computational burden is heavy with thousands of weight parameters with just six layers. In future, it is necessary to sparsify the weight parameters and layers of the MFCN network to speed up computing.

Wen, S, Xie, X, Yan, Z, Huang, T & Zeng, Z 2018, 'General memristor with applications in multilayer neural networks', Neural Networks, vol. 103, pp. 142-149.
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© 2018 Elsevier Ltd Memristor describes the relationship between charge and flux. Although several window functions for memristors based on the HP linear and nonlinear dopant drift models have been studied, most of them are inadequate to capture the full characteristics of memristors. To address this issue, this paper proposes a unified window function to describe a general memristor with restrictions of its parameters given. Compared with other window functions, the proposed function demonstrates high validity and accuracy. In order to make the simulation results have high consistency with the results of actual circuit, we apply the new window function to the simulation of a memristor-based multilayer neural network (MNN) circuit. The overall accuracy will vary with the change of control parameters in the window function. It implies that the proposed model can guide the design of actual memristor-based circuits.

Wen, T, Cai, C, Gardner, L, Dixit, V, Waller, ST & Chen, F 2018, 'A Strategic User Equilibrium for Independently Distributed Origin‐Destination Demands', Computer-Aided Civil and Infrastructure Engineering, vol. 33, no. 4, pp. 316-332.
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AbstractThis article proposes an extension of the strategic user equilibrium proposed by Waller and colleagues and Dixit and colleagues. The proposed model relaxes the assumption of proportional Origin‐Destination (O‐D) demand, as it accounts for users’ strategic link choice under independently distributed O‐D demands. The convexity of the mathematical formulation is proved when each O‐D demand is assumed to follow a Poisson distribution independently; link flow distributions and users’ strategic link choice are also proved to be unique. Network performance measures are given analytically. A numerical analysis is conducted on the Sioux Falls network. A Monte Carlo method is used to simulate network performance measures, which are then compared to the results computed from the analytical expression. It is illustrated that the model is capable of accounting for demand volatility while maintaining computation efficiency.

Wen, T, Cai, C, Gardner, L, Waller, ST, Dixit, V & Chen, F 2018, 'Estimation of sparse O–D matrix accounting for demand volatility', IET Intelligent Transport Systems, vol. 12, no. 9, pp. 1020-1026.
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A critical issue in origin-destination (O-D) demand estimation is under-determination: the number of O-D pairs to be estimated is often much greater than the number of monitored links. In real world, some centroids tend to be more popular than others, and only few trips are made for intro-zonal travel. Consequently, a large portion of trips will be made for a small portion of O-D pairs, meaning many O-D pairs have only a few or even zero trips. Mathematically, this implies that the O-D matrix is sparse. Also, the correlation between link flows is often neglected in the O-D estimation problem, which can be obtained from day-to-day loop detector count data. Thus, sparsity regularisation is combined with link flow correlation to provide additional inputs for the O-D estimation process to mitigate the issue of under-determination and thereby improve estimation quality. In addition, a novel strategic user equilibrium model is implemented to provide route choice of users for the O-D estimation problem, which explicitly accounts for demand and link flow volatility. The model is formulated as a convex generalised least squares problem with regularisation, the usefulness of sparsity assumption, and link flow correlation is presented in the numerical analysis.

Wen, T, Gardner, L, Dixit, V, Waller, ST, Cai, C & Chen, F 2018, 'Two Methods to Calibrate the Total Travel Demand and Variability for a Regional Traffic Network', Computer-Aided Civil and Infrastructure Engineering, vol. 33, no. 4, pp. 282-299.
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AbstractThis article proposes a novel methodology that uses the bi‐level programming formulation to calibrate the expected total demand and the corresponding demand variability of traffic networks. In the bi‐level formulation the upper‐level is either a new maximum likelihood estimation method or a least squares method and the lower‐level is the strategic user equilibrium assignment model (StrUE) which accounts for the day‐to‐day demand volatility. The maximum likelihood method proposed in this article has the ability to utilize information from day‐to‐day observed link flows to provide a unique estimation of the total demand distribution, whereas the least squares method is capable of capturing link flow variations. The lower‐level StrUE model can take the total demand distribution as input, and output a set of link flow distributions which can then be compared to the link‐level observations. The mathematical proof demonstrates the convexity of the model, and the sensitivity to the prediction error is analytically derived. Numerical analysis is conducted to illustrate the efficiency and sensitivity of the proposed model. Some possible future research is discussed in the conclusion.

Wen, T, Mihăiţă, A-S, Nguyen, H, Cai, C & Chen, F 2018, 'Integrated Incident Decision-Support using Traffic Simulation and Data-Driven Models', Transportation Research Record: Journal of the Transportation Research Board, vol. 2672, no. 42, pp. 247-256.
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This paper introduces the framework of an innovative incident management platform with the main objective of providing decision-support and situation awareness for transport management purposes on a real-time basis. The logic of the platform is to detect and then classify incidents into two types: recurrent and non-recurrent, based on their frequency and characteristics. Under this logic, recurrent incidents trigger the data-driven machine learning module which can predict and analyze the incident impact, in order to facilitate informed decisions for transport management operators. Non-recurrent incidents activate the simulation module, which then evaluates quantitatively the performance of candidate response plans in parallel. The simulation output is used for choosing the most appropriate response plan for incident management. The current platform uses a data processing module to integrate complementary data sets, for the purpose of improving modeling outputs. Two real-world case studies are presented: 1) for recurrent incident management using a data-driven model, and 2) for non-recurrent incident management using traffic simulation with parallel scenario evaluation. The case studies demonstrate the viability of the proposed incident management framework, which provides an integrated approach for real-time incident decision-support on large-scale networks.

Wickham, R, Xie, S, Galway, B, Bustamante, H & Nghiem, LD 2018, 'Anaerobic digestion of soft drink beverage waste and sewage sludge', Bioresource Technology, vol. 262, pp. 141-147.
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© 2018 Soft drink beverage waste (BW) was evaluated as a potential substrate for anaerobic co-digestion with sewage sludge to increase biogas production. Results from this study show that the increase in biogas production is proportional to the increase in organic loading rate (OLR) rate due to BW addition. The OLR increase of 86 and 171% corresponding to 10 and 20% BW by volume in the feed resulted in 89 and 191% increase in biogas production, respectively. Under a stable condition, anaerobic co-digestion with BW did not lead to any significant impact on digestate quality (in terms of COD removal and biosolids odour) and biogas composition. The results suggest that existing nutrients in sewage sludge can support an increase in OLR by about 2 kg COD/m3/d from a carbon rich substrate such as soft drink BW without inhibition or excessive impact on subsequent handling of the digestate.

Wickramasinghe Abeywardana, DB, Acuna, P, Hredzak, B, Aguilera, RP & Agelidis, VG 2018, 'Single-Phase Boost Inverter-Based Electric Vehicle Charger With Integrated Vehicle to Grid Reactive Power Compensation', IEEE Transactions on Power Electronics, vol. 33, no. 4, pp. 3462-3471.
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© 1986-2012 IEEE. Vehicle to grid (V2G) reactive power compensation using electric vehicle (EV) onboard chargers helps to ensure grid power quality by achieving unity power factor operation. However, the use of EVs for V2G reactive power compensation increases the second-order harmonic ripple current component at the DC-side of the charger. For single-phase, single-stage EV chargers, the ripple current component has to be supplied by the EV battery, unless a ripple compensation method is employed. Additionally, continuous usage of EV chargers for reactive power compensation, when the EV battery is not charging from the grid, exposes the EV battery to these undesirable ripple current components for a longer period and discharges the battery due to power conversion losses. This paper presents a way to provide V2G reactive power compensation through a boost inverter-based single stage EV charger and a DC-side capacitor without adversely affecting the EV battery. The operation of the boost inverter-based EV charger with second-order harmonic and switching frequency ripple current reduction, the dynamic behavior of the system, the transition between different operating modes, the DC-side capacitor voltage control above a minimum allowed voltage, and the DC-side capacitor sizing are extensively analyzed. The performance of the proposed system is verified using an experimental prototype, and presented results demonstrate the ability of the system to provide V2G reactive power compensation both with and without the EV battery.

Wijaya, FB, Sepehrirahnama, S & Lim, K-M 2018, 'Interparticle force and torque on rigid spheroidal particles in acoustophoresis', Wave Motion, vol. 81, pp. 28-45.
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Williams, P, Kirby, R, Hill, J, Åbom, M & Malecki, C 2018, 'Reducing low frequency tonal noise in large ducts using a hybrid reactive-dissipative silencer', Applied Acoustics, vol. 131, pp. 61-69.
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© 2017 Elsevier Ltd Noise generated by fans or turbines normally consists of a combination of narrow and broadband noise. To lower transmitted noise levels, it is attractive to use a combination of reactive and dissipative elements. However, this approach presents a number of challenges for larger systems. This is because reactive elements are commonly placed around the duct circumference where they are normally only effective up to the frequency at which the first higher order mode cuts on in the duct. For larger systems, this means that reactive elements work only in the low, and often very low, frequency range, whereas dissipative elements, which are distributed across the duct cross-section, generally work well in the medium to high frequency range. This can cause noise problems in the low to medium frequency range in larger systems. This article presents an alternative approach for delivering noise attenuation over the low to medium frequency range that is suitable for application in larger duct systems. This approach takes advantage of those splitter silencer designs commonly used in larger systems to integrate a reactive element into the splitter design. This delivers a hybrid splitter that uses a combination of dissipative and reactive elements so that the reactive element partitions the main airway. This has the advantage of introducing a quasi-planar transverse sound pressure field for each resonator in the low to medium frequency range, including frequencies above the first cut-on. It is demonstrated using predictions and measurements taken for a number of example silencers, that this approach enables reactive elements to work over an extended low to medium frequency range, including at frequencies above the first cut-on mode in the main duct. Accordingly, it is shown that a hybrid dissipative-reactive splitter design is capable of delivering improved levels of attenuation in the crucial low to medium frequency range.

Winter, M, Hardy, T, Rezaei, M, Nguyen, V, Zander‐Fox, D, Ebrahimi Warkiani, M & Thierry, B 2018, 'Isolation of Circulating Fetal Trophoblasts Using Inertial Microfluidics for Noninvasive Prenatal Testing', Advanced Materials Technologies, vol. 3, no. 7, pp. 1800066-1800066.
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AbstractWhile noninvasive prenatal testing based on cell‐free fetal DNA has recently revolutionized the field of aneuploidy screening in pregnancy, it remains limited to aneuploidy and microdeletion screening, and is unable to reliably detect single gene disorders. A number of recent studies have demonstrated the potential of circulating trophoblastic cells in providing cell‐based noninvasive diagnosis with sequencing or array‐based assays. However, considering the extreme rarity of these cells in blood, efficient, high‐throughput, and clinically applicable enrichment technologies are yet to be developed. This study demonstrates for the first time the utility of inertial microfluidics for efficient isolation of trophoblastic cells from maternal peripheral blood. Under optimal operating conditions, high‐recovery yields (79%) are obtained using a trophoblastic cell‐line, which is subsequently confirmed with analysis of maternal blood. Feasibility of obtaining a diagnosis from cells isolated from a maternal sample is demonstrated in a case of confirmed fetal trisomy 21 in which six fetal cells are found in a 7 mL blood sample using fluorescence in situ hybridization. Finally, it is demonstrated that trophoblastic cells isolated using inertial microfluidics could be picked and subjected to a clinically validated sequencing assay, paving the way for further validation of this technology and larger clinical studies.

Wong, GY, Leung, FHF & Ling, S-H 2018, 'A hybrid evolutionary preprocessing method for imbalanced datasets', Information Sciences, vol. 454-455, pp. 161-177.
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© 2018 Imbalanced datasets are commonly encountered in real-world classification problems. Many machine learning algorithms are originally designed for well-balanced datasets, therefore re-sampling has become an important step to pre-process imbalanced data. This aims to balance the datasets by increasing the samples of the smaller class or decreasing the samples of the larger class, which are known as over-sampling and under-sampling, respectively. In this paper, a sampling strategy that is based on both over-sampling and under-sampling is proposed, in which the new samples of the smaller class are created based on fuzzy logic. Improvement of the datasets is done by the evolutionary computational method of Cross-generational elitist selection, Heterogeneous recombination and Cataclysmic mutation (CHC) that under-samples both the minority and majority samples. Consequently, a hybrid preprocessing method is proposed to re-sample imbalanced datasets. The evaluation is done by applying the Support Vector Machine (SVM), C4.5 decision tree and nearest neighbor rule to train a classification model from the re-sampled training sets. From the experimental results, it can be seen that our proposed method improves both the F−measure and AUC. The over-sampling rate and complexity of the classification model are also compared. Our proposed method is found to be superior to all other methods under comparison and it is more robust in different classifiers.

Wong, S-W, Zheng, B-L, Lin, J-Y, Zhang, Z-C, Yang, Y, Zhu, L & He, Y 2018, 'Design of Three-State Diplexer Using a Planar Triple-Mode Resonator', IEEE Transactions on Microwave Theory and Techniques, vol. 66, no. 9, pp. 4040-4046.
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© 1963-2012 IEEE. A highly integrated three-state diplexer (TSD) on a single planar elliptical structure is for the first time presented in this paper. Three resonant modes are investigated in a planar elliptical resonator, e.g., two TM11 degenerate modes and one TM21 mode. These three resonant modes are designed to form three filtering channels, which are further combined to generate three states of a diplexer, namely, TSD. The planar elliptical triple-mode resonator is fed by three microstrip lines to form a triple-mode TSD. In order to validate the concept, the designed planar TSD is fabricated and measured. The measured results are in good agreement with the simulated ones.

Woo, YC, Kim, Y, Yao, M, Tijing, LD, Choi, J-S, Lee, S, Kim, S-H & Shon, HK 2018, 'Hierarchical Composite Membranes with Robust Omniphobic Surface Using Layer-By-Layer Assembly Technique', Environmental Science & Technology, vol. 52, no. 4, pp. 2186-2196.
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© 2018 American Chemical Society. In this study, composite membranes were fabricated via layer-by-layer (LBL) assembly of negatively charged silica aerogel (SiA) and 1H,1H,2H,2H-perfluorodecyltriethoxysilane (FTCS) on a polyvinylidene fluoride phase inversion membrane and interconnecting them with positively charged poly(diallyldimethylammonium chloride) (PDDA) via electrostatic interaction. The results showed that the PDDA-SiA-FTCS coated membrane had significantly enhanced the membrane structure and properties. New trifluoromethyl and tetrafluoroethylene bonds appeared at the surface of the coated membrane, which led to lower surface free energy of the composite membrane. Additionally, the LBL membrane showed increased surface roughness. The improved structure and property gave the LBL membrane an omniphobic property, as indicated by its good wetting resistance. The membrane performed a stable air gap membrane distillation (AGMD) flux of 11.22 L/m2 h with very high salt rejection using reverse osmosis brine from coal seam gas produced water as feed with the addition of up to 0.5 mM SDS solution. This performance was much better compared to those of the neat membrane. The present study suggests that the enhanced membrane properties with good omniphobicity via LBL assembly make the porous membranes suitable for long-term AGMD operation with stable permeation flux when treating challenging saline wastewater containing low surface tension organic contaminants.

Wu, B, Wu, D, Gao, W & Song, C 2018, 'Time-variant random interval natural frequency analysis of structures', Journal of Sound and Vibration, vol. 414, pp. 284-298.
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© 2017 Elsevier Ltd This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

Wu, D, Gao, W, Hui, D, Gao, K & Li, K 2018, 'Stochastic static analysis of Euler-Bernoulli type functionally graded structures', Composites Part B: Engineering, vol. 134, pp. 69-80.
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In this study, the uncertain static analysis of Euler-Bernoulli type functionally graded structures with probabilistic parameters is investigated. An effective, yet efficient, computational method is proposed within the framework of the finite element analysis (FEA). Various uncertain systematic parameters, which are including the material properties, dimensions of structural elements, as well as applied forces, can be simultaneously incorporated within the unified analysis framework. By meticulously combining the matrix perturbation theory with Tayler's series expansion, both first and second order statistical characteristics (i.e., mean and variances) of the concerned structural responses can be robustly estimated for practically motivated functionally graded structures. In order to illustrate the applicability, accuracy, as well as efficiency of the proposed computational approach, three distinctive functionally graded engineering structures are thoroughly investigated by comparing the performance of the proposed approach with the simulation based reference method. Furthermore, complementary parametric investigations are also conducted to explore the sensitivity of the Euler-Bernoulli type functionally graded structures against various degrees of uncertainty of each considered uncertain system parameter.

Wu, D, King, J-T, Chuang, C-H, Lin, C-T & Jung, T-P 2018, 'Spatial Filtering for EEG-Based Regression Problems in Brain–Computer Interface (BCI)', IEEE Transactions on Fuzzy Systems, vol. 26, no. 2, pp. 771-781.
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© 1993-2012 IEEE. Electroencephalogram (EEG) signals are frequently used in brain-computer interfaces (BCIs), but they are easily contaminated by artifacts and noise, so preprocessing must be done before they are fed into a machine learning algorithm for classification or regression. Spatial filters have been widely used to increase the signal-to-noise ratio of EEG for BCI classification problems, but their applications in BCI regression problems have been very limited. This paper proposes two common spatial pattern (CSP) filters for EEG-based regression problems in BCI, which are extended from the CSP filter for classification, by using fuzzy sets. Experimental results on EEG-based response speed estimation from a large-scale study, which collected 143 sessions of sustained-attention psychomotor vigilance task data from 17 subjects during a 5-month period, demonstrate that the two proposed spatial filters can significantly increase the EEG signal quality. When used in LASSO and k-nearest neighbors regression for user response speed estimation, the spatial filters can reduce the root-mean-square estimation error by 10.02-19.77\%, and at the same time increase the correlation to the true response speed by 19.39-86.47\%.

Wu, D, Liu, A, Huang, Y, Huang, Y, Pi, Y & Gao, W 2018, 'Dynamic analysis of functionally graded porous structures through finite element analysis', Engineering Structures, vol. 165, pp. 287-301.
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A finite element method (FEM) analysis framework is introduced for the free and forced vibration analyses of functionally graded porous (FGP) beam type structures. Within the proposed computational scheme, both Euler-Bernoulli and Timoshenko beam theories have been adopted such that the explicit stiffness and mass matrices for 2-D FGP beam element through both beam theories are explicitly expressed. Both Young's modulus and material density of the FGP beam element are simultaneously considered as grading through the thickness of the beam. The material constitutive law of a FGP beam is governed by the typical open-cell metal foam. Furthermore, the damping effects of the FGP structures can be also incorporated within the proposed FEM analysis framework through the Rayleigh damping model. Consequently, the proposed approach establishes a more unified analysis framework which can investigate simple FGP beams as well as complex FGP structural systems involving mixture of different materials. In order to demonstrate the applicability, accuracy, as well as the efficiency of the proposed computational scheme, both FGP beams and frame structures with multiple porosities have been rigorously explored.

Wu, D, Liu, A, Huang, Y, Huang, Y, Pi, Y & Gao, W 2018, 'Mathematical programming approach for uncertain linear elastic analysis of functionally graded porous structures with interval parameters', Composites Part B: Engineering, vol. 152, pp. 282-291.
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© 2018 Elsevier Ltd This paper investigates the non-deterministic linear elastic problem of bar-type functionally graded porous (FGP) structures with uncertain-but-bounded system parameters. For achieving a robust uncertainty analysis framework, a non-stochastic structural analysis for FGP engineering structures, whose system inputs possess interval uncertainties, through the framework of Finite Element Method (FEM) is proposed. The Timoshenko beam theory is adopted to incorporate the shear effect, so a more generalized uncertain static analysis of FGP structures can be anticipated. Various uncertain system input parameters, for example, the Young's moduli, the dimensions of the cross-sections, the porosities, as well as the applied loads can be simultaneously incorporated within the proposed method. To demonstrate the capability of the proposed approach, two distinctive numerical examples have been thoroughly investigated. Additional numerical experiments have also been conducted to further explore various effects of uncertainties of different system inputs acting on the overall FGP structural responses.

Wu, H, Fan, J, Zhang, J, Ngo, HH & Guo, W 2018, 'Large-scale multi-stage constructed wetlands for secondary effluents treatment in northern China: Carbon dynamics', Environmental Pollution, vol. 233, pp. 933-942.
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Multi-stage constructed wetlands (CWs) have been proved to be a cost-effective alternative in the treatment of various wastewaters for improving the treatment performance as compared with the conventional single-stage CWs. However, few long-term full-scale multi-stage CWs have been performed and evaluated for polishing effluents from domestic wastewater treatment plants (WWTP). This study investigated the seasonal and spatial dynamics of carbon and the effects of the key factors (input loading and temperature) in the large-scale seven-stage Wu River CW polishing domestic WWTP effluents in northern China. The results indicated a significant improvement in water quality. Significant seasonal and spatial variations of organics removal were observed in the Wu River CW with a higher COD removal efficiency of 64-66% in summer and fall. Obvious seasonal and spatial variations of CH4 and CO2 emissions were also found with the average CH4 and CO2 emission rates of 3.78-35.54 mg m-2 d-1 and 610.78-8992.71 mg m-2 d-1, respectively, while the higher CH4 and CO2 emission flux was obtained in spring and summer. Seasonal air temperatures and inflow COD loading rates significantly affected organics removal and CH4 emission, but they appeared to have a weak influence on CO2 emission. Overall, this study suggested that large-scale Wu River CW might be a potential source of GHG, but considering the sustainability of the multi-stage CW, the inflow COD loading rate of 1.8-2.0 g m-2 d-1 and temperature of 15-20 °C may be the suitable condition for achieving the higher organics removal efficiency and lower greenhouse gases (GHG) emission in polishing the domestic WWTP effluent. The obtained knowledge of the carbon dynamics in large-scale Wu River CW will be helpful for understanding the carbon cycles, but also can provide useful field experience for the design, operation and management of multi-stage CW treatments.

Wu, H, Zhang, J, Guo, W, Liang, S & Fan, J 2018, 'Secondary effluent purification by a large-scale multi-stage surface-flow constructed wetland: A case study in northern China', Bioresource Technology, vol. 249, pp. 1092-1096.
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Assessment of treatment performance in the large-scale constructed wetland (CW) for secondary effluent purification remains limited. The aim of this case study was to therefore to investigate the long-term treatment capacity of organics and ammonium pollutants in a large-scale multi-stage surface-flow (SF) CW fed with secondary effluents from the wastewater treatment plants (WWTPs) in northern China. The results for two-and-half-year study period indicated that the water quality parameters including chemical oxygen demand (COD) and ammonium (NH4+-N) met the Chinese Grade III of Environmental Quality Standards. The mass reductions of COD and NH4+-N were 53% (4032 kg ha-1 y-1) and 72% (511 kg ha-1 y-1), respectively. However, there was a significant positive correlation between influent loads and treatment performance. The optimal loading of 2.5 g m-2 d-1 for COD and 0.3 g m-2 d-1 for NH4+-N could be recommended for designing the sustainable large-scale multi-stage SF CW wastewater treatments.

Wu, J, Luo, Z, Zhang, N & Gao, W 2018, 'A new sequential sampling method for constructing the high-order polynomial surrogate models', Engineering Computations, vol. 35, no. 2, pp. 529-564.
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PurposeThis paper aims to study the sampling methods (or design of experiments) which have a large influence on the performance of the surrogate model. To improve the adaptability of modelling, a new sequential sampling method termed as sequential Chebyshev sampling method (SCSM) is proposed in this study.Design/methodology/approachThe high-order polynomials are used to construct the global surrogated model, which retains the advantages of the traditional low-order polynomial models while overcoming their disadvantage in accuracy. First, the zeros of Chebyshev polynomials with the highest allowable order will be used as sampling candidates to improve the stability and accuracy of the high-order polynomial model. In the second step, some initial sampling points will be selected from the candidates by using a coordinate alternation algorithm, which keeps the initial sampling set uniformly distributed. Third, a fast sequential sampling scheme based on the space-filling principle is developed to collect more samples from the candidates, and the order of polynomial model is also updated in this procedure. The final surrogate model will be determined as the polynomial that has the largest adjusted R-square after the sequential sampling is terminated.FindingsThe SCSM has better performance in efficiency, accuracy and stability compared with several popular sequential sampling methods, e.g. LOLA-Voronoi algorithm and global Monte Carlo method from the SED toolbox, and the Halton sequence.Originality/valueThe SCSM has good performance in building the high-order surrogate model, inclu...

Wu, J, Pan, S, Zhou, C, Li, G, He, W & Zhang, C 2018, 'Advances in Processing, Mining, and Learning Complex Data: From Foundations to Real‐World Applications', Complexity, vol. 2018, no. 1, pp. 1-3.
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Wu, J, Pan, S, Zhu, X, Zhang, C & Wu, X 2018, 'Multi-Instance Learning with Discriminative Bag Mapping', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 6, pp. 1065-1080.
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© 1989-2012 IEEE. Multi-instance learning (MIL) is a useful tool for tackling labeling ambiguity in learning because it allows a bag of instances to share one label. Bag mapping transforms a bag into a single instance in a new space via instance selection and has drawn significant attention recently. To date, most existing work is based on the original space, using all instances inside each bag for bag mapping, and the selected instances are not directly tied to an MIL objective. As a result, it is difficult to guarantee the distinguishing capacity of the selected instances in the new bag mapping space. In this paper, we propose a discriminative mapping approach for multi-instance learning (MILDM) that aims to identify the best instances to directly distinguish bags in the new mapping space. Accordingly, each instance bag can be mapped using the selected instances to a new feature space, and hence any generic learning algorithm, such as an instance-based learning algorithm, can be used to derive learning models for multi-instance classification. Experiments and comparisons on eight different types of real-world learning tasks (including 14 data sets) demonstrate that MILDM outperforms the state-of-The-Art bag mapping multi-instance learning approaches. Results also confirm that MILDM achieves balanced performance between runtime efficiency and classification effectiveness.

Wu, K, Ni, W, Su, T, Liu, RP & Guo, YJ 2018, 'Fast and Accurate Estimation of Angle-of-Arrival for Satellite-Borne Wideband Communication System', IEEE Journal on Selected Areas in Communications, vol. 36, no. 2, pp. 314-326.
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© 1983-2012 IEEE. Accurate estimation of angle-of-arrival (AoA) is critical to wideband satellite communications, but is susceptible to receive noises and can be ambiguous due to space/cost-effective hybrid antenna array designs with localized analog phased subarrays. As a matter of fact, there has yet to be an unambiguous estimator even for narrow-band systems. This paper proposes a new design of subarray-specific time-varying phase shifts, which enables unambiguous and noise-tolerant estimation of AoA in localized hybrid arrays. Particularly, the new phase shifts deliver deterministic phase changes in the cross-correlations of receive signals between subarrays, and enable the cross-correlations to be coherently accumulated across subarrays and sub-carriers to eliminate ambiguities and tolerate noises. Another important contribution of the paper is that we optimize the frequency interval for coherent accumulation across sub-carriers, leveraging between estimation errors, and accumulation gains. Evident from simulations, our approach is able to dramatically improve the estimation accuracy by orders of magnitudes with significantly reduced requirements of complexities and training symbols, as compared with the state of the art. The approach is robust against noises, with estimation errors asymptotically achieving a rigorously developed lower bound.

Wu, K, Ni, W, Su, T, Liu, RP & Guo, YJ 2018, 'Robust Unambiguous Estimation of Angle-of-Arrival in Hybrid Array With Localized Analog Subarrays', IEEE Transactions on Wireless Communications, vol. 17, no. 5, pp. 2987-3002.
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© 2018 IEEE. Hybrid array is able to leverage array gains, transceiver sizes, and costs for massive multiple-input-multiple-output systems in millimeter-wave frequencies. Challenges arise from the estimation of angle-of-arrival (AoA) in localized hybrid arrays, due to the array structure and the resultant estimation ambiguities and susceptibility to noises. This paper eliminates the ambiguities and enhances the tolerance to the noises based on our new discoveries. Particularly, by designing new subarray-specific time-varying phase shifts, we discover that the cross-correlations between the gains of consecutive subarrays have consistent signs except the strongest. This enables the cross-correlations to be deterministically calibrated and constructively combined for the noise-tolerant estimation of the propagation phase offset between adjacent subarrays. Given the phase offset, the AoA can be estimated unambiguously with few training symbols. We also derive a closed-form lower bound for the mean square error of AoA estimation. Corroborated by simulations, our approach is able to dramatically improve estimation accuracy by orders of magnitude while reducing complexity and training symbols, as compared to the state of the art. With the ambiguities eliminated, the estimation errors of our method asymptotically approach the lower bound, as training symbols increase.

Wu, L, Xu, M, Zhu, G, Wang, J & Rao, T 2018, 'Appearance features in Encoding Color Space for visual surveillance', Neurocomputing, vol. 308, pp. 21-30.
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© 2018 Elsevier B.V. Person re-identification and visual tracking are two important tasks in video surveillance. Many works have been done on appearance modeling for these two tasks. However, existing feature descriptors are mainly constructed on three-channel color spaces, such like RGB, HSV and XYZ. These color spaces somehow enable meaningful representation for color, yet may lack distinctiveness for real-world tasks. In this paper, we propose a multi-channel Encoding Color Space (ECS), and consider the color distinction with the design of image feature descriptor. In order to overcome the illumination variation and shape deformation, we design features on the basis of the Encoding Color Space and Histogram of Oriented Gradient (HOG), which enables rich color-gradient characteristics. Additionally, we extract Second Order Histogram (SOH) on the descriptor constructed to capture abstract information with layout constrains. Exhaustive experiments are performed on datasets VIPeR, CAVIAR, CUHK01 and Visual Tracking Benchmark. Experimental results on these datasets show that our feature descriptors could achieve promising performance.

Wu, W, Li, B, Chen, L, Zhu, X & Zhang, C 2018, '$K$ -Ary Tree Hashing for Fast Graph Classification', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 5, pp. 936-949.
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IEEE Existing graph classification usually relies on an exhaustive enumeration of substructure patterns, where the number of substructures expands exponentially w.r.t. with the size of the graph set. Recently, the Weisfeiler-Lehman (WL) graph kernel has achieved the best performance in terms of both accuracy and efficiency among state-of-the-art methods. However, it is still time-consuming, especially for large-scale graph classification tasks. In this paper, we present a < formula > < tex > $k$ < /tex > < /formula > -Ary Tree based Hashing (KATH) algorithm, which is able to obtain competitive accuracy with a very fast runtime. The main idea of KATH is to construct a traversal table to quickly approximate the subtree patterns in WL using < formula > < tex > $k$ < /tex > < /formula > -ary trees. Based on the traversal table, KATH employs a recursive indexing process that performs only < formula > < tex > $r$ < /tex > < /formula > times of matrix indexing to generate all < formula > < tex > $(r-1)$ < /tex > < /formula > -depth < formula > < tex > $k$ < /tex > < /formula > -ary trees, where the leaf node labels of a tree can uniquely specify the pattern. After that, the MinHash scheme is used to fingerprint the acquired subtree patterns for a graph. Our experimental results on both real world and synthetic datasets show that KATH runs significantly faster than state-of-the-art methods while achieving competitive or better accuracy.

Wu, W-H, Thomas, P, Hume, P & Jin, J 2018, 'Effective Conversion of Amide to Carboxylic Acid on Polymers of Intrinsic Microporosity (PIM-1) with Nitrous Acid', Membranes, vol. 8, no. 2, pp. 20-20.
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Carboxylate-functionalised polymers of intrinsic microporosity (C-PIMs) are highly desirable materials for membrane separation applications. The recently reported method to afford C-PIMs was via an extensive base hydrolysis process requiring 360 h. Herein, a novel and effective method to convert PIM-CONH2 to C-PIM using nitrous acid was studied. The chemical structure of C-PIM was characterised by 1H NMR, 13C NMR, FTIR, elemental analysis, UV-Vis, TGA and TGA-MS. Complete conversion from amide to carboxylic acid groups was confirmed. Decarboxylation of C-PIM was also successfully studied by TGA-MS for the first time, with a loss of m/z 44 amu (CO2) observed at the first degradation stage. TGA also revealed decreased thermal stability of C-PIM relative to PIM-CONH2 under both N2 and air atmosphere. Gel permeation chromatography (GPC) analysis showed continuous molecular weight degradation of C-PIM with extended reaction time. Aromatic nitration was also observed as a side reaction in some cases.

Wu, Y, Fang, J, He, Y & Li, W 2018, 'Crashworthiness of hierarchical circular-joint quadrangular honeycombs', Thin-Walled Structures, vol. 133, pp. 180-191.
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© 2018 Elsevier Ltd The new hierarchical circular-joint quadrangular honeycomb is proposed by iteratively replacing the edge-junctions of regular honeycomb with a circular joint. Firstly, the nonlinear finite element analysis is performed through LS-DYNA and the results are validated by experimental data. Then, analytical solutions to crushing resistance of the hierarchical honeycomb are obtained based on the Simplified Super Folding Element (SSFE) theory. The results between the numerical and analytical method are in good agreement, which indicates that the analytical solutions are reliable. Furthermore, parametric studies of the first and second hierarchical order structures are conducted numerically. The results show that the specific energy absorption of the first and second-order hierarchical honeycomb is improved by up to 81.8%, 115.3% respectively compared with the regular honeycomb. It is also found that the out-of-plane crashworthiness performance of the second-order hierarchical honeycomb can be enhanced by increasing relative density. However, the peak crushing force would also increase with the increase in relative density. The findings of this study show that the proposed hierarchical honeycomb is a structural configuration with high energy absorption capacity.

Wu, Y, Li, S, Liu, J, Liu, X, Ruan, W, Lu, J, Liu, Y, Lawson, T, Shimoni, O, Lovejoy, DB, Walker, AK, Cong, Y & Shi, B 2018, 'Stilbenes from Veratrum maackii Regel Protect against Ethanol-Induced DNA Damage in Mouse Cerebellum and Cerebral Cortex', ACS Chemical Neuroscience, vol. 9, no. 7, pp. 1616-1624.
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© Copyright 2018 American Chemical Society. Ethanol is a principle ingredient of alcoholic beverages with potential neurotoxicity and genotoxicity, and the ethanol-associated oxidative DNA damage in the central nervous system is well documented. Natural source compounds may offer new options to protect the brain against ethanol-induced genotoxicity. Veratrum maackii Regel is a toxic rangeland plant linked to teratogenicity which is also used in traditional Chinese medicine as 'Lilu' and is reported to contain a family of compounds called stilbenes that can have positive biological activity. In this study, nine stilbenes were isolated from the aerial parts of V. maackii Regel, and their structures were identified as cis-mulberroside A (1), resveratrol-4,3′-O-β-d-diglucopyranoside (2), mulberroside A (3), gentifolin K (4), resveratrol-3,5-O-β-d-diglucopyranoside (5), oxyresveratrol- 4′-O-β-d-glucopyranoside (6), oxyresveratrol-3-O-β-d-glucopyranoside (7), oxyresveratrol (8), and resveratrol (9) using ESI-MS and NMR techniques. The total concentration of extracted compounds 2-9 was 2.04 mg/g, suggesting that V. maackii Regel is a novel viable source of these compounds. In an in vivo comet assay, compounds 1-9 were observed to decrease DNA damage in mouse cerebellum and cerebral cortex caused by acute ethanol administration. Histological observation also revealed decreased brain injury in mice administered with compounds 1-9 after acute ethanol administration. The protective effects of compound 6 were associated with increasing T-SOD and GSH-PX activities and a decrease in NO and MDA concentrations. These findings suggest that these compounds are potent inhibitors of ethanol-induced brain injury possibly via the inhibition of oxidative stress and may be valuable leads for future therapeutic development.

Wu, Y, Li, W, Fang, J & Lan, Q 2018, 'Multi-objective robust design optimization of fatigue life for a welded box girder', Engineering Optimization, vol. 50, no. 8, pp. 1252-1269.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group. To reduce the scatter of fatigue life for welded structures, a robust optimization method is presented in this study based on a dual surrogate modelling and multi-objective particle swam optimization algorithm. Considering the perturbations of material parameters and environment variables, the mean and standard deviation of fatigue life are fitted using dual surrogate modelling and selected as the objective function to be minimized. As an example, a welded box girder is presented to reduce the standard deviation of fatigue life. A set of non-dominated solutions is produced through a multi-objective particle swam optimization algorithm. A cognitive approach is used to select the optimum solution from the Pareto sets. As a comparative study, traditional single objective optimizations are also presented in this study. The results reduced the standard deviation of the fatigue life by about 16.5%, which indicated that the procedure improved the robustness of the fatigue life.

Wu, Z, Li, G, Liu, Q, Xu, G & Chen, E 2018, 'Covering the Sensitive Subjects to Protect Personal Privacy in Personalized Recommendation', IEEE Transactions on Services Computing, vol. 11, no. 3, pp. 493-506.
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Wu, Z, Xu, G, Lu, C, Chen, E, Jiang, F & Li, G 2018, 'An effective approach for the protection of privacy text data in the CloudDB', World Wide Web, vol. 21, no. 4, pp. 915-938.
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© 2017 Springer Science+Business Media, LLC Due to the advantages of pay-on-demand, expand-on-demand and high availability, cloud databases (CloudDB) have been widely used in information systems. However, since a CloudDB is distributed on an untrusted cloud side, it is an important problem how to effectively protect massive private information in the CloudDB. Although traditional security strategies (such as identity authentication and access control) can prevent illegal users from accessing unauthorized data, they cannot prevent internal users at the cloud side from accessing and exposing personal privacy information. In this paper, we propose a client-based approach to protect personal privacy in a CloudDB. In the approach, privacy data before being stored into the cloud side, would be encrypted using a traditional encryption algorithm, so as to ensure the security of privacy data. To execute various kinds of query operations over the encrypted data efficiently, the encrypted data would be also augmented with additional feature index, so that as much of each query operation as possible can be processed on the cloud side without the need to decrypt the data. To this end, we explore how the feature index of privacy data is constructed, and how a query operation over privacy data is transformed into a new query operation over the index data so that it can be executed on the cloud side correctly. The effectiveness of the approach is demonstrated by theoretical analysis and experimental evaluation. The results show that the approach has good performance in terms of security, usability and efficiency, thus effective to protect personal privacy in the CloudDB.

Wu, Z, Zheng, C, Xiejian, J, Zhou, Z, Xu, G & Chen, E 2018, 'An approach for the protection of users’ book browsing preference privacy in a digital library', The Electronic Library, vol. 36, no. 6, pp. 1154-1166.
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PurposeThe problem of privacy protection in digital libraries is causing people to have increasingly extensive concerns. This study aims to design an approach to protect the preference privacy behind users’ book browsing behaviors in a digital library.Design/methodology/approachThis paper proposes a client-based approach, whose basic idea is to construct a group of plausible book browsing dummy behaviors, and submit them together with users’ true behaviors to the untrusted server, to cover up users’ sensitive preferences.FindingsBoth security analysis and evaluation experiment demonstrate the effectiveness of the approach, which can ensure the privacy security of users’ book browsing preferences on the untrusted digital library server, without compromising the usability, accuracy and efficiency of book services.Originality/valueTo the best of the authors’ knowledge, this paper provides the first attempt to the protection of users’ behavior privacy in digital libraries, which will have a positive influence on the development of privacy-preserving libraries in the new network era.

Xia, H, Zhuge, R, Li, H, Song, S, Jiang, F & Xu, M 2018, 'Single Image Rain Removal via a Simplified Residual Dense Network', IEEE Access, vol. 6, pp. 66522-66535.
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© 2013 IEEE. The single-image rain removal problem has attracted tremendous interests within the deep learning domains. Although deep learning based de-raining methods outperform many conventional methods, there are still unresolved issues in regards to improving the performance. In this paper, we propose a simplified residual dense network (SRDN) to improve the de-raining performance and cut down the computation time. Inspired by the image processing domain knowledge that a rainy image can be decomposed into a base (low-pass) layer and a detail (high-pass) layer, we train our network by directly learning the residual between the detail layer of rainy images and the detail layer of clean images. It can both significantly reduce the mapping range from input to output and easily employ the image enhancement operation to handle the heavy rain with hazy looks. Instead of designing a deeper network structure to increase the learning ability of network, we propose a simplified dense block to explore more effective information between layers and, hence, reduce the computation time of network. Experiments on both synthetic and real-world images demonstrate that our SRDN network can achieve competitive results in comparison with the benchmarked and conventional approaches for single-image rain removal.

Xiang, T, Li, Y, Li, X, Zhong, S & Yu, S 2018, 'Collaborative ensemble learning under differential privacy', Web Intelligence, vol. 16, no. 1, pp. 73-87.
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Ensemble learning plays an important role in big data analysis. A great limitation is that multiple parties cannot share their knowledge extracted from ensemble learning model with privacy guarantee, therefore it is a great demand to develop privacy-preserving collaborative ensemble learning. This paper proposes a privacy-preserving collaborative ensemble learning framework under differential privacy. In the framework, multiple parties can independently build their local ensemble models with personalized privacy budgets, and collaboratively share their knowledge to obtain a stronger classifier with the help of central agent in a privacy-preserving way. Under this framework, this paper presents the differentially private versions of two widely-used ensemble learning algorithms: collaborative random forests under differential privacy (CRFsDP) and collaborative adaptive boosting under differential privacy (CAdaBoostDP). Theoretical analysis and extensive experimental results show that our proposed framework achieves a good balance between privacy and utility in an efficient way.

Xiang, Y, Natgunanathan, I, Peng, D, Hua, G & Liu, B 2018, 'Spread Spectrum Audio Watermarking Using Multiple Orthogonal PN Sequences and Variable Embedding Strengths and Polarities', IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 26, no. 3, pp. 529-539.
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Xiao, F, Wang, Z, Ye, N, Wang, R & Li, X-Y 2018, 'One More Tag Enables Fine-Grained RFID Localization and Tracking', IEEE/ACM Transactions on Networking, vol. 26, no. 1, pp. 161-174.
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Xiao, L, Zhang, Y, Zhang, J, Wang, Q & Li, Y 2018, 'Combining HWEBING and HOG‐MLBP features for pedestrian detection', The Journal of Engineering, vol. 2018, no. 16, pp. 1421-1426.
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Pedestrian detection has vital value in many areas such as driver assistance systems, driverless cars, intelligent tourism systems etc., but there are some difficulties that need to be solved. The algorithm with high detection rate is complex and requires substantial time. Therefore, how to improve the detection accuracy and speed has become the key of pedestrian detection. For these reasons, firstly, an improved algorithm, called hash and window enhancement of binarised normed gradients (HWEBING), based on binarised normed gradients feature is proposed. Subsequently, the authors present an improved local texture feature, namely mean of local binary pattern (MLBP), based on uniform pattern local binary pattern (ULBP) for increasing the detection rate. Finally, after using the HWEBING algorithm to get the candidate windows, the combination of MLBP feature and histograms of oriented gradients feature is extracted from these windows to further enhance the detection accuracy. Experimental results reveal that speed of using the HWEBING algorithm for pre‐detection is 5.5 times faster than the traditional method of pedestrian detection. Furthermore, the detection rate of MLBP feature is 3.5 and 2.1% higher than those of ULBP and basic pattern local binary pattern (Basic‐LBP), respectively.

Xiao, S, Xie, X, Wen, S, Zeng, Z, Huang, T & Jiang, J 2018, 'GST-memristor-based online learning neural networks', Neurocomputing, vol. 272, pp. 677-682.
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At present, it is an urgent issue to effectively train artificial neural network (ANN), especially when the data is large. Online learning has been used to solve the problem, most of which is based on least mean square (LMS). However, it is inefficient to implement the LMS on conventional digital hardware, because of the physical separation between the memory arrays and arithmetic module. To solve this problem, CMOS has been utilized. However, it costs too many powers and areas while designing CMOS synapses in the very large scale integrated (VLSI) circuit. As a novel device, memristor is believed to overcome this shortcoming as memristors could be utilized to store the weights which could be changed by a voltage pulse. The filamentary bipolar memristive switching in Ge2Sb2Te5 (GST) has been proved to be an ideal choice for memristive materials. And it has two states—amorphous and crystalline, which can be changed by DC sweep. In this paper, we consider an artificial synapse which includes a GST-memristor and two MOSFET transistors (p-type and n-type). A number of artificial synapses are employed to form a circuit which is expected to consume 2−8% of the area compared to CMOS-only circuit. And the accuracy is about 80%, which is good enough in realistic diagnosis and has good robustness with noise.

Xiao, Y, Pei, Q, Liu, X & Yu, S 2018, 'A Novel Trust Evaluation Mechanism for Collaborative Filtering Recommender Systems', IEEE Access, vol. 6, pp. 70298-70312.
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© 2018 IEEE. In online social networks (OSNs), high trust value entities play an important role in service recommendation when users inquire certain service. Generally, users in OSNs are more willing to choose those services recommended by high trust value entities. In fact, users may suffer from great loss of property once they accept some bad services provided by high trust value entities. However, current schemes do not consider this problem. Hence, we propose a scheme called RHT (recommendation from high trust value entities) to evaluate the trust degree of service recommended by high trust value entities. To be specific, there exist other users who provide their ratings to the service recommended by a high trust value entity, and RHT first selects the trusted ones from those users by computing the similarity between target user and them. Simultaneously, RHT also withstands malicious attacks during the trusted nodes selection. In addition, we also design an adaptive trust computation method to calculate trust value according to the ratings of trusted users. The experimental results show that RHT has higher accuracy in trust evaluation compared with current representative schemes and do effectively resistant four common attacks when choosing trusted nodes.

Xie, H, He, Z & Veitch, D 2018, 'Disturbance observer-based visual servoing for multirotor unmanned aerial vehicles', at - Automatisierungstechnik, vol. 66, no. 3, pp. 258-267.
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Abstract This paper presents a disturbance observer based input saturated visual servoing law for a quadrotor unmanned aerial vehicle (UAV). The controller regulates the 4D relative pose, i. e., 3D translational and yaw motion, between the vehicle and a planar horizontal visual target in an environment with external disturbances. A feedforward control is used to compensate the lumped disturbance consisting of both system uncertainties and external disturbances. The feedback control part is based on a nested saturation control, which is used to bound the orientation of the UAV and therefore helps to keep the visual target in the camera’s field of view. Simulation results are provided to demonstrate controller performance.

Xie, K, Fu, Q, Webley, PA & Qiao, GG 2018, 'MOF Scaffold for a High‐Performance Mixed‐Matrix Membrane', Angewandte Chemie International Edition, vol. 57, no. 28, pp. 8597-8602.
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AbstractA novel composite membrane consisting of an interconnected MOF scaffold coated with cross‐linked poly(ethylene glycol) (PEG) has been developed. As a result of its unique structure, the membrane shows an exceptional 18‐fold permeability enhancement as compared to pristine PEG membranes, without compromising the selectivity. This performance is unattainable with current mixed‐matrix membranes (MMMs). Our optimized membrane has a permeability of 2700 Barrer with a CO2/N2 selectivity of 35, which surpasses the latest Robeson upper bound.

Xie, K, Fu, Q, Webley, PA & Qiao, GG 2018, 'MOF Scaffold for a High‐Performance Mixed‐Matrix Membrane', Angewandte Chemie, vol. 130, no. 28, pp. 8733-8738.
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AbstractA novel composite membrane consisting of an interconnected MOF scaffold coated with cross‐linked poly(ethylene glycol) (PEG) has been developed. As a result of its unique structure, the membrane shows an exceptional 18‐fold permeability enhancement as compared to pristine PEG membranes, without compromising the selectivity. This performance is unattainable with current mixed‐matrix membranes (MMMs). Our optimized membrane has a permeability of 2700 Barrer with a CO2/N2 selectivity of 35, which surpasses the latest Robeson upper bound.

Xie, K, Fu, Q, Xu, C, Lu, H, Zhao, Q, Curtain, R, Gu, D, Webley, PA & Qiao, GG 2018, 'Continuous assembly of a polymer on a metal–organic framework (CAP on MOF): a 30 nm thick polymeric gas separation membrane', Energy & Environmental Science, vol. 11, no. 3, pp. 544-550.
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A 30 nm thick polymeric membrane on a metal–organic framework substrate was fabricated via a bottom-up approach, exhibiting excellent CO₂/N₂ separation performance.

Xie, M, Luo, W, Guo, H, Nghiem, LD, Tang, CY & Gray, SR 2018, 'Trace organic contaminant rejection by aquaporin forward osmosis membrane: Transport mechanisms and membrane stability', Water Research, vol. 132, pp. 90-98.
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We investigated transport mechanisms of trace organic contaminants (TrOCs) through aquaporin thin-film composite forward osmosis (FO) membrane, and membrane stability under extreme conditions with respect to TrOC rejections. Morphology and surface chemistry of the aquaporin membrane were characterised to identify the incorporation of aquaporin vesicles into membrane active layer. Pore hindrance model was used to estimate aquaporin membrane pore size as well as to describe TrOC transport. TrOC transport mechanisms were revealed by varying concentration and type of draw solutions. Experimental results showed that mechanism of TrOC transport through aquaporin-embedded FO membrane was dominated by solution-diffusion mechanism. Non-ionic TrOC rejections were molecular-weight dependent, suggesting steric hindrance mechanisms. On the other hand, ionic TrOC rejections were less sensitive to molecular size, indicating electrostatic interaction. TrOC transport through aquaporin membrane was also subjected to retarded forward diffusion where reverse draw solute flux could hinder the forward diffusion of feed TrOC solutes, reducing their permeation through the FO membrane. Aquaporin membrane stability was demonstrated by either heat treatment or ethanol solvent challenges. Thermal stability of the aquaporin membrane was manifested as a relatively unchanged TrOC rejection before and after the heat treatment challenge test. By contrast, ethanol solvent challenge resulted in a decrease in TrOC rejection, which was evident by the disappearance of the lipid tail of the aquaporin vesicles from infrared spectrum and a notable decrease in the membrane pore size.

Xie, S, Higgins, MJ, Bustamante, H, Galway, B & Nghiem, LD 2018, 'Current status and perspectives on anaerobic co-digestion and associated downstream processes', Environmental Science: Water Research & Technology, vol. 4, no. 11, pp. 1759-1770.
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Anaerobic co-digestion (AcoD) has the potential to utilise spare digestion capacity at existing wastewater treatment plants to simultaneously enhance biogas production by digesting organic rich industrial waste and achieve sustainable organic waste management.

Xie, X, Wen, S, Zeng, Z & Huang, T 2018, 'Memristor-based circuit implementation of pulse-coupled neural network with dynamical threshold generators', Neurocomputing, vol. 284, pp. 10-16.
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Pulse-coupled neural network (PCNN) is inspired from the visual cortex of cats. It is superior to the traditional algorithm in the field of digital image processing. Meanwhile, memristor is considered as an important circuit element to implement brain intelligence hardware. In order to realize the memristor-based circuit of PCNN, a threshold generator is designed to dynamically update the memristance under input excitation with the exponential memristor model. Furthermore, the whole circuit of non-simplified pulse-coupled neural network is realized via memristor. Finally, the image processing function is demonstrated by the proposed circuit via simulation.

Xiong, F, Wang, X, Pan, S, Yang, H, Wang, H & Zhang, C 2018, 'Social Recommendation With Evolutionary Opinion Dynamics', IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, no. 10, pp. 1-13.
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IEEE When users in online social networks make a decision, they are often affected by their neighbors. Social recommendation models utilize social information to reveal the impact of neighbors on user preferences, and this impact is often described by the linear superposition of neighbor preferences or by global trust propagation. Further exploration needs to be undertaken to determine whether the influence pattern of other users from online interaction behaviors is adequately described. In this paper, we introduce evolutionary opinion dynamics from the field of statistical physics into recommender systems, characterizing the impact of other users. We propose an opinion dynamic model by evolutionary game theory. To describe online user interactions, we define the strategies during an interaction between two users, and present the payoff for each strategy in terms of errors of estimated ratings. Therefore, user behaviors are associated with their preferences and ratings. In addition, we measure user influence according to their topological roles in the social network. We incorporate evolutionary opinion dynamics and user influence into the recommendation framework for the prediction of unknown ratings. Experiment results on two real-world datasets demonstrate that our method outperforms state-of the-art models in terms of accuracy, and it also performs well for cold-start users. Our method reduces the divergence of user preferences, in accordance with online opinion interactions. Furthermore, our method has approximate computational complexity with matrix factorization, and results in less computation than state-of-the-art models. Our method is quite general, and indicates that studies in social physics, statistics, and other research fields may be involved in recommendation to improve the performance.

Xu, B, Ahmed, MB, Zhou, JL, Altaee, A, Xu, G & Wu, M 2018, 'Graphitic carbon nitride based nanocomposites for the photocatalysis of organic contaminants under visible irradiation: Progress, limitations and future directions', Science of The Total Environment, vol. 633, pp. 546-559.
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© 2018 Elsevier B.V. Graphitic carbon nitride (g-C3N4) has drawn great attention recently because of its visible light response, suitable energy band gap, good redox ability, and metal-free nature. g-C3N4 can absorb visible light directly, therefore has better photocatalytic ability under solar irradiation and is more energy-efficient than TiO2. However, pure g-C3N4 still has the drawbacks of insufficient light absorption, small surface area and fast recombination of photogenerated electron and hole pairs. This review summarizes the recent progress in the development of g-C3N4 nanocomposites to photodegrade organic contaminants in water. Element doping especially by potassium has been reported to be an efficient method to promote the degradation efficacy. In addition, compound doping improves photodegradation performance of g-C3N4, especially Ag3PO4-g-C3N4 which can completely degrade 10 mg L−1 of methyl orange under visible light irradiation in 5 min, with the rate constant (k) as high as 0.236 min−1. Moreover, co-doping enhances the photodegradation rate of multiple contaminants while immobilization significantly improves catalyst stability. Most of g-C3N4 composites possess high reusability enabling their practical applications in wastewater treatment. Furthermore, environmental conditions such as solution pH, reaction temperature, dissolved oxygen, and dissolved organic matter all have important effects on the photocatalytic ability of g-C3N4 photocatalyst. Future work should focus on the synthesis of innovative g-C3N4 nanocomposites for the efficient removal of organic contaminants in water and wastewater.

Xu, C, Jin, W, Wang, X, Zhao, G & Yu, S 2018, 'MC-VAP: A multi-connection virtual access point for high performance software-defined wireless networks', Journal of Network and Computer Applications, vol. 122, pp. 88-98.
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© 2018 Elsevier Ltd Aiming to exploit the power of multiple accesses from ubiquitous wireless networks, researchers employed multiple virtualized interfaces connecting to multiple APs for mobile users. However, these schemes require expensive modifications and additional cost on mobile device, which are hard to be implemented. Complementarily, in this paper, we propose a multi-connection virtual access point (MC-VAP) to virtualize and manipulate physical APs to provide multi-path transmission for a user while avoiding any modifications on the user side. As a result, the independent flows from an application can be dispatched to multiple paths separately and transmitted on multiple APs simultaneously, which can improve the throughput obviously. In order to maximize each application's throughput, the flow assignment is formulated as a mixed integer non-linear programming (MINLP) problem. In particular, a low-complexity heuristic algorithm, namely, narrowing search set with cutting-off solution space (NS-CoS) algorithm, is presented to solve the MINLP problem through relaxing it into simple LP problems. Moreover, we implement a prototype of MC-VAP, and the extensive real-world experiments demonstrate that MC-VAP can realize seamless handover and provide faster yet efficient solutions of flow assignment in contrast to the optimal method to achieve multifold throughput improvement for applications over regular WiFi.

Xu, D, Tsang, I & Zhang, Y 2018, 'Online Product Quantization', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 11, pp. 1-1.
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© 1989-2012 IEEE. Approximate nearest neighbor (ANN) search has achieved great success in many tasks. However, existing popular methods for ANN search, such as hashing and quantization methods, are designed for static databases only. They cannot handle well the database with data distribution evolving dynamically, due to the high computational effort for retraining the model based on the new database. In this paper, we address the problem by developing an online product quantization (online PQ) model and incrementally updating the quantization codebook that accommodates to the incoming streaming data. Moreover, to further alleviate the issue of large scale computation for the online PQ update, we design two budget constraints for the model to update partial PQ codebook instead of all. We derive a loss bound which guarantees the performance of our online PQ model. Furthermore, we develop an online PQ model over a sliding window with both data insertion and deletion supported, to reflect the real-time behavior of the data. The experiments demonstrate that our online PQ model is both time-efficient and effective for ANN search in dynamic large scale databases compared with baseline methods and the idea of partial PQ codebook update further reduces the update cost.

Xu, J-X, Zhang, XY, Li, H-Y & Yang, Y 2018, 'Narrowband Single-Pole Double-Throw Filtering Switch Based on Dielectric Resonator', IEEE Microwave and Wireless Components Letters, vol. 28, no. 7, pp. 594-596.
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© 2001-2012 IEEE. In this letter, a narrowband single-pole double-throw (SPDT) filtering switch based on dielectric resonators (DRs) is presented. It consists of two DRs shared by two channels for size reduction. Printed circuit boards are embedded in the metal cavity to integrate the PIN diodes. The switching between two channels is enabled by controlling the PIN diodes connected to the two output feeding lines. The electromagnetic field distributions of the DR at the TE -{11\delta } mode are studied to control the coupling between the DR and two output feeding lines. When one channel is on, the PIN diode for this channel is turned off, which does not introduce loss and affect the linearity. For the off-state channel, isolation is obtained by controlling the coupling between the DR and output feeding line, which is considerably enhanced. For demonstration, the DR filtering SPDT switch is implemented. The measured results exhibit that the proposed filtering SPDT switch has narrow bandwidth, low loss, high isolation, and high linearity.

Xu, KD, Li, M, Liu, Y, Yang, Y & Liu, QH 2018, 'Design of Triplexer Using E-Stub-Loaded Composite Right-/Left-Handed Resonators and Quasi-Lumped Impedance Matching Network', IEEE Access, vol. 6, pp. 18814-18821.
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© 2013 IEEE. A compact triplexer based on E-stub-loaded composite right-/left-handed (ESL-CRLH) resonators with quasi-lumped impedance matching network is presented in this paper. The equivalent circuit model of the ESL-CRLH resonator is presented first and its left-/right-handed capacitance/inductance elements are fully derived. Then, a quasi-lumped impedance matching circuit is designed to connect the three ESL-CRLH resonator based filter channels for the triplexer construction. Finally, the designed triplexer obtains high isolations among the ports and low in-band insertion losses of the three filter channels centered at 1.86, 2.41, and 3.25 GHz, of which a miniaturized layout has been realized. Good agreement between the simulated and measured results can be observed to validate the design idea.

Xu, KJ, Liu, MD, Indraratna, B & Horpibulsuk, S 2018, 'Explicit stress–strain equations for modeling frictional materials', Marine Georesources & Geotechnology, vol. 36, no. 6, pp. 722-734.
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Xu, Q, Liu, X, Fu, Y, Li, Y, Wang, D, Wang, Q, Liu, Y, An, H, Zhao, J, Wu, Y, Li, X, Yang, Q & Zeng, G 2018, 'Feasibility of enhancing short-chain fatty acids production from waste activated sludge after free ammonia pretreatment: Role and significance of rhamnolipid', Bioresource Technology, vol. 267, pp. 141-148.
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© 2018 Elsevier Ltd This study reported a new, renewable and high-efficient strategy for anaerobic fermentation, i.e., using free ammonia (FA) to pretreat waste activated sludge (WAS) for 1 d and then combining with rhamnolipid (RL), by which the short-chain fatty acids (SCFA) production was remarkably improved. Experimental results showed the maximal SCFA production of 324.7 ± 13.9 mg COD/g VSS was achieved at 62.6 mg FA/L pretreatment combined with 0.04 g RL/g TSS, which was respectively 5.95-fold, 1.63-fold and 1.41-fold of that from control, FA pretreatment and RL pretreatment. Mechanism investigations revealed that FA + RL enhanced sludge solubilization and hydrolysis, providing more organics for subsequent SCFA production. It was also found that the combined method inhibited acidogenesis and methanogenesis, but the inhibition to methanogenesis was much severer than that to acidogenesis. Finally, the feasibility of NH4+-N and PO3−4-P, released in fermentation liquor, being recovered as magnesium ammonium phosphate (MAP) was confirmed.

Xu, Q, Liu, X, Wang, D, Wu, Y, Wang, Q, Liu, Y, Li, X, An, H, Zhao, J, Chen, F, Zhong, Y, Yang, Q & Zeng, G 2018, 'Free ammonia-based pretreatment enhances phosphorus release and recovery from waste activated sludge', Chemosphere, vol. 213, pp. 276-284.
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© 2018 Elsevier Ltd The recovery of phosphorus from waste activated sludge (WAS) was usually at low levels due to low phosphorus release. This study presents a novel, cost-effective and eco-friendly pretreatment method, e.g., using free ammonia (FA) to pretreat WAS, to enhance the phosphorus release from WAS. Experimental results showed that the phosphorus release from WAS was significantly increased after FA pretreatment at up to 189.4 mg NH3-N L−1 for 24 h, under which the released PO43--P (i.e. 101.6 ± 6.7 mg L−1) was higher than that pH 9 (i.e. 62.6 ± 4.54 mg L−1) and control (without pH and FA pretreatment) (i.e. 15.1 ± 1.86 mg L−1). More analysis revealed that the FA induced improvement in phosphorus release could be attributed to the disintegration of extracellular polymeric substances (EPS) and cell envelope of sludge cells. Moreover, the released phosphorus recovered as magnesium ammonium phosphate (MAP) was confirmed. The findings reported may guide engineers to develop an economic and practical strategy to enhance resources and energy recovery from WAS.

Xu, Q, Liu, X, Zhao, J, Wang, D, Wang, Q, Li, X, Yang, Q & Zeng, G 2018, 'Feasibility of enhancing short-chain fatty acids production from sludge anaerobic fermentation at free nitrous acid pretreatment: Role and significance of Tea saponin', Bioresource Technology, vol. 254, pp. 194-202.
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© 2018 Elsevier Ltd Short-chain fatty acids (SCFA), raw substrates for biodegradable plastic production and preferred carbon source for biological nutrients removal, can be produced from anaerobic fermentation of waste activated sludge (WAS). This paper reports a new, high-efficient and eco-friendly strategy, i.e., using free nitrous acid (FNA) pretreatment combined with Tea saponin (TS), to enhance SCFA production. Experimental results showed 0.90 mg/L FNA pretreatment and 0.05 g/g total suspended solids TS addition (FNA + TS) not only significantly increased SCFA production to 315.3 ± 8.8 mg COD/g VSS (5.52, 1.76 and 1.93 times higher than that from blank, solo FNA and solo TS, respectively) but also shortened fermentation time to 4 days. Mechanism investigations revealed that FNA pretreatment combined with TS cause a positive synergetic effect on sludge solubilization, resulting in more release of organics. It was also found that the combination benefited hydrolysis and acidogenesis processes but inhibited the methanogenesis.

Xu, R & Fatahi, B 2018, 'Geosynthetic-reinforced cushioned piles with controlled rocking for seismic safeguarding', Geosynthetics International, vol. 25, no. 6, pp. 561-581.
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In this study, a cushioned pile foundation reinforced with geosynthetics is proposed to protect buildings and foundations from seismic energy. This composite foundation utilises piles to control foundation settlement while the geosynthetic-reinforced cushion modifies the dynamic structural characteristics and the load transfer mechanism. The seismic performance of this proposed foundation system is evaluated numerically using FLAC3D software. A fully coupled nonlinear dynamic analysis was conducted in the time domain. The variation of shear modulus corresponding to shear strains in the soil is used to simulate the dynamic behaviour of the soil, while the influence of the plasticity index is also captured. The soil-geosynthetic interface utilises the Mohr-Coulomb failure criterion to capture possible sliding and pull-out of the reinforcement layers. 3D numerical predictions of the tensile forces mobilised in the geosynthetic layers, the shear forces, the lateral deformations and maximum and residual inter-storey drifts in the building are presented and discussed in this paper, as well as how the shear forces and bending moments develop in the piles, and the lateral pile displacements. The results indicate that the proposed geosynthetic-reinforced cushioned pile foundation can provide design engineers with an alternative solution for safeguarding buildings constructed on soft soils in earthquake-prone regions.

Xu, R & Fatahi, B 2018, 'Influence of geotextile arrangement on seismic performance of mid-rise buildings subjected to MCE shaking', Geotextiles and Geomembranes, vol. 46, no. 4, pp. 511-528.
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Geotextile layers make it possible to construct mid-rise buildings sitting on shallow foundations in unfavourablesoil conditions; this study investigates how the arrangement of geotextiles affects the seismic performance ofmid-rise buildings under Maximum Considered Earthquake (MCE) shaking. The geotextile arrangement con-sidered here includes the stiffness (5000 kN/m–12000 kN/m), the length with respect to width of the foun-dation (B) (1B–4B), the number of geotextile layers (1–7 layers), and their spacing (250 mm–1000 mm).FLAC3D is used for the numerical simulation and to carry out nonlinear dynamic analysis in the time domain,and an inelastic constitutive model is used to simulate the behaviour of the structure and the geotextile layersunder seismic loads. Variations in the shear modulus of soil and the corresponding damping ratio with cyclicshear strain are considered using a hysteretic damping algorithm to model the reasonable dissipation of energyin the soil. The interface between the foundation and ground surface, including the material and geometricalnonlinearities, are used to capture any possible slide and uplift in the foundations. The results are presented withregard to the geotextile arrangement considered, and include the tensile force mobilised in the geotextile layers,the response spectra at the bedrock and ground surface, the shear force developed in the structure, the maximumrocking angle of the foundation, permanent foundation settlement, maximum lateral displacement and themaximum and residual inter-storey drifts. The results show that the geotextile layers close to the edges of thefoundation sustained most of the stress induced by foundation rocking, and the geotextile arrangement has asignificant influence on the seismic response of mid-rise buildings. Thus, to satisfy the seismic performance ofbuildings and to optimise the design of foundations reinforced with geotextiles, the stiffness, length, number andspacing of the geotextile layers sh...

Xu, S, Wu, C, Liu, Z & Li, J 2018, 'Numerical study of ultra-high-performance steel fibre–reinforced concrete columns under monotonic push loading', Advances in Structural Engineering, vol. 21, no. 8, pp. 1234-1248.
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A finite element model is developed to investigate the behaviour of ultra-high-performance steel fibre–reinforced concrete columns under combined axial compression and horizontal monotonic push loading. The effects of steel fibre content, axial compression ratio, reinforcement ratio (or rebar ratio), stirrup ratio and shear span ratio on the structural behaviour of ultra-high-performance steel fibre–reinforced concrete columns are investigated in detail. The numerical model shows good agreement in bond–slip behaviour of specimens based on CEB model results and numerical results, and such behaviour should be taken into consideration in engineering practice. The results indicate that the developed finite element model could predict the structural behaviour and failure mode of ultra-high-performance steel fibre–reinforced concrete columns effectively. It is found that the reinforcement ratio, axial compression ratio, shear span ratio and volume fraction of steel fibre have a great influence on both the structural behaviour and failure modes of specimens.

Xu, T, Castel, A & Gilbert, RI 2018, 'On the Reliability of Serviceability Calculations for Flexural Cracked Reinforced Concrete Beams', Structures, vol. 13, pp. 201-212.
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Under in-service conditions, beams and slabs in reinforced concrete structures are almost always cracked, as the tensile strength of the concrete is low. Due to the irreversible reduction in overall stiffness resulting from cracking and the residual deflection after unloading, the structural response is load path dependent. In this paper, an existing average moment of inertia model and Monte Carlo simulation (MCS) are adopted to take into account the effect of historical cracking damage on the reliability of serviceability calculations for reinforced concrete (RC) members. The suitability of the average moment of inertia model for reliability analysis is verified by considering experimental tests on a total of eleven reinforced concrete beams. The errors associated with both the effective and average moment of inertia predicted by the model are calibrated using the experimental data. By using the proposed approach to account for the various sources of uncertainty in reinforced concrete beams, the quantitative loss in the short-term and long-term serviceability reliability of a cracked reinforced concrete beam was calculated. The results confirm that the effect of historical cracking damage on short-term serviceability reliability should be taken into account when the deflection induced by historical loading is larger than the deflection limitation. Light historical damage has no influence on the short-term serviceability reliability, although it affects the probability density distribution of the deflection. However, in the long-term serviceability reliability analysis, even when the historical damage is light, the long-term serviceability reliability index is decreased as the cracking damage to the stiffness affects the time-dependent deflection. Additionally, the later a damaging load is applied to a reinforced concrete beam, the less is the influence of cracking damage on the long-term serviceability reliability.

Xu, T, Huang, J, Castel, A, Zhao, R & Yang, C 2018, 'Influence of steel–concrete bond damage on the dynamic stiffness of cracked reinforced concrete beams', Advances in Structural Engineering, vol. 21, no. 13, pp. 1977-1989.
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In this article, experiments focusing at the influence of steel–concrete bond damage on the dynamic stiffness of cracked reinforced concrete beams are reported. In these experiments, the bond between concrete and reinforcing bar was damaged using appreciate flexural loads. The static stiffness of cracked reinforced concrete beam was assessed using the measured load–deflection response under cycles of loading and unloading, and the dynamic stiffness was analyzed using the measured natural frequencies with and without sustained loading. Average moment of inertia model (Castel et al. model) for cracked reinforced beams by taking into account the respective effect of bending cracks (primary cracks) and the steel–concrete bond damage (interfacial microcracks) was adopted to calculate the static load–deflection response and the natural frequencies of the tested beams. The experimental results and the comparison between measured and calculated natural frequencies show that localized steel–concrete bond damage does not influence remarkably the dynamic stiffness and the natural frequencies both with and without sustained loading applied. Castel et al. model can be used to calculate the dynamic stiffness of cracked reinforced concrete beam by neglecting the effect of interfacial microcracks.

Xu, T, Zhu, L, Castel, A & Gilbert, RI 2018, 'Assessing Immediate and Time-Dependent Instantaneous Stiffness of Cracked Reinforced Concrete Beams Using Residual Cracks', Journal of Structural Engineering, vol. 144, no. 4, pp. 04018022-04018022.
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Xu, X, Motta, G, Tu, Z, Xu, H, Wang, Z & Wang, X 2018, 'A new paradigm of software service engineering in big data and big service era', Computing, vol. 100, no. 4, pp. 353-368.
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© 2018, Springer-Verlag GmbH Austria, part of Springer Nature. In the big data era, servitization becomes one of the important development trends of the IT world. More and more software resources are developed and existed in the format as services on the Internet. These services from multi-domains and multi-networks are converged as a huge complicated service network or ecosystem, which can be called as Big Service. How to reuse the abundant open service resources to rapidly develop the new applications or comprehensive service solutions to meet massive individualized customer requirements is a key issue in the big data and big service ecosystem. Based on analyzing the ecosystem of big service, this paper presents a new paradigm of software service engineering, Requirement-Engineering Two-Phase of Service Engineering Paradigm (RE2SEP), which includes service oriented requirement engineering, domain oriented service engineering, and the development approach of software services. By means of the RE2SEP approach, the adaptive service solutions can be efficiently designed and implemented to match the requirement propositions of massive individualized customers in Big Service ecosystem. A case study of the RE2SEP applications, which is a project on citizens mobility service in smart city environment, is also given in this paper. The RE2SEP paradigm will change the way of traditional life-cycle oriented software engineering, and lead a new approach of software service engineering.

Xu, X, Tsang, IW & Liu, C 2018, 'Complementary Attributes: A New Clue to Zero-Shot Learning', IEEE transactions on cybernetics, vol. 51, no. 3, pp. 1519-1530.
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Zero-shot learning (ZSL) aims to recognize unseen objects using disjoint seenobjects via sharing attributes. The generalization performance of ZSL isgoverned by the attributes, which transfer semantic information from seenclasses to unseen classes. To take full advantage of the knowledge transferredby attributes, in this paper, we introduce the notion of complementaryattributes (CA), as a supplement to the original attributes, to enhance thesemantic representation ability. Theoretical analyses demonstrate thatcomplementary attributes can improve the PAC-style generalization bound oforiginal ZSL model. Since the proposed CA focuses on enhancing the semanticrepresentation, CA can be easily applied to any existing attribute-based ZSLmethods, including the label-embedding strategy based ZSL (LEZSL) and theprobability-prediction strategy based ZSL (PPZSL). In PPZSL, there is a strongassumption that all the attributes are independent of each other, which isarguably unrealistic in practice. To solve this problem, a novel rankaggregation framework is proposed to circumvent the assumption. Extensiveexperiments on five ZSL benchmark datasets and the large-scale ImageNet datasetdemonstrate that the proposed complementary attributes and rank aggregation cansignificantly and robustly improve existing ZSL methods and achieve thestate-of-the-art performance.

Xu, Y, Chen, X, Yuan, Z & Ni, B-J 2018, 'Modeling of Pharmaceutical Biotransformation by Enriched Nitrifying Culture under Different Metabolic Conditions', Environmental Science & Technology, vol. 52, no. 5, pp. 2835-2843.
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© 2018 American Chemical Society. Pharmaceutical removal could be significantly enhanced through cometabolism during nitrification processes. To date, pharmaceutical biotransformation models have not considered the formation of transformation products associated with the metabolic type of microorganisms. Here we report a comprehensive model to describe and evaluate the biodegradation of pharmaceuticals and the formation of their biotransformation products by enriched nitrifying cultures. The biotransformation of parent compounds was linked to the microbial processes via cometabolism induced by ammonium-oxidizing bacteria (AOB) growth, metabolism by AOB, cometabolism by heterotrophs (HET) growth, and metabolism by HET in the model framework. The model was calibrated and validated using experimental data from pharmaceutical biodegradation experiments at realistic levels, taking two pharmaceuticals as examples, i.e., atenolol and acyclovir. Results demonstrated the good predictive performance of the established biotransformation model under different metabolic conditions, as well as the reliability of the established model in predicting different pharmaceutical biotransformations. The linear positive correlation between ammonia oxidation rate and pharmaceutical degradation rate confirmed the major role of cometabolism induced by AOB in the pharmaceutical removal. Dissolved oxygen was also revealed to be capable of regulating the pharmaceutical biotransformation cometabolically, and the substrate competition between ammonium and pharmaceuticals existed especially at high ammonium concentrations.

Xu, Y, Thakur, CS, Singh, RK, Hamilton, TJ, Wang, RM & van Schaik, A 2018, 'A FPGA Implementation of the CAR-FAC Cochlear Model', Frontiers in Neuroscience, vol. 12, no. APR.
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© 2018 Xu, Thakur, Singh, Hamilton, Wang and van Schaik. This paper presents a digital implementation of the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC) cochlear model. The CAR part simulates the basilar membrane's (BM) response to sound. The FAC part models the outer hair cell (OHC), the inner hair cell (IHC), and the medial olivocochlear efferent system functions. The FAC feeds back to the CAR by moving the poles and zeros of the CAR resonators automatically. We have implemented a 70-section, 44.1 kHz sampling rate CAR-FAC system on an Altera Cyclone V Field Programmable Gate Array (FPGA) with 18% ALM utilization by using time-multiplexing and pipeline parallelizing techniques and present measurement results here. The fully digital reconfigurable CAR-FAC system is stable, scalable, easy to use, and provides an excellent input stage to more complex machine hearing tasks such as sound localization, sound segregation, speech recognition, and so on.

Xuan, J, Lu, J, Yan, Z & Zhang, G 2018, 'Bayesian Deep Reinforcement Learning via Deep Kernel Learning', International Journal of Computational Intelligence Systems, vol. 12, no. 1, pp. 164-164.
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Xuan, J, Lu, J, Zhang, G, Xu, RYD & Luo, X 2018, 'Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 5, pp. 1835-1849.
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© 2012 IEEE. Sparse nonnegative matrix factorization (SNMF) aims to factorize a data matrix into two optimized nonnegative sparse factor matrices, which could benefit many tasks, such as document-word co-clustering. However, the traditional SNMF typically assumes the number of latent factors (i.e., dimensionality of the factor matrices) to be fixed. This assumption makes it inflexible in practice. In this paper, we propose a doubly sparse nonparametric NMF framework to mitigate this issue by using dependent Indian buffet processes (dIBP). We apply a correlation function for the generation of two stick weights associated with each column pair of factor matrices while still maintaining their respective marginal distribution specified by IBP. As a consequence, the generation of two factor matrices will be columnwise correlated. Under this framework, two classes of correlation function are proposed: 1) using bivariate Beta distribution and 2) using Copula function. Compared with the single IBP-based NMF, this paper jointly makes two factor matrices nonparametric and sparse, which could be applied to broader scenarios, such as co-clustering. This paper is seen to be much more flexible than Gaussian process-based and hierarchial Beta process-based dIBPs in terms of allowing the two corresponding binary matrix columns to have greater variations in their nonzero entries. Our experiments on synthetic data show the merits of this paper compared with the state-of-the-art models in respect of factorization efficiency, sparsity, and flexibility. Experiments on real-world data sets demonstrate the efficiency of this paper in document-word co-clustering tasks.

Xue, R, Huang, S, Luo, X, Jiang, D & Da Xu, RY 2018, 'Semantic emotion-topic model based social emotion mining', Journal of Web Engineering, vol. 17, no. 1-2, pp. 73-92.
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With the booming of social media users, more and more short texts with emotion labels appear, which contain users' rich emotions and opinions about social events or enterprise products. Social emotion mining on social media corpus can help government or enterprise make their decisions. Emotion mining models involve statistical-based and graph-based approaches. Among them, the former approaches are more popular, e.g. Latent Dirichlet Allocation (LDA)-based Emotion Topic Model. However, they are suffering from low retrieval performance, such as the bad accuracy and the poor interpretability, due to them only considering the bag-of-words or the emotion labels in social media corpus. In this paper, we propose a LDA-based Semantic Emotion-Topic Model (SETM) combining emotion labels and inter-word relations to enhance the retrieval performance of social emotion mining result. The performance influence of four factors on SETM are considered, i.e., association relations, computing time, topic number and semantic interpretability. Experimental results show that the accuracy of our proposed model is 0.750, compared with 0.606, 0.663 and 0.680 of Emotion Topic Model (ETM), Multi-label Supervised Topic Model (MSTM) and Sentiment Latent Topic Model (SLTM) respectively. Besides, the computing time of our model is reduced by 87.81% through limiting word frequency, and its accuracy is 0.703, compared with 0.501, 0.648 and 0.642 of the above baseline methods. Thus, the proposed model has broad prospects in social emotion mining area.

Yan, B, Zhao, Q, Wang, Z & Zhang, JA 2018, 'Adaptive decomposition-based evolutionary approach for multiobjective sparse reconstruction', Information Sciences, vol. 462, pp. 141-159.
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© 2018 Elsevier Inc. This paper aims at solving the sparse reconstruction (SR) problem via a multiobjective evolutionary algorithm. Existing multiobjective evolutionary algorithms for the SR problem have high computational complexity, especially in high-dimensional reconstruction scenarios. Furthermore, these algorithms focus on estimating the whole Pareto front rather than the knee region, thus leading to limited diversity of solutions in knee region and waste of computational effort. To tackle these issues, this paper proposes an adaptive decomposition-based evolutionary approach (ADEA) for the SR problem. Firstly, we employ the decomposition-based evolutionary paradigm to guarantee a high computational efficiency and diversity of solutions in the whole objective space. Then, we propose a two-stage iterative soft-thresholding (IST)-based local search operator to improve the convergence. Finally, we develop an adaptive decomposition-based environmental selection strategy, by which the decomposition in the knee region can be adjusted dynamically. This strategy enables to focus the selection effort on the knee region and achieves low computational complexity. Experimental results on simulated signals, benchmark signals and images demonstrate the superiority of ADEA in terms of reconstruction accuracy and computational efficiency, compared to five state-of-the-art algorithms.

Yan, T, Ye, Y, Ma, H, Zhang, Y, Guo, W, Du, B, Wei, Q, Wei, D & Ngo, HH 2018, 'A critical review on membrane hybrid system for nutrient recovery from wastewater', Chemical Engineering Journal, vol. 348, pp. 143-156.
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© 2018 Wastewater has been investigated as a source for nutrient recovery for two reasons: firstly it contains a high concentration of nutrients; and secondly, it exists in large quantities. Recovering nutrient from wastewater can minimize the environmental footprint of wastewater treatment; simultaneously, the recovered nutrient can be added to fertilizer production to ensure food security. The membrane technique integrated with chemical and biological processes as a membrane hybrid system is a promising method to recover nutrient from wastewater since the membrane can enrich nutrient. It can subsequently increase the technical and economic feasibility of the nutrient recovery process. For this reason, this paper comprehensively and critically reviews the current state of the membrane hybrid system for nutrient recovery from wastewater. Membrane hybrid systems consisting of membrane-based hybrid systems and membrane bioreactor (MBR)-based hybrid systems are explained with reference to their general features, such as mechanisms and processes. Furthermore the advantages and challenges of the membrane hybrid systems are compared as well as their economic feasibility. Future research avenues into membrane hybrid systems are suggested and what can the system more accessible.

Yan, Y, Sencadas, V, Jin, T, Huang, X, Lie, W, Wei, D & Jiang, Z 2018, 'Effect of multi-walled carbon nanotubes on the cross-linking density of the poly(glycerol sebacate) elastomeric nanocomposites', Journal of Colloid and Interface Science, vol. 521, pp. 24-32.
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© 2018 Elsevier Inc. Processing conditions deeply affect the mechanical, chemical and biological properties of elastomeric based nanocomposites. In this work, multi-walled carbon nanotubes (MWCNTs) were dispersed in poly(glycerol sebacate) (PGS) prepolymer, followed by curing under vacuum at 120 °C. It was observed an increase of the water contact angle with the amount of MWCNTs added, as well as the tensile strength and Young modulus, without compromising the elastomeric behaviour of the pristine PGS matrix. The cross-linking degree was determined by the Flory-Rehner swelling method and through the mechanical rubber elasticity model, and an increase of more than six-fold was observed, which demonstrates the chemical conjugation between the MWCNTs and the PGS polymer chains, resulting in stiff and elastomeric nanocomposites. Finally, in vitro cell culture of adult mouse hypothalamus neurons A59 cells showed good support for cell viability and stimulation for axons and dendrites growth. The unique features of these nanocomposites make them promise for biomedical applications, as soft tissue substrates with tailored mechanical properties.

Yang, E, Deng, C, Li, C, Liu, W, Li, J & Tao, D 2018, 'Shared Predictive Cross-Modal Deep Quantization', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 11, pp. 5292-5303.
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© 2012 IEEE. With explosive growth of data volume and ever-increasing diversity of data modalities, cross-modal similarity search, which conducts nearest neighbor search across different modalities, has been attracting increasing interest. This paper presents a deep compact code learning solution for efficient cross-modal similarity search. Many recent studies have proven that quantization-based approaches perform generally better than hashing-based approaches on single-modal similarity search. In this paper, we propose a deep quantization approach, which is among the early attempts of leveraging deep neural networks into quantization-based cross-modal similarity search. Our approach, dubbed shared predictive deep quantization (SPDQ), explicitly formulates a shared subspace across different modalities and two private subspaces for individual modalities, and representations in the shared subspace and the private subspaces are learned simultaneously by embedding them to a reproducing kernel Hilbert space, where the mean embedding of different modality distributions can be explicitly compared. In addition, in the shared subspace, a quantizer is learned to produce the semantics preserving compact codes with the help of label alignment. Thanks to this novel network architecture in cooperation with supervised quantization training, SPDQ can preserve intramodal and intermodal similarities as much as possible and greatly reduce quantization error. Experiments on two popular benchmarks corroborate that our approach outperforms state-of-the-art methods.

Yang, G, Wang, D, Yang, Q, Zhao, J, Liu, Y, Wang, Q, Zeng, G, Li, X & Li, H 2018, 'Effect of acetate to glycerol ratio on enhanced biological phosphorus removal', Chemosphere, vol. 196, pp. 78-86.
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© 2017 Elsevier Ltd Enhanced biological phosphorus removal (EBPR) is a sustainable and promising technology for phosphorus removal from wastewater. The efficiency of this technology, however, is often discounted due to the insufficient carbon sources in influent. In this work, the effect of acetate to glycerol ratio on the EBPR performance was evaluated. The experimental results showed when the ratio of acetate to glycerol decreased from 100/0% to 50/50%, the EBPR efficiency increased from 90.2% to 96.2%. Further decrease of acetate to glycerol ratio to 0/100% decreased the efficiency of EBPR to 30.5%. Fluorescence in situ hybridization analysis demonstrated appropriate increase of glycerol benefited to increase the relative abundance of phosphate accumulating organisms. Further investigation revealed the proper addition of glycerol increased the amount of polyhydroxyalkanoates synthesis, and then produced sufficient energy for oxic luxury phosphorus in the subsequent oxic phase.

Yang, G, Xu, Q, Wang, D, Tang, L, Xia, J, Wang, Q, Zeng, G, Yang, Q & Li, X 2018, 'Free ammonia-based sludge treatment reduces sludge production in the wastewater treatment process', Chemosphere, vol. 205, pp. 484-492.
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© 2018 Elsevier Ltd Excessive sludge production is one of the major challenges for biological wastewater treatment plants. This paper reports a new strategy to enhance sludge reduction from the wastewater treatment process. In this strategy, 1/5 of the sludge is withdrawn from the mainstream reactor into a side-stream unit for sludge treatment with 16 mg/L free ammonia (FA) for 24–40 h. The FA-treated sludge mixture is then returned to the mainstream reactor. To demonstrate this concept, two reactors treating synthetic domestic wastewater were operated, with one serving as the experimental reactor and the other as the control. Experimental results showed that the experimental reactor exhibited 20% lower in sludge production than the control. FA treatment effectively disintegrated a portion of extracellular or intracellular substances of sludge cells in the FA treatment unit and lowered the observed sludge yields in the mainstream reactor, which were the main reasons for the sludge reduction. Although FA treatment decreased the activities of nitrifiers, denitrifiers, and polyphosphate accumulating organisms in the FA treatment unit, this strategy did not negatively affect the reactor performance and sludge properties of the experimental reactor such as sludge settleability, organic removal, nitrogen removal and phosphorus removal. Further investigation showed that the organics released from the FA treatment process could be used by PAOs and denitrifiers for carbon sources.

Yang, J, Zhang, W, Yang, S, Zhang, Y, Lin, X & Yuan, L 2018, 'Efficient set containment join', The VLDB Journal, vol. 27, no. 4, pp. 471-495.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. In this paper, we study the problem of set containment join. Given two collections R and S of records, the set containment join R⋈ ⊆S retrieves all record pairs { (r, s) } ∈ R× S such that r⊆ s. This problem has been extensively studied in the literature and has many important applications in commercial and scientific fields. Recent research focuses on the in-memory set containment join algorithms, and several techniques have been developed following intersection-oriented or union-oriented computing paradigms. Nevertheless, we observe that two computing paradigms have their limits due to the nature of the intersection and union operators. Particularly, intersection-oriented method relies on the intersection of the relevant inverted lists built on the elements of S. A nice property of the intersection-oriented method is that the join computation is verification free. However, the number of records explored during the join process may be large because there are multiple replicas for each record in S. On the other hand, the union-oriented method generates a signature for each record in R and the candidate pairs are obtained by the union of the inverted lists of the relevant signatures. The candidate size of the union-oriented method is usually small because each record contributes only one replica in the index. Unfortunately, union-oriented method needs to verify the candidate pairs, which may be cost expensive especially when the join result size is large. As a matter of fact, the state-of-the-art union-oriented solution is not competitive compared to the intersection-oriented ones. In this paper, we propose a new union-oriented method, namely TT-Join, which not only enhances the advantage of the previous union-oriented methods but also integrates the goodness of intersection-oriented methods by imposing a variant of prefix tree structure. We conduct extensive experiments on 20 real-life datas...

Yang, L, Zeng, Z & Wen, S 2018, 'A full-function Pavlov associative memory implementation with memristance changing circuit', Neurocomputing, vol. 272, pp. 513-519.
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Positive voltages and negative voltages are applied to adjust memristance in most memristive circuits. This paper presents a memristance changing circuit in which memristance is changed only by the positive voltage. A mathematical calculation method is proposed to analyze the memristance change approximately. Furthermore, memristance changing circuits are utilized as synapses to construct a neural network to imitate full-function Pavlov associative memory. Compared to the classical Pavlov associative memory, the full-function Pavlov associative memory contains additional food forgetting and ring forgetting processes. The forgetting processes will be triggered in the condition that either the food or the ring is given to the dog after the learning processes. The learning and forgetting time of the associative memory can be obtained by the proposed mathematical calculation method in advance approximately.

Yang, L, Zeng, Z, Huang, Y & Wen, S 2018, 'Memristor-Based Circuit Implementations of Recognition Network and Recall Network With Forgetting Stages', IEEE Transactions on Cognitive and Developmental Systems, vol. 10, no. 4, pp. 1133-1142.
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This paper proposes a novel memistor-based neuron circuit, in which the memristor-CMOS hybrid synaptic circuit simply utilizes the positive voltage to change the memristance. At the same time, in order to obtain the memristance and output voltage changes in the neuron circuit, a mathematical deduction is implemented according to the circuit structure. Then, the memristor-based recognition and recall network circuits are constructed based on the proposed neuron circuit. The recognition and recall functions are realized by associative learning between the unconditional stimuli and the conditional stimuli (CS). After the learning stages, the single presentation of CS activates forgetting stages in the two networks. Furthermore, the related parameter changes in the learning and forgetting stages can be calculated by the deduced equations approximately. The PSPICE simulations are implemented to demonstrate the effectiveness of the proposed circuits and the deduced equations.

Yang, M, Zhu, T, Liu, B, Xiang, Y & Zhou, W 2018, 'Differential Private POI Queries via Johnson-Lindenstrauss Transform', IEEE Access, vol. 6, pp. 29685-29699.
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© 2013 IEEE. The growing popularity of location-based services is giving untrusted servers relatively free reign to collect huge amounts of location information from mobile users. This information can reveal far more than just a user's locations but other sensitive information, such as the user's interests or daily routines, which raises strong privacy concerns. Differential privacy is a well-acknowledged privacy notion that has become an important standard for the preservation of privacy. Unfortunately, existing privacy preservation methods based on differential privacy protect user location privacy at the cost of utility, aspects of which have to be sacrificed to ensure that privacy is maintained. To solve this problem, we present a new privacy framework that includes a semi-trusted third party. Under our privacy framework, both the server and the third party only hold a part of the user's location information. Neither the server nor the third party knows the exact location of the user. In addition, the proposed perturbation method based on the Johnson Lindenstrauss transform satisfies the differential privacy. Two popular point of interest queries, -NN and Range, are used to evaluate the method on two real-world data sets. Extensive comparisons against two representative differential privacy-based methods show that the proposed method not only provides a strict privacy guarantee but also significantly improves performance.

Yang, M, Zhu, T, Liu, B, Xiang, Y & Zhou, W 2018, 'Machine Learning Differential Privacy With Multifunctional Aggregation in a Fog Computing Architecture', IEEE Access, vol. 6, pp. 17119-17129.
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© 2018 IEEE. Data aggregation plays an important role in the Internet of Things, and its study and analysis has resulted in a range of innovative services and benefits for people. However, the privacy issues associated with raw sensory data raise significant concerns due to the sensitive nature of the user information it often contains. Thus, numerous schemes have been proposed over the last few decades to preserve the privacy of users' data. Most methods are based on encryption technology, which is computationally and communicationally expensive. In addition, most methods can only handle a single aggregation function. Therefore, in this paper, we propose a multifunctional data aggregation method with differential privacy. The method is based on machine learning and can support a wide range of statistical aggregation functions, including additive and non-additive aggregation. It operates within a fog computing architecture, which extends cloud computing to the edge of the network, alleviating much of the computational burden on the cloud server. And, by only reporting the results of the aggregation to the server, communication efficiency is improved. Extensive experimental results show that the proposed method not only answers flexible aggregation queries that meet diversified aggregation goals, but also produces aggregation results with high accuracy.

Yang, N, Fan, X, Puthal, D, He, X, Nanda, P & Guo, S 2018, 'A Novel Collaborative Task Offloading Scheme for Secure and Sustainable Mobile Cloudlet Networks', IEEE Access, vol. 6, pp. 44175-44189.
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© 2013 IEEE. With the advancement of wireless networking technologies and communication infrastructures, mobile cloud computing has emerged as a pervasive paradigm to execute computing tasks for capacity-limited mobile devices. More specifically, at the network edge, the resource-rich and trusted cloudlet system can provide in-proximity computing services by executing the workloads for nearby devices. Nevertheless, there are chances for malicious users to generate distributed denial-of-service (DDoS) flooding tasks to overwhelm cloudlet servers and block computing services from legitimate users. Load balancing is one of the most effective methods to solve DDoS attacks in distributed networks. However, existing solutions require overall load information to achieve load balancing in cloudlet networks, making it costly in both communication and computation. To achieve more efficient and low-cost load balancing, we propose CTOM, a novel collaborative task offloading scheme to avoid DDoS attacks for secure and sustainable mobile cloudlet networks. The proposed solution is based on the balls-and-bins theory and it can balance the task loads with extremely limited information. The CTOM reduces the number of overloaded cloudlets smoothly, thus handling the potential DDoS attacks in mobile cloudlet networks. Extensive simulations and evaluation demonstrate that, the proposed CTOM outperforms the conventional random and proportional allocation schemes in reducing the task gaps between maximum load and minimum load among mobile cloudlets by 65% and 55%, respectively.

Yang, S, Hu, F, Thompson, RG, Wang, W, Li, Y, Li, S & Ni, W 2018, 'Criticality ranking for components of a transportation network at risk from tropical cyclones', International Journal of Disaster Risk Reduction, vol. 28, pp. 43-55.
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Yang, T, Ding, C, Ziolkowski, RW & Guo, YJ 2018, 'Circular hole ENZ photonic crystal fibers exhibit high birefringence', Optics Express, vol. 26, no. 13, pp. 17264-17264.
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© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement —A novel photonic crystal fiber (PCF) design that yields very high birefringence is proposed and analyzed. Its significantly enhanced birefringence is achieved by filling selected air holes in the cladding with an epsilon-near-zero (ENZ) material. Extensive simulation results of this asymmetric material distribution in the lower THz range demonstrate that the reported PCF has a birefringence above 0.1 and a loss below 0.01 cm−1 over a wide band of frequencies. Moreover, it exhibits near zero dispersion at 0.75 THz for both the X- and Y-polarization modes and a birefringence equal to 0.28. This THz PCF is then scaled successfully to optical frequencies. While the high birefringence is maintained, this optical PCF has a very high loss in its Y-polarization mode and, consequently, yields single-polarization single-mode (SPSM) propagation, exhibiting near zero dispersion at the optical telecom wavelength of 1.55 μm. The ideal ENZ materials used for these conceptual models are replaced with realistic ones for both the THz and optical PCF designs. With the currently available ENZ materials, the realistic PCFs still have a high birefringence, but with higher losses compared to the idealized results. Future developments of ENZ materials that achieve lower loss properties will mitigate this issue in any frequency band of high interest.

Yang, T, Ding, C, Ziolkowski, RW & Jay Guo, Y 2018, 'A Scalable THz Photonic Crystal Fiber With Partially-Slotted Core That Exhibits Improved Birefringence and Reduced Loss', Journal of Lightwave Technology, vol. 36, no. 16, pp. 3408-3417.
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© 1983-2012 IEEE. A photonic crystal fiber (PCF) based on high resistivity silicon is reported that exhibits high birefringence, low loss, and flat dispersion characteristics across a wide bandwidth in the THz regime. Except for the center region, which remains the background dielectric, its core is occupied by a set of rectangular air slots. The material and configuration lead to high birefringence and low loss. The simulation results, which include the material losses, indicate that a birefringence value of 0.82 and a total loss of 0.011 cm-1, including the effective material loss and confinement losses, are achieved at 1.0 THz. These values are a factor of ten times higher and four times lower, respectively, than many recent designs. The numerical analyses also demonstrate that the reported PCF can be scaled to any desired portion of the THz regime, while maintaining a similar birefringence, simply by changing the lattice constant. This 'scalable' characteristic is shown to be applicable to other PCF designs. It could facilitate a novel way of testing THz fibers, i.e., it suggests that one only needs to test the preform to validate the performance of the fiber at higher frequencies. This outcome would significantly reduce the design complexity and the costs of PCF testing.

Yang, W, Li, J, Zheng, H & Xu, RYD 2018, 'A Nuclear Norm Based Matrix Regression Based Projections Method for Feature Extraction', IEEE Access, vol. 6, pp. 7445-7451.
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© 2013 IEEE. In the traditional graph embedding framework, the graph is usually built by k-NN or r-ball. Since it is difficult to manually set the parameters k and r in the high-dimensional space, sparse representation-based methods are usually introduced to automatically build the graphs. In recent years, nuclear norm-based matrix regression (NMR) has been proposed for face recognition using the low rank structural information (i.e., the image matrix-based error model). Inspired by NMR, we give a NMR-based projections (NMRP) method for feature extraction and recognition. The experiments on FERET and extended Yale B face databases show that NMR can be used to build the graph while NMRP is an effective feature extraction method.

Yang, Y & Zhu, X 2018, 'A Wideband Reconfigurable Antenna With 360° Beam Steering for 802.11ac WLAN Applications', IEEE Transactions on Antennas and Propagation, vol. 66, no. 2, pp. 600-608.
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© 1963-2012 IEEE. A novel 360° beam steering patch antenna with parasitic elements is presented in this paper. The designed antenna consists of a radiating patch and six parasitic elements, each of which is connected through a group of shorting vias controlled by p-i-n diode switches. By switching on the desired groups of the shorting vias, the electric field distribution inside substrate cavity appears at the desired beam direction. Rotationally switching on the groups of the shorting vias, the performance of 360° beam scanning is realized. To further understand operating mechanism, the antenna is modeled with equivalent circuit in terms of the on and off status of a sector of the antenna, which can be used as a design guide for shorting-vias-controlled reconfigurable microstrip patch antennas. The fabricated antenna achieves a bandwidth of 14.5%, a peak gain of 10 dBi, and the efficiency of 80.5%. The achieved beamwidths are 42° and 97° in azimuth and elevation planes, respectively. With an ability of being steered around zenith axis at six directions, the scanned beam range covers the entire 360°. The physical dimension is only 2.5 λg for the size and 0.5λg for the profile. This antenna operates from 5.1 to 5.9 GHz and has significant meaning in the IEEE 802.11ac wireless local area network applications due to its capabilities of generating 360° steered beams.

Yang, Y, Li, Z, Wang, S, Chen, X, Wang, J & Guo, YJ 2018, 'Miniaturized High-Order-Mode Dipole Antennas Based on Spoof Surface Plasmon Polaritons', IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 12, pp. 2409-2413.
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© 2002-2011 IEEE. A miniaturization method for antennas is developed based on spoof surface plasmon polaritons (SSPPs). With a large phase constant on the SSPPs transmission line, the guide wavelength can be dramatically reduced, with great potential on the miniaturization application of antennas. By introducing a miniaturization factor M, the relationship between M and the phase constant on the SSPPs dipole is studied, providing guidance to the design of miniaturized SSPPs dipoles. Then, SSPPs dipoles operating at 2.4 GHz are designed, including both the odd-And even-resonance dipoles. Simple feeding structures are developed for the odd-And even-resonance dipoles, respectively, and particularly for the even-resonance mode to realize a transition from 50 Ω to very large input impedance of the dipole. The miniaturized SSPPs dipoles operating at the 1st, 2nd, 3rd, and 4th modes are fabricated. The measured reflection coefficients and radiation patterns show good agreements with the simulated results. It can be concluded that the dipole lengths for these modes are reduced by 8%, 11%, 10%, and 13%, respectively, compared with the conventional printed dipoles on the same substrate.

Yang, Y, Zhou, M, Niu, Y, Li, C, Cao, R, Wang, B, Yan, P, Ma, Y & Xiang, J 2018, 'Epileptic Seizure Prediction Based on Permutation Entropy', Frontiers in Computational Neuroscience, vol. 12.
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© 2018 Yang, Zhou, Niu, Li, Cao, Wang, Yan, Ma and Xiang. Epilepsy is a chronic non-communicable disorder of the brain that affects individuals of all ages. It is caused by a sudden abnormal discharge of brain neurons leading to temporary dysfunction. In this regard, if seizures could be predicted a reasonable period of time before their occurrence, epilepsy patients could take precautions against them and improve their safety and quality of life. However, the potential that permutation entropy(PE) can be applied in human epilepsy prediction from intracranial electroencephalogram (iEEG) recordings remains unclear. Here, we described the novel application of PE to track the dynamical changes of human brain activity from iEEG recordings for the epileptic seizure prediction. The iEEG signals of 19 patients were obtained from the Epilepsy Centre at the University Hospital of Freiburg. After preprocessing, PE was extracted in a sliding time window, and a support vector machine (SVM) was employed to discriminate cerebral state. Then a two-step post-processing method was applied for the purpose of prediction. The results showed that we obtained an average sensitivity (SS) of 94% and false prediction rates (FPR) with 0.111 h−1. The best results with SS of 100% and FPR of 0 h−1 were achieved for some patients. The average prediction horizon was 61.93 min, leaving sufficient treatment time before a seizure. These results indicated that applying PE as a feature to extract information and SVM for classification could predict seizures, and the presented method shows great potential in clinical seizure prediction for human.

Yang, Y, Zhu, H, Zhu, X & Xue, Q 2018, 'A Low-Loss Bandpass Filter using Edge-Coupled Resonator With Capacitive Feeding in (Bi)-CMOS Technology', IEEE Electron Device Letters, vol. 39, no. 6, pp. 787-790.
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© 1980-2012 IEEE. In this Letter, a flexible approach for low-loss on-chip bandpass filter (BPF) design in CMOS technology is presented. The proposed approach takes the advantages of a combination of an edge-coupled electromagnetic structure, namely resonator, and a pair of metal-insulator-metal capacitors for BPF implementation. To demonstrate the insight of the approach, the designed resonator is analyzed in details by means of a simplified equivalent LC-circuit model. Then, the impact on the BPF design due to the variations of the feeding capacitance is investigated. To prove the concept, both the resonator and BPF are fabricated in a standard 0.13- μ m CMOS technology. The measured results show that the designed resonator can generate a notch with 20-dB attenuation at 59.4 GHz, while the BPF has a center frequency of 35.4 GHz with an insertion loss of 1.7 dB. The chip size of both devices, excluding the test pads, is only 0.039 mm2 (0.15 × 0.26 mm2).

Yang, Y, Zhu, X & Xue, Q 2018, 'Design of an Ultracompact On-Chip Bandpass Filter Using Mutual Coupling Technique', IEEE Transactions on Electron Devices, vol. 65, no. 3, pp. 1087-1093.
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© 1963-2012 IEEE. In this paper, design of an ultracompact bandpass filter (BPF) in GaAs technology without compromising its electrical performance is investigated by means of both theoretical analysis and electromagnetic simulation. In particular, the relationship between the external quality factor and the coupling coefficient of the second-order BPF is formulized to better understand the principle of the mutual coupling effect. To prove the concept, the designed filter is implemented in a commercial 0.1-μm GaAs technology. A step-by-step design guideline is elaborated. The BPF has not only the merits of ultracompactness, but also remarkable insertion loss (IL) compared with other state-of-The-Art on-chip designs. The measurement results show that the 1-dB bandwidth of the BPF is from 28 to 36 GHz, while the IL is less than 1 dB at 29.5 GHz. In addition, more than 40-dB rejection is achieved from 56 to 69 GHz. The size of the filter is only 230 × 280 μm2, excluding the pads, which is equivalent to 0.074 × 0.09 λg μm2} at 28 GHz. To the best of our knowledge, the proposed design is known to be the most compact one in the open literature using GaAs technologies.

Yang, Y-C, Wang, P-H, Tsai, Y-T & Ong, H-C 2018, 'Influences of feedstock and plasma spraying parameters on the fabrication of tubular solid oxide fuel cell anodes', Ceramics International, vol. 44, no. 7, pp. 7824-7830.
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Yang, Z, Yu, C, Kim, J, Li, Z & Wang, L 2018, 'Evolution of cooperation driven by majority-pressure based interdependence', New Journal of Physics, vol. 20, no. 8, pp. 083047-083047.
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Yao, J, Sun, Y, Wang, Y, Fu, Q, Xiong, Z & Liu, Y 2018, 'Magnet-induced aligning magnetorheological elastomer based on ultra-soft matrix', Composites Science and Technology, vol. 162, pp. 170-179.
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A novel magnet-induced aligning magnetorheological elastomer (MIMRE) based on ultra-soft polymeric matrix was prepared through an innovative synthetic approach, enables the magnetic particles to mobile and align in elastomer matrix under magnetic field at room temperature. The effect of polymeric matrix modulus on the formation of MIMRE was investigated in detail. It was found that the MIMRE showed excellent magnetorheological (MR) effect, and the absolute and relative MR effect was of 3.61 MPa and 17,286%, respectively. The relative MR effect of magnetorheological elastomer was almost 100 times higher than that of elastomers reported in previous literature. In addition, the application of MIMRE in actuators and self-healing materials was evaluated. The present MIMRE thus opens up a new avenue for the improvement of MR effect of magnetorheological elastomer, while avoiding the use of conventional plasticizer (e.g. silicon oil).

Yao, L, Sheng, QZ, Benatallah, B, Dustdar, S, Wang, X, Shemshadi, A & Kanhere, SS 2018, 'WITS: an IoT-endowed computational framework for activity recognition in personalized smart homes', Computing, vol. 100, no. 4, pp. 369-385.
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Yao, L, Sheng, QZ, Li, X, Gu, T, Tan, M, Wang, X, Wang, S & Ruan, W 2018, 'Compressive Representation for Device-Free Activity Recognition with Passive RFID Signal Strength', IEEE Transactions on Mobile Computing, vol. 17, no. 2, pp. 293-306.
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© 2017 IEEE. Understanding and recognizing human activities is a fundamental research topic for a wide range of important applications such as fall detection and remote health monitoring and intervention. Despite active research in human activity recognition over the past years, existing approaches based on computer vision or wearable sensor technologies present several significant issues such as privacy (e.g., using video camera to monitor the elderly at home) and practicality (e.g., not possible for an older person with dementia to remember wearing devices). In this paper, we present a low-cost, unobtrusive, and robust system that supports independent living of older people. The system interprets what a person is doing by deciphering signal fluctuations using radio-frequency identification (RFID) technology and machine learning algorithms. To deal with noisy, streaming, and unstable RFID signals, we develop a compressive sensing, dictionary-based approach that can learn a set of compact and informative dictionaries of activities using an unsupervised subspace decomposition. In particular, we devise a number of approaches to explore the properties of sparse coefficients of the learned dictionaries for fully utilizing the embodied discriminative information on the activity recognition task. Our approach achieves efficient and robust activity recognition via a more compact and robust representation of activities. Extensive experiments conducted in a real-life residential environment demonstrate that our proposed system offers a good overall performance and shows the promising practical potential to underpin the applications for the independent living of the elderly.

Yao, L, Sheng, QZ, Wang, X, Wang, S, Li, X & Wang, S 2018, 'Collaborative text categorization via exploiting sparse coefficients', World Wide Web, vol. 21, no. 2, pp. 373-394.
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© 2017, Springer Science+Business Media New York. Text categorization is widely characterized as a multi-label classification problem. Robust modeling of the semantic similarity between a query text and training texts is essential to construct an effective and accurate classifier. In this paper, we systematically investigate the Web page/text classification problem via integrating sparse representation with random measurements. In particular, we first adopt a very sparse data-independent random measurement matrix to map the original high dimensional text feature space to a lower dimensional space without loss of key information. We then propose a generic sparse representation method to obtain the sparse solution by decoding the semantic correlations between the query text and entire training samples. Based on the above method, we also design and examine a series of rules by taking advantage of the sparse coefficients to propagate multiple labels for the given query texts. We have conducted extensive experiments using real-world datasets to examine our proposed approach, and the results show the effectiveness of the proposed approach.

Yao, L, Sheng, QZ, Wang, X, Zhang, WE & Qin, Y 2018, 'Collaborative Location Recommendation by Integrating Multi-dimensional Contextual Information', ACM Transactions on Internet Technology, vol. 18, no. 3, pp. 1-24.
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Point-of-Interest (POI) recommendation is a new type of recommendation task that comes along with the prevalence of location-based social networks and services in recent years. Compared with traditional recommendation tasks, POI recommendation focuses more on making personalized and context-aware recommendations to improve user experience. Traditionally, the most commonly used contextual information includes geographical and social context information. However, the increasing availability of check-in data makes it possible to design more effective location recommendation applications by modeling and integrating comprehensive types of contextual information, especially the temporal information. In this article, we propose a collaborative filtering method based on Tensor Factorization, a generalization of the Matrix Factorization approach, to model the multi-dimensional contextual information. Tensor Factorization naturally extends Matrix Factorization by increasing the dimensionality of concerns, within which the three-dimensional model is the one most popularly used. Our method exploits a high-order tensor to fuse heterogeneous contextual information about users’ check-ins instead of the traditional two-dimensional user-location matrix. The factorization of this tensor leads to a more compact model of the data that is naturally suitable for integrating contextual information to make POI recommendations. Based on the model, we further improve the recommendation accuracy by utilizing the internal relations within users and locations to regularize the latent factors. Experimental results on a large real-world dataset demonstrate the effectiveness of our approach.

Yao, M, Woo, YC, Tijing, LD, Choi, J-S & Shon, HK 2018, 'Effects of volatile organic compounds on water recovery from produced water via vacuum membrane distillation', Desalination, vol. 440, pp. 146-155.
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© 2017 Elsevier B.V. Membrane distillation (MD) has great potentials to treat produced water in energy industries. However, volatile organic compounds (VOCs) existing in the produced water added in the fracking process can hinder the treatment process regarding two aspects: permeate quality and MD flux performance. To address this challenge, this study aims to systematically study the effects of the VOCs on the MD permeation performance and permeate quality, and the mechanism of its penetration. Acetic acid, ethylene glycol, isopropyl alcohol (IPA), and 2-Butoxyethanol (2-BE), which are commonly found in the produced water, were extensively investigated and their impacts were reviewed and compared. Among all the VOCs, 2-BE had the highest mass transfer despite its low vapour pressure and large molecule weight. Some of the VOCs had surfactant properties, which meant they could penetrate the membrane pores easily during MD process. In long-term operation, pore wetting started to appear as the salt rejection was dropping in the MD process, and flux was also decreasing. Based on the results, this study suggested that the strength of surfactant properties and intra-molecular hydrogen bonds between water molecules and VOCs are as significant as vapour pressure for the VOCs in terms of mass transfer efficiency in MD system.

Yaprak, A, Yosun, T & Cetindamar, D 2018, 'The influence of firm-specific and country-specific advantages in the internationalization of emerging market firms: Evidence from Turkey', International Business Review, vol. 27, no. 1, pp. 198-207.
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This paper examines the role of institutional factors that enable firm- and country-specific drivers of emerging market (EM) firms’ internationalization based on case-based research conducted in one EM, Turkey. Findings indicate that 10 major factors comprised of firm-specific and country-specific advantages drove the focal case study firms abroad: the firm-specific factors ranged from financial and operations supremacy; excellence in value chain activities; inexpensive human resources; rapid learning capabilities in production and technology development; and adaptability to foreign markets; while the country-specific factors included home-government policies supporting internationalization; logistical advantages arising from geographical position; adaptability capabilities resulting from former survival through institutional voids; strong social ties formed through networks; and availability of low cost resources. These findings are discussed and future research questions are offered.

Yasin, A, Liu, L, Li, T, Wang, J & Zowghi, D 2018, 'Design and preliminary evaluation of a cyber Security Requirements Education Game (SREG)', Information and Software Technology, vol. 95, pp. 179-200.
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© 2017 Elsevier B.V. Context: Security, in digitally connected organizational environments of today, involves many different perspectives, including social, physical, and technical factors. In order to understand the interactions among these correlated aspects and elicit potential threats geared towards a given organization, different security requirements analysis approaches are proposed in the literature. However, the body of knowledge is yet to unleash its full potential due to the complex nature of security problems, and inadequate ways to improve security awareness of key players in the organization. Objective: Objective(s) of the research study is to improve the security awareness of players utilizing serious games via: (i) Know-how of security concepts and security protection; (ii) guided process of identifying valuable assets and vulnerabilities in a given organizational setting; (iii) guided process of defining successful security attacks to the organization. Method: Important methods used to address the above objectives include: (i) a comprehensive review of the literature to better understand security and game design elements; (ii) designing a serious game using cyber security knowledge and game-based techniques combined with security requirements engineering concepts; (iii) using empirical evaluation (observation and survey) to verify the effectiveness of the proposed game design. Result: The solution proposed is a serious game for security requirements education, which: (i) can be an effective and fun way of learning security related concepts; (ii) mimics a real life problem setting in a presentable and understandable way; (iii) motivates players to learn more about security related concepts in future. Conclusion: From this study, we conclude that the proposed Security Requirement Education Game (SREG) has positive results and is helpful for players of the game to get an understanding of security attacks and vulnerabilities.

Ye, D & Zhang, M 2018, 'A Self-Adaptive Sleep/Wake-Up Scheduling Approach for Wireless Sensor Networks', IEEE Transactions on Cybernetics, vol. 48, no. 3, pp. 979-992.
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Sleep/wake-up scheduling is one of the fundamental problems in wireless sensor networks, since the energy of sensor nodes is limited and they are usually unrechargeable. The purpose of sleep/wake-up scheduling is to save the energy of each node by keeping nodes in sleep mode as long as possible (without sacrificing packet delivery efficiency) and thereby maximizing their lifetime. In this paper, a self-adaptive sleep/wake-up scheduling approach is proposed. Unlike most existing studies that use the duty cycling technique, which incurs a tradeoff between packet delivery delay and energy saving, the proposed approach, which does not us duty cycling, avoids such a tradeoff. The proposed approach, based on the reinforcement learning technique, enables each node to autonomously decide its own operation mode (sleep, listen, or transmission) in each time slot in a decentralized manner. Simulation results demonstrate the good performance of the proposed approach in various circumstances.

Ye, D, He, Q, Wang, Y & Yang, Y 2018, 'An agent-based service adaptation approach in distributed multi-tenant service-based systems', Journal of Parallel and Distributed Computing, vol. 122, pp. 11-25.
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Service adaptation aims to alleviate the runtime quality management problem of distributed service-based systems (SBSs). Most of the existing service adaptation approaches are designed for single-tenant SBSs. However, modern distributed SBSs must achieve multi-tenancy due to simultaneous existence of multiple tenants. Thus, it is vital to study service adaptation in distributed multi-tenant SBSs. Currently, service adaptation has not been properly addressed in distributed multi-tenant SBSs. Existing approaches for service adaptation in multi-tenant SBSs are centralised which are not very efficient if the SBSs are large and distributed. Some decentralised service adaptation approaches, which are developed in single-tenant SBSs, may be extended to accommodate multi-tenant SBSs. These approaches, however, either incur significant communication overhead to obtain required information, or simply assume that some specific global information is already known, which is not realistic in large and distributed SBSs. To overcome the limitations of existing approaches, in this paper, a novel agent-based hybrid service adaptation approach for distributed multi-tenant SBSs is proposed, which is based on the multi-agent coalition formation technique. Our hybrid approach combines the advantages of both centralised and decentralised approaches while avoiding their disadvantages. The experimental results demonstrate the effectiveness of the proposed approach.

Ye, D, He, Q, Wang, Y & Yang, Y 2018, 'Detection of transmissible service failure in distributed service-based systems', Journal of Parallel and Distributed Computing, vol. 119, pp. 36-49.
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© 2018 Elsevier Inc. Detection of service failure, also known as service monitoring, is an important research problem in distributed service-based systems (SBSs). Failure of services is a transmissible threat in distributed SBSs, because services in distributed SBSs may have dependent relationships among them and thus the failure of one service may cause the failure of other services. Therefore, such transmissible service failure has to be detected in a timely manner whereas the corresponding resource consumption should be as little as possible. Most of the existing service monitoring approaches are centralised which suffer the potential of single point of failure and are not suitable in large scale distributed SBSs. Moreover, these centralised approaches are designed only in single-tenant SBSs. Nowadays, the scale of distributed SBSs is extremely large, i.e., including a large number of services and clients. Thus, it is essential for monitoring approaches to work well in large scale distributed SBSs and support multi-tenancy. Towards this end, in this paper, a novel agent-based decentralised service monitoring approach is developed in distributed SBSs. Compared to the centralised approaches, the proposed decentralised approach can avoid the single point of failure and can balance the computation over the monitoring agents. Also, unlike existing approaches which consider only single tenancy, the proposed approach takes multi-tenancy into account in distributed SBSs. Experimental results demonstrate that the proposed approach can respond as quickly as centralised approaches with much less computation overhead.

Ye, D, Le, TP, Kuei, B, Zhu, C, Zwart, PH, Wang, C, Gomez, ED & Gomez, EW 2018, 'Resonant Soft X-Ray Scattering Provides Protein Structure with Chemical Specificity', Structure, vol. 26, no. 11, pp. 1513-1521.e3.
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Ye, K & Ji, J 2018, 'Natural Frequency Analysis of a Spar-Type Offshore Wind Turbine Tower With End Mass Components', Journal of Offshore Mechanics and Arctic Engineering, vol. 140, no. 6, pp. 1-5.
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Abstract Different from the fixed-based wind turbines, the floating type wind turbines are regarded as under a free–free end operating condition. The tower structure of a floating offshore wind turbine is an integrated part connecting the nacelle and support platform. An analytic solution is presented in this technical brief for the free-vibration of the tower structure of a spar-type offshore wind turbine. The tower structure is modeled as a free–free beam based on Euler–Bernoulli beam-column theory. The platform and the nacelle are considered as two large mass components connected by torsion springs at two tower ends with different stiffness. The effects of system parameters on the natural frequencies are investigated under a range of variables, including the tower structure parameters, platform and nacelle parameters, and the connection types. Nonlinear relationships between those variables and the natural frequency of the tower structure are numerically found and some design issues are discussed for the spar-type floating wind turbines.

Ye, K & Ji, J 2018, 'The effect of the rotor adjustment on the vibration behaviour of the drive-train system for a 5 MW direct-drive wind turbine', Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 232, no. 17, pp. 3027-3044.
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Direct-drive wind turbines, different from the standard geared wind turbines, widely use a direct-drive permanent-magnet generator to avoid the gearbox failures. In the absence of a gearbox in the drive-train system, the direct-drive generator operates at low rotating speeds. Thus direct-drive wind turbines require a larger sized generator (higher weight) to transfer the kinetic energy into electrical energy. The inherent unbalanced magnetic pull force of the generator can have impact on the vibration behaviour of the drive-train system. This paper studies the effect of rotor position and weight adjustment on the vibration behaviour of the drive-train system within a 5 MW direct-drive wind turbine by considering the unbalanced magnetic pull force. The adjustment of rotor position and weight changes the location of the centre of gravity of the drive-train system. The drive-train system which consists of the main shaft, rotor, hub and blades is modelled as a four degree-of-freedom nonlinear system. Both rotor displacement and bearing forces are obtained for a wide range of rotor position and weight under different rotating speeds. The obtained results would provide useful information on the optimized rotor position and mass ratio to improve the performance of the drive-train system.

Ye, L, Argha, A, Yu, H, Celler, BG, Nguyen, HT & Su, S 2018, 'Dynamic characteristics of oxygen consumption', BioMedical Engineering OnLine, vol. 17, no. 1, pp. 44-44.
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Previous studies have indicated that oxygen uptake ([Formula: see text]) is one of the most accurate indices for assessing the cardiorespiratory response to exercise. In most existing studies, the response of [Formula: see text] is often roughly modelled as a first-order system due to the inadequate stimulation and low signal to noise ratio. To overcome this difficulty, this paper proposes a novel nonparametric kernel-based method for the dynamic modelling of [Formula: see text] response to provide a more robust estimation.Twenty healthy non-athlete participants conducted treadmill exercises with monotonous stimulation (e.g., single step function as input). During the exercise, [Formula: see text] was measured and recorded by a popular portable gas analyser ([Formula: see text], COSMED). Based on the recorded data, a kernel-based estimation method was proposed to perform the nonparametric modelling of [Formula: see text]. For the proposed method, a properly selected kernel can represent the prior modelling information to reduce the dependence of comprehensive stimulations. Furthermore, due to the special elastic net formed by [Formula: see text] norm and kernelised [Formula: see text] norm, the estimations are smooth and concise. Additionally, the finite impulse response based nonparametric model which estimated by the proposed method can optimally select the order and fit better in terms of goodness-of-fit comparing to classical methods.Several kernels were introduced for the kernel-based [Formula: see text] modelling method. The results clearly indicated that the stable spline (SS) kernel has the best performance for [Formula: see text] modelling. Particularly, based on the experimental data from 20 participants, the estimated response from the proposed method with SS kernel was significantly better than the results from the benchmark method [i.e., prediction error method (PEM)] ([Formula: see text] vs [Formula: see text]).The proposed nonparametric modelling m...

Ye, Y, Liu, W, Jiang, W, Kang, J, Ngo, HH, Guo, W & Liu, Y 2018, 'Defluoridation by magnesia–pullulan: Surface complexation modeling and pH neutralization of treated fluoride water by aluminum', Journal of the Taiwan Institute of Chemical Engineers, vol. 93, pp. 625-631.
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Ye, Y, Ngo, HH, Guo, W, Liu, Y, Chang, SW, Nguyen, DD, Liang, H & Wang, J 2018, 'A critical review on ammonium recovery from wastewater for sustainable wastewater management', Bioresource Technology, vol. 268, pp. 749-758.
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© 2018 Elsevier Ltd The growing global population's demand for ammonium has triggered an increase in its supply, given that ammonium plays a crucial role in fertilizer production for the purpose of food security. Currently, ammonia used in fertilizer production is put through what is known as the industrial Haber Bosch process, but this approach is substantially expensive and requires much energy. For this reason, looking for effective methods to recover ammonium is important for environmental sustainability. One of the greatest opportunities for ammonium recovery occurs in wastewater treatment plants due to wastewater containing a large quantity of ammonium ions. The comprehensively and critically review studies on ammonium recovery conducted, have the potential to be applied in current wastewater treatment operations. Technologies and their ammonium recovery mechanisms are included in this review. Furthermore the economic feasibility of such processes is analysed. Possible future directions for ammonium recovery from wastewater are suggested.

Ye, Y, Yang, J, Jiang, W, Kang, J, Hu, Y, Ngo, HH, Guo, W & Liu, Y 2018, 'Fluoride removal from water using a magnesia-pullulan composite in a continuous fixed-bed column', Journal of Environmental Management, vol. 206, pp. 929-937.
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A magnesia-pullulan composite (MgOP) was previously shown to effectively remove fluoride from water. In the present study, a continuous fixed-bed column was used to examine the application of the composite at an industrial scale. The influencing parameters included bed mass (4.0, 6.0 and 8.0 g), influent flow rate (8, 16 and 32 mL/min), inlet fluoride concentration (5, 10 and 20 mg/L), reaction temperature (20, 30 and 40 °C), influent pH (4, 7 and 10) and other existing anions (HCO3-, SO42-, Cl- and NO3-), through which the breakthrough curves could be depicted for the experimental data analysis. The results indicated that MgOP is promising for fluoride removal with a defluoridation capacity of 16.6 mg/g at the bed mass of 6.0 g, influent flow rate of 16 mL/min and inlet fluoride concentration of 10 mg/L. The dynamics of the fluoride adsorption process were modeled using the Thomas and Yan models, in which the Yan model presented better predictions for the breakthrough curves than the Thomas model. Moreover, the concentration of magnesium in the effluent was monitored to determine Mg stability in the MgOP composite. Results indicated the effluent concentration of Mg2+ ions could be kept at a safe level. Calcination of fluoride-loaded MgOP effectively regenerated the material.

Yi, Z, Merenda, A, Kong, L, Radenovic, A, Majumder, M & Dumée, LF 2018, 'Single step synthesis of Schottky-like hybrid graphene - titania interfaces for efficient photocatalysis', Scientific Reports, vol. 8, no. 1, p. 8154.
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AbstractThe development of 2D nanomaterial coatings across metal surfaces is a challenge due to the mismatch between the metal microstructure and the nanoscale materials. The naturally occurring thin oxidative layer present across all metal surfaces, may lead to low adherence and connectivity. In this paper, graphene/titania/Titanium hybrid films were for the first time fabricated by a single step chemical vapour deposition process across Titanium foils. The presence of graphene as a dopant was found to enhance the photocatalytic performance of the final products, applied to the degradation of organic molecules and to lead to Schottky-like junction formation at the metal/oxide interface. These Schottky junctions, where vacancies are present across the titania material due to the graphene doping and where Ti3+ ions are predominantly located, yield enhanced catalytic performance. The highest degradation rate was found to be 9.66 × 10−6 min−1, achieved by the sample grown at 700 °C for 5 min, which was 62% higher than the sample just treated at that temperature without graphene growth. This work provides evidence that graphene may be grown across pure Titanium metal and opens new avenues in biomedical devices design, tribological or separation applications.

Yin, S, Ji, J, Deng, S & Wen, G 2018, 'Neimark-Sacker Bifurcations Near Degenerate Grazing Point in a Two Degree-of-Freedom Impact Oscillator', Journal of Computational and Nonlinear Dynamics, vol. 13, no. 11.
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Saddle-node or period-doubling bifurcations of the near-grazing impact periodic motions have been extensively studied in the impact oscillators, but the near-grazing Neimark-Sacker bifurcations have not been discussed yet. For the first time, this paper uncovers the novel dynamic behavior of Neimark-Sacker bifurcations, which can appear in a small neighborhood of the degenerate grazing point in a two degree-of-freedom impact oscillator. The higher order discontinuity mapping technique is used to determine the degenerate grazing point. Then, shooting method is applied to obtain the one-parameter continuation of the elementary impact periodic motion near degenerate grazing point and the peculiar phenomena of Neimark-Sacker bifurcations are revealed consequently. A two-parameter continuation is presented to illustrate the relationship between the observed Neimark-Sacker bifurcations and degenerate grazing point. New features that differ from the reported situations in literature can be found. Finally, the observed Neimark-Sacker bifurcation is verified by checking the existence and stability conditions in line with the generic theory of Neimark-Sacker bifurcation. The unstable bifurcating quasi-periodic motion is numerically demonstrated on the Poincaré section.

Yin, S, Yu, D, Luo, Z & Xia, B 2018, 'An arbitrary polynomial chaos expansion approach for response analysis of acoustic systems with epistemic uncertainty', Computer Methods in Applied Mechanics and Engineering, vol. 332, pp. 280-302.
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© 2017 Elsevier B.V. By introducing the arbitrary polynomial chaos theory, the Evidence-Theory-based Arbitrary Polynomial Chaos Expansion Method (ETAPCEM) is proposed to improve the computational accuracy of polynomial chaos expansion methods for the evidence-theory-based analysis of acoustic systems with epistemic uncertainty. In ETAPCEM, the epistemic uncertainty of acoustic systems is treated with evidence theory. The response of acoustic systems in the range of variation of evidence variables is approximated by the arbitrary polynomial chaos expansion, through which the lower and upper bounds of the response over all focal elements can be efficiently calculated by a number of numerical solvers. Inspired by the application of polynomial chaos theory in the interval and random analysis, the weight function of the optimal polynomial basis of ETAPCEM for evidence-theory-based uncertainty analysis is derived from the uniformity approach. Compared with the conventional evidence-theory-based polynomial chaos expansion methods, including the recently proposed evidence-theory-based Jacobi expansion method, the main advantage of ETAPCEM is that the polynomial basis orthogonalized with arbitrary weight functions can be obtained to construct the polynomial chaos expansion. Thereby the optimal polynomial basis of polynomial chaos expansion for arbitrary types of the evidence variable can be established by using ETAPCEM. The effectiveness of the proposed method for acoustic problems has been fully demonstrated by comparing it with the conventional evidence-theory-based polynomial chaos expansionmethods.

Yin, S, Yu, D, Luo, Z & Xia, B 2018, 'Unified polynomial expansion for interval and random response analysis of uncertain structure–acoustic system with arbitrary probability distribution', Computer Methods in Applied Mechanics and Engineering, vol. 336, pp. 260-285.
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© 2018 Elsevier B.V. For structure–acousticsystem with uncertainties, the interval model, the random model and the hybrid uncertain model have been introduced. In the interval model and the random model, the uncertain parameters are described as either the random variable with well defined probability density function (PDF) or the interval variable without any probability information, whereas in the hybrid uncertain model both interval variable and random variable exist simultaneously. For response analysis of these three uncertain models of structure–acoustic problem involving arbitrary PDFs, a unified polynomial expansion method named as the Interval and Random Arbitrary Polynomial Chaos method (IRAPCM) is proposed. In IRAPCM, the response of the structure–acoustic system is approximated by APC expansion in a unified form. Particularly, only the weight function of polynomial basis is required to be changed to construct the APC expansion for the response of different uncertain models. Through the unified APC expansion, the uncertain properties of the response of three uncertain models can be efficiently obtained. As the APC expansion can provide a free choice of the polynomial basis, the optimal polynomial basis for the random variable with arbitrary PDFs can be obtained by using the proposed IRAPCM. The IRAPCM has been employed to solve a mathematical problem and a structure–acoustic problem, and the effectiveness of the unified IRAPCM for response analysis of three uncertain models is demonstrated by fully comparing it with the hybrid first-order perturbation method and several existing polynomial chaos methods.

Ying, M 2018, 'Toward Automatic Verification of Quantum Programs.', CoRR, vol. abs/1807.11610, no. 1, pp. 3-25.
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© 2018, British Computer Society. This paper summarises the results obtained by the author and his collaborators in a program logic approach to the verification of quantum programs, including quantum Hoare logic, invariant generation and termination analysis for quantum programs. It also introduces the notion of proof outline and several auxiliary rules for more conveniently reasoning about quantum programs. Some problems for future research are proposed at the end of the paper.

Ying, M & Feng, Y 2018, 'Model Checking Quantum Systems - A Survey.', CoRR, vol. abs/1807.09466, no. 1, pp. 28-31.
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Ying, XY, Kan, Q & Ding, G 2018, 'The form of street spatial layout based on a wind environmental perspective', Lowland Technology International, vol. 20, no. 3, pp. 305-312.
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With China's rapid urbanization, the construction of central areas in city with numerous buildings and dense population has greatly changed the microclimate. Different street spatial layouts change the internal wind environment, which affect the pedestrian comfort. Computational fluid dynamics (CFD) models are used to study the correlation between the three-main street spatial layout factors, which are near-line rate, street interface density and street aspect ratio, under the simulation of relevant weather conditions. Firstly, the wind speed within the street change with the increase of the near-line rate like a parabola trend, and the wind speed reaches its peak about at a near-line rate of 70%. In that case, it’s conducive to ventilation. Secondly, with the reduction of street interface density the variation of the wind speed of each measuring point in the streets is getting bigger and bigger, and the pedestrian walking in them will feel the change of wind speed which makes the comfort of pedestrian decrease. Thirdly, the average wind speed in urban streets is inversely proportional to the street aspect ratio. These conclusions will provide an important reference and evaluation basis for urban designers at the beginning of design and effectively avoid future wind environment problems.

Ying, XY, Li, WZ, Kan, Q, Zhang, Z & Ding, G 2018, 'Numerical method for shape optimization of standard floor of the high-rise buildings in hot-summer and cold-winter areas under the low energy consumption target—taking the L-shape as an example', Lowland Technology International, vol. 20, no. 1, pp. 57-64.
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Shape is an important consideration in building design due to its significant impact on building performance in energy consumption. This paper presents a methodology to program planes using MATLAB language. Three side length factors were proposed as the design variables for L-shaped layouts, and eighteen kinds of L-shaped layouts were generated by changing those variables individually. An energy consumption simulation software (DesignBuilder) was developed to simulate the energy consumption of these layouts of high-rise buildings as experimental models. The correlativity between the width ratio and depth ratio of all experimental models and their energy consumption was examined when deriving the corresponding polynomial function. The main finding of the study suggested that there were certain critical points for both width ratio and depth ratio of the standard floor of high-rise buildings with L-shaped plane, which was 0.4 for width ratio and 0.67 for depth ratio. The energy consumption increased rapidly beyond the critical point, and there was a slight fluctuation at another interval. Further, this paper provided a range of side length ratio in contour plots which showed the variation of energy consumption of L-shape high-rise buildings with width ratio and depth ratio under the weather condition in Hangzhou, China.

Young, AIJ, Timpson, P, Gallego-Ortega, D, Ormandy, CJ & Oakes, SR 2018, 'Myeloid cell leukemia 1 (MCL-1), an unexpected modulator of protein kinase signaling during invasion', Cell Adhesion & Migration, vol. 12, no. 6, pp. 513-523.
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Youssry, A, Ferrie, C & Tomamichel, M 2018, 'Efficient online quantum state estimation using a matrix-exponentiated gradient method', New J. Phys., vol. 21, no. 3, p. 033006.
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In this paper, we explore an efficient online algorithm for quantum stateestimation based on a matrix-exponentiated gradient method previously used inthe context of machine learning. The state update is governed by a learningrate that determines how much weight is given to the new measurement resultsobtained in each step. We show convergence of the running state estimate inprobability to the true state for both noiseless and noisy measurements. Wefind that in the latter case the learning rate has to be chosen adaptively anddecreasing to guarantee convergence beyond the noise threshold. As a practicalalternative we then propose to use running averages of the measurementstatistics and a constant learning rate to overcome the noise problem. Theproposed algorithm is numerically compared with batch maximum-likelihood andleast-squares estimators. The results show a superior performance of the newalgorithm in terms of accuracy and runtime complexity.

Yu, D, Xu, Z, Kao, Y & Lin, C-T 2018, 'The Structure and Citation Landscape of IEEE Transactions on Fuzzy Systems (1994–2015)', IEEE Transactions on Fuzzy Systems, vol. 26, no. 2, pp. 430-442.
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Yu, G, Liu, J, Du, J, Hu, M & Sugumaran, V 2018, 'An Integrated Approach for Massive Sequential Data Processing in Civil Infrastructure Operation and Maintenance', IEEE Access, vol. 6, pp. 19739-19751.
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Yu, H, Ye, L, Naik, GR, Song, R, Nguyen, HT & Su, SW 2018, 'Nonparametric dynamical model of cardiorespiratory responses at the onset and offset of treadmill exercises', Medical & Biological Engineering & Computing, vol. 56, no. 12, pp. 2337-2351.
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© 2018, International Federation for Medical and Biological Engineering. This paper applies a nonparametric modelling method with kernel-based regularization to estimate the carbon dioxide production during jogging exercises. The kernel selection and regularization strategies have been discussed; several commonly used kernels are compared regarding the goodness-of-fit, sensitivity, and stability. Based on that, the most appropriate kernel is then selected for the construction of the regularization term. Both the onset and offset of the jogging exercises are investigated. We compare the identified nonparametric models, which include both impulse response models and step response models for the two periods, as well as the relationship between oxygen consumption and carbon dioxide production. The result statistically indicates that the steady-state gain of the carbon dioxide production in the onset of exercise is bigger than that in the offset while the response time of both onset and offset are similar. Compared with oxygen consumption, the response speed of carbon dioxide production is slightly slower in both onset and offset period while its steady-state gains are similar for both periods. The effectiveness of the kernel-based method for the dynamic modelling of cardiorespiratory response to exercise is also well demonstrated. [Figure not available: see fulltext.].

Yu, J, Ji, J, Miao, Z & Zhou, J 2018, 'Formation control with collision avoidance for uncertain networked Lagrangian systems via adaptive gain techniques', IET Control Theory & Applications, vol. 12, no. 10, pp. 1393-1401.
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This study addresses the problem of formation control with collision avoidance for networked Lagrangian systems with uncertain parameters interacting on directed network communication topologies. Two adaptive formation control strategies with collision avoidance are proposed by making use of adaptive gain techniques for both cases of with and without a dynamic leader. The main objective of the proposed control strategies is to dispatch a group of agents to maintain a desired geometric pattern, while still guarantee collision avoidance at any time, and eventually to achieve velocity matching. A distinctive feature of the developed adaptive gain is to adapt itself duly based on both the network communication topology and collision avoidance constraints, so it is feasible to be implemented in practice. Some general criteria are derived to guarantee that the desired formation with collision avoidance for the networked Lagrangian systems can be achieved. Finally, numerical simulations are given to show the performance of the proposed control methodologies.

Yu, KL, Show, PL, Ong, HC, Ling, TC, Chen, W-H & Salleh, MAM 2018, 'Biochar production from microalgae cultivation through pyrolysis as a sustainable carbon sequestration and biorefinery approach', Clean Technologies and Environmental Policy, vol. 20, no. 9, pp. 2047-2055.
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Yu, X & Porikli, F 2018, 'Imagining the Unimaginable Faces by Deconvolutional Networks', IEEE Transactions on Image Processing, vol. 27, no. 6, pp. 2747-2761.
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Yu, Y, Chen, X, Gao, W, Li, Q, Wu, D & Liu, M 2018, 'Stochastic leaching analysis on cementitious materials considering the influence of material uncertainty', Construction and Building Materials, vol. 184, pp. 186-202.
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© 2018 Elsevier Ltd Uncertainties significantly influence the durability-related experiments and field studies, which can hardly be addressed by deterministic approaches. This work aims at developing a stochastic numerical framework to disentangle the influence of material uncertainty on the case of leaching. To ensure the robustness of the numerical framework, a realistic stochastic reactive-transportation model is developed, which consists of a novel sampling algorithm and a comprehensive deterministic model. By using the proposed sampling algorithm, a more effective and efficient sampling process can be achieved without compromising the randomness of the uncertain properties. Besides, realistic mechanisms of leaching are considered by the deterministic model, including the simultaneous processes of ionic transportation, chemical reactions and material degradation. By performing the stochastic leaching analyses, numerical results suggest the overwhelming influence of the physical uncertainty on long-term leaching, while the impact of chemical uncertainty is more evident in terms of short-term leaching. It is also revealed that the root-time relation as determined from short-term experiments is inappropriate for long-term predictions. Thus, a modified relation is developed based on the stochastic leaching analysis, which generates accurate predictions for both the short-term and long-term leaching.

Yu, Y, Li, W, Li, J & Nguyen, TN 2018, 'A novel optimised self-learning method for compressive strength prediction of high performance concrete', Construction and Building Materials, vol. 184, pp. 229-247.
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© 2018 Elsevier Ltd Concrete strength (CS) is one of the most important performance parameters that are crucial in the design of concrete structure. The reliable prediction of strength can reduce the cost and time in design and avoid the waste of materials caused by a large number of mixture trials. In this study, a novel predictive model is put forward to predict the CS of high performance concrete (HPC) using support vector machine (SVM) approach, which has benefits of nonlinear mapping, high robustness and great generalisation capacity. In the proposed model, the input variables include the contents of water, cement, blast furnace slag, fly ash, super plasticiser, coarse and fine aggregates and curing age, which produces the CS of HPC as the output. In order to improve the model performance, a type of enhanced cat swarm optimisation (ECSO) is adopted to optimise the key parameters of SVM. Finally, the model is trained and evaluated using a total of 1761 data records, which are collected from existing literatures. The results indicate that the proposed SVM-based model exhibits better recognition ability and higher prediction accuracy than other commonly used models, and it can be considered as an effective method to predict the CS property of HPC in infrastructure practice.

Yu, Y, Li, Y, Li, J, Gu, X & Royel, S 2018, 'Nonlinear Characterization of the MRE Isolator Using Binary-Coded Discrete CSO and ELM', International Journal of Structural Stability and Dynamics, vol. 18, no. 08, pp. 1840007-1840007.
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Magnetorheological elastomer (MRE) isolator has been proved as a promising semi-active control device for structural vibration control. For its engineering application, developing an accurate and robust model is definitely necessary and also a challenging task. Most of the present models, belonging to parametric models, need to identify various model parameters and sometimes are not capable of perfectly capturing the unique characteristics of the device. In this work, a novel nonparametric model is proposed to characterize the inherent dynamics of the MRE isolator with the features of hysteresis and nonlinearity. Initially, dynamic tests are conducted to evaluate the performance of the isolator under various loading conditions, including harmonic, random, and seismic excitations. Then, on the basis of the captured experimental results, a hybrid learning method is designed to forecast the nonlinear responses of the device with known external inputs. In this method, a type of single hidden layer feed-forward network, called extreme learning machine (ELM), is developed to forecast the nonlinear responses (shear force) of the device with captured velocity, displacement, and current level. To obtain optimal performance of the developed model, an improved binary-coded discrete cat swarm optimization (BCDCSO) method is adopted to select optimal inputs and neuron number in the hidden layer for the network development. The performance of the proposed method is verified through the comparison between experimental results and model predictions. Due to the noise influence in the practical condition, the robustness of the proposed method is also validated via adding noise disturbance into the supplying currents. The results show that the proposed method outperforms the standard ELM in terms of characterization of the MRE isolator, even though the captured responses are polluted with external measurement noises.

Yu, Z, Zhang, X, Ngo, HH, Guo, W, Wen, H, Deng, L, Li, Y & Guo, J 2018, 'Removal and degradation mechanisms of sulfonamide antibiotics in a new integrated aerobic submerged membrane bioreactor system', Bioresource Technology, vol. 268, pp. 599-607.
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Yuan, B, Jin, H, Zou, D, Yang, LT & Yu, S 2018, 'A Practical Byzantine-Based Approach for Faulty Switch Tolerance in Software-Defined Networks', IEEE Transactions on Network and Service Management, vol. 15, no. 2, pp. 825-839.
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© 2004-2012 IEEE. Over the past few years, software-defined networking (SDN) has stimulated worldwide interests in both academia and industry for its proven benefits. However, the reliability of SDN has become a significant barrier in adopting it. Many efforts have been made to enhance the reliability of SDNs. However, the research all assume a benign data plane, and overlook the fundamental question: what if the switches provide tainted network state information (controller's inputs) to the controller? To obtain a global view and produce networking decisions, SDN controllers must collect detailed and up-to-date network state information from the switches. Therefore, tainted inputs can easily disrupt the correctness of controller and reduce the reliability of SDN. In this paper, we argue that faulty switches can easily taint the controller's inputs in SDN, which would further mislead the controller. We investigate possible consequences of the existence of faulty switches with thorough analyses and practical examples. Aiming at enhancing the reliability of SDNs, we design and implement a prototype system that leverages Byzantine model to automatically tolerate faulty switches. Extensive experiments show that the proposed system can guarantee the correctness of the controller's inputs (specifically, flow statistics information) even when faulty switches exist with trivial overheads.

Yuan, L, Qin, L, Zhang, W, Chang, L & Yang, J 2018, 'Index-Based Densest Clique Percolation Community Search in Networks.', IEEE Trans. Knowl. Data Eng., vol. 30, no. 5, pp. 922-935.
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© 1989-2012 IEEE. Community search is important in graph analysis and can be used in many real applications. In the literature, various community models have been proposed. However, most of them cannot well identify the overlaps between communities which is an essential feature of real graphs. To address this issue, the κ-clique percolation community model was proposed and has been proven effective in many applications. Motivated by this, in this paper, we adopt the κ-clique percolation community model and study the densest clique percolation community search problem which aims to find the κ-clique percolation community with the maximum K value that contains a given set of query nodes. We adopt an index-based approach to solve this problem. Based on the observation that a κ-clique percolation community is a union of maximal cliques, we devise a novel compact index, DCPC - Index, to preserve the maximal cliques and their connectivity information of the input graph. With DCPC- Index, we can answer the densest clique percolation community query efficiently. Besides, we also propose an index construction algorithm based on the definition of DCPC-Index and further improve the algorithm in terms of efficiency and memory consumption. We conduct extensive performance studies on real graphs and the experimental results demonstrate the efficiency of our index-based query processing algorithm and index construction algorithm.

Yuan, W, Wu, N, Yan, C, Li, Y, Huang, X & Hanzo, L 2018, 'A Low-Complexity Energy-Minimization-Based SCMA Detector and Its Convergence Analysis', IEEE Transactions on Vehicular Technology, vol. 67, no. 12, pp. 12398-12403.
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© 2018 IEEE. Sparse code multiple access (SCMA) has emerged as a promising non-orthogonal multiple access technique for the next-generation wireless communication systems. Since the signal of multiple users is mapped to the same resources in SCMA, its detection imposes a higher complexity than that of the orthogonal schemes, where each resource slot is dedicated to a single user. In this paper, we propose a low-complexity receiver for SCMA systems based on the radical variational free energy framework. By exploiting the pairwise structure of the likelihood function, the Bethe approximation is utilized for estimating the data symbols. The complexity of the proposed algorithm only increases linearly with the number of users, which is much lower than that of the maximum a posteriori detector associated with exponentially increased complexity. Furthermore, the convergence of the proposed algorithm is analyzed, and its convergence conditions are derived. Simulation results demonstrate that the proposed receiver is capable of approaching the error probability performance of the conventional message-passing-based receiver.

Yuan, X, Feng, Z, Xu, W, Ni, W, Zhang, JA, Wei, Z & Liu, RP 2018, 'Capacity Analysis of UAV Communications: Cases of Random Trajectories', IEEE Transactions on Vehicular Technology, vol. 67, no. 8, pp. 7564-7576.
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© 1967-2012 IEEE. This paper analyzes the link capacity between autonomous unmanned aerial vehicles (UAVs) with random three-dimensional (3-D) trajectories. This is distinctively different from existing works typically under the assumption of either two-dimensional (2-D) or deterministic trajectories, and particularly interesting to applications such as surveillance and air combat. The key idea is that we geometrically derive the probability distributions of the UAV-to-UAV (U2U) distances which, by exploiting the Jensen's inequality, can be translated to the closed-form bounds for the capacity between UAVs, and between UAVs and ground stations. Another important aspect is that we extrapolate the idea to dense UAV networks, and analyze the impact of network densification, imperfect channel state information, and interference from ground transmitters on the capacity. Corroborated by simulations, our analysis shows that a U2U link with random 2-D trajectories is superior in terms of capacity due to its short average link distance. It is also revealed that a UAV-to-ground link can incur substantially lower capacity than a U2U link even in the case the 3-D coverage of the UAVs is the same, as the result of its longer average link length.

Yuan, X, Feng, Z-Y, Xu, W-J, Wei, Z-Q & Liu, R-P 2018, 'Secure connectivity analysis in unmanned aerial vehicle networks', Frontiers of Information Technology & Electronic Engineering, vol. 19, no. 3, pp. 409-422.
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© 2018, Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature. The distinctive characteristics of unmanned aerial vehicle networks (UAVNs), including highly dynamic network topology, high mobility, and open-air wireless environments, may make UAVNs vulnerable to attacks and threats. In this study, we propose a novel trust model for UAVNs that is based on the behavior and mobility pattern of UAV nodes and the characteristics of inter-UAV channels. The proposed trust model consists of four parts: direct trust section, indirect trust section, integrated trust section, and trust update section. Based on the trust model, the concept of a secure link in UAVNs is formulated that exists only when there is both a physical link and a trust link between two UAVs. Moreover, the metrics of both the physical connectivity probability and the secure connectivity probability between two UAVs are adopted to analyze the connectivity of UAVNs. We derive accurate and analytical expressions of both the physical connectivity probability and the secure connectivity probability using stochastic geometry with or without Doppler shift. Extensive simulations show that compared with the physical connection probability with or without malicious attacks, the proposed trust model can guarantee secure communication and reliable connectivity between UAVs and enhance network performance when UAVNs face malicious attacks and other security risks.

Yuan, X, Li, B, Sun, H, Yang, Y, Meng, H, Xu, L, Song, Y & Xu, J 2018, 'Surgical Outcome in Adolescents and Adults With Anomalous Left Coronary Artery From Pulmonary Artery', The Annals of Thoracic Surgery, vol. 106, no. 6, pp. 1860-1867.
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Yuan, X, Teng, X, Wang, Y & Yao, Y 2018, 'Recipient treatment with acetylcholinesterase inhibitor donepezil attenuates primary graft failure in rats through inhibiting post-transplantational donor heart ischaemia/reperfusion injury', European Journal of Cardio-Thoracic Surgery, vol. 53, no. 2, pp. 400-408.
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Yusoff, B, Merigó, JM, Ceballos, D & Peláez, JI 2018, 'Weighted-selective aggregated majority-OWA operator and its application in linguistic group decision making', International Journal of Intelligent Systems, vol. 33, no. 9, pp. 1929-1948.
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© 2018 Wiley Periodicals, Inc. This paper focuses on the aggregation operations in the group decision-making model based on the concept of majority opinion. The weighted-selective aggregated majority-OWA (WSAM-OWA) operator is proposed as an extension of the SAM-OWA operator, where the reliability of information sources is considered in the formulation. The WSAM-OWA operator is generalized to the quantified WSAM-OWA operator by including the concept of linguistic quantifier, mainly for the group fusion strategy. The QWSAM-IOWA operator, with an ordering step, is introduced to the individual fusion strategy. The proposed aggregation operators are then implemented for the case of alternative scheme of heterogeneous group decision analysis. The heterogeneous group includes the consensus of experts with respect to each specific criterion. The exhaustive multicriteria group decision-making model under the linguistic domain, which consists of two-stage aggregation processes, is developed in order to fuse the experts’ judgments and to aggregate the criteria. The model provides greater flexibility when analyzing the decision alternatives with a tolerance that considers the majority of experts and the attitudinal character of experts. A selection of investment problem is given to demonstrate the applicability of the developed model.

Yuting, L, Li, C, Zhou, K, Guan, G, Appleton, PL, Lang, S, McGloin, D, Huang, Z & Nabi, G 2018, 'Microscale characterization of prostate biopsies tissues using optical coherence elastography and second harmonic generation imaging', Laboratory Investigation, vol. 98, no. 3, pp. 380-390.
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© 2018 USCAP, Inc All rights reserved. Photonics, especially optical coherence elastography (OCE) and second harmonic generation (SHG) imaging are novel high-resolution imaging modalities for characterization of biological tissues. Following our preliminary experience, we hypothesized that OCE and SHG imaging would delineate the microstructure of prostate tissue and aid in distinguishing cancer from the normal benign prostatic tissue. Furthermore, these approaches may assist in characterization of the grade of cancer, as well. In this study, we confirmed a high diagnostic accuracy of OCE and SHG imaging in the detection and characterization of prostate cancer for a large set of biopsy tissues obtained from men suspected to have prostate cancer using transrectal ultrasound (TRUS). The two techniques and methods described here are complementary, one depicts the stiffness of tissues and the other illustrates the orientation of collagen structure around the cancerous lesions. The results showed that stiffness of cancer tissue was ∼57.63% higher than that of benign tissue (Young's modulus of 698.43±125.29 kPa for cancerous tissue vs 443.07±88.95 kPa for benign tissue with OCE. Using histology as a reference standard and 600 kPa as a cut-off threshold, the data analysis showed sensitivity and specificity of 89.6 and 99.8%, respectively. Corresponding positive and negative predictive values were 99.5 and 94.6%, respectively. There was a significant difference noticed in terms of Young's modulus for different Gleason scores estimated by OCE (P-value<0.05). For SHG, distinct patterns of collagen distribution were seen for different Gleason grade disease with computed quantification employing a ratio of anisotropic to isotropic (A:I ratio) and this correlated with disease aggressiveness.

Zahid, R, Hj. Hassan, M, Alabdulkarem, A, Varman, M, Kalam, MA, Mufti, RA, Mohd Zulkifli, NW, Gulzar, M, Bhutta, MU, Ali, MA, Abdullah, U & Yunus, RH 2018, 'Tribological characteristics comparison of formulated palm trimethylolpropane ester and polyalphaolefin for cam/tappet interface of direct acting valve train system', Industrial Lubrication and Tribology, vol. 70, no. 5, pp. 888-901.
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PurposeThere is a continuous drive in automotive sector to shift from conventional lubricants to environmental friendly ones without adversely affecting critical tribological performance parameters. Because of their favorable tribological properties, chemically modified vegetable oils such as palm trimethylolpropane ester (TMP) are one of the potential candidates for the said role. To prove the suitability of TMP for applications involving boundary-lubrication regime such as cam/tappet interface of direct acting valve train system, a logical step forward is to investigate their compatibility with conventional lubricant additives.Design/methodology/approachIn this study, extreme pressure and tribological characteristics of TMP, formulated with glycerol mono-oleate (GMO), molybdenum dithiocarbamate (MoDTC) and zinc dialkyldithiophosphate (ZDDP), has been investigated using four-ball wear tester and valve train test rig. For comparison, additive-free and formulated versions of polyalphaolefin (PAO) were used as reference. Moreover, various surface characterization techniques were deployed to investigate mechanisms responsible for a particular tribological behavior.FindingsIn additive-free form, TMP demonstrated better extreme pressure characteristics compared to PAO and lubricant additives which are actually optimized for conventional base-oils such as PAO, are also proved to be compatible with TMP to some extent, especially ZDDP. During cylinder head tests, additive-free TMP proved to be more effective compared to PAO in reducing friction of cam/tappet interface, but opposite behavior was seen when formulated lubricants were used. Therefore, there is a need to synthesize speci...

Zahid, R, Mufti, RA, Gulzar, M, Bin Haji Hassan, M, Alabdulkarem, A, Varman, M, Kalam, MA, Binti Mohd Zulkifli, NW & Yunus, R 2018, 'Tribological compatibility analysis of conventional lubricant additives with palm trimethylolpropane ester (TMP) and tetrahedral amorphous diamond-like carbon coating (ta-C)', Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, vol. 232, no. 8, pp. 999-1013.
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Modern industrial applications involve rigorous operating conditions due to which lubricant either slips out of the contact or its thin layer resides between the interacting surfaces. Deposition of diamond-like carbon coatings and using lubricants capable of physically adsorbing on the interacting surfaces can significantly improve tribological performance. In this study, tribological compatibility of glycerol mono-oleate, molybdenum dithiocarbamate and zinc dialkyldithiophosphate with palm trimethylolpropane ester and tetrahedral amorphous diamond-like carbon coating has been investigated using universal wear testing machine. For comparison, additive-free and formulated versions of polyalphaolefin were used. Moreover, spectroscopic techniques were used to investigate mechanisms responsible for a particular tribological behavior. Among base oils, trimethylolpropane ester proved to be more effective in enhancing friction performance and mitigating wear of contacts when one of the interacting surfaces was ferrous-based. Self-mated tetrahedral amorphous diamond-like carbon coating surfaces resulted in lowest values of friction and wear coefficient of balls.

Zainal, BS, Zinatizadeh, AA, Chyuan, OH, Mohd, NS & Ibrahim, S 2018, 'Effects of process, operational and environmental variables on biohydrogen production using palm oil mill effluent (POME)', International Journal of Hydrogen Energy, vol. 43, no. 23, pp. 10637-10644.
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Zakeri, A, Saberi, M, Hussain, OK & Chang, E 2018, 'Addressing Missing Data and Data Competitiveness Issues: Transforming Tacit Knowledge into Explicit Form by Fuzzy Inference Learning System', International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1224-1239.
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© 2017, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. Although we are living in the era of big data, in many real-world applications, being able to access the right set and quantity of data is still a challenging task. One solution to address this drawback is to transform the existing information and knowledge from its tacit form back to data which can be used to simulate and regenerate the required knowledge in different scenarios for further analysis in explicit form. In this paper, we present our developed fuzzy inference-based learning system to achieve this objective. Our proposed framework is based on both conventional fuzzy-based modelling and the adaptive network-based fuzzy inference system (ANFIS) that first transforms the existing tacit information and knowledge into a fuzzy form which is then fed into ANFIS to develop a trained model that regenerates them for analysis purposes. We validate our proposed model and demonstrate its accuracy to estimate the fuel efficiency of heavy duty trucks using real-world data.

Zakeri, A, Saberi, M, Hussain, OK & Chang, E 2018, 'An Early Detection System for Proactive Management of Raw Milk Quality: An Australian Case Study', IEEE Access, vol. 6, pp. 64333-64349.
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© 2013 IEEE. Milk is a highly perishable product, whose quality degrades while moving downstream in an imperfect cold dairy supply chain. Existing literature adopts a reactive approach for evaluating and preventing milk with a high microbial index from moving further downstream in a dairy supply chain. In this paper, we argue that such an approach is not the best response if the intention is to maximize milk life in terms of quality. We propose a proactive approach that monitors the metrics of the temperature and the level that are the building blocks of microorganisms in milk. This information is then used to determine the status at which the storage tank should hold the milk in accordance with standards. This status is then compared with the tank's actual status, and if they are different from one another, it will prompt the farmers to take the required preventive actions to manage the quality of milk. The developed proactive management of raw milk quality approach is modeled by using a rule-based system and machine learning techniques with a high level of accuracy. To test the validity of our approach and demonstrate its applicability, we apply it to a milk farm in Queensland, Australia.

Zeng, D, Zhang, S, Gu, L, Yu, S & Fu, Z 2018, 'Quality-of-sensing aware budget constrained contaminant detection sensor deployment in water distribution system', Journal of Network and Computer Applications, vol. 103, pp. 274-279.
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© 2017 Elsevier Ltd Water contamination or pollution has raised serious disasters and social impact. It is significant to alleviate its impact or reduce the risks. Deploying water quality monitoring sensors in the water distribution systems naturally becomes a promising solution. In the consideration of sensor deployment, the deployment cost and the achieved quality-of-sensing, usually in terms of coverage, are always two contradictive issues. Although massively deploying sensors implies higher quality-of-sensing, it may also incur extremely high deployment cost. Actually, it is usually infeasible with the consideration of limited sensor deployment budget. In this paper, we are motivated to investigate a budget constrained sensor deployment in water distribution system, with the goal of maximizing the quality-of-sensing. Two kinds of sensors with different prices and hence different communication capabilities are considered. The cheaper one equips with only sensor-to-sensor communication capability. While, the expensive one is further capable of cellular communication. We first formally describe our problem using a mixed integer non-linear programming (MINLP) problem. To address the complexity on solving MINLP, we further propose a heuristic algorithm based on genetic algorithm, whose high efficiency is extensively validated by simulation based studies.

Zeng, J, Lv, T, Liu, RP, Su, X, Peng, M, Wang, C & Mei, J 2018, 'Investigation on Evolving Single-Carrier NOMA Into Multi-Carrier NOMA in 5G', IEEE Access, vol. 6, pp. 48268-48288.
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© 2013 IEEE. Non-orthogonal multiple access (NOMA) is one promising technology, which provides high system capacity, low latency, and massive connectivity, to address several challenges in the fifth-generation wireless systems. In this paper, we first reveal that the NOMA techniques have evolved from single-carrier NOMA (SC-NOMA) into multi-carrier NOMA (MC-NOMA). Then, we comprehensively investigated on the basic principles, enabling schemes and evaluations of the two most promising MC-NOMA techniques, namely sparse code multiple access (SCMA) and pattern division multiple access (PDMA). Meanwhile, we consider that the research challenges of SCMA and PDMA might be addressed with the stimulation of the advanced and matured progress in SC-NOMA. Finally, yet importantly, we investigate the emerging applications, and point out the future research trends of the MC-NOMA techniques, which could be straightforwardly inspired by the various deployments of SC-NOMA.

Zeng, J, Peng, J, Liu, RP & Su, X 2018, 'Comments on “Cross-Tier Cooperation for Optimal Resource Utilization in Ultra-Dense Heterogeneous Networks”', IEEE Transactions on Vehicular Technology, vol. 67, no. 11, pp. 11307-11308.
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© 2018 IEEE. Two adaptive dedicated channel allocation algorithms, namely dynamic dedicated channel partitioning (D2CP) and dynamic dedicated channel partitioning with cooperation (D2CP-C), were proposed in [1] to improve the system throughput of ultra-dense networks (UDN). However, due to the incorrect use of the geometric-arithmetic mean inequality theorem, the average system throughput could not be guaranteed to be optimal. In this letter, we study the proposed D2CP and D2CP-C algorithms in UDN and deduce the average system throughput. Consequently, we prove that the equal resource allocation strategy proposed in [1] is strictly not optimal.

Zeng, X & Lu, J 2018, 'Decision Support Systems with Uncertainties in Big Data Environments', Knowledge-Based Systems, vol. 143, pp. 327-327.
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Zeng, X, Wen, S, Zeng, Z & Huang, T 2018, 'Design of memristor-based image convolution calculation in convolutional neural network', Neural Computing and Applications, vol. 30, no. 2, pp. 503-508.
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In this paper, an architecture based on memristors is proposed to implement image convolution computation in convolutional neural networks. This architecture could extract different features of input images when using different convolutional kernels. Bipolar memristors with threshold are employed in this work, which vary their conductance values under different voltages. Various kernels are needed to extract information of input images, while different kernels contain different weights. The memristances of bipolar memristors with threshold are convenient to be varied and kept, which make them suitable to act as the weights of kernels. The performances of the design are verified by simulation results.

Zeng, Y, Li, K, Yu, S, Zhou, Y & Li, K 2018, 'Parallel and Progressive Approaches for Skyline Query Over Probabilistic Incomplete Database', IEEE Access, vol. 6, pp. 13289-13301.
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The advanced productivity of the modern society has created a wide range of similar commodities. However, the descriptions of commodities are always incomplete. Therefore, it is difficult for consumers to make choices. In the face of this problem, skyline query is a useful tool. However, the existing algorithms are unable to address incomplete probabilistic databases. In addition, it is necessary to wait for query completion to obtain even partial results. Furthermore, traditional skyline algorithms are usually serial. Thus, they cannot utilize multi-core processors effectively. Therefore, a parallel progressive skyline query algorithm for incomplete databases is imperative, which provides answers gradually and much faster. To address these problems, we design a new algorithm that uses multi-level grouping, pruning strategies, and pruning tuple transferring, which significantly decreases the computational costs. Experimental results demonstrate that the skyline results can be obtained in a short time. The parallel efficiency for an Octa-core processor reaches 90% on high-dimensional, large databases.

Zeweldi, HG, Limjuco, LA, Bendoy, AP, Kim, H-S, Park, MJ, Shon, HK, Johnson, EM, Lee, H, Chung, W-J & Nisola, GM 2018, 'The potential of monocationic imidazolium-, phosphonium-, and ammonium-based hydrophilic ionic liquids as draw solutes for forward osmosis', Desalination, vol. 444, pp. 94-106.
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© 2018 The widespread implementation of forward osmosis (FO) is highly constrained by the limited availability of suitable draw solutes (DS). Herein, monocationic hydrophilic ionic liquids (ILs) were probed as FO DS. Water (Jv), reverse solute (Js), and specific reverse solute (Js/Jv) fluxes were determined and correlated with IL properties: Van't Hoff factor (i), ionic strength, hydrated ionic radius (rH), diffusivity and membrane affinity. Most of the ILs have comparable Jv with the benchmark draw solute NaCl but their Js were significantly lower, particularly under PRO mode. Their remarkably lower Js/Jv (i.e. <0.010 ± 7.45 × 10−4 mol L−1) than NaCl (0.021 ± 0.003 mol L−1) validates their potential use as FO DS. Tetraethylammonium bromide ([N2222]Br) is the most suitable IL DS due to its high π high ionic strength, small rH, least membrane permeability (B = 0.14 L m−2 h−1) and lowest Js/Jv = 0.004 ± 5.53 × 10−4 mol L−1. Moreover, [N2222]Br effectively desalinated seawater (0.6 M NaCl). It is thermally stable and can be effectively regenerated through direct contact membrane distillation. The final permeated water had only trace [N2222]Br, which is safe for consumption as confirmed by in vitro toxicity tests. These results demonstrate that certain ILs like [N2222]Br can be identified as suitable draw solutes for FO desalination process.

Zha, X, Ni, W, Wang, X, Liu, RP, Guo, YJ, Niu, X & Zheng, K 2018, 'The Impact of Link Duration on the Integrity of Distributed Mobile Networks', IEEE Transactions on Information Forensics and Security, vol. 13, no. 9, pp. 2240-2255.
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© 2005-2012 IEEE. A major challenge in distributed mobile networks is network integrity, resulting from short link duration and severe transmission collisions. This paper analyzes the impact of link duration and transmission collisions on a range of on-the-fly authentication protocols, which operate based on predistributed keys and can instantly verify and forward messages. All unexpired messages within a link duration can be verified retrospectively, once the keys are matched on-the-air. We develop a new general 4D Markov model which, apart from the first three dimensions modeling a cycle of the protocols, is able to unprecedentedly capture unexpired messages between cycles in the fourth dimension. Validated by simulation, our analysis reveals that the on-the-fly authentication is efficient under short link duration, but is susceptible to transmission collisions. The authentication requires holistic cross-layer designs of retransmission and rekeying. The proposed model is able to facilitate the design of the protocol parameters, which allows the protocols to significantly outperform the state of the art.

Zhang, C, Qin, Y, Xu, Q, Liu, X, Liu, Y, Ni, B-J, Yang, Q, Wang, D, Li, X & Wang, Q 2018, 'Free Ammonia-Based Pretreatment Promotes Short-Chain Fatty Acid Production from Waste Activated Sludge', ACS Sustainable Chemistry & Engineering, vol. 6, no. 7, pp. 9120-9129.
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© Copyright 2018 American Chemical Society. This work reports a new waste activated sludge (WAS) pretreatment method based on free ammonia (FA) for promoting the generation of short-chain fatty acids (SCFAs). Experimental results showed that pretreatment of WAS for 3 days with FA largely improved WAS disintegration, with the highest dissolution (soluble chemical oxygen demand (COD), 3400 ± 120 mg/L at initial FA level of 237.8 mg/L) being 4.5-fold that without FA pretreatment. The pretreatment method by FA facilitated the breakdown of extracellular polymeric substances and cell envelope of sludge cells and killed more live microbial cells, which thereby accelerated the dissolution of substances from WAS. It was also found that FA severely suppressed the SCFA consumption process, but the acetogenesis process was unaffected. Although FA also inhibited hydrolysis, acidogenesis, and homoacetogenesis to some extent, the inhibitions did not largely affect the biodegradation of the relevant substances at all the tested FA levels. Finally, using FA to pretreat WAS for SCFA enhancement was confirmed. When FA concentrations ranged from 53.5 to 176.5 mg/L, the maximum generation of SCFA was enhanced from 196.8 to 267.2 mg COD/g VSS, which was 2.3-3.2 times that of the blank. Further FA leveling (237.8 mg/L) caused a slight decline of maximum SCFA generation (226.9 mg COD/g VSS). The findings reported may instruct engineers to develop an economic and effective strategy to enhance SCFA production, which might support the operation of wastewater treatment plants in sustainable paradigms with low energy input in the future.

Zhang, C-C, Zhu, H-H, Shi, B & Fatahi, B 2018, 'A long term evaluation of circular mat foundations on clay deposits using fractional derivatives', Computers and Geotechnics, vol. 94, pp. 72-82.
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© 2017 Elsevier Ltd This study proposes to use fractional derivatives to evaluate the long term performance of circular mat foundations overlying clays and also predict the associated ground settlement. Closed form solutions for the deflection and bending moment of foundations and the subsequent reaction of subgrade are obtained with the Mittag–Leffler function. Numerical examples are used to determine how the fractional order affects the time dependent properties of the foundation and ground settlement, and to simulate the case history of a large standpipe constructed over Tertiary sediments. New insights into design and prediction of shallow foundations and ground settlement are also discussed.

Zhang, G, Piccardi, M & Borzeshi, EZ 2018, 'Sequential Labeling With Structural SVM Under Nondecomposable Losses', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 9, pp. 4177-4188.
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IEEE Sequential labeling addresses the classification of sequential data, which are widespread in fields as diverse as computer vision, finance, and genomics. The model traditionally used for sequential labeling is the hidden Markov model (HMM), where the sequence of class labels to be predicted is encoded as a Markov chain. In recent years, HMMs have benefited from minimum-loss training approaches, such as the structural support vector machine (SSVM), which, in many cases, has reported higher classification accuracy. However, the loss functions available for training are restricted to decomposable cases, such as the 0-1 loss and the Hamming loss. In many practical cases, other loss functions, such as those based on the F & #x2081; measure, the precision/recall break-even point, and the average precision (AP), can describe desirable performance more effectively. For this reason, in this paper, we propose a training algorithm for SSVM that can minimize any loss based on the classification contingency table, and we present a training algorithm that minimizes an AP loss. Experimental results over a set of diverse and challenging data sets (TUM Kitchen, CMU Multimodal Activity, and Ozone Level Detection) show that the proposed training algorithms achieve significant improvements of the F & #x2081; measure and AP compared with the conventional SSVM, and their performance is in line with or above that of other state-of-the-art sequential labeling approaches.

Zhang, H & Ji, J 2018, 'Group synchronization of coupled harmonic oscillators without velocity measurements', Nonlinear Dynamics, vol. 91, no. 4, pp. 2773-2788.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. This paper investigates the group synchronization of coupled harmonic oscillators over a directed network topology in the absence of velocity measurements. Each harmonic oscillator can only obtain the sampled position states relative to its neighbors at a series of discrete-time instants. Two distributed control protocols are proposed based on the impulsive control and sampled-data control strategies. Theoretical analysis shows that the desired sampling period is determined by the position gain and the eigenvalues of the Laplacian matrix associated with the network topology. Some necessary and sufficient conditions for group synchronization are analytically established in virtue of matrix analysis, graph theory and polynomial Schur stability theory. Different to the synchronization criteria presented in the form of linear matrix inequality or general inequality, which may need to be verified, this paper explicitly gives the ranges for all feasible sampling periods. A significant feature of the synchronization criteria is that certain functional relationships between the feasible sampling period, the largest real part of the eigenvalues of the Laplacian matrix, the largest ratio of the imaginary part to the real part of the eigenvalues of the Laplacian matrix (if there exist complex eigenvalues) and the position gain are analytically established. Some effective iterative methods are then derived to calculate the endpoints of the feasible range of the sampling periods for achieving group synchronization. Finally, numerical experiments further verify the correctness of the theoretical results.

Zhang, H & Xu, M 2018, 'Recognition of Emotions in User-Generated Videos With Kernelized Features', IEEE Transactions on Multimedia, vol. 20, no. 10, pp. 2824-2835.
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© 1999-2012 IEEE. Recognition of emotions in user-generated videos has attracted increasing research attention. Most existing approaches are based on spatial features extracted from video frames. However, due to the broad affective gap between spatial features of images and high-level emotions, the performance of existing approaches is restricted. To bridge the affective gap, we propose recognizing emotions in user-generated videos with kernelized features. We reformulate the equation of the discrete Fourier transform as a linear kernel function and construct a polynomial kernel function based on the linear kernel. The polynomial kernel is applied to spatial features of video frames to generate kernelized features. Compared with spatial features, kernelized features show superior discriminative capability. Moreover, we are the first to apply the sparse representation method to reduce the impact of noise contained in videos; this method helps contribute to performance improvement. Extensive experiments are conducted on two challenging benchmark datasets, that is, VideoEmotion-8 and Ekman-6. The experimental results demonstrate that the proposed method achieves state-of-the-art performance.

Zhang, H, Chen, CY, Yu, S & Quan, W 2018, 'Guest Editorial: Security Architecture and Technologies for 5G', IET Networks, vol. 7, no. 2, pp. 51-52.
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Zhang, H, Ji, J & Wu, Q 2018, 'Sampled‐data control of coupled harmonic oscillators using measured position states only', IET Control Theory & Applications, vol. 12, no. 7, pp. 985-991.
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This brief study investigates the synchronisation of undirected coupled harmonic oscillators by using a sampled‐data control strategy. In the absence of measured velocity information, each of the networked oscillators can only obtain the measurements of the position states relative to its neighbours at the sampling moments. A distributed protocol based on the sampled relative position measurements at a series of time instants is proposed for the coupled harmonic oscillators. Necessary and sufficient conditions for achieving synchronisation are analytically established in virtue of the graph theory, matrix analysis theory and Schur stability theory of cubic polynomials. Theoretical results indicate that the explicit range that contains all the desirable sampling periods is uniquely determined by the largest eigenvalue of the Laplacian matrix associated with the network graph and the position gain of the harmonic oscillators. An effective simple iterative method is then developed to calculate the range in which the desirable sampling periods fall. Finally, numerical simulations are performed to illustrate the correctness of the theoretical results and effectiveness of the proposed protocol.

Zhang, H, Wu, Q & Ji, J 2018, 'Synchronization of Discretely Coupled Harmonic Oscillators Using Sampled Position States Only', IEEE Transactions on Automatic Control, vol. 63, no. 11, pp. 3994-3999.
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© 1963-2012 IEEE. This technical note studies the synchronization of discretely coupled harmonic oscillators by using an impulsive control strategy. In the absence of velocity measurements, a distributed protocol for the coupled harmonic oscillators is proposed under the assumption that each oscillator can only obtain the information of its position relative to its neighbors at a series of discrete time moments. Necessary and sufficient conditions are established for the synchronization of the networked system with and without an active leader over an undirected communication topology. The desirable sampling period is analytically found to be dependent on the network topology and position gain. A simple iterative method is developed to calculate the range in which the sampling period falls. Finally, numerical simulations are performed to show the effectiveness of the proposed protocols.

Zhang, H, Xu, G, Liang, X, Xu, G, Li, F, Fu, K, Wang, L & Huang, T 2018, 'An Attention-Based Word-Level Interaction Model for Knowledge Base Relation Detection', IEEE Access, vol. 6, pp. 75429-75441.
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© 2018 IEEE. Relation detection plays a crucial role in knowledge base question answering, and it is challenging because of the high variance of relation expression in real-world questions. Traditional relation detection models based on deep learning follow an encoding-comparing paradigm, where the question and the candidate relation are represented as vectors to compare their semantic similarity. Max-or average-pooling operation, which is used to compress the sequence of words into fixed-dimensional vectors, becomes the bottleneck of information flow. In this paper, we propose an attention-based word-level interaction model (ABWIM) to alleviate the information loss issue caused by aggregating the sequence into a fixed-dimensional vector before the comparison. First, attention mechanism is adopted to learn the soft alignments between words from the question and the relation. Then, fine-grained comparisons are performed on the aligned words. Finally, the comparison results are merged with a simple recurrent layer to estimate the semantic similarity. Besides, a dynamic sample selection strategy is proposed to accelerate the training procedure without decreasing the performance. Experimental results of relation detection on both SimpleQuestions and WebQuestions datasets show that ABWIM achieves the state-of-the-art accuracy, demonstrating its effectiveness.

Zhang, J, Devitt, SJ, You, JQ & Nori, F 2018, 'Holonomic surface codes for fault-tolerant quantum computation', Physical Review A, vol. 97, no. 2.
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© 2018 American Physical Society. Surface codes can protect quantum information stored in qubits from local errors as long as the per-operation error rate is below a certain threshold. Here we propose holonomic surface codes by harnessing the quantum holonomy of the system. In our scheme, the holonomic gates are built via auxiliary qubits rather than the auxiliary levels in multilevel systems used in conventional holonomic quantum computation. The key advantage of our approach is that the auxiliary qubits are in their ground state before and after each gate operation, so they are not involved in the operation cycles of surface codes. This provides an advantageous way to implement surface codes for fault-tolerant quantum computation.

Zhang, J, Dorrell, DG, Li, L & Guo, Y 2018, 'Decoupling Controller Design and Controllable Regions Analysis for the Space Vector Modulated Matrix Converter-Unified Power Flow Controller in Transmission Systems', Electric Power Components and Systems, vol. 46, no. 1, pp. 1-14.
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© 2018, Copyright © Taylor & Francis Group, LLC. The flexible alternating current transmission systems (FACTS) devices are essential components of the transmission system to enhance the controllability and elevate the transfer capacity of the network. The unified power flow controller is known as the most versatile device in the FACTS family. This work studies a distinctive unified power flow controller (UPFC) structure based on the direct matrix converter to regulate the active and reactive power in a transmission system. In contrast to the conventional UPFC, there is no requirement for a bulky energy storage element in this structure. This results in various benefits including: decreased system volume, improved efficiency, prolonged lifetime, reduced maintenance and removal of the DC-link control. The full power controllable regions are analyzed and graphically obtained for the MC-UPFC, which facilitates the selection of proper UPFC ratings. The working principles and a model of the MC-UPFC are put forward and discussed, followed by explanations of direct space vector modulation (SVM) for this application. Based on the SVM modulation scheme, PID controllers are developed to control power flows in a double-line transmission system. In addition, decoupling controllers are derived by feeding back the coupling components into controllers. The numerical simulation results for a double-line transmission system corroborate the feasibility and effectiveness of the proposition.

Zhang, J, Hou, T, Ling, Y, Zhang, L & Luo, J 2018, 'An efficient process for the synthesis of gem-dinitro compounds under high steric hindrance by nitrosation and oxidation of secondary nitroalkanes', Tetrahedron Letters, vol. 59, no. 30, pp. 2880-2883.
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Zhang, J, Hou, T, Zhang, L & Luo, J 2018, '2,4,4,6,8,8-Hexanitro-2,6-diazaadamantane: A High-Energy Density Compound with High Stability', Organic Letters, vol. 20, no. 22, pp. 7172-7176.
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Zhang, J, Li, L & Dorrell, D 2018, 'Control and applications of direct matrix converters: A review', Chinese Journal of Electrical Engineering, vol. 4, no. 2, pp. 18-27.
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In recent decades, the matrix converter (MC) has emerged as a promising AC/AC converter that performs the direct AC-to-AC conversion. Because of its attractive features such as compact volume, bidirectional power flow, controllable input power factor and sinusoidal waveforms, there has been an increase in MC related research work. Many control techniques have been proposed to control MCs and many potential applications have been investigated. This paper presents the state-of-the-art review in the recent development of control strategies and applications of MCs, starting with MC fundamentals. Some relevant simulation and experimental results are presented to show the performance of the corresponding controllers in specific applications. A wide range of control techniques and potential application fields are covered. Industrial products and modules are also discussed. Comparisons of different control strategies and different applications are summarized and presented. It is concluded that the MC is a promising converter and more research and industry interest is expected, particularly in AC motor drives and renewable energy microgrids.

Zhang, J, McBurney, P & Musial, K 2018, 'Convergence of trading strategies in continuous double auction markets with boundedly-rational networked traders', Review of Quantitative Finance and Accounting, vol. 50, no. 1, pp. 301-352.
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© 2017, Springer Science+Business Media New York. This paper considers the convergence of trading strategies among artificial traders connected to one another in a social network and trading in a continuous double auction financial marketplace. Convergence is studied by means of an agent-based simulation model called the Social Network Artificial stoCk marKet model. Six different canonical network topologies (including no-network) are used to represent the possible connections between artificial traders. Traders learn from the trading experiences of their connected neighbours by means of reinforcement learning. The results show that the proportions of traders using particular trading strategies are eventually stable. Which strategies dominate in these stable states depends to some extent on the particular network topology of trader connections and the types of traders.

Zhang, J, Yang, H, Wang, T, Li, L, Dorrell, DG & Lu, DD 2018, 'Field‐oriented control based on hysteresis band current controller for a permanent magnet synchronous motor driven by a direct matrix converter', IET Power Electronics, vol. 11, no. 7, pp. 1277-1285.
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The hysteresis band controller offers excellent dynamic performance. It has been widely researched and applied to the voltage source inverter and inverter fed drives, however it has not been investigated within the context of a matrix converter or a matrix converter based motor drive. In this study, both fixed‐band and sinusoidal‐band hysteresis current controllers are proposed and developed for a direct matrix converter. A comprehensive comparative evaluation of the two methods is then carried out. Both methods have fast dynamic performance and they inherently integrate the line modulation technique of the virtual rectifier stage into the overall modulation. Surge currents are prevented with the proposed scheme. The sinusoidal‐band hysteresis controller demonstrates lower total harmonic distortion at the expense of higher average switching frequency, which is only significantly observable at very high sampling frequencies. The proposed controller is integrated with the field‐oriented control to drive a matrix converter fed permanent magnet synchronous machine. The proposed methods are simple and incur a light computational burden, which advances the practical applications of matrix converters in AC motor drives. The simulation and experiment results demonstrate the effectiveness and feasibility of the proposed scheme.

Zhang, JA, Huang, X, Guo, YJ, Yuan, J & Jr, RWH 2018, 'Multibeam for Joint Communication and Sensing Using Steerable Analog Antenna Arrays', IEEE Transactions on Vehicular Technology,2019, vol. 68, no. 1, pp. 671-685.
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Beamforming has great potential for joint communication and sensing (JCAS),which is becoming a demanding feature on many emerging platforms such asunmanned aerial vehicles and smart cars. Although beamforming has beenextensively studied for communication and radar sensing respectively, itsapplication in the joint system is not straightforward due to differentbeamforming requirements by communication and sensing. In this paper, wepropose a novel multibeam framework using steerable analog antenna arrays,which allows seamless integration of communication and sensing. Different toconventional JCAS schemes that support JCAS using a single beam, our frameworkis based on the key innovation of multibeam technology: providing fixed subbeamfor communication and packet-varying scanning subbeam for sensing,simultaneously from a single transmitting array. We provide a systemarchitecture and protocols for the proposed framework, complying well withmodern packet communication systems with multicarrier modulation. We alsopropose low-complexity and effective multibeam design and generation methods,which offer great flexibility in meeting different communication and sensingrequirements. We further develop sensing parameter estimation algorithms usingconventional digital Fourier transform and 1D compressive sensing techniques,matching well with the multibeam framework. Simulation results are provided andvalidate the effectiveness of our proposed framework, beamforming designmethods and the sensing algorithms.

Zhang, L & Ji, JC 2018, 'One-to-three resonant Hopf bifurcations of a maglev system', Nonlinear Dynamics, vol. 93, no. 3, pp. 1277-1286.
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© 2018, Springer Science+Business Media B.V., part of Springer Nature. This paper studies the dynamics of a maglev system around 1:3 resonant Hopf–Hopf bifurcations. When two pairs of purely imaginary roots exist for the corresponding characteristic equation, the maglev system has an interaction of Hopf–Hopf bifurcations at the intersection of two bifurcation curves in the feedback control parameter and time delay space. The method of multiple time scales is employed to drive the bifurcation equations for the maglev system by expressing complex amplitudes in a combined polar-Cartesian representation. The dynamics behavior in the vicinity of 1:3 resonant Hopf–Hopf bifurcations is studied in terms of the controller’s parameters (time delay and two feedback control gains). Finally, numerical simulations are presented to support the analytical results and demonstrate some interesting phenomena for the maglev system.

Zhang, M, Qu, X, Kalhori, H & Ye, L 2018, 'Indirect monitoring of distributed ice loads on a steel gate in a cold region', Cold Regions Science and Technology, vol. 151, pp. 267-287.
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A steel gate is one of the major components of a hydraulic power station for storing water and monitoring the water level. In cold regions, the temperature decreases to well below the freezing point, and the water turns to ice, which can apply high loads on the steel gate, leading to large deformations and failure of the gate. This study aims to monitor and analyse the ice load distribution on a steel gate using an inverse method. As a case study, a steel gate at the hydraulic station on the Songhua River in Harbin is selected. The steel gate is equipped with several vibrating wire strain gauges, and deformation data for various locations on the structure was collected for 100 days. As experimental identification of the system transfer matrix requires information concerning the actual loads, which is not directly attainable, the transfer matrix was constructed using a finite element method. Five inverse methods were verified with a certain number of load patterns to determine the optimal method. The ice load distribution obtained using the optimal method is verified with the deformation data, indicating accurate load identification. Consequently, variation in the ice load distribution during the freezing period is monitored, and the relationship between the total ice force and temperature is obtained. During the winter of 2015–2016, the average ice line load gradually increased until reaching a maximum of approximately 25 kN/m on 11 Dec. 2015. Subsequently, the ice line load fluctuated between 17 and 25 kN/m. Finally, the ice released all of the force within 3 days beginning on 15 Mar. 2016.

Zhang, Q, Wu, J, Zhang, Q, Zhang, P, Long, G & Zhang, C 2018, 'Dual influence embedded social recommendation', World Wide Web, vol. 21, no. 4, pp. 849-874.
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© 2017, Springer Science+Business Media, LLC. Recommender systems are designed to solve the information overload problem and have been widely studied for many years. Conventional recommender systems tend to take ratings of users on products into account. With the development of Web 2.0, Rating Networks in many online communities (e.g. Netflix and Douban) allow users not only to co-comment or co-rate their interests (e.g. movies and books), but also to build explicit social networks. Recent recommendation models use various social data, such as observable links, but these explicit pieces of social information incorporating recommendations normally adopt similarity measures (e.g. cosine similarity) to evaluate the explicit relationships in the network - they do not consider the latent and implicit relationships in the network, such as social influence. A target user’s purchase behavior or interest, for instance, is not always determined by their directly connected relationships and may be significantly influenced by the high reputation of people they do not know in the network, or others who have expertise in specific domains (e.g. famous social communities). In this paper, based on the above observations, we first simulate the social influence diffusion in the network to find the global and local influence nodes and then embed this dual influence data into a traditional recommendation model to improve accuracy. Mathematically, we formulate the global and local influence data as new dual social influence regularization terms and embed them into a matrix factorization-based recommendation model. Experiments on real-world datasets demonstrate the effective performance of the proposed method.

Zhang, T, Bao, J, Cai, Z, Yang, Y, Zhu, H, Zhu, X & Dutkiewicz, E 2018, 'A <inline-formula> <tex-math notation='LaTeX'>$C$ </tex-math> </inline-formula>-Band Compact Wideband Bandpass Filter With High Selectivity and Improved Return Loss', IEEE Microwave and Wireless Components Letters, vol. 28, no. 9, pp. 777-779.
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© 2001-2012 IEEE. In this letter, a C-band compact wideband bandpass filter (BPF) with high selectivity and improved return loss (RL) is proposed. Two pairs of short-circuited stubs are employed on a transmission-line model to generate three transmission poles and two transmission zeros (TZs), where the odd-and even-mode analysis is used to analyze the resonant frequencies of the BPF. By applying the transversal signal-interference technique, two additional TZs can be generated in the upper and lower stopbands, respectively. The measured results show that the 3-dB fractional bandwidth is 62.8% at the center frequency of 5 GHz. The RL and the insertion loss within the passband are better than 22 and 0.6 dB, respectively. Moreover, the roll-off rate is up to 100 dB/GHz.

Zhang, T, Jia, W, Gong, C, Sun, J & Song, X 2018, 'Semi-supervised dictionary learning via local sparse constraints for violence detection', Pattern Recognition Letters, vol. 107, pp. 98-104.
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© 2017 Elsevier B.V. In this paper, we propose a novel semi-supervised learning framework for violence detection in video surveillance. With this framework, a classifier which distinguishes violent behavior from normal behavior can be trained using inexpensive unlabeled data with the assistance of human operators. Our approach can learn a single dictionary and a predictive linear classifier jointly. Specifically, we integrate the reconstruction error of labeled and unlabeled data, representation constraints and the coefficient incoherence into an objective function for dictionary learning, which enhances the representative and discriminative power of the established dictionary. This has contributed to that the dictionary and the classifier learned from the labeled set yield very small generalization error on unseen data. Experimental results on benchmark datasets have demonstrated the effectiveness of our approach in violence detection.

Zhang, T, Li, J, Jia, W, Sun, J & Yang, H 2018, 'Fast and robust occluded face detection in ATM surveillance', Pattern Recognition Letters, vol. 107, pp. 33-40.
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© 2017 Elsevier B.V. Crimes with respect to ATMs (Automatic Teller Machines) have attracted more and more attention, where criminals deliberately cover their faces in order to avoid being identified. This paper proposes a fast and robust face occlusion detection algorithm for ATM surveillance, which is demonstrated to be effective and efficient to handle arbitrarily occluded faces. In this algorithm, we innovatively propose to make use of the Omega shape formed by the head and shoulder of the person for head localization to tackle severe face occlusion. For this purpose, we first construct a novel energy function for elliptical head contour detection. Then, we develop a fast and robust head tracking algorithm, which utilizes the gradient and shape cues in a Bayesian framework. Lastly, to verify whether a detected head is occluded or not, we propose to fuse information from both skin color and face structure using the AdaBoost algorithm. Experimental results on real world data show that our proposed algorithm can achieve 98.64% accuracy on face detection and 98.56% accuracy on face occlusion detection, even though there are severe occlusions in faces, at a speed of up to 12 frames per second.

Zhang, T, Zou, J & Jia, W 2018, 'Fast and robust road sign detection in driver assistance systems', Applied Intelligence, vol. 48, no. 11, pp. 4113-4127.
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© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Road sign detection plays a critical role in automatic driver assistance systems. Road signs possess a number of unique visual qualities in images due to their specific colors and symmetric shapes. In this paper, road signs are detected by a two-level hierarchical framework that considers both color and shape of the signs. To address the problem of low image contrast, we propose a new color visual saliency segmentation algorithm, which uses the ratios of enhanced and normalized color values to capture color information. To improve computation efficiency and reduce false alarm rate, we modify the fast radial symmetry transform (RST) algorithm, and propose to use an edge pairwise voting scheme to group feature points based on their underlying symmetry in the candidate regions. Experimental results on several benchmarking datasets demonstrate the superiority of our method over the state-of-the-arts on both efficiency and robustness.

Zhang, X, Hu, Z, Ngo, HH, Zhang, J, Guo, W, Liang, S & Xie, H 2018, 'Simultaneous improvement of waste gas purification and nitrogen removal using a novel aerated vertical flow constructed wetland', Water Research, vol. 130, pp. 79-87.
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Insufficient oxygen supply is identified as one of the major factors limiting organic pollutant and nitrogen (N) removal in constructed wetlands (CWs). This study designed a novel aerated vertical flow constructed wetland (VFCW) using waste gas from biological wastewater treatment systems to improve pollutant removal in CWs, its potential in purifying waste gas was also identified. Compared with unaerated VFCW, the introduction of waste gas significantly improved NH4+-N and TN removal efficiencies by 128.48 ± 3.13% and 59.09 ± 2.26%, respectively. Furthermore, the waste gas ingredients, including H2S, NH3, greenhouse gas (N2O) and microbial aerosols, were remarkably reduced after passing through the VFCW. The removal efficiencies of H2S, NH3 and N2O were 77.78 ± 3.46%, 52.17 ± 2.53%, and 87.40 ± 3.89%, respectively. In addition, the bacterial and fungal aerosols in waste gas were effectively removed with removal efficiencies of 42.72 ± 3.21% and 47.89 ± 2.82%, respectively. Microbial analysis results revealed that the high microbial community abundance in the VFCW, caused by the introduction of waste gas from the sequencing batch reactor (SBR), led to its optimized nitrogen transformation processes. These results suggested that the VFCW intermittently aerated with waste gas may have potential application for purifying wastewater treatment plant effluent and waste gas, simultaneously.

Zhang, X, Hu, Z, Zhang, J, Fan, J, Ngo, HH, Guo, W, Zeng, C, Wu, Y & Wang, S 2018, 'A novel aerated surface flow constructed wetland using exhaust gas from biological wastewater treatment: Performance and mechanisms', Bioresource Technology, vol. 250, pp. 94-101.
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© 2017 In this study, a novel aerated surface flow constructed wetland (SFCW) using exhaust gas from biological wastewater treatment was investigated. Compared with un-aerated SFCW, the introduction of exhaust gas into SFCW significantly improved NH4+-N, TN and COD removal efficiencies by 68.30 ± 2.06%, 24.92 ± 1.13% and 73.92 ± 2.36%, respectively. The pollutants removal mechanism was related to the microbial abundance and the highest microbial abundance was observed in the SFCW with exhaust gas because of the introduction of exhaust gas from sequencing batch reactor (SBR), and thereby optimizing nitrogen transformation processes. Moreover, SFCW would significantly mitigate the risk of exhaust gas pollution. SFCW removed 20.00 ± 1.23%, 34.78 ± 1.39%, and 59.50 ± 2.33% of H2S, NH3 and N2O in the exhaust gas, respectively. And 31.32 ± 2.23% and 32.02 ± 2.86% of bacterial and fungal aerosols in exhaust gas were also removed through passing SFCW, respectively.

Zhang, X, Lin, J, Chen, Z, Sun, F, Zhu, X & Fang, G 2018, 'An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture', Sensors, vol. 18, no. 6, pp. 1828-1828.
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Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR). The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN) and long short-term memory (LSTM) is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96%) with less transmitted data (about 90%) was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

Zhang, X, Lv, T, Ni, W, Cioffi, JM, Beaulieu, NC & Guo, YJ 2018, 'Energy-Efficient Caching for Scalable Videos in Heterogeneous Networks', IEEE Journal on Selected Areas in Communications, vol. 36, no. 8, pp. 1802-1815.
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© 1983-2012 IEEE. By suppressing repeated content deliveries, wireless caching has the potential to substantially improve the energy efficiency (EE) of the fifth-generation communication networks. In this paper, we propose two novel energy-efficient caching schemes in heterogeneous networks, namely, scalable video coding (SVC)-based fractional caching and SVC-based random caching, which can provide on-demand video services with different perceptual qualities. We derive the expressions for successful transmission probabilities and ergodic service rates. Based on the derivations and the established power consumption models, the EE maximization problems are formulated for the two proposed caching schemes. By taking logarithmic approximations of the l0-norm, the problems are efficiently solved by the standard gradient projection method. Numerical results validate the theoretical analysis and demonstrate the superiority of our proposed caching schemes, compared to three benchmark strategies.

Zhang, X, Xu, J & Ji, J 2018, 'Modelling and tuning for a time-delayed vibration absorber with friction', Journal of Sound and Vibration, vol. 424, pp. 137-157.
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© 2018 Elsevier Ltd This paper presents an integrated analytical and experimental study to the modelling and tuning of a time-delayed vibration absorber (TDVA) with friction. In system modelling, this paper firstly applies the method of averaging to obtain the frequency response function (FRF), and then uses the derived FRF to evaluate the fitness of different friction models. After the determination of the system model, this paper employs the obtained FRF to evaluate the vibration absorption performance with respect to tunable parameters. A significant feature of the TDVA with friction is that its stability is dependent on the excitation parameters. To ensure the stability of the time-delayed control, this paper defines a sufficient condition for stability estimation. Experimental measurements show that the dynamic response of the TDVA with friction can be accurately predicted and the time-delayed control can be precisely achieved by using the modelling and tuning technique provided in this paper.

Zhang, Y, Aughterson, R, Karatchevtseva, I, Kong, L, Tran, TT, Čejka, J, Aharonovich, I & Lumpkin, GR 2018, 'Uranyl oxide hydrate phases with heavy lanthanide ions: [Ln(UO₂)₂O₃(OH)]·0.5H₂O (Ln = Tb, Dy, Ho and Yb)', New Journal of Chemistry, vol. 42, no. 15, pp. 12386-12393.
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Four iso-structured uranyl oxide hydrate phases containing heavy lanthanide ions have been synthesized under hydrothermal conditions and characterized.

Zhang, Y, Cui, Q, Ni, W & Zhang, P 2018, 'Energy-Efficient Transmission of Hybrid Array With Non-Ideal Power Amplifiers and Circuitry', IEEE Transactions on Wireless Communications, vol. 17, no. 6, pp. 3945-3958.
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Zhang, Y, Dong, P, Yu, S, Luo, H, Zheng, T & Zhang, H 2018, 'An Adaptive Multipath Algorithm to Overcome the Unpredictability of Heterogeneous Wireless Networks for High-Speed Railway', IEEE Transactions on Vehicular Technology, vol. 67, no. 12, pp. 11332-11344.
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© 2018 IEEE. Accessing Internet services in high-speed mobile scenario is an increasing demand for passengers and vendors. Owing to the bandwidth limitation of a single wireless network, researchers attempt to utilize the heterogeneous wireless networks along tracks to achieve multipath parallel transmission. These multipath transmission schemes usually depend on the accurate estimation of network quality to achieve high performance. However, due to the unpredictability of wireless networks in high-speed mobile scenario, current multipath transmission schemes perform poorly. In this paper, first, we make quantitative analysis for the unpredictability of wireless networks. With lots of results of real experiments, we make quantitative analysis for the estimation error of classical algorithms in different scenarios. Second, aiming at the unpredictability of wireless networks, we propose a multipath transmission algorithm named receiver adaptive incremental delay (RAID) that can aggregate bandwidth for heterogeneous networks independent of accurate network quality estimation. Final, we deploy the RAID algorithm into a real system. Abundant of real experiments and simulations prove that our proposed algorithm has a better performance than the earliest completion first algorithm and the weighted round Robin (WRR) algorithm in high-speed mobile scenario.

Zhang, Y, Guan, L & Liu, Q 2018, 'Liu Tungsheng: A geologist from a traditional Chinese cultural background who became an international star of science', Journal of Asian Earth Sciences, vol. 155, pp. 8-20.
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Zhang, Y, He, Q, Xiang, Y, Zhang, LY, Liu, B, Chen, J & Xie, Y 2018, 'Low-Cost and Confidentiality-Preserving Data Acquisition for Internet of Multimedia Things', IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3442-3451.
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Zhang, Y, Huang, R, Huang, Y, Huang, S, Ma, Y, Xu, S & Zhou, P 2018, 'Effect of ambient temperature on the puffing characteristics of single butanol-hexadecane droplet', Energy, vol. 145, pp. 430-441.
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© 2018 Elsevier Ltd Puffing characteristics of BUT50 (50% n-butanol and 50% n-hexadecane by mass) were investigated using the droplet suspension technology under 638, 688 and 738 K. Experimental results showed that BUT50 underwent transient heating, fluctuation evaporation and equilibrium evaporation phases under all ambient temperatures. In the fluctuation evaporation phase, the fluctuation frequency of 738 K was higher than that of 638 K. (Dmax/D0)2 of 738 K was lower than that of 638 K. Easy bubble rupture led to high fluctuation frequency and low (Dmax/D0)2 at 738 K. Three turning points were found in transient temperature growth rate at 638 and 738 K. Four characteristic droplet temperatures were analyzed, including droplet temperatures at the start (T1) and end (T2) of transient heating phase, at (Dmax/D0)2 (T3) and at the end of total lifetime (T4). T2 was slightly lower and T3 was slightly higher than the boiling point of n-butanol. T4 was lower than the boiling point of n-hexadecane. Furthermore, the transient heating duration (tTH), fluctuation evaporation duration (tFE) and total lifetime (tTL) decreased with increasing ambient temperature. The reduction of tFE played an important role in the decrease of tTL. The percentages of tTH/tTL and tFE/tTL were stable with increasing ambient temperature.

Zhang, Y, Huang, R, Huang, Y, Huang, S, Zhou, P, Chen, X & Qin, T 2018, 'Experimental study on combustion characteristics of an n-butanol-biodiesel droplet', Energy, vol. 160, pp. 490-499.
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© 2018 Elsevier Ltd This work was aimed to study droplet combustion which was a foundation of spray combustion. Combustion characteristics of BUT00 (pure biodiesel) and BUT50 (50% n-butanol and 50% biodiesel by mass) were investigated using droplet suspension technology under 1 bar and 900 K. One flame was observed for BUT00 while two flames were observed for BUT50. The flame of BUT00 underwent successively faint luminosity, bright luminosity, soot aggregate and soot spread. The first flame of BUT50 was faint and the second one was similar to that of BUT00 because they were caused by n-butanol and biodiesel combustion respectively. Before the auto-ignition of BUT00, (D/D0)2 was approximately unchanged at 1.0 and similarity degree (SD) was higher than 97%. Temperature growth rate (TGR) decreased first quickly and then slowly. After the auto-ignition of BUT00, (D/D0)2 sharply decreased and SD was in the range of 90–97%. The flame heating led to the increase of TGR. For BUT50, obvious fluctuations were found in (D/D0)2, SD and TGD. The SD of BUT50 was generally lower than 97%. The (D/D0)2 of BUT50 included transient heating, fluctuation evaporation and equilibrium evaporation phases. Some characteristic parameters were deterministic although (D/D0)2 in fluctuation evaporation phase was a non-deterministic process.

Zhang, Y, Huang, Y, Huang, R, Huang, S, Ma, Y, Xu, S & Wang, Z 2018, 'A new puffing model for a droplet of butanol-hexadecane blends', Applied Thermal Engineering, vol. 133, pp. 633-644.
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© 2018 Elsevier Ltd A new model was developed to investigate the puffing process of a butanol-hexadecane droplet. The puffing model took into account all the key processes, including the surface evaporation, bubble formation, bubble growth and bubble breakup. The Rayleigh equation was modified to simulate the bubble growth inside a small droplet. The sub-models for surface evaporation and bubble growth were firstly verified against the previous experimental data. Then the droplet puffing experiments of butanol-hexadecane blends were conducted under 1 bar and 750 K condition using the droplet suspension technique to further verify the puffing model. Results showed that the puffing model well simulated three phases of BUT50 (50% butanol and 50% hexadecane by mass). The three phases were the transient heating, fluctuation evaporation and equilibrium evaporation phases. An extremely strong fluctuation and several weak fluctuations were observed during the fluctuation evaporation phase from the experimental normalized squared diameter. Due to the model hypotheses, these weak fluctuations were ignored and only the strong fluctuation was simulated in the present model. Furthermore, a significant turning point was observed in the experimental temperature curve when the droplet diameter had the strong fluctuation. The occurrence of the strong fluctuation was caused by the obvious bubble expansion inside the droplet. The numerical results showed that the significant heat absorption for the bubble expansion led to the turning point in the temperature curve.

Zhang, Y, Lu, J, Liu, F, Liu, Q, Porter, A, Chen, H & Zhang, G 2018, 'Does deep learning help topic extraction? A kernel k-means clustering method with word embedding', Journal of Informetrics, vol. 12, no. 4, pp. 1099-1117.
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© 2018 All rights reserved. Topic extraction presents challenges for the bibliometric community, and its performance still depends on human intervention and its practical areas. This paper proposes a novel kernel k-means clustering method incorporated with a word embedding model to create a solution that effectively extracts topics from bibliometric data. The experimental results of a comparison of this method with four clustering baselines (i.e., k-means, fuzzy c-means, principal component analysis, and topic models) on two bibliometric datasets demonstrate its effectiveness across either a relatively broad range of disciplines or a given domain. An empirical study on bibliometric topic extraction from articles published by three top-tier bibliometric journals between 2000 and 2017, supported by expert knowledge-based evaluations, provides supplemental evidence of the method's ability on topic extraction. Additionally, this empirical analysis reveals insights into both overlapping and diverse research interests among the three journals that would benefit journal publishers, editorial boards, and research communities.

Zhang, Y, Saberi, M & Chang, E 2018, 'A semantic-based knowledge fusion model for solution-oriented information network development: a case study in intrusion detection field', Scientometrics, vol. 117, no. 2, pp. 857-886.
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© 2018, Akadémiai Kiadó, Budapest, Hungary. Building information networks using semantic based techniques to avoid tedious work and to achieve high efficiency has been a long-term goal in the information management world. A great volume of research has focused on developing large scale information networks for general domains to pursue the comprehensiveness and integrity of the information. However, constructing customised information networks containing subject-specific knowledge has been neglected. Such research can potentially return high value in terms of both theoretical and practical contribution. In this paper, a new type of network, solution-oriented information network, is coined that includes research problems and proposed techniques as nodes, and the relationship between them. A lightweight Semantic-based Knowledge Fusion Model (SKFM) is proposed leveraging the power of Natural Language Processing (NLP) and Crowdsourcing to construct the proposed information networks using academic papers (knowledge) from Scopus. SKFM relies on NLP in terms of automatic components while Crowdsourcing is initiated when uncertain cases arise. Applying the NLP technique assists to develop a semi-automatic knowledge fusion method for saving effort and time in extracting information from academic papers. Leveraging human power in uncertain cases is to make sure the essential concepts for developing the information networks are extracted reliably and connected correctly. SKFM shows a theoretical contribution in terms of lightweight knowledge extraction and reconstruction framework, as well as practical value by providing solutions proposed in academic papers to address corresponding research issues in subject-specific areas. Experiments have been implemented which have shown promising results. In the research field of intrusion detection, the information of attack types and proposed solutions has been extracted and integrated in a graphic manner with high accuracy ...

Zhang, Z, Chen, J, Wu, Q & Shao, L 2018, 'GII Representation-Based Cross-View Gait Recognition by Discriminative Projection With List-Wise Constraints', IEEE Transactions on Cybernetics, vol. 48, no. 10, pp. 2935-2947.
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© 2017 IEEE. Remote person identification by gait is one of the most important topics in the field of computer vision and pattern recognition. However, gait recognition suffers severely from the appearance variance caused by the view change. It is very common that gait recognition has a high performance when the view is fixed but the performance will have a sharp decrease when the view variance becomes significant. Existing approaches have tried all kinds of strategies like tensor analysis or view transform models to slow down the trend of performance decrease but still have potential for further improvement. In this paper, a discriminative projection with list-wise constraints (DPLC) is proposed to deal with view variance in cross-view gait recognition, which has been further refined by introducing a rectification term to automatically capture the principal discriminative information. The DPLC with rectification (DPLCR) embeds list-wise relative similarity measurement among intraclass and inner-class individuals, which can learn a more discriminative and robust projection. Based on the original DPLCR, we have introduced the kernel trick to exploit nonlinear cross-view correlations and extended DPLCR to deal with the problem of multiview gait recognition. Moreover, a simple yet efficient gait representation, namely gait individuality image (GII), based on gait energy image is proposed, which could better capture the discriminative information for cross view gait recognition. Experiments have been conducted in the CASIA-B database and the experimental results demonstrate the outstanding performance of both the DPLCR framework and the new GII representation. It is shown that the DPLCR-based cross-view gait recognition has outperformed the-state-of-the-art approaches in almost all cases under large view variance. The combination of the GII representation and the DPLCR has further enhanced the performance to be a new benchmark for cross-view gait recognition.

Zhang, Z, Dissanayake, D, Saputra, A, Wu, D & Song, C 2018, 'Three-dimensional damage analysis by the scaled boundary finite element method', Computers & Structures, vol. 206, pp. 1-17.
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© 2018 Elsevier Ltd A novel and effective approach within the framework of the scaled boundary finite element method (SBFEM) is proposed for the damage analysis of structures in three dimensions. The integral-type nonlocal model is extended to SBFEM to eliminate the mesh sensitivity concerning the strain localization. In order to reduce the number of degrees of freedoms (DOFs), an automatic mesh generation algorithm using octree decomposition is employed to refine the localized damage process zone (DPZ), but no extra effort is required to deal with hanging nodes existing between adjacent subdomains with different sizes. A double-notched tension beam is simulated with two different meshes to illustrate the mesh-independence. Three benchmarks are modelled to further verify the effectiveness and robustness of the proposed approach. It is shown that the proposed computational approach is capable of accurately capturing the damage evolution under complicated boundary conditions, and the results agree well with the experimental observations and prior numerical simulations reported in the literatures.

Zhao, F, Wu, Y, Qiu, L, Sivakumar, B, Zhang, F, Sun, Y, Sun, L, Li, Q & Voinov, A 2018, 'Spatiotemporal features of the hydro-biogeochemical cycles in a typical loess gully watershed', Ecological Indicators, vol. 91, pp. 542-554.
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© 2018 Elsevier Ltd Hydrological and biogeochemical processes are essential for material and energy exchange among climate-soil-plant systems and, thus, play an important role in terrestrial ecosystems. In particular, the water-carbon dynamics determine the status and change of ecosystems. Therefore, understanding the spatiotemporal features of the water and carbon cycles is of great importance for watershed ecosystem management. This study employed a newly coupled hydro-biogeochemical model (SWAT-DayCent) to investigate the spatiotemporal characteristics and evolution of the water cycle (evapotranspiration (ET), soil water, and water yield) and carbon cycle (net primary productivity (NPP), soil organic carbon (SOC)) in a typical loess gully watershed (the Jinghe River Basin, JRB) on the Loess Plateau of China during the period of 2000–2010. The satisfactory performance of the coupled model demonstrates that the SWAT-DayCent model is capable of simulating hydro-biogeochemical processes at the watershed scale in the Loess Plateau region. The spatial distributions of hydro-biogeochemical components varied significantly over the JRB—a decreasing gradient from south to north in hydrological variables and NPP, a higher SOC in the western margin than other parts, and a general increasing trend for all the five components in the southeastern part. Temporally, the hydrological variables showed a slightly decreasing trend, the NPP underwent a slight upward trend, but the SOC decreased significantly in the whole basin under the current climate conditions. The correlation analysis between hydrologic components and carbon cycle indicated that the water cycle may have synergies with NPP but may exert little influence on SOC. Overall, our quantitative analyses over time and space can be informative in soil and water conservation practices and ecosystem service enhancement in the JRB specifically and other parts of the Loess Plateau region as well.

Zhao, H, Zhang, C, Zhang, B, Duan, P & Yang, Y 2018, 'Decomposition-based sub-problem optimal solution updating direction-guided evolutionary many-objective algorithm', Information Sciences, vol. 448-449, pp. 91-111.
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© 2018 Elsevier Inc. The many-objective optimization problem (MaOP) is a common problem in the fields of engineering and scientific computing. It requires the optimization of multiple conflicting objectives. Due to the complexity of the MaOP, its optimization requires considerable amounts of time and computation resources to execute. Moreover, demand for a general optimization method for different types of MaOPs is becoming increasingly urgent. In this paper, the reference-vector-guided evolutionary algorithm (RVEA) is modified to accelerate the optimization speed and to improve its adaptability. To achieve more rapid convergence, a sub-problem optimal solution updating direction-guided variation strategy is developed to replace the original variation strategy of the RVEA. A comparative experiment on the typical test suites verifies that the proposed method offers preferable performance. Our experiment shows that the performance of the OD-RVEA declines when optimizing MaOPs with irregular Pareto fronts (PFs). To address this issue, an adaptive reference vector adjustment strategy is designed as a means of enhancing the optimization capabilities of MaOPs with irregular PFs by adjusting the distribution of reference vectors. Our comparative experiment on test cases that involve irregular PFs shows that the algorithm that applies this strategy outperforms the algorithm that applies fixed reference vectors.

Zhao, J, Liu, Y, Wang, Y, Lian, Y, Wang, Q, Yang, Q, Wang, D, Xie, G-J, Zeng, G, Sun, Y, Li, X & Ni, B-J 2018, 'Clarifying the Role of Free Ammonia in the Production of Short-Chain Fatty Acids from Waste Activated Sludge Anaerobic Fermentation', ACS Sustainable Chemistry & Engineering, vol. 6, no. 11, pp. 14104-14113.
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Copyright © 2018 American Chemical Society. Free ammonia (FA) could accumulate at high levels in the sludge anaerobic fermentation, especially under alkaline fermentation conditions, which might significantly affect the anaerobic fermentation. However, its role in the sludge fermentation process has not been revealed fundamentally. This work therefore aims to fill the knowledge gap through the integration of experimental and mathematical approaches. Experimental results showed that when the initial ammonium concentration increased from 20 to 300 mg/L, the maximal short-chain fatty acid (SCFA) yield from fermentation systems with different pH values varied from 91.2 to 296.7 mg of chemical oxygen demand/g volatile suspended solids (VSS). The increasing SCFA production was observed to correlate with the FA level rather than the ammonium level, suggesting that FA, instead of ammonium, is likely the true contributor to enhance SCFA production. Batch tests confirmed that ammonium in the fermentation-strength range (e.g., 0-300 mg/L) did not affect any process of sludge fermentation, but all the processes were affected significantly by FA, pH, or combined FA-pH. It was found that FA facilitated sludge disintegration but inhibited the processes of hydrolysis, acidification, and methanogenesis. When FA and alkaline conditions were combined, synergistic effects on all these processes were observed. The significant contribution of FA to SCFA production was finally confirmed by a sludge fermentation mathematical model proposed recently. The findings reported here revealed the actually existing, yet previously unrecognized contributor to the sludge fermentation, which help engineers better understand the role of FA in sludge anaerobic fermentation.

Zhao, J, Mao, X & Zhang, J 2018, 'Learning deep facial expression features from image and optical flow sequences using 3D CNN', The Visual Computer, vol. 34, no. 10, pp. 1461-1475.
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© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Facial expression is highly correlated with the facial motion. According to whether the temporal information of facial motion is used or not, the facial expression features can be classified as static and dynamic features. The former, which mainly includes the geometric features and appearance features, can be extracted by convolution or other learning filters; the latter, which are aimed to model the dynamic properties of facial motion, can be calculated through optical flow or other methods, respectively. When 3D convolutional neural networks (CNNs) are introduced, the extraction of two different types of features mentioned above becomes easy. In this paper, one 3D CNN architecture is presented to learn the static and dynamic features from facial image sequences and extract high-level dynamic features from optical flow sequences. Two types of dense optical flow, which contain the tracking information of facial muscle movement, are calculated according to different image pair construction methods. One is the common optical flow, and the other is an enhanced optical flow which is called accumulative optical flow. Four components of each type of optical flow are used in experiments. Three databases, two acted databases and one nearly realistic database, are selected to conduct the experiments. The experiments on the two acted databases achieve state-of-the-art accuracy, and indicate that the vertical component of optical flow has an advantage over other components in recognizing facial expression. The experimental results on the three selected databases show that more discriminative features can be learned from image sequences than from optical flow or accumulative optical flow sequences, and the accumulative optical flow contains more motion information than optical flow if the frame distance of the image pairs used to calculate them is not too large.

Zhao, J, Wang, D, Liu, Y, Ngo, HH, Guo, W, Yang, Q & Li, X 2018, 'Novel stepwise pH control strategy to improve short chain fatty acid production from sludge anaerobic fermentation', Bioresource Technology, vol. 249, pp. 431-438.
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This study reports an innovative strategy known as stepwise pH fermentation, developed to enhance the production of short chain volatile fatty acids (SCFA) from waste activated sludge (WAS) anaerobic fermentation. Experimental results confirmed the optimal pH for WAS disruption and acidification was 11 and 9, respectively, and corresponding optimal time was, respectively, 5 d and 2 d. In this scenario, the optimal SCFA yield was 2356 mg chemical oxygen demand (COD)/L, which was much higher than that derived from alkaline fermentation system. Investigation of the mechanism indicated that pH 11 could accelerate the disruption of WAS and inhibit the activities of methanogens; furthermore, pH 9 was beneficial to the activity of acid-producing bacteria, resulting in more SCFA production. Stepwise pH fermentation integrated with sodium chloride (NaCl) present in WAS had synergistic impacts on WAS anaerobic fermentation.

Zhao, L, Huang, S & Dissanayake, G 2018, 'Linear SFM: A hierarchical approach to solving structure-from-motion problems by decoupling the linear and nonlinear components', ISPRS Journal of Photogrammetry and Remote Sensing, vol. 141, pp. 275-289.
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© 2018 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) This paper presents a novel hierarchical approach to solving structure-from-motion (SFM) problems. The algorithm begins with small local reconstructions based on nonlinear bundle adjustment (BA). These are then joined in a hierarchical manner using a strategy that requires solving a linear least squares optimization problem followed by a nonlinear transform. The algorithm can handle ordered monocular and stereo image sequences. Two stereo images or three monocular images are adequate for building each initial reconstruction. The bulk of the computation involves solving a linear least squares problem and, therefore, the proposed algorithm avoids three major issues associated with most of the nonlinear optimization algorithms currently used for SFM: the need for a reasonably accurate initial estimate, the need for iterations, and the possibility of being trapped in a local minimum. Also, by summarizing all the original observations into the small local reconstructions with associated information matrices, the proposed Linear SFM manages to preserve all the information contained in the observations. The paper also demonstrates that the proposed problem formulation results in a sparse structure that leads to an efficient numerical implementation. The experimental results using publicly available datasets show that the proposed algorithm yields solutions that are very close to those obtained using a global BA starting with an accurate initial estimate. The C/C++ source code of the proposed algorithm is publicly available at https://github.com/LiangZhaoPKUImperial/LinearSFM.

Zhao, L, Wu, S, Jiang, J, Li, W, Luo, J & Li, J 2018, 'Novel overlapping subgraph clustering for the detection of antigen epitopes', Bioinformatics, vol. 34, no. 12, pp. 2061-2068.
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Abstract Motivation Antigens that contain overlapping epitopes have been occasionally reported. As current algorithms mainly take a one-antigen-one-epitope approach to the prediction of epitopes, they are not capable of detecting these multiple and overlapping epitopes accurately, or even those multiple and separated epitopes existing in some other antigens. Results We introduce a novel subgraph clustering algorithm for more accurate detection of epitopes. This algorithm takes graph partitions as seeds, and expands the seeds to merge overlapping subgraphs based on the term frequency-inverse document frequency (TF-IDF) featured similarity. Then, the merged subgraphs are each classified as an epitope or non-epitope. Tests of our algorithm were conducted on three newly collected datasets of antigens. In the first dataset, each antigen contains only a single epitope; in the second, each antigen contains only multiple and separated epitopes; and in the third, each antigen contains overlapping epitopes. The prediction performance of our algorithm is significantly better than the state-of-art methods. The lifts of the averaged f-scores on top of the best existing methods are 60, 75 and 22% for the single epitope detection, the multiple and separated epitopes detection, and the overlapping epitopes detection, respectively. Availability and implementation The source code is available at github.com/lzhlab/glep/. Supplementary information Supplementary data are...

Zhao, L, Xie, J, Bai, L, Chen, W, Wang, M, Zhang, Z, Wang, Y, Zhao, Z & Li, J 2018, 'Mining statistically-solid k-mers for accurate NGS error correction', BMC Genomics, vol. 19, no. S10, pp. 912-912.
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BACKGROUND:NGS data contains many machine-induced errors. The most advanced methods for the error correction heavily depend on the selection of solid k-mers. A solid k-mer is a k-mer frequently occurring in NGS reads. The other k-mers are called weak k-mers. A solid k-mer does not likely contain errors, while a weak k-mer most likely contains errors. An intensively investigated problem is to find a good frequency cutoff f0 to balance the numbers of solid and weak k-mers. Once the cutoff is determined, a more challenging but less-studied problem is to: (i) remove a small subset of solid k-mers that are likely to contain errors, and (ii) add a small subset of weak k-mers, that are likely to contain no errors, into the remaining set of solid k-mers. Identification of these two subsets of k-mers can improve the correction performance. RESULTS:We propose to use a Gamma distribution to model the frequencies of erroneous k-mers and a mixture of Gaussian distributions to model correct k-mers, and combine them to determine f0. To identify the two special subsets of k-mers, we use the z-score of k-mers which measures the number of standard deviations a k-mer's frequency is from the mean. Then these statistically-solid k-mers are used to construct a Bloom filter for error correction. Our method is markedly superior to the state-of-art methods, tested on both real and synthetic NGS data sets. CONCLUSION:The z-score is adequate to distinguish solid k-mers from weak k-mers, particularly useful for pinpointing out solid k-mers having very low frequency. Applying z-score on k-mer can markedly improve the error correction accuracy.

Zhao, N, Yang, X, Ren, A, Zhang, Z, Zhao, W, Hu, F, Ur Rehman, M, Abbas, H & Abolhasan, M 2018, 'Antenna and Propagation Considerations for Amateur UAV Monitoring', IEEE Access, vol. 6, pp. 28001-28007.
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© 2013 IEEE. The broad application spectrum of unmanned aerial vehicles is making them one of the most promising technologies of Internet of Things era. Proactive prevention for public safety threats is one of the key areas with vast potential of surveillance and monitoring drones. Antennas play a vital role in such applications to establish reliable communication in these scenarios. This paper considers line-of-sight and non-line-of-sight threat scenarios with the perspective of antennas and electromagnetic wave propagation.

Zhao, S, Cheng, E, Qiu, X, Burnett, I & Chia-chun Liu, J 2018, 'Spatial decorrelation of wind noise with porous microphone windscreens', The Journal of the Acoustical Society of America, vol. 143, no. 1, pp. 330-339.
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This paper explores the wind noise reduction mechanism of porous microphone windscreens by investigating the spatial correlation of wind noise. First, the spatial structure of the wind noise signal is studied by simulating the magnitude squared coherence of the pressure measured with two microphones at various separation distances, and it is found that the coherence of the two signals decreases with the separation distance and the wind noise is spatially correlated only within a certain distance less than the turbulence wavelength. Then, the wind noise reduction of the porous microphone windscreen is investigated, and the porous windscreen is found to be the most effective in attenuating wind noise in a certain frequency range, where the windscreen diameter is approximately 2 to 4 times the turbulence wavelengths (2 &lt; D0/ξ &lt; 4), regardless of the wind speed and windscreen diameter. The spatial coherence between the wind noise outside and inside a porous microphone windscreen is compared with that without the windscreen, and the coherence is found to decrease significantly when the windscreen diameter is approximately 2 to 4 times the turbulence wavelengths, corresponding to the most effective wind noise reduction frequency range of the windscreen. Experimental results with a fan are presented to support the simulations. It is concluded that the wind noise reduction mechanism of porous microphone windscreens is related to the spatial decorrelation effect on the wind noise signals provided by the porous material and structure.

Zhao, S, Dabin, M, Cheng, E, Qiu, X, Burnett, I & Liu, JC-C 2018, 'Mitigating wind noise with a spherical microphone array', The Journal of the Acoustical Society of America, vol. 144, no. 6, pp. 3211-3220.
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This paper utilizes a rigid spherical microphone array to reduce wind noise. In the experiments conducted, a loudspeaker is used to reproduce the desired sound signal and an axial fan is employed to generate wind noise in an anechoic chamber. The sound signal and wind noise are measured separately with the spherical microphone array and analyzed in the spherical harmonic domain. The wind noise is found to be irregularly distributed in the spherical harmonic domain, distinct from the sound signal which is concentrated in the first few spherical harmonic modes. This difference is utilized to reduce wind noise without degrading the desired sound pressure level (SPL) by use of a low pass filter method in the spherical harmonic domain. Experimental results with both single-tonal and multi-tonal sound signals demonstrate that the proposed method can reduce wind noise by more than 10 dB in the frequency range below 500 Hz. The SPL of the desired sound signal can be extracted from wind noise with an error within 1.0 dB, even when the sound level is 8 dB lower than wind noise.

Zhao, S, He, T, Li, X, Gao, C, Shon, HK, Nghiem, LD & Elimelech, M 2018, 'Highlights of international forward osmosis technology symposium (IFOS2016): is forward osmosis feasible?', Huagong Xuebao/CIESC Journal, vol. 69, no. 4, pp. 1255-1260.
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The research highlights on forward osmosis (FO) technology at the International Forward Osmosis Symposium (IFOS2016) in Sydney by the end of 2016 are summarized. For FO membrane materials, reduction in the structure parameter of the support layer, rather than the increase of the permeability of the active separation layer, is the key to improve the FO flux. Overall, the improvement in the rejection and antifouling properties is the key factor for high performance membrane. For draw solutes, inorganic salts appear to be the most promising candidates. Osmotic dilution and hybrid processes with other separation technologies for treating high salinity wastewater remain the main potential application. Unfortunately, in a short term, FO based salinity power generation is not competitive to other new energy alternatives.

Zhao, Z, Li, X, Du, X, Chen, Q, Zhao, Y, Su, F, Chang, X & Hauptmann, AG 2018, 'A unified framework with a benchmark dataset for surveillance event detection', Neurocomputing, vol. 278, pp. 62-74.
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© 2017 Elsevier B.V. As an important branch of multimedia content analysis, Surveillance Event Detection (SED) is still a quite challenging task due to high abstraction and complexity such as occlusions, cluttered backgrounds and viewpoint changes etc. To address the problem, we propose a unified SED detection framework which divides events into two categories, i.e., short-term events and long-duration events. The former can be represented as a kind of snapshots of static key-poses and embodies an inner-dependencies, while the latter contains complex interactions between pedestrians, and shows obvious inter-dependencies and temporal context. For short-term event, a novel cascade Convolutional Neural Network (CNN)-HsNet is first constructed to detect the pedestrian, and then the corresponding events are classified. For long-duration event, Dense Trajectory (DT) and Improved Dense Trajectory (IDT) are first applied to explore the temporal features of the events respectively, and subsequently, Fisher Vector (FV) coding is adopted to encode raw features and linear SVM classifiers are learned to predict. Finally, a heuristic fusion scheme is used to obtain the results. In addition, a new large-scale pedestrian dataset, named SED-PD, is built for evaluation. Comprehensive experiments on TRECVID SEDtest datasets demonstrate the effectiveness of proposed framework.

Zheng, B-L, Wong, S-W, Feng, S-F, Zhu, L & Yang, Y 2018, 'Multi-Mode Bandpass Cavity Filters and Duplexer With Slot Mixed-Coupling Structure', IEEE Access, vol. 6, pp. 16353-16362.
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© 2018 IEEE. The quasi-elliptic multi-mode bandpass cavity filters and duplexer with slot mixed-coupling structure are proposed in this paper. A single metal cavity embedded with a rectangular-shaped slot-cut metal plate is utilized to constitute a multi-mode bandpass filter with a few features including wide passband, low profile and controllable transmission zeros (TZs). In this paper, the slot-cut metal plane serves as the multi-mode resonators. In detail, the slot on the metal plane functions as the circuit element to move the higher order modes within the reasonable frequency-band, while serving as a mixed-coupling structure to generate out-of-band transmission zeros. To demonstrate the multiple-mode capability in filter design, the dual-mode, triple-mode, and quadruple-mode filters are developed by appropriately allocating a few TZs in the upper stopbands using the proposed slot mixed-coupling approach, namely, Type-I filters. Next, a quadruple-mode cavity filter with both lower and higher TZs is designed, namely, Type-II filter, which is further applied for the exploration of a duplexer. Finally, the filter and duplexer prototypes are fabricated and measured. The measurement results are found in good agreement with the simulated ones.

Zheng, D, Zhang, H, Zhang, JA & Su, SW 2018, 'Stability Analysis for Switched Systems with Sequence-based Average Dwell Time', International Journal of Control, pp. 1-9.
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This note investigates the stability of both linear and nonlinear switchedsystems with average dwell time. Two new analysis methods are proposed.Different from existing approaches, the proposed methods take into account thesequence in which the subsystems are switched. Depending on the predecessor orsuccessor subsystems to be considered, sequence-based average preceding dwelltime (SBAPDT) and sequence-based average subsequence dwell time (SBASDT)approaches are proposed and discussed for both continuous and discrete timesystems. These proposed methods, when considering the switch sequence, have thepotential to further reduce the conservativeness of the existing approaches. Acomparative numerical example is also given to demonstrate the advantages ofthe proposed approaches.

Zheng, D, Zhang, H, Zhang, JA & Wang, G 2018, 'Consensus of multi-agent systems with faults and mismatches under switched topologies using a delta operator method', Neurocomputing, vol. 315, pp. 198-209.
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© 2018 Elsevier B.V. This paper studies the consensus of multi-agent systems with faults and mismatches under switched topologies using a delta operator method. Since faults and mismatches can result in failure of the consensus even for a fixed topology with a spanning tree, how to reach a consensus is a complicated and challenging problem under such circumstances especially when part topologies have no spanning tree. Although some works studied the influence of faults and mismatches on the consensus, there is little work on reaching a consensus for the multi-agent systems with faults and mismatches. In this paper, we introduce the delta operator to unify the consensus analysis for continuous, discrete, or sampled systems under one framework. We develop the theories on the delta operator systems first and then apply theories of the delta operator systems to the consensus problems. By converting the consensus problems into stability problems, we investigate and prove consensus and the associated conditions for systems 1) without any fault, 2) with a known fault, and 3) with unknown faults, under switching topologies with matching or mismatching coefficients. Numerical examples are provided and validate the effectiveness of the theoretical results.

Zheng, J, Li, Y, Hu, M, Wen, J, Wang, J & Kan, J 2018, 'Feasibility study of a miniaturized magnetorhological grease timing trigger as safety and arming device for spinning projectile', Smart Materials and Structures, vol. 27, no. 11, pp. 115030-115030.
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Safety and arming (S&A) device is to keep the fuze for projectile unarmed during shipping, handling and storage, while arming the firing section at a proper time via sensing external conditions such as pressure, position, etc. With the increasing need for smaller S&A devices, miniature design with a compact configuration and high reliability is on demand. This paper proposes a miniaturized timing trigger as S&A device for a spinning projectile by utilizing the "locking" and "unlocking" properties of magnetorheological (MR) grease with/without the presence of magnetic field. The design and arming mechanism of the timing trigger are firstly introduced in which the MR grease is locked by a magnetic field generated by two permanent magnets (PMs). Under sufficient firing acceleration, the PMs disengage to unlock the contraction flow of MR grease, which enables its triggering function. A theoretical analysis was conducted to interpolate the delayed time against the geometry of the device, shear/extensional characteristics of MR grease and the spinning rate of a projectile. A series of tests have been conducted to measure the delayed times by tuning the physical parameters, including particle concentration, spinning rate and orifice diameter, etc. The experimental results showed that this theoretical model is capable of well calculating the delayed time of MR grease timing trigger.

Zheng, J, Li, Y, Wang, J, Shiju, E & Li, X 2018, 'Accelerated thermal aging of grease-based magnetorheological fluids and their lifetime prediction', Materials Research Express, vol. 5, no. 8, pp. 085702-085702.
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© 2018 IOP Publishing Ltd. In this article, the effect of elevated temperature on the rheological properties of grease-based magnetorheological fluids (G-MRFs) with the focus on long-term storage lifetime has been investigated. These G-MRF samples were subjected to accelerated heat aging process for the estimation of thermal stability and useful lifetime prediction. The well-known Arrhenius-Weibull relationship with a modified Powell-Beal conjugate gradient (CGP) algorithm was employed to model the 'life in service' for the achievement of possible life distribution at different temperature conditions. By defining the failure criteria of G-MRF samples as a maximum reduction of either viscosity or shear stress by more than 10%, the underlying degradation mechanism was revealed through Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) analysis. Based on the statistical inference from accelerated life test (ALT), the life expectancy of G-MRF under nominal operating temperature is estimated to be 15.2 years, which outpaces the capability of most industrial applications. Experimental results showed that the performance of shear stress is more likely to degrade under long-term treatment of high temperature in comparison with low temperature. Thus, it is suggested to store the G-MRF at relatively low temperatures for longevity extension and reliability improvement.

Zheng, L, Zhu, J, Lu, DD-C, Wang, G & He, T 2018, 'Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries', Energy, vol. 150, pp. 759-769.
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© 2018 Elsevier Ltd The reliability and safety of battery operations necessitate an efficient battery management system (BMS) with accurate battery state of charge (SOC) and capacity estimation techniques. This paper investigates the incremental capacity analysis (ICA) and differential voltage analysis (DVA) methods for onboard battery SOC and capacity estimation. Since the conventional cell terminal voltage based ICA/DVA methods are sensitive to the changed battery resistance and polarization during battery aging processes, the SOC based ICA/DVA methods are proposed to address this problem as so to accurately identify features of interest on incremental capacity (IC) and differential voltage (DV) curves for applications. Three feature points (FPs) that are potential to be easily identified by battery management systems are extracted from the SOC based IC/DV curves, and then the relations between FPs and cell SOCs/capacities are quantified and applied for battery SOC and capacity estimation. The robustness of the proposed approach against various aging levels and erroneous cumulative capacities is evaluated. Promising results with the maximum absolute error of 1.0% and the relative error of 2.0% can be achieved for battery SOC and capacity estimation, respectively.

Zheng, L, Zhu, J, Wang, G, Lu, DD-C & He, T 2018, 'Differential voltage analysis based state of charge estimation methods for lithium-ion batteries using extended Kalman filter and particle filter', Energy, vol. 158, pp. 1028-1037.
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© 2018 Elsevier Ltd Accurate battery state of charge (SOC) estimation can contribute to safe and reliable utilization of the battery. However, commonly used battery model-based SOC estimation methods suffer from the lack of a universal battery model for cells in a battery pack since the model parameters of each cell are inevitably different from each other and variable with battery aging, leading to difficulties in promoting the model-based methods for real applications. To solve this problem, a differential voltage (DV) analysis based universal battery model and two associated SOC estimation algorithms using extended Kalman filter (EKF) and particle filter (PF), respectively, are proposed in this paper. By means of a natural cubic interpolation approach, a battery SOC-DV model is firstly derived from the SOC based DV curves of various cells at different aging levels. A novel battery model-based scheme is then proposed to incorporate the SOC-DV model for the estimation. The robustness of the proposed approaches against different cell aging levels is evaluated, and the promising SOC estimates with the maximum absolute error of 1.75% and the root mean square error of less than 1.10% can be achieved.

Zheng, L, Zhu, J, Wang, G, Lu, DD-C & He, T 2018, 'Lithium-ion Battery Instantaneous Available Power Prediction Using Surface Lithium Concentration of Solid Particles in a Simplified Electrochemical Model', IEEE Transactions on Power Electronics, vol. 33, no. 11, pp. 9551-9560.
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© 1986-2012 IEEE. Accurate battery power capability prediction can contribute to reliable and sufficient utilization of the battery to absorb or deliver a certain amount of power within its safe operating area. The power capability of a battery is a finite quantity that is limited by the electrochemical reaction properties occurring inside the battery. Note that the instantaneous available power of the battery is strongly related to the surface lithium concentration of solid particles in battery electrodes, but their relationship has not been explored sufficiently yet. This paper proposes a novel method for battery instantaneous available power prediction using a practical physical limit (i.e., lithium concentration limit) rather than the limits of macroscopically observed variables, such as the cell terminal voltage and current, thus providing a direct insight into electrochemical processes inside batteries. The surface lithium concentration of the solid particle is derived from a simplified battery electrochemical model, and a relationship between battery instantaneous available power and surface lithium concentration is quantified for the power capability prediction. Promising results with small forecast errors can be achieved for battery charging and discharging at different cell aging levels and ambient temperatures, which highlights the superior accuracy and robustness of the proposed method.

Zheng, M, Tao, W, Zou, Y, Farokhzad, OC & Shi, B 2018, 'Nanotechnology-Based Strategies for siRNA Brain Delivery for Disease Therapy', Trends in Biotechnology, vol. 36, no. 5, pp. 562-575.
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Zheng, Y, Dzakpasu, M, Wang, X, Zhang, L, Ngo, HH, Guo, W & Zhao, Y 2018, 'Molecular characterization of long-term impacts of macrophytes harvest management in constructed wetlands', Bioresource Technology, vol. 268, pp. 514-522.
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Zheng, Y, Gao, L, Xiao, M, Li, H & Luo, Z 2018, 'Robust topology optimization considering load uncertainty based on a semi-analytical method', The International Journal of Advanced Manufacturing Technology, vol. 94, no. 9-12, pp. 3537-3551.
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© 2017, Springer-Verlag London Ltd. Uncertainty is omnipresent in engineering design and manufacturing. This paper dedicates to present a robust topology optimization (RTO) methodology for structural compliance minimization problems considering load uncertainty, which includes magnitude and direction uncertainty subjected to Gaussian distribution. To this end, comprehensible semi-analytical formulations are derived to fleetly calculate the statistical data of structural compliance, which is critical to the probability-based RTO problem. In order to avoid the influence of numerical units on evaluating the robust results, this paper considers a generic coefficient of variation (GCV) as robust index which contains both the expected compliance and standard variance. In addition, the accuracy and efficiency of semi-analytical formulas are validated by the Monte Carlo (MC) simulation; comparison results provide higher calculation efficiency over the MC-based optimization algorithms. Four numerical examples are provided via density-based approach to demonstrate the effectiveness and robustness of the proposed method.

Zheng, Y, Peng, H, Zhang, X, Zhao, Z, Yin, J & Li, J 2018, 'Predicting adverse drug reactions of combined medication from heterogeneous pharmacologic databases', BMC Bioinformatics, vol. 19, no. S19, pp. 49-59.
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BACKGROUND:Early and accurate identification of potential adverse drug reactions (ADRs) for combined medication is vital for public health. Existing methods either rely on expensive wet-lab experiments or detecting existing associations from related records. Thus, they inevitably suffer under-reporting, delays in reporting, and inability to detect ADRs for new and rare drugs. The current application of machine learning methods is severely impeded by the lack of proper drug representation and credible negative samples. Therefore, a method to represent drugs properly and to select credible negative samples becomes vital in applying machine learning methods to this problem. RESULTS:In this work, we propose a machine learning method to predict ADRs of combined medication from pharmacologic databases by building up highly-credible negative samples (HCNS-ADR). Specifically, we fuse heterogeneous information from different databases and represent each drug as a multi-dimensional vector according to its chemical substructures, target proteins, substituents, and related pathways first. Then, a drug-pair vector is obtained by appending the vector of one drug to the other. Next, we construct a drug-disease-gene network and devise a scoring method to measure the interaction probability of every drug pair via network analysis. Drug pairs with lower interaction probability are preferentially selected as negative samples. Following that, the validated positive samples and the selected credible negative samples are projected into a lower-dimensional space using the principal component analysis. Finally, a classifier is built for each ADR using its positive and negative samples with reduced dimensions. The performance of the proposed method is evaluated on simulative prediction for 1276 ADRs and 1048 drugs, comparing using four machine learning algorithms and with two baseline approaches. Extensive experiments show that the proposed way to represent drugs characterizes drugs accu...

Zheng, Y, Zhang, G, Zhang, Z & Lu, J 2018, 'A reducibility method for the weak linear bilevel programming problems and a case study in principal-agent', Information Sciences, vol. 454-455, pp. 46-58.
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© 2018 A weak linear bilevel programming (WLBP) problem often models problems involving hierarchy structure in expert and intelligent systems under the pessimistic point. In the paper, we deal with such a problem. Using the duality theory of linear programming, the WLBP problem is first equivalently transformed into a jointly constrained bilinear programming problem. Then, we show that the resolution of the jointly constrained bilinear programming problem is equivalent to the resolution of a disjoint bilinear programming problem under appropriate assumptions. This may give a possibility to solve the WLBP problem via a single-level disjoint bilinear programming problem. Furthermore, some examples illustrate the solution process and feasibility of the proposed method. Finally, the WLBP problem models a principal-agent problem under the pessimistic point that is also compared with a principal-agent problem under the optimistic point.

Zhong, Y, Dutkiewicz, E, Yang, Y, Zhu, X, Zhou, Z & Jiang, T 2018, 'Internet of Mission-Critical Things: Human and Animal Classification—A Device-Free Sensing Approach', IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3369-3377.
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© 2014 IEEE. The well-known Internet of Things (IoT) is recently being considered for critical missions, such as search and rescue, surveillance, and border patrol. One of the most critical issues that these applications are currently facing is how to correctly distinguish between human and animal targets in a cost-effective way. In this paper, we present a relatively low-cost, but robust approach that uses a combination of device-free sensing (DFS) and machine-learning technologies to tackle this issue. In order to validate the feasibility of the presented approach, a variety of data is collected in a cornfield using impulse-radio ultra-wideband (IR-UWB) transceivers. These data are then used to investigate the influence of different statistical properties of the radio-frequency (RF) signal on the accuracy of human/animal target classification. Based on the probability density function of different statistical properties, two distinguishing features for target classification are found, namely, standard deviation and root mean spread delay spread. Using them, the impact on the classification accuracy due to different classifiers, number of training samples, and different values of signal-To-noise ratio is extensively verified. Even with the worst case, the classification accuracy of the system is still better than 91% in terms of distinguishing between human and animal targets (including goats and dogs), which indicates that the presented approach has a great potential to be deployed in the near future.

Zhong, Y, Yang, Y, Zhu, X, Huang, Y, Dutkiewicz, E, Zhou, Z & Jiang, T 2018, 'Impact of Seasonal Variations on Foliage Penetration Experiment: A WSN-Based Device-Free Sensing Approach', IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 9, pp. 5035-5045.
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© 2018 IEEE. Foliage penetration (FOPEN) has been found to be a critical mission for a variety of applications, ranging from surveillance to military. Recently, an emerging technology, namely wireless sensor network (WSN)-based device-free sensing (DFS), has been introduced to the domain of FOPEN. This technology only utilizes radio-frequency signals for target detection and classification; thus, no additional hardware is required, just a wireless transceiver. Although the feasibility of using this technology for human detection indoors has been explored to some extent, it is questionable if the same technology can be transferred to outdoors. As far as FOPEN is concerned, the impact of seasonal variations on detection accuracy can be severe. To address this concern, in this paper, an experiment is conducted in four seasons, and how to ensure reasonable detection accuracy with seasonal variations is intensively investigated. To fully evaluate the potential of using the WSN-based DFS for FOPEN, an impulse-radio ultrawideband technology-based prototype is used to collect data samples in different seasons. Unlike the conventional approach based on a combination of statistical properties of received-signal strength and a support vector machine, this approach adopts two special measures for performance enhancement. One measure is to use a higher order cumulant (HOC) algorithm for feature extraction, so that the impact on detection accuracy due to unwanted clutters can be minimized. The other one is to determine the optimal parameters of the classifier by means of a flower pollination algorithm. Consequently, the adverse effects on detection accuracy due to variations of weather conditions in four seasons can be accommodated. According to the experimental result, it is shown that the average classification accuracy of the presented approach can be improved by at least 20% under all seasons with an ensured robustness.

Zhou, A, Wu, S, Li, J & Sheng, D 2018, 'Including degree of capillary saturation into constitutive modelling of unsaturated soils', Computers and Geotechnics, vol. 95, pp. 82-98.
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The degree of saturation (S) of soil can be separated into two components: the degree of capillary saturation (S′) that is based on the capillary water and the degree of adsorptive saturation (S″) that is based on the adsorbed water. This paper discusses the role of the degree of capillary saturation (S′) in modelling the coupled hydro-mechanical behaviour of unsaturated soils and proposes a new constitutive model for unsaturated soils by using the degree of capillary saturation (S′) and the effective inter-particle stress (σij′). An enhanced hydraulic model is introduced to describe the hydraulic hysteresis and hydro-mechanical interaction in terms of the degree of capillary saturation (S′). In the proposed constitutive model, the shear strength, yield stress and deformation behaviour of unsaturated soils are governed directly by the above two constitutive variables, namely σij′ and S′. To be in line with the existing finite element frameworks for unsaturated soils, the proposed model is eventually generalised to constitutive functions consisting of only primary variables such as the net stress (σij), suction (s) and degree of saturation (S). The typical performance of the model for simulating the characteristic trends of unsaturated soil behaviour is discussed in several different scenarios. The model is then validated against a variety of experimental data in the literature, and the results show that a reasonable agreement can be obtained using this new constitutive model.

Zhou, J & Chen, F 2018, 'DecisionMind: revealing human cognition states in data analytics-driven decision making with a multimodal interface', Journal on Multimodal User Interfaces, vol. 12, no. 2, pp. 67-76.
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© 2017, Springer International Publishing AG. Despite the recognized value of machine learning (ML) techniques and high expectation of applying ML techniques within various applications, significant barriers to widespread adoption and local implementation of ML approaches still exist in the areas of trust (of ML results), comprehension (of ML processes) and related workload, as well as confidence (in decision making based on ML results) by users. This paper argues that the revealing of human cognition states with a multimodal interface during ML-based data analytics-driven decision making could provide a rich view for both ML researchers and domain experts to learn the effectiveness of ML technologies in applications. On the one hand, human cognition states could help understand to what degree users accept innovative technologies. On the other hand, through understanding human cognition states during data analytics-driven decision making, ML-based decision attributes and even ML models can be adaptively refined in order to make ML transparent. The paper also identifies examples of impact challenges and obstacles, as well as high-demand research directions in making ML transparent.

Zhou, J, Arshad, SZ, Wang, X, Li, Z, Feng, D & Chen, F 2018, 'End-User Development for Interactive Data Analytics: Uncertainty, Correlation and User Confidence', IEEE Transactions on Affective Computing, vol. 9, no. 3, pp. 383-395.
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This paper investigates End-User Development (EUD) for interactive data-analytic interfaces—building upon the ideas of making machine learning transparent. The research is carried out in a business operation environment (water pipe failure prediction in our case) motivated to integrate advanced analytics into decision-making processes of an urban Internet of Things (IoT) concept. We explore effects of revealing uncertainty and correlation on user confidence in a data-driven decision making scenario. It was found that user confidence varied significantly amongst various user groups when different machine learning models were displayed with/without supplementary information. Galvanic Skin Response (GSR) signals were analyzed and shown as reasonable indices for predicting user confidence levels. Supplementary data visualizations (of inherent uncertainty and correlation in data) contributed to explicability principles while GSR indexing added towards correctibility principles. We recommend transparent machine learning as the key to effective EUD for interactive data analytics.

Zhou, L, Fu, A, Yu, S, Su, M & Kuang, B 2018, 'Data integrity verification of the outsourced big data in the cloud environment: A survey', Journal of Network and Computer Applications, vol. 122, pp. 1-15.
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© 2018 Elsevier Ltd With the explosive growth of data and the rapid development of science technology, big data analysis has attracted increasing attention. Due to the restrictive performance of traditional devices, cloud computing emerges as a convenient storage and computing platform for big data analysis. Driven by benefits, cloud servers may intentionally delete or modify outsourced big data. Therefore, users need to make sure that the servers correctly store the outsourced big data prior to deploying the cloud computing applications in practice. To resolve the issue, many researchers have concentrated on enabling users to check the completeness of data with data integrity verification (DIV) technique. We have therefore collated a summary of the existing literature, aiming to present a solid and stimulating review of current academic achievements for interested readers. Firstly, we present a fundamental introduction by defining seven major topics in order to offer a summary of the existing research domain for DIV study. Secondly, we classify the state-of-the-art DIV solutions into four categories, and then we parse each category based on dynamics, providing a clear and hierarchical classification of forthcoming DIV efforts. Thirdly, we discuss the principal topics and technical means utilized to equip DIV schemes with different requirements. Finally, we discuss the issues and challenges anticipated in future work, thus suggesting possible directions for follow-up research.

Zhou, L, Yuksel, A, Markovich, O, Gabrael, N & Catchpoole, D 2018, 'The Tumour Bank at the Children’s Hospital at Westmead: An Australian Paediatric Cancer Biorepository', Open Journal of Bioresources, vol. 5, no. 0.
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© 2018 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/. The Tumor Bank at The Children's Hospital at Westmead was established in 1998 with the purpose of facilitating research into childhood malignancy through the active provision of well annotated, ethically collected tissue samples and providing a pathway for the Children Hospital at Westmead to engage in leading research initiatives, supporting international investigations and clinical trials. Within 20 years practice as a single institute biorepository, The Tumour Bank has established standard operating procedures for collection of tissue, blood and bone marrow that were integrated into routine patient management systems. In addition, three main operational areas have been developed: collection of biospecimens and written consent; management of clinical data and biospecimen inventory database; and implementation of an open access policy to support childhood cancer research around the world. Regulatory oversight is provided by the Tumour Bank Committee, Human Research Ethics Committee and Governance Department. This concerted effort has resulted in collecting 20340 specimens from 3788 patients within 20 years, and The Tumour bank has supported over 108 national and international research projects, and contributed to over 70 peer-reviewed publications to date, with a mean time-to-publication of 19.1 ± 9.0 months and average Impact Factor of 6.11 ± 4.53. In conclusion, the Children's Hospital at Westmead Tumour Bank has demonstrated a sustained single institutional biorepository model for facilitating translational research of rare cancer. It has provided strong evidence that integration of a single institutional biobank into ...

Zhou, S, Lin, J-Y, Wong, S-W, Deng, F, Zhu, L, Yang, Y, He, Y & Tu, Z-H 2018, 'Spoof Surface Plasmon Polaritons Power Divider with large Isolation', Scientific Reports, vol. 8, no. 1.
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AbstractPeriodic corrugated metal structure is designed to support and propagate spoof surface plasmon polaritons (SSPPs) wave in the microwave frequencies. In this paper, firstly a plasmonic waveguide consisting of oval-ring shaped cells is proposed with the performance of high transmission efficiency in a wide frequency range. The coplanar waveguides (CPWs) with 50 Ω impedance are adopted to feed the energies or extract signals at both ends of the plasmonic waveguide. Then a well-isolated power divider is constructed based on the SSPPs waveguides aiming to equally split the energy of the SSPPs wave into two equal parts. The stepped-impedances are co-designed with the three input/output ports of the power divider to achieve the impedance-matching between the SSPPs waveguides and the coplanar waveguides. Besides, a single resistor is placed in the middle of two symmetrical half oval-rings to realize the isolation between the two output ports over the spectrum of 4.5–7.5 GHz. Finally, both plasmonic waveguide and the power divider are fabricated and tested to verify the predicted characteristics.

Zhou, X, Jin, W, Sun, C, Gao, S-H, Chen, C, Wang, Q, Han, S-F, Tu, R, Latif, MA & Wang, Q 2018, 'Microbial degradation of N,N-dimethylformamide by Paracoccus sp. strain DMF-3 from activated sludge', Chemical Engineering Journal, vol. 343, pp. 324-330.
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© 2018 Elsevier B.V. N,N-dimethylformamide (DMF) was a typical toxic chemical and existed extensively in industrial wastewater. In this study, a strain of the high-efficient DMF degrading bacteria DMF-3 belonging to Paracoccus sp. was enriched and isolated from activated sludge. The removal rate of DMF by DMF-3 was up to 100% while 1000 mg/L DMF was used as the sole carbon and nitrogen source. Growth kinetics model of DMF-3 was thus established, and the kinetic constants were determined with maximum specific growth rate μmax = 0.22 (h−1), saturation constant Ks = 0.41 (g/L) and inhibition constant Ki = 25.93 (g/L). Based on the analysis of the intermediate products, it was found that DMF was firstly converted into dimethylamine and formic acid, and these intermediates were finally degraded to ammonia and carbon dioxide following the typical metabolic pathway of methylotrophs. In addition, to enhance the degrading capacity of DMF-3 in high DMF concentration, ultraviolet mutagenesis process was applied. Compared with the usage of the original strain of DMF-3, the degradation rate was increased by 14.8% with the usage of obtained mutant strain with applied initial DMF concentration 10,000 mg/L.

Zhou, X, Mitkova, L, Zhang, Y, Huang, L, Cunningham, S, Shang, L, Yu, H & Wang, K 2018, 'Technology-driven mergers and acquisitions of Chinese acquirers: development of a multi-dimensional framework for post-innovation performance', International Journal of Technology Management, vol. 78, no. 4, pp. 280-280.
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© 2018 Inderscience Enterprises Ltd. While some studies have observed the beneficial impact of mergers and acquisitions (M&As) on a firm's innovation performance in developed countries, others have found the consequences to be neutral or even negative. This article develops an integrated framework to elucidate how the combination of technological relatedness and product relatedness between acquiring and target firms affects post-innovation performance of technology-driven M&As. This performance is investigated by using a set of parameters, namely R&D input, patent and product activity, and the financial results from commercialisation. We conducted case studies on China's high-tech firms derived from three diverse industry sectors, and the empirical results indicate that both types of relatedness between the partners of technology-driven M&As are conducive to the intensification of R&D expenditures. The acquisition of similar technologies and products has more significant effects on R and D input and output, and M&As without technology relatedness have better financial performance, since they lead acquirers to new technology sectors or sub-sectors. In comparison, M&As with technological complementarity and product complementarity have negative effects on related innovation processes in the short term.

Zhou, Y, Zheng, K, Ni, W & Liu, RP 2018, 'Elastic Switch Migration for Control Plane Load Balancing in SDN', IEEE Access, vol. 6, pp. 3909-3919.
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© 2013 IEEE. Software-defined network (SDN) provides a solution for the scalable network framework with decoupled control and data plane. Migrating switches can balance the resource utilization of controllers and improve network performance. Switch migration problem has to date been formulated as a resource utilization maximization problem to address the scalability of the control plane. However, this problem is NP-hard with high-computational complexities and without addressing the security challenges of the control plane. In this paper, we propose a switch migration method, which interprets switch migration as a signature matching problem and is formulated as a 3-D earth mover's distance model to protect strategically important controllers in the network. Considering the scalability, we further propose a heuristic method which is time-efficient and suitable to large-scale networks. Simulation results show that our proposed methods can disguise strategically important controllers by diminishing the difference of traffic load between controllers. Moreover, our proposed methods can significantly relieve the traffic pressure of controllers and prevent saturation attacks.

Zhu, B, Duke, M, Dumée, LF, Merenda, A, Des Ligneris, E, Kong, L, Hodgson, PD & Gray, S 2018, 'Short Review on Porous Metal Membranes—Fabrication, Commercial Products, and Applications', Membranes, vol. 8, no. 3, pp. 83-83.
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Porous metal membranes have recently received increasing attention, and significant progress has been made in their preparation and characterisation. This progress has stimulated research in their applications in a number of key industries including wastewater treatment, dairy processing, wineries, and biofuel purification. This review examines recent significant progress in porous metal membranes including novel fabrication concepts and applications that have been reported in open literature or obtained in our laboratories. The advantages and disadvantages of the different membrane fabrication methods were presented in light of improving the properties of current membrane materials for targeted applications. Sintering of particles is one of the main approaches that has been used for the fabrication of commercial porous metal membranes, and it has great advantages for the fabrication of hollow fibre metal membranes. However, sintering processes usually result in large pores (e.g., >1 µm). So far, porous metal membranes have been mainly used for the filtration of liquids to remove the solid particles. For porous metal membranes to be more widely used across a number of separation applications, particularly for water applications, further work needs to focus on the development of smaller pore (e.g., sub-micron) metal membranes and the significant reduction of capital and maintenance costs.

Zhu, C, Cao, L, Liu, Q, Yin, J & Kumar, V 2018, 'Heterogeneous Metric Learning of Categorical Data with Hierarchical Couplings', IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 7, pp. 1254-1267.
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Zhu, G, Corcoran, J, Shyy, P, Pileggi, SF & Hunter, J 2018, 'Analysing journey-to-work data using complex networks', Journal of Transport Geography, vol. 66, pp. 65-79.
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© 2017 Elsevier Ltd It is well known that journey-to-work (JTW) data can be represented using complex network graphs. What is less evident is the way in which this approach can be used to quantitatively analyse the structure, connectivity and dynamics of commuting behaviour. This paper employs a complex network approach to spatially disaggregated JTW data in order to examine commuting behaviour for six different modes of transport (car, car passengers, train, bus, cycling and walking) within three of the most populous metropolitan areas in Australia. A set of network measures (degree, strength, clustering coefficient, maximum cliques, average shortest path length and betweenness) are computed from both the unweighted and weighted graphs corresponding to JTW data for the Sydney, Melbourne and the South East Queensland regions from the time periods: 2001, 2006 and 2011. Results reveal a number of interesting dynamics, one being that Melbourne exhibits shorter (and presumed to be faster) alternate commuting paths than either Sydney or South East Queensland given its lower betweenness and shortest path values allied with higher clustering coefficients. The interpretation of these metrics demonstrates that complex networks have the capacity to reveal new insights from JTW data, by enabling a more comprehensive, systematic, empirical and fine-grained analysis of changes in commuting behaviour over time.

Zhu, H & Abbosh, AM 2018, 'A Compact Tunable Directional Coupler with Continuously Tuned Differential Phase', IEEE Microwave and Wireless Components Letters, vol. 28, no. 1, pp. 19-21.
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© 2001-2012 IEEE. A tunable directional coupler with outputs that have continuously tuned phase difference and constant magnitude is presented. The initial design is based on a 3-dB branch-line coupler with two arms having variable electrical lengths. To realize the variable-length lines, a novel concept of tunable phase shifting unit, which includes a pair of inductor-varactor loaded coupled lines, is proposed. By controlling the shifting phase of the two arms, the differential phase (i.e., the phase difference between the two output ports) can be tuned continuously. Explicit relation between the objective differential phase of the device and the required shifting phase of those units is analyzed and explained. To validate the design, a prototype is built, simulated, and tested. The experimental and predicted results agree well and show that the device can realize arbitrary and continuously tunable differential phase from 45° to 135°. The overall size of the design is only 0.18 λ{g} \times 0.24 λ{g} , which is extremely compact compared with using a cascaded coupler-phase shifters and is thus suitable for miniaturized wireless systems.

Zhu, H, Abbosh, AM & Guo, L 2018, 'Planar In-Phase Filtering Power Divider With Tunable Power Division and Controllable Band for Wireless Communication Systems', IEEE Transactions on Components, Packaging and Manufacturing Technology, vol. 8, no. 8, pp. 1458-1468.
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© 2011-2012 IEEE. A wideband in-phase power divider with tunable power division ratio (PDR) and filtering response is presented. The proposed design is quite compact and consists of a three-line coupled structure and loaded with a pair of varactor-loaded short-ended stubs at two output terminations. A variable power division is realized by tuning the coupling factors between the centerline and sidelines of the three-line coupled structure using a pair of varactors. A varactor at the center of the loaded short-ended stub and another one connecting the end of the stub to the ground is used to control the center frequency and band of operation. A prototype is modeled using the microstrip technique and then simulated and tested. The experimental result indicates a tunability of PDR from 0.5:1 to 2:1 across wideband range of 60% and a controllable band from 35% to 63.2%, with 13% center frequency tunability, sharp passband cutoff selectivity, as well as harmonic suppression to more than 6 GHz (4 times the center frequency). Moreover, the overall loss is around 1-1.2 dB; the isolation is more than 14 dB, whereas the differential phase is less than 7° in all the investigated cases.

Zhu, H, Yang, Y, Zhu, X, Sun, Y & Wong, S-W 2018, 'Miniaturized Resonator and Bandpass Filter for Silicon-Based Monolithic Microwave and Millimeter-Wave Integrated Circuits', IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 12, pp. 4062-4071.
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© 2018 IEEE. This paper introduces a unique approach for the implementation of a miniaturized on-chip resonator and its application for the first-order bandpass filter (BPF) design. This approach utilizes a combination of a broadside-coupling technique and a split-ring structure. To fully understand the principle behind it, simplified LC equivalent-circuit models are provided. By analyzing these models, guidelines for implementation of an ultra-compact resonator and a BPF are given. To further demonstrate the feasibility of using this approach in practice, both the implemented resonator and the filter are fabricated in a standard 0.13-μm (Bi)-CMOS technology. The measured results show that the resonator can generate a resonance at 66.75 GHz, while the BPF has a center frequency at 40 GHz and an insertion loss of 1.7 dB. The chip size of both the resonator and the BPF, excluding the pads, is only 0.012mm2 (0.08 × 0.144 mm2).

Zhu, H, Zhu, X, Yang, Y & Xue, Q 2018, 'Design of Wideband Third-Order Bandpass Filters Using Broadside-Coupled Resonators in 0.13-$\mu$ m (Bi)-CMOS Technology', IEEE Transactions on Microwave Theory and Techniques, vol. 66, no. 12, pp. 5593-5604.
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© 2018 IEEE. In this paper, two third-order bandpass filters (BPFs) designed for millimeter-wave applications are presented. Unlike previously published ones, the proposed designs use a 'cell-based' approach, which utilizes identical broadside-coupled resonators (BCRs) with series and shunt capacitors. The capacitors are mainly used as J -inverters to achieve the desired frequency responses. To fully understand the operational mechanism of the presented approach, both the BCR and BPFs are analyzed using the simplified LC-equivalent circuit models. To prove the concept, both BPFs are implemented in a standard 0.13- μm silicon-germanium bipolar complementary metal-oxide-semiconductor technology. According to the on-wafer measurement results, the BPFs exhibit the excellent performance including flat in-band responses with relatively large harmonic suppression. The first design has a 1-dB bandwidth from 23.9 to 39.7 GHz with an insertion loss of 3.9 dB at the center frequency of 31 GHz. The stopband attenuation is better than 45 dB at 58 GHz. The 1-dB bandwidth of the second design covers from 26.7 to 44.3 GHz with an insertion loss of 3.1 dB at the center frequency of 35 GHz, and stopband attenuation up to 35 dB is achieved at 59 GHz. Both designs occupy an identical area of 0.073 mm 2 (0.248×0.294 mm 2 ), excluding the G-S-G testing pads.

Zhu, J, Chu, C-H, Deng, L, Zhang, C, Yang, Y & Li, S 2018, 'mm-Wave High Gain Cavity-Backed Aperture-Coupled Patch Antenna Array', IEEE Access, vol. 6, pp. 44050-44058.
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© 2013 IEEE. A wideband and high gain cavity-backed 4 × 4 patch antenna array is proposed in this paper. Each patch antenna element of the array is enclosed by a rectangular cavity and differentially-fed by the slot underneath. By optimizing the geometry of the radiating patch and the cavity, a very uniform E-field distribution at the antenna aperture is achieved, leading to the high array aperture efficiency and thus the gain. Taking advantages of the higher-order substrate integrated cavity excitation, the elements of the array are efficiently fed with the same amplitude and phase in a simplified feeding mechanism instead of the conventional bulky and lossy power-splitter-based feeding network. Measured results show the antenna bandwidth is from 56 to 63.1-GHz (16.1%) with the peak gain reaching 21.4 dBi. The radiation patterns of the array are very stable over the entire frequency band and the cross-polarizations are as low as -30 dB. These good characteristics demonstrate that the proposed array can be a good candidate for the future 60-GHz communication system applications.

Zhu, J, Li, S, Deng, L, Zhang, C, Yang, Y & Zhu, H 2018, 'Broadband tunable terahertz polarization converter based on a sinusoidally-slotted graphene metamaterial', Optical Materials Express, vol. 8, no. 5, pp. 1164-1164.
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© 2018 Optical Society of Americaunder. A new wideband sinusoidally-slotted graphene-based cross-polarization converter (CPC) is proposed in this paper. The proposed polarization converter can realize a broadband terahertz polarization conversion from 1.28 to 2.13-THz with a polarization conversion ratio (PCR) of more than 0.85. Taking advantage of the gradient width modulation of the graphene-based unit structure, the continuous plasmon resonances are excited at the edges of the sinusoidal slot. Therefore, the proposed converter can achieve a broadband polarization conversion in a simplified structure. Furthermore, the polarization conversion characteristics of the CPC are insensitive to the incident angle. The PCR remains more than 0.85 with little bandwidth degradation even as the incident angle increases to as high as 50°. More importantly, the operating bandwidth and the magnitude of the PCR can be tuned easily by adjusting the chemical potential and the electron scattering times of the graphene. In a way, we believe this kind of graphene-based polarization converter can enrich the polarization conversion community for realizing broadband and tunable polarization conversion.

Zhu, J, Li, S, Liao, S, Yang, Y & Zhu, H 2018, '60 GHz Substrate-Integrated-Waveguide-Fed Patch Antenna Array With Quadri-Polarization', IEEE Transactions on Antennas and Propagation, vol. 66, no. 12, pp. 7406-7411.
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© 1963-2012 IEEE. This communication presents a new design of a quadri-polarization-agile aperture-coupled patch antenna array for 60 GHz applications. Four polarization states, namely, vertical linear polarization, horizontal linear polarization, left-hand circular polarization (LHCP), and right-hand circular polarization (RHCP) can be flexibly reconfigured by dynamically switching the excitation of the corresponding port. More importantly, as the LP and CP radiations are achieved by using differential feeding and sequential-rotation feeding, respectively, the array exhibits wide impedance and axial ratio (AR) bandwidths, high polarization purity as well as symmetrical pattern with the main beam fixed at boresight. The-10 dB impedance bandwidths are better than 11.6% (57-64 GHz) for the four polarization states. The measured AR bandwidths are from 58 to more than 64 GHz for both the LHCP and RHCP. The good radiation performance together with the quadri-polarization-agile capability of this new array, as demonstrated in the communication, underlines its suitability for the future 5G communication systems, especially in a multipath propagation environment.

Zhu, J, Liao, S, Yang, Y, Li, S & Xue, Q 2018, '60 GHz Dual-Circularly Polarized Planar Aperture Antenna and Array', IEEE Transactions on Antennas and Propagation, vol. 66, no. 2, pp. 1014-1019.
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© 1963-2012 IEEE. This communication presents new designs of dual-circularly polarized (CP) planar aperture antenna and array for 60 GHz applications. First, a four-port planar aperture antenna with its feeding network is developed that exhibits wide impedance bandwidth, dual-CP radiation as well as high gain. Then, based on the proposed antenna, a new scheme of building a dual-CP array is proposed. With this new scheme that combines the power splitting network and series feeding method, four sequentially fed antenna elements are successfully combined to form a CP radiation array. The experimental results show that the -10 dB impedance bandwidths of the antenna and the array are more than 18.2% (55-66 GHz). While the 3 dB axial ratio bandwidths are from 54.2 to 64.3 GHz (17.2%) for the antenna and from 54.8 to 65 GHz (17%) for the array. The maximum gains achieved are 13.7 and 17.85 dBic for the antenna and array, respectively.

Zhu, J, Yang, Y & Li, S 2018, 'A photo-excited broadband to dual-band tunable terahertz prefect metamaterial polarization converter', Optics Communications, vol. 413, pp. 336-340.
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© 2018 Elsevier B.V. A new and simple design of photo-excited broadband to dual-band tunable terahertz (THz) metamaterial cross polarization converter is proposed in this paper. The tunable converter is a sandwich structure with the center-cut cross-shaped metallic patterned structure as a resonator, the middle dielectric layer as a spacer and the bottom metallic film as the ground. The conductivity of the photoconductive semiconductor (Silicon) filled in the gap of the cross-shaped metallic resonator can be tuned by the incident pump power, leading to an easy modulation of the electromagnetic response of the proposed converter. The results show that the proposed cross-polarization converter can be tuned from a broadband with polarization conversion ratio (PCR) beyond 95% (1.86–2.94 THz) to dual frequency bands (fl=1.46 THz & fh=2.9 THz). The conversion peaks can reach 99.9% for the broadband and, 99.5% (fl) and 99.7% (fh) for the dual-band, respectively. Most importantly, numerical simulations demonstrate that the broadband/dual-band polarization conversion mechanism of the converter originates from the localized surface plasmon modes, which make the design simple and different from previous designs. With these good features, the proposed broadband to dual-band tunable polarization converter is expected to be used in widespread applications.

Zhu, M, He, B & Wu, Q 2018, 'Single Image Dehazing Based on Dark Channel Prior and Energy Minimization', IEEE Signal Processing Letters, vol. 25, no. 2, pp. 174-178.
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© 2017 IEEE. Hazy images have limited visibility and low contrast. The degradation is expressed by transmission map, which is one of the most important estimates of single image dehazing. Transmission map estimation is an underconstraint problem, and lots of priors have been proposed. Among them, the dark channel prior is widely recognized. However, traditional methods have not fully exploited its power due to improper assumptions or operations, which cause unwanted artifacts. The postrefinement algorithms employed to remove these artifacts in turn undermine the merits of the prior. In this letter, a novel method for estimating transmission map by energy minimization is proposed to solve this problem. The energy function combines the dark channel prior with piecewise smoothness. The method is compared to the state-of-the-art methods and shows outstanding performance.

Zhu, R, Xu, W, Ye, C, Zhu, J, Lei, G & Li, X 2018, 'Design Optimization of a Novel Heteropolar Radial Hybrid Magnetic Bearing Using Magnetic Circuit Model', IEEE Transactions on Magnetics, vol. 54, no. 3, pp. 1-5.
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© 2017 IEEE. In this paper, one novel heteropolar radial hybrid magnetic bearing (HRHMB) with low-power loss is proposed for flywheel energy storage system. First, its structure and equivalent magnetic circuit (EMC) are introduced in detail. Then, some main design parameters are analyzed based on EMC, including air-gap bias flux density, magnetic pole area, permanent magnet (PM) dimensions, and control current. Furthermore, to improve the performances of the novel HRHMB, the optimizations are implemented both on its structure and some key size parameters, such as the second air-gap length, PM height, and width. Finally, the optimal scheme is verified by the 3-D finite-element analysis, which indicates the maximum control current can be reduced to only 40% that of initial design by the optimizations.

Zhu, X, Mochiku, T, Fujii, H, Tang, K, Hu, Y, Huang, Z, Luo, B, Ozawa, K & Wang, L 2018, 'A new sodium iron phosphate as a stable high-rate cathode material for sodium ion batteries', Nano Research, vol. 11, no. 12, pp. 6197-6205.
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© 2018, Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature. Low-cost room-temperature sodium-ion batteries (SIBs) are expected to promote the development of stationary energy storage applications. However, due to the large size of Na+, most Na+ host structures resembling their Li+ counterparts show sluggish ion mobility and destructive volume changes during Na ion (de)intercalation, resulting in unsatisfactory rate and cycling performances. Herein, we report a new type of sodium iron phosphate (Na0.71Fe1.07PO4), which exhibits an extremely small volume change (~ 1%) during desodiation. When applied as a cathode material for SIBs, this new phosphate delivers a capacity of 78 mA·h·g−1 even at a high rate of 50 C and maintains its capacity over 5,000 cycles at 20 C. In situ synchrotron characterization disclosed a highly reversible solid-solution mechanism during charging/discharging. The findings are believed to contribute to the development of high-performance batteries based on Earth-abundant elements. [Figure not available: see fulltext.].

Zhu, XQ, Law, SS & Huang, L 2018, 'Identification of Railway Ballasted Track Systems from Dynamic Responses of In-Service Trains', Journal of Aerospace Engineering, vol. 31, no. 5, pp. 04018060-04018060.
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© 2018 American Society of Civil Engineers. Railway track is one of the most important parts of the railway system, and monitoring its condition is essential to ensure the safety of trains and reduce maintenance cost. An adaptive regularization approach is adopted in this paper to identify the parameters of a railway ballasted track system (substructure) from dynamic measurements on in-service vehicles. The vehicle-track interaction system is modeled as a discrete spring-mass model on a Winkler elastic foundation. Damage is defined as the stiffness reduction of the track due to foundation settlement, loosening in the rail fastener, and lack of compaction of the ballast. Accelerometers are installed on the underframe of the train to capture the dynamic responses from which the interaction forces between the vehicle and the railway track are determined. The damage of the railway track can be detected via changes in the interaction force. Numerical results show that the proposed approach can identify all stiffness parameters successfully at a low moving speed and at a high sampling rate when measurement noise is involved.

Zhu, XQ, Law, SS, Huang, L & Zhu, SY 2018, 'Damage identification of supporting structures with a moving sensory system', Journal of Sound and Vibration, vol. 415, pp. 111-127.
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© 2017 Elsevier Ltd An innovative approach to identify local anomalies in a structural beam bridge with an instrumented vehicle moving as a sensory system across the bridge. Accelerations at both the axle and vehicle body are measured from which vehicle-bridge interaction force on the structure is determined. Local anomalies of the structure are estimated from this interaction force with the Newton's iterative method basing on the homotopy continuation method. Numerical results with the vehicle moving over simply supported or continuous beams show that the acceleration responses from the vehicle or the bridge structure are less sensitive to the local damages than the interaction force between the wheel and the structure. Effects of different movement patterns and moving speed of the vehicle are investigated, and the effect of measurement noise on the identified results is discussed. A heavier or slower vehicle has been shown to be less sensitive to measurement noise giving more accurate results.

Zou, S, Tang, Y, Ni, W, Liu, RP & Wang, L 2018, 'Resource multi-objective mapping algorithm based on virtualized network functions: RMMA', Applied Soft Computing, vol. 66, pp. 220-231.
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Zou, Y, Liu, Y, Yang, Z, Zhang, D, Lu, Y, Zheng, M, Xue, X, Geng, J, Chung, R & Shi, B 2018, 'Effective and Targeted Human Orthotopic Glioblastoma Xenograft Therapy via a Multifunctional Biomimetic Nanomedicine', Advanced Materials, vol. 30, no. 51.
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AbstractGlioblastoma multiforme (GBM) is a fatal central nervous system tumor without effective treatment. Chemotherapeutic agents are mainstays in the treatment of glioblastoma. However, the effectiveness of these is seriously hindered by poor blood–brain‐barrier (BBB) penetrance and tumor targeting, together with short biological half‐life. Improved chemotherapy is thus urgently needed for GBM. Multifunctional nanoparticle delivery systems offer much promise in overcoming current limitations. Accordingly, a multifunctional biomimetic nanomedicine is developed by functionalizing the surface of red blood cell membranes (RBCms) with angiopep‐2 and loading pH‐sensitive nanoparticles (polymer, doxorubicin (Dox), and lexiscan (Lex)) using the functionalized cell membrane to generate the novel nanomedicine, Ang‐RBCm@NM‐(Dox/Lex). The studies toward orthotopic U87MG human glioblastoma tumor‐bearing nude mice show that the Ang‐RBCm@NM‐(Dox/Lex) nanomedicine has much improved blood circulation time, superb BBB penetration, superior tumor accumulation and retention. Moreover, effective suppression of tumor growth and significantly improved medium survival time are also observed after Ang‐RBCm@NM‐(Dox/Lex) treatment. The results show that this biomimetic nanoplatform can serve as a flexible and powerful system for GBM treatment which can be readily adapted for the treatment of other central nervous system (CNS) disorders.

Zucca, P, Morosan, DE, Rouillard, AP, Fallows, R, Gallagher, PT, Magdalenic, J, Klein, K-L, Mann, G, Vocks, C, Carley, EP, Bisi, MM, Kontar, EP, Rothkaehl, H, Dabrowski, B, Krankowski, A, Anderson, J, Asgekar, A, Bell, ME, Bentum, MJ, Best, P, Blaauw, R, Breitling, F, Broderick, JW, Brouw, WN, Brüggen, M, Butcher, HR, Ciardi, B, de Geus, E, Deller, A, Duscha, S, Eislöffel, J, Garrett, MA, Grießmeier, JM, Gunst, AW, Heald, G, Hoeft, M, Hörandel, J, Iacobelli, M, Juette, E, Karastergiou, A, van Leeuwen, J, McKay-Bukowski, D, Mulder, H, Munk, H, Nelles, A, Orru, E, Paas, H, Pandey, VN, Pekal, R, Pizzo, R, Polatidis, AG, Reich, W, Rowlinson, A, Schwarz, DJ, Shulevski, A, Sluman, J, Smirnov, O, Sobey, C, Soida, M, Thoudam, S, Toribio, MC, Vermeulen, R, van Weeren, RJ, Wucknitz, O & Zarka, P 2018, 'Shock location and CME 3D reconstruction of a solar type II radio burst with LOFAR', Astronomy & Astrophysics, vol. 615, pp. A89-A89.
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Context. Type II radio bursts are evidence of shocks in the solar atmosphere and inner heliosphere that emit radio waves ranging from sub-meter to kilometer lengths. These shocks may be associated with coronal mass ejections (CMEs) and reach speeds higher than the local magnetosonic speed. Radio imaging of decameter wavelengths (20–90 MHz) is now possible with the Low Frequency Array (LOFAR), opening a new radio window in which to study coronal shocks that leave the inner solar corona and enter the interplanetary medium and to understand their association with CMEs.Aims. To this end, we study a coronal shock associated with a CME and type II radio burst to determine the locations at which the radio emission is generated, and we investigate the origin of the band-splitting phenomenon.Methods. Thetype II shock source-positions and spectra were obtained using 91 simultaneous tied-array beams of LOFAR, and the CME was observed by the Large Angle and Spectrometric Coronagraph (LASCO) on board the Solar and Heliospheric Observatory (SOHO) and by the COR2A coronagraph of the SECCHI instruments on board the Solar Terrestrial Relation Observatory(STEREO). The 3D structure was inferred using triangulation of the coronographic observations. Coronal magnetic fields were obtained from a 3D magnetohydrodynamics (MHD) polytropic model using the photospheric fields measured by the Heliospheric Imager (HMI) on board the Solar Dynamic Observatory (SDO) as lower boundary.Results. The type II radio source of the coronal shock observed between 50 and 70 MHz was found to be located at the expanding flank of the CME, where the shock geometry is quasi-perpendicular with θBn ~ 70°. The type II radio burst showed first and second harmonic emission; the second harmo...

Zuo, H, Zhang, G, Pedrycz, W, Behbood, V & Lu, J 2018, 'Granular Fuzzy Regression Domain Adaptation in Takagi–Sugeno Fuzzy Models', IEEE Transactions on Fuzzy Systems, vol. 26, no. 2, pp. 847-858.
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© 1993-2012 IEEE. In classical data-driven machine learning methods, massive amounts of labeled data are required to build a high-performance prediction model. However, the amount of labeled data in many real-world applications is insufficient, so establishing a prediction model is impossible. Transfer learning has recently emerged as a solution to this problem. It exploits the knowledge accumulated in auxiliary domains to help construct prediction models in a target domain with inadequate training data. Most existing transfer learning methods solve classification tasks; only a few are devoted to regression problems. In addition, the current methods ignore the inherent phenomenon of information granularity in transfer learning. In this study, granular computing techniques are applied to transfer learning. Three granular fuzzy regression domain adaptation methods to determine the estimated values for a regression target are proposed to address three challenging cases in domain adaptation. The proposed granular fuzzy regression domain adaptation methods change the input and/or output space of the source domain's model using space transformation, so that the fuzzy rules are more compatible with the target data. Experiments on synthetic and real-world datasets validate the effectiveness of the proposed methods.

Zuo, Y, Wu, Q, An, P & Shang, X 2018, 'Integrated cosparse analysis model with explicit edge inconsistency measurement for guided depth map upsampling', Journal of Electronic Imaging, vol. 27, no. 04, pp. 1-1.
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© 2018 SPIE and IS & T. A low-resolution depth map can be upsampled through the guidance from the registered high-resolution color image. This type of method is so-called guided depth map upsampling. Among the existing methods based on Markov random field (MRF), either data-driven or model-based prior is adopted to construct the regularization term. The data-driven prior can implicitly reveal the relation between color-depth image pair by training on external data. The model-based prior provides the anisotropic smoothness constraint guided by high-resolution color image. These types of priors can complement each other to solve the ambiguity in guided depth map upsampling. An MRF-based approach is proposed that takes both of them into account to regularize the depth map. Based on analysis sparse coding, the data-driven prior is defined by joint cosparsity on the vectors transformed from color-depth patches using the pair of learned operators. It is based on the assumption that the cosupports of such bimodal image structures computed by the operators are aligned. The edge inconsistency measurement is explicitly calculated, which is embedded into the model-based prior. It can significantly mitigate texture-copying artifacts. The experimental results on Middlebury datasets demonstrate the validity of the proposed method that outperforms seven state-of-the-art approaches.

Zuo, Y, Wu, Q, Zhang, J & An, P 2018, 'Explicit Edge Inconsistency Evaluation Model for Color-Guided Depth Map Enhancement', IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 2, pp. 439-453.
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© 2016 IEEE. Color-guided depth enhancement is used to refine depth maps according to the assumption that the depth edges and the color edges at the corresponding locations are consistent. In methods on such low-level vision tasks, the Markov random field (MRF), including its variants, is one of the major approaches that have dominated this area for several years. However, the assumption above is not always true. To tackle the problem, the state-of-the-art solutions are to adjust the weighting coefficient inside the smoothness term of the MRF model. These methods lack an explicit evaluation model to quantitatively measure the inconsistency between the depth edge map and the color edge map, so they cannot adaptively control the efforts of the guidance from the color image for depth enhancement, leading to various defects such as texture-copy artifacts and blurring depth edges. In this paper, we propose a quantitative measurement on such inconsistency and explicitly embed it into the smoothness term. The proposed method demonstrates promising experimental results compared with the benchmark and state-of-the-art methods on the Middlebury ToF-Mark, and NYU data sets.

Zuo, Y, Wu, Q, Zhang, J & An, P 2018, 'Minimum Spanning Forest With Embedded Edge Inconsistency Measurement Model for Guided Depth Map Enhancement', IEEE Transactions on Image Processing, vol. 27, no. 8, pp. 4145-4159.
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© 1992-2012 IEEE. Guided depth map enhancement based on Markov random field (MRF) normally assumes edge consistency between the color image and the corresponding depth map. Under this assumption, the low-quality depth edges can be refined according to the guidance from the high-quality color image. However, such consistency is not always true, which leads to texture-copying artifacts and blurring depth edges. In addition, the previous MRF-based models always calculate the guidance affinities in the regularization term via a non-structural scheme, which ignores the local structure on the depth map. In this paper, a novel MRF-based method is proposed. It computes these affinities via the distance between pixels in a space consisting of the minimum spanning trees (forest) to better preserve depth edges. Furthermore, inside each minimum spanning tree, the weights of edges are computed based on the explicit edge inconsistency measurement model, which significantly mitigates texture-copying artifacts. To further tolerate the effects caused by noise and better preserve depth edges, a bandwidth adaption scheme is proposed. Our method is evaluated for depth map super-resolution and depth map completion problems on synthetic and real data sets, including Middlebury, ToF-Mark, and NYU. A comprehensive comparison against 16 state-of-the-art methods is carried out. Both qualitative and quantitative evaluations present the improved performances.

Zwinkau, R, Möhle, R, Frentrup, S & Deuse, J 2018, 'Metall/Nichtmetall-Klassifikation von Partikeln mit Deep Learning', JOT Journal für Oberflächentechnik, vol. 58, no. 10, pp. 50-57.
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