Publications

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.

Bishop, AN, Moral, PD & Niclas, A 2018, An introduction to Wishart matrix moments, Now Publishers.
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This article provides a comprehensive, rigorous, and self-contained introduction to the analysis of Wishart matrix moments. This article may act as an introduction to some aspects of random matrix theory, or as a self-contained exposition of Wishart matrix moments. Random matrix theory plays a central role in nuclear and statistical physics, computational mathematics and engineering sciences, including data assimilation, signal processing, combinatorial optimization, compressed sensing, econometrics and mathematical finance, among numerous others. The mathematical foundations of the theory of random matrices lies at the intersection of combinatorics, non-commutative algebra, geometry, multivariate functional and spectral analysis, and of course statistics and probability theory. As a result, most of the classical topics in random matrix theory are technical, and mathematically difficult to penetrate for non-experts and regular users and practitioners. The technical aim of this article is to review and extend some important results in random matrix theory in the specific context of real random Wishart matrices. This special class of Gaussian-type sample covariance matrix plays an important role in multivariate analysis and in statistical theory. We derive non-asymptotic formulae for the full matrix moments of real valued Wishart random matrices. As a corollary, we derive and extend a number of spectral and trace-type results for the case of non-isotropic Wishart random matrices. We also derive the full matrix moment analogues of some classic spectral and trace-type moment results. For example, we derive semi-circle and Marchencko-Pastur-type laws in the non-isotropic and full matrix cases. Laplace matrix transforms and matrix moment estimates are also studied, along with new spectral and trace concentration-type inequalities.

Argha, A, Su, S, Li, L, Nguyen, HT & Celler, B 2018, 'DSMC for NCSs involving consecutive measurement packet losses' in Advances in Discrete-Time Sliding Mode Control Theory and Applications, 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.

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, 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.

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.

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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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.

Al-Ani, A & Mesbah, M 2018, 'EEG rhythm/channel selection for fuzzy rule-based alertness state characterization', Neural Computing and Applications, vol. 30, no. 7, pp. 2257-2267.
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© 2016 The Natural Computing Applications ForumThe aim of the paper is to automatically select the optimal EEG rhythm/channel combinations capable of classifying human alertness states. Four alertness states were considered, namely ‘engaged’, ‘calm’, ‘drowsy’ and ‘asleep’. The features used in the automatic selection are the energies associated with the conventional rhythms, (Formula presented.) and (Formula presented.), extracted from overlapping windows of the different EEG channels. The selection process consists of two stages. In the first stage, the optimal brain regions, represented by sets of EEG channels, are selected using a simple search technique based on support vector machine (SVM), extreme learning machine (ELM) and LDA classifiers. In the second stage, a fuzzy rule-based alertness classification system (FRBACS) is used to identify, from the previously selected EEG channels, the optimal features and their supports. The IF–THEN rules used in FRBACS are constructed using a novel differential evolution-based search algorithm particularly designed for this task. Each alertness state is represented by a set of IF–THEN rules whose antecedent parts contain EEG rhythm/channel combination. The selected spatio-frequency features were found to be good indicators of the different alertness states, as judged by the classification performance of the FRBACS that was found to be comparable to those of the SVM, ELM and LDA classifiers. Moreover, the proposed classification system has the advantage of revealing simple and easy to interpret decision rules associated with each of the alertness states.

Al-Dmour, H & Al-Ani, A 2018, 'A clustering fusion technique for MR brain tissue segmentation', Neurocomputing, vol. 275.
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© 2017 Elsevier B.V. In recent decades, a large number of segmentation methods have been introduced and applied to magnetic resonance (MR) brain image analysis to measure and visualize the anatomical structures of interest. In this paper, an efficient fully-automatic brain tissue segmentation algorithm based on a clustering fusion technique is presented. In the training phase of this algorithm, the pixel intensity value is scaled to enhance the contrast of the image. The brain image pixels that have similar intensity are then grouped into objects using a superpixel algorithm. Further, three clustering techniques are utilized to segment each object. For each clustering technique, a neural network (NN) model is fed with features extracted from the image objects and is trained using the labels produced by that clustering technique. In the testing phase, pre-processing step includes scaling and resizing the brain image are applied then the superpixel algorithm partitions the image into multiple objects (similar to the training phase). The three trained neural network models are then used to predict the respective class of each object and the obtained classes are combined using majority voting. The efficiency of the proposed method is demonstrated on various MR brain images and compared with the three base clustering techniques.

Al-Zubi, MM & Sanagavarapu, A 2018, 'Modeling a Composite Molecular Communication Channel', IEEE Transactions on Communications, vol. 66, no. 8.
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The paper deals with development of diffusive propagation model for molecular communication in composite biological microenvironments with multiple regions each with distinct diffusion properties for the understanding of the transport of information molecules. We propose a generalized analytical approach for modelling a composite, diffusive, molecular communication channel for arbitrary placement of the transmitting and receiving nano-machines. Using this approach, we derive a generalised closed-form expression for the channel impulse response of a three dimensionally (3D) diffusive medium having “N” multiple regions. In addition, a particle-based simulator for modelling a 3-D diffusive medium with multiple regions is also proposed. We use the exact analytical solution to validate the simulations. The pulse peak amplitude, pulse peak time and pulse width are derived to evaluate the system performance using both analytical and simulation approaches. It is shown that the channel impulse response and other communication metrics are significantly affected by the diffusion coefficients, region thickness, interface properties as well as the positions of transmitter and receiver nano-machines with respect to the interfaces.

Al-Zubi, MM & Sanagavarapu, A 2018, 'Modeling of Ligand-Receptor Protein Interaction in Biodegradable Spherical Bounded Biological Micro-Environments', IEEE Access, vol. PP, no. 99.
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In this paper, we propose a generalized model for the Ligand-Receptor protein interaction in 3-D spherically bounded, diffusive biological microenvironments using molecular communication paradigm. Modeling a targeted cell as a receiver nano-machine, we derive analytical expressions for the Green’s function as well as for the expected number of the activated receptors. The molecular degradation in the environment due to enzymatic effects and the changes in pH levels are included via the first-order degradation reaction mechanism. A second-order reversible reaction mechanism is employed to model the reception process that involve the reaction of ligands to activate the receptor proteins lying on the receiver surface to form ligand-receptor complexes. We also present a particle-based simulator that incorporates the reversible reaction of molecules with the receptors present on the surface of a receiver that is located inside a bounded, 3-D microfluidic environment. Our simulations also include molecular degradation and boundary absorption of the ligands due to collision. The simulation results show perfect agreement with the results obtained from the analytical, bounded, and 3-D spherical model of the medium. The proposed models can be used for accurate prediction of the drug concentration profiles and number of activated receptors at any targeted cell.

Anam, K & Al-Jumaily, A 2018, 'Optimized kernel extreme learning machine for myoelectric pattern recognition', International Journal of Electrical and Computer Engineering, vol. 8, no. 1, pp. 483-496.
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© 2018 Institute of Advanced Engineering and Science. All rights reserved. Myoelectric pattern recognition (MPR) is used to detect user's intention to achieve a smooth interaction between human and machine. The performance of MPR is influenced by the features extracted and the classifier employed. A kernel extreme learning machine especially radial basis function extreme learning machine (RBF-ELM) has emerged as one of the potential classifiers for MPR. However, RBF-ELM should be optimized to work efficiently. This paper proposed an optimization of RBF-ELM parameters using hybridization of particle swarm optimization (PSO) and a wavelet function. These proposed systems are employed to classify finger movements on the amputees and able-bodied subjects using electromyography signals. The experimental results show that the accuracy of the optimized RBF-ELM is 95.71% and 94.27% in the healthy subjects and the amputees, respectively. Meanwhile, the optimization using PSO only attained the average accuracy of 95.53 %, and 92.55 %, on the healthy subjects and the amputees, respectively. The experimental results also show that SW-RBF-ELM achieved the accuracy that is better than other well-known classifiers such as support vector machine (SVM), linear discriminant analysis (LDA) and k-nearest neighbor (kNN).

Argha, A, Li, L & Su, S 2018, 'H2-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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This 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 urn:x-wiley:rnc:media:rnc3852:rnc3852-math-0004 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, Savkin, A, Liaw, S-T & Celler, BG 2018, 'Effect of Seasonal Variation on Clinical Outcome in Patients with Chronic Conditions: Analysis of the Commonwealth Scientific and Industrial Research Organization (CSIRO) National Telehealth Trial.', JMIR medical informatics, vol. 6, no. 1, pp. e16-e16.
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Seasonal variation has an impact on the hospitalization rate of patients with a range of cardiovascular diseases, including myocardial infarction and angina. This paper presents findings on the influence of seasonal variation on the results of a recently completed national trial of home telemonitoring of patients with chronic conditions, carried out at five locations along the east coast of Australia.The aim is to evaluate the effect of the seasonal timing of hospital admission and length of stay on clinical outcome of a home telemonitoring trial involving patients (age: mean 72.2, SD 9.4 years) with chronic conditions (chronic obstructive pulmonary disease coronary artery disease, hypertensive diseases, congestive heart failure, diabetes, or asthma) and to explore methods of minimizing the influence of seasonal variations in the analysis of the effect of at-home telemonitoring on the number of hospital admissions and length of stay (LOS).Patients were selected from a hospital list of eligible patients living with a range of chronic conditions. Each test patient was case matched with at least one control patient. A total of 114 test patients and 173 control patients were available in this trial. However, of the 287 patients, we only considered patients who had one or more admissions in the years from 2010 to 2012. Three different groups were analyzed separately because of substantially different climates: (1) Queensland, (2) Australian Capital Territory and Victoria, and (3) Tasmania. Time series data were analyzed using linear regression for a period of 3 years before the intervention to obtain an average seasonal variation pattern. A novel method that can reduce the impact of seasonal variation on the rate of hospitalization and LOS was used in the analysis of the outcome variables of the at-home telemonitoring trial.Test patients were monitored for a mean 481 (SD 77) days with 87% (53/61) of patients monitored for more than 12 months. Trends in seasonal variat...

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. 1-17.
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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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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.

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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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.

Bertoli, F & Bishop, AN 2018, 'Nonlinear stochastic receding horizon control: stability, robustness and Monte Carlo methods for control approximation', International Journal of Control, vol. 91, no. 10, pp. 2387-2402.
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© 2017 Informa UK Limited, trading as Taylor & Francis Group This work considers the stability of nonlinear stochastic receding horizon control when the optimal controller is only computed approximately. A number of general classes of controller approximation error are analysed including deterministic and probabilistic errors and even controller sample and hold errors. In each case, it is shown that the controller approximation errors do not accumulate (even over an infinite time frame) and the process converges exponentially fast to a small neighbourhood of the origin. In addition to this analysis, an approximation method for receding horizon optimal control is proposed based on Monte Carlo simulation. This method is derived via the Feynman–Kac formula which gives a stochastic interpretation for the solution of a Hamilton–Jacobi–Bellman equation associated with the true optimal controller. It is shown, and it is a prime motivation for this study, that this particular controller approximation method practically stabilises the underlying nonlinear process.

Bishop, AN & Del Moral, P 2018, 'On the robustness of Riccati flows to complete model misspecification', Journal of the Franklin Institute, vol. 355, no. 15, pp. 7178-7200.
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© 2018 The Franklin Institute Consider the continuous-time matrix Riccati operator Ricc(Q)=AQ+QA′−QSQ+R. In this work, we consider the robustness of this operator to direct perturbations of the matrices (A, R, S) and, in particular, the flow robustness of the corresponding Riccati differential equation. For a given class of perturbation, we show that the corresponding differential equation is well defined in the sense it is bounded above and below, it has a well-defined fixed point, and it converges to this fixed point exponentially fast. Moreover, the flow of the perturbed Riccati flow is close to the nominal Riccati flow when the perturbation is small; i.e. we prove a continuity-type condition in the size of the perturbation.

Bishop, AN & Moral, PD 2018, 'On the Stability of Matrix-Valued Riccati Diffusions'.
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The stability properties of matrix-valued Riccati diffusions are investigated. The matrix-valued Riccati diffusion processes considered in this work are of interest in their own right, as a rather prototypical model of a matrix-valued quadratic stochastic process. In addition, this class of stochastic models arise in signal processing and data assimilation, and more particularly in ensemble Kalman-Bucy filtering theory. In this context, the Riccati diffusion represents the flow of the sample covariance matrices associated with McKean-Vlasov-type interacting Kalman-Bucy filters. Under rather natural observability and controllability conditions, we derive exponential contraction inequalities, and time-uniform moment and fluctuation estimates. Our approach combines spectral theory with nonlinear semigroup methods and stochastic flow matrix calculus. The analysis developed in this article applies to filtering problems with unstable signals. These results seem to be the first this kind for this class of matrix-valued stochastic differential equation.

Bishop, AN, Del Moral, P & Pathiraja, SD 2018, 'Perturbations and projections of Kalman–Bucy semigroups', Stochastic Processes and their Applications, vol. 128, no. 9, pp. 2857-2904.
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© 2017 Elsevier B.V. We analyse various perturbations and projections of Kalman–Bucy semigroups and Riccati equations. For example, covariance inflation-type perturbations and localisation methods (projections) are common in the ensemble Kalman filtering literature. In the limit of these ensemble methods, the regularised sample covariance tends toward a solution of a perturbed/projected Riccati equation. With this motivation, results are given characterising the error between the nominal and regularised Riccati flows and Kalman–Bucy filtering distributions. New projection-type models are also discussed; e.g. Bose–Mesner projections. These regularisation models are also of interest on their own, and in, e.g., differential games, control of stochastic/jump processes, and robust control.

Bishop, AN, Houssineau, J, Angley, D & Ristic, B 2018, 'Spatio-temporal tracking from natural language statements using outer probability theory', Information Sciences, vol. 463-464, pp. 56-74.
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© 2018 Elsevier Inc. This work considers a target tracking problem where the observed information is in the form of natural language-type statements. More specifically, the focus is on a spatio-temporal tracking problem where each uttered expression may involve both spatial, motion and temporal uncertainty, and a general modelling framework for natural language statements of a rather general semantic form is developed. This framework involves the definition of some tuple that allows one to extract the common semantics from arbitrary parsed expressions conveying some canonical information. Given this tuple, an estimation and tracking method based on the concept of outer probability measures is introduced and an estimation algorithm for handling this temporal uncertainty, along with delayed and out-of-sequence information arrival, is developed. This framework allows for modelling imprecise information in a more general and realistic sense.

Bradbury, P, Traini, D, Ammit, AJ, Young, PM & Ong, HX 2018, 'Repurposing of statins via inhalation to treat lung inflammatory conditions', Advanced Drug Delivery Reviews, vol. 133, pp. 93-106.
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© 2018 Elsevier B.V. Despite many therapeutic advancements over the past decade, the continued rise in chronic inflammatory lung diseases incidence has driven the need to identify and develop new therapeutic strategies, with superior efficacy to treat these diseases. Statins are one class of drug that could potentially be repurposed as an alternative treatment for chronic lung diseases. They are currently used to treat hypercholesterolemia by inhibiting the 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, that catalyses the rate limiting step in the mevalonate biosynthesis pathway, a key intermediate in cholesterol metabolism. Recent research has identified statins to have other protective pleiotropic properties including anti-inflammatory, anti-oxidant, muco-inhibitory effects that may be beneficial for the treatment of chronic inflammatory lung diseases. However, clinical studies have yielded conflicting results. This review will summarise some of the current evidences for statins pleiotropic effects that could be applied for the treatment of chronic inflammatory lung diseases, their mechanisms of actions, and the potential to repurpose statins as an inhaled therapy, including a detailed discussion on their different physical-chemical properties and how these characteristics could ultimately affect treatment efficacies. The repurposing of statins from conventional anti-cholesterol oral therapy to inhaled anti-inflammatory formulation is promising, as it provides direct delivery to the airways, reduced risk of side effects, increased bioavailability and tailored physical-chemical properties for enhanced efficacy.

Celler, B, Argha, A, Varnfield, M & Jayasena, R 2018, 'Patient Adherence to Scheduled Vital Sign Measurements During Home Telemonitoring: Analysis of the Intervention Arm in a Before and After Trial.', JMIR medical informatics, vol. 6, no. 2.
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In a home telemonitoring trial, patient adherence with scheduled vital signs measurements is an important aspect that has not been thoroughly studied and for which data in the literature are limited. Levels of adherence have been reported as varying from approximately 40% to 90%, and in most cases, the adherence rate usually dropped off steadily over time. This drop is more evident in the first few weeks or months after the start. Higher adherence rates have been reported for simple types of monitoring and for shorter periods of intervention. If patients do not follow the intended procedure, poorer results than expected may be achieved. Hence, analyzing factors that can influence patient adherence is of great importance.The goal of the research was to present findings on patient adherence with scheduled vital signs measurements in the recently completed Commonwealth Scientific and Industrial Research Organisation (CSIRO) national trial of home telemonitoring of patients (mean age 70.5 years, SD 9.3 years) with chronic conditions (chronic obstructive pulmonary disease, coronary artery disease, hypertensive diseases, congestive heart failure, diabetes, or asthma) carried out at 5 locations along the east coast of Australia. We investigated the ability of chronically ill patients to carry out a daily schedule of vital signs measurements as part of a chronic disease management care plan over periods exceeding 6 months (302 days, SD 135 days) and explored different levels of adherence for different measurements as a function of age, gender, and supervisory models.In this study, 113 patients forming the test arm of a Before and After Control Intervention (BACI) home telemonitoring trial were analyzed. Patients were required to monitor on a daily basis a range of vital signs determined by their chronic condition and comorbidities. Vital signs included noninvasive blood pressure, pulse oximetry, spirometry, electrocardiogram (ECG), blood glucose level, body temperature, ...

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 : the official journal of the American Society for Bone and Mineral Research, vol. 33, no. 5, pp. 795-802.
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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 cardiovascular disease and diabetes, highlighting their importance and potential benefit for early intervention and treatment. © 2018 American Society fo...

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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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 : an official journal of the American Association for Cancer Research, vol. 24, no. 22, pp. 5772-5783.
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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.

Ganesan, B, Luximon, A, Al-Jumaily, AA, Yip, J, Gibbons, PJ & Chivers, A 2018, 'Developing a Three-Dimensional (3D) Assessment Method for Clubfoot-A Study Protocol.', Frontiers in Physiology, vol. 8, pp. 1098-1098.
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Background: Congenital talipes equinovarus (CTEV) or clubfoot is a common pediatric congenital foot deformity that occurs 1 in 1,000 live births. Clubfoot is characterized by four types of foot deformities: hindfoot equinus; midfoot cavus; forefoot adductus; and hindfoot varus. A structured assessment method for clubfoot is essential for quantifying the initial severity of clubfoot deformity and recording the progress of clubfoot intervention. Aim: This study aims to develop a three-dimensional (3D) assessment method to evaluate the initial severity of the clubfoot and monitor the structural changes of the clubfoot after each casting intervention. In addition, this study explores the relationship between the thermophysiological changes in the clubfoot at each stage of the casting intervention and in the normal foot. Methods: In this study, a total of 10 clubfoot children who are <2 years old will be recruited. Also, the data of the unaffected feet of a total of 10 children with unilateral clubfoot will be obtained as a reference for normal feet. A Kinect 3D scanner will be used to collect the 3D images of the clubfoot and normal foot, and an Infrared thermography camera (IRT camera) will be used to collect the thermal images of the clubfoot. Three-dimensional scanning and IR imaging will be performed on the foot once a week before casting. In total, 6-8 scanning sessions will be performed for each child participant. The following parameters will be calculated as outcome measures to predict, monitor, and quantify the severity of the clubfoot: Angles cross section parameters, such as length, width, and the radial distance; distance between selected anatomical landmarks, and skin temperature of the clubfoot and normal foot. The skin temperature will be collected on selected areas (forefoot, mid foot, and hindfoot) to find out the relationship between the thermophysiological changes in the clubfoot at each stage of the casting treatment and in the normal foot. Ethics...

Ghorbani, S, Eyni, H, Tiraihi, T, Asl, LS, Soleimani, M, Atashi, A, Beiranvand, SP & Warkiani, ME 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.

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.
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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.

Hao, J, Chou, J, Kuroda, S, Otsuka, M, Kasugai, S & Lang, NP 2018, 'Injectable simvastatin gel for minimally invasive periosteal distraction: In vitro and in vivo studies in rat.', Clinical Oral Implants Research, vol. 29, no. 2, pp. 227-234.
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To evaluate whether the subperiosteal injection of simvastatin (SIM) with a novel in situ gel-forming system, SrHA/Alg (strontium hydroxyapatite/alginate), can stimulate vertical bone augmentation in a rat calvarial model.The SrHA/Alg solution was synthesized and combined with different doses of SIM (0.01, 0.02, 0.1, and 0.2 mg) to form the following groups: (1) SrHA/Alg only, (2) SrHA/Alg/0.01, (3) SrHA/Alg/0.02, (4) SrHA/Alg/0.1, and (5) SrHA/Alg/0.2. The SIM release pattern was analyzed, and rat primary periosteum-derived cell (PDC) responses were investigated. Twenty male Wistar rats were enrolled in the calvarial subperiosteal injection experiment with each animal receiving a 200-μl single subperiosteal injection of SrHA/Alg with different amounts of SIM (0, 0.01, 0.02, and 0.1 mg) incorporated (n = 5). The 0.2 mg dose group was not tested in vivo due to the severe toxicity found in vitro. The new bone formation was assessed histologically and radiologically at 8 weeks.The slow release of SIM was confirmed, and PDC viability decreased in the SrHA/Alg/0.2 group. Alkaline phosphatase positive areas and mineralization areas were significantly greater in the SrHA/Alg/0.01 and SrHA/Alg/0.02 groups (p < .05). The mRNA expression level of Runx2 significantly increased in the SrHA/Alg/SIM-0.02 group by day 7 (p < .05) and significantly higher levels of VEGF were found in the SrHA/Alg/0.01 and SrHA/Alg/0.02 groups at different time points (p < .05). In vivo, no prominent clinical sign of inflammation was observed, and the most significant bone gain was shown in the SrHA/Alg/0.02 group (p < .05). The osteoclast formation within the newly formed bone area was reduced in the SrHA/Alg/0.1 group (p < .05).When combined with SrHA/Alg system, the 0.02 mg SIM seemed to be the optimal dose to stimulate subperiosteal bone formation without inducing inflammation. This combination may hold potential therapeutic benefits for clinical bone augmentation in a minimally invasive mann...

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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We present here a new method to easily and reliably generate an array of hundreds of dispersed nanoliter-volume semi-droplets for single-cells culture and analysis. The liquid segmentation step occurs directly in indexed traps by a tweezer-like mechanism and is stabilized by spatial confinement. Unlike common droplet-based techniques, the semi-droplet wets its surrounding trap walls thus supporting the culturing of both adherent and non-adherent cells. To eliminate cross-droplet cell migration and chemical cross-talk each semi-droplet is separated from a nearby trap by an ∼80 pL air plug. The overall setup and injection procedure takes less than 10 minutes, is insensitive to fabrication defects and supports cell recovery for downstream analysis. The method offers a new approach to easily capture, image and culture single cells in a chemically isolated microenvironment as a preliminary step towards high-throughput single-cell assays.

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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Hill, M & Tran, N 2018, 'MicroRNAs Regulating MicroRNAs in Cancer.', Trends in Cancer, vol. 4, no. 7, pp. 465-468.
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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-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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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.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.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.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.We conclude that the osteogenomic profile constructed from BMD-associated genetic variants is modestly associated with long-term changes in femoral neck BMD in women, but not in men.

Ho-Pham, LT, Chau, PMN, Do, AT, Nguyen, HC & Nguyen, TV 2018, 'Type 2 diabetes is associated with higher trabecular bone density but lower cortical bone density: the Vietnam Osteoporosis Study.', Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, vol. 29, no. 9, pp. 2059-2067.
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It is not clear why type 2 diabetes (T2D) has an increased risk of fracture despite higher areal bone mineral density. This study showed that compared with controls, T2D patients had higher trabecular bone density but lower cortical bone density, resulting in a lower bone strength. INTRODUCTION:To define the association between type 2 diabetes and bone architecture and measures of bone strength. METHODS:The study was part of the Vietnam Osteoporosis Study, in which 1115 women and 614 men aged ≥ 30 were randomly recruited from Ho Chi Minh City. HbA1c levels were measured with analyzers ADAMS™ A1c HA-8160 (Arkray, Kyoto, Japan). The diagnosis of T2D was made if HbA1c was ≥ 6.5%. Trabecular and cortical volumetric bone density (vBMD) was measured in the forearm and leg by a pQCT XCT2000 (Stratec, Germany). Polar stress strain index (pSSI) was derived from the pQCT measurements. Difference in bone parameters between T2D and non-diabetic individuals was assessed by the number of standard deviations (effect size [ES]) by the propensity score analysis. RESULTS:The prevalence of T2D was ~ 8%. The results of propensity score matching for age, sex, and body mass index in 137 pairs of diabetic and non-diabetic individuals showed that T2D patients had significantly higher distal radius trabecular vBMD (ES 0.26; 95% CI, 0.02 to 0.50), but lower cortical vBMD (ES - 0.22; - 0.46 to 0.00) and reduced pSSI (ES - 0.23; - 0.47 to - 0.02) compared with non-diabetic individuals. Multiple linear regression analysis based on the entire sample confirmed the results of the propensity score analysis. CONCLUSION:Compared with non-diabetic individuals, patients with T2D have greater trabecular but lower cortical vBMD which leads to lower bone strength.

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.
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Houssineau, J & Bishop, AN 2018, 'Smoothing and filtering with a class of outer measures', SIAM/ASA Journal on Uncertainty Quantification, vol. 6, no. 2, pp. 845-866.
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© 2018 Society for Industrial and Applied Mathematics and American Statistical Association. Filtering and smoothing with a generalized representation of uncertainty is considered. Here, uncertainty is represented using a class of outer measures. It is shown how this representation of uncertainty can be propagated using outer-measure-type versions of Markov kernels and generalized Bayesian-like update equations. This leads to a system of generalized smoothing and filtering equations where integrals are replaced by supremums and probability density functions are replaced by positive functions with supremum equal to one. Interestingly, these equations retain most of the structure found in the classical Bayesian filtering framework. It is additionally shown that the Kalman filter recursion can be recovered from weaker assumptions on the available information on the corresponding hidden Markov model.

Ibrahim, MF & Al-Jumaily, A 2018, 'Auto-Encoder based Deep Learning for Surface Electromyography Signal Processing', Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 1, pp. 94-102.
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Feature extraction is taking a very vital and essential part of bio-signal processing. We need to choose one of two paths to identify and select features in any system. The most popular track is engineering handcrafted, which mainly depends on the user experience and the field of application. While the other path is feature learning, which depends on training the system on recognising and picking the best features that match the application. The main concept of feature learning is to create a model that is expected to be able to learn the best features without any human intervention instead of recourse the traditional methods for feature extraction or reduction and avoid dealing with feature extraction that depends on researcher experience. In this paper, Auto-Encoder will be utilised as a feature learning algorithm to practice the recommended model to excerpt the useful features from the surface electromyography signal. Deep learning method will be suggested by using Auto-Encoder to learn features. Wavelet Packet, Spectrogram, and Wavelet will be employed to represent the surface electromyography signal in our recommended model. Then, the newly represented bio-signal will be fed to stacked autoencoder (2 stages) to learn features and finally, the behaviour of the proposed algorithm will be estimated by hiring different classifiers such as Extreme Learning Machine, Support Vector Machine, and SoftMax Layer. The Rectified Linear Unit (ReLU) will be created as an activation function for extreme learning machine classifier besides existing functions such as sigmoid and radial basis function. ReLU will show a better classification ability than sigmoid and Radial basis function (RBF) for wavelet, Wavelet scale 5 and wavelet packet signal representations implemented techniques. ReLU will illustrate better classification ability, as an activation function, than sigmoid and poorer than RBF for spectrogram signal representation. Both confidence interval and Analysis of Va...

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-+.
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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.

Keall, PJ, Doan, TN, O'Brien, R, Caillet, V, Hewson, E, Poulsen, PR, Bromley, R, Bell, L, Eade, T, Kneebone, A, Martin, J & Booth, JT 2018, 'The first clinical implementation of real-time image-guided adaptive radiotherapy using a standard linear accelerator', RADIOTHERAPY AND ONCOLOGY, vol. 127, no. 1, pp. 6-11.
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Keall, PJ, Doan, TN, O'Brien, R, Zhang, P, Happersett, L, Bertholet, J & Poulsen, PR 2018, 'Review of Real-Time 3-Dimensional Image Guided Radiation Therapy on Standard-Equipped Cancer Radiation Therapy Systems: Are We at the Tipping Point for the Era of Real-Time Radiation Therapy?', INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, vol. 102, no. 4, pp. 922-931.
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Khan, H, Razmjou, A, Warkiani, ME, Kottapalli, A & Asadnia, M 2018, 'Sensitive and flexible polymeric strain sensor for accurate human motion monitoring', Sensors (Switzerland), vol. 18, no. 2.
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© 2018 by the authors. Licensee MDPI, Basel, Switzerland. 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.

Kim, H, Wrann, CD, Jedrychowski, M, Vidoni, S, Kitase, Y, Nagano, K, Zhou, C, Chou, J, Parkman, V-JA, Novick, SJ, Strutzenberg, TS, Pascal, BD, Le, PT, Brooks, DJ, Roche, AM, Gerber, KK, Mattheis, L, Chen, W, Tu, H, Bouxsein, ML, Griffin, PR, Baron, R, Rosen, CJ, Bonewald, LF & Spiegelman, BM 2018, 'Irisin Mediates Effects on Bone and Fat via αV Integrin Receptors.', Cell, vol. 175, no. 7, pp. 1756-1768.e17.
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Irisin is secreted by muscle, increases with exercise, and mediates certain favorable effects of physical activity. In particular, irisin has been shown to have beneficial effects in adipose tissues, brain, and bone. However, the skeletal response to exercise is less clear, and the receptor for irisin has not been identified. Here we show that irisin binds to proteins of the αV class of integrins, and biophysical studies identify interacting surfaces between irisin and αV/β5 integrin. Chemical inhibition of the αV integrins blocks signaling and function by irisin in osteocytes and fat cells. Irisin increases both osteocytic survival and production of sclerostin, a local modulator of bone remodeling. Genetic ablation of FNDC5 (or irisin) completely blocks osteocytic osteolysis induced by ovariectomy, preventing bone loss and supporting an important role of irisin in skeletal remodeling. Identification of the irisin receptor should greatly facilitate our understanding of irisin's function in exercise and human health.

Kim, J-H, Nguyen, DT, Booth, JT, Huang, C-Y, Fuangrod, T, Poulsen, P, O'Brien, R, Caillet, V, Eade, T, Kneebone, A & Keall, P 2018, 'The accuracy and precision of Kilovoltage Intrafraction Monitoring (KIM) six degree-of-freedom prostate motion measurements during patient treatments.', Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, vol. 126, no. 2, pp. 236-243.
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BACKGROUND AND PURPOSE:To perform a quantitative analysis of the accuracy and precision of Kilovoltage Intrafraction Monitoring (KIM) six degree-of-freedom (6DoF) prostate motion measurements during treatments. MATERIAL AND METHODS:Real-time 6DoF prostate motion was acquired using KIM for 14 prostate cancer patients (377 fractions). KIM outputs the 6DoF prostate motion, combining 3D translation and 3D rotational motion information relative to its planning position. The corresponding groundtruth target motion was obtained post-treatment based on kV/MV triangulation. The accuracy and precision of the 6DoF KIM motion estimates were calculated as the mean and standard deviation differences compared with the ground-truth. RESULTS:The accuracy ± precision of real-time 6DoF KIM-measured prostate motion were 0.2 ± 1.3° for rotations and 0.1 ± 0.5 mm for translations, respectively. The magnitude of KIM-measured motion was well-correlated with the magnitude of ground-truth motion resulting in Pearson correlation coefficients of  ≥0.88 in all DoF. CONCLUSIONS:The results demonstrate that KIM is capable of providing the real-time 6DoF prostate target motion during patient treatments with an accuracy ± precision of within 0.2 ± 1.3° and 0.1 ± 0.5 mm for rotation and translation, respectively. As KIM only requires a single X-ray imager, which is available on most modern cancer radiotherapy devices, there is potential for widespread adoption of this technology.

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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© 2018 The Author(s). Distant 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, M 2018, 'The use of microfluidic technology for cancer applications and liquid biopsy', Micromachines, vol. 9.
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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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The 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.

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. Suppl 6, 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...

Liu, PZY, Nguyen, DT, Feain, I, O'Brien, R, Keall, PJ & Booth, JT 2018, 'Technical Note: Real-time image-guided adaptive radiotherapy of a rigid target for a prototype fixed beam radiotherapy system.', Medical physics, vol. 45, no. 10, pp. 4660-4666.
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PURPOSE:Fixed beam radiotherapy systems utilize couch movement and rotation instead of gantry rotation in order to simplify linear accelerator design. We investigate the ability to deliver fixed beam treatments with the same level of clinical accuracy as conventional (rotating beam) treatments using real-time image guidance to maintain this accuracy in the presence of rigid target motion. METHODS:A prototype fixed beam radiotherapy system was built using a standard linac with the beam fixed in the vertical position and a computer controlled rotation stage that rotated a rigid phantom about the superior-inferior axis. Kilovoltage Intrafraction Monitoring (KIM) and real-time beam adaptation with MLC tracking was applied to a five-field IMRT treatment plan with motion introduced to the phantom. The same IMRT treatment was also delivered with real-time adaptation using the conventional rotating beam geometry. Film dosimetry was used to measure the dose delivered with a fixed beam compared to a rotating beam, as well as to compare treatments delivered with and without real-time adaptation. RESULTS:The dose distributions were found to be equivalent between the fixed beam and rotating beam geometry for real-time adaptive radiotherapy using KIM and MLC tracking beam adaptation. Gamma analysis on the films showed agreement >98% using a 2%/2 mm criteria with adaptation for static shifts and periodic motion. CONCLUSIONS:Fixed beam treatments with real-time beam adaptation are dosimetrically equivalent to conventional treatments with a rotating beam, even in the presence of rigid target motion. This suggests that, for a rigid target, the high clinical accuracy of real-time adaptive radiotherapy can be achieved with simpler beam geometry.

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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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.

Lu, R, Wang, C, Wang, X, Wang, Y, Wang, N, Chou, J, Li, T, Zhang, Z, Ling, Y & Chen, S 2018, 'Effects of hydrogenated TiO2 nanotube arrays on protein adsorption and compatibility with osteoblast-like cells.', International Journal of Nanomedicine, vol. 13, pp. 2037-2049.
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Modified titanium (Ti) substrates with titanium dioxide (TiO2) nanotubes have broad usage as implant surface treatments and as drug delivery systems.To improve drug-loading capacity and accelerate bone integration with titanium, in this study, we hydrogenated anodized titanium dioxide nanotubes (TNTs) by a thermal treatment. Three groups were examined, namely: hydrogenated TNTs (H2-TNTs, test), unmodified TNTs (air-TNTs, control), and Ti substrates (Ti, control).Our results showed that oxygen vacancies were present in all the nanotubes. The quantity of -OH groups greatly increased after hydrogenation. Furthermore, the protein adsorption and loading capacity of the H2-TNTs were considerably enhanced as compared with the properties of the air-TNTs (P<0.05). Additionally, time-of-flight secondary ion mass spectrometry (TOF-SIMS) was used to investigate the interactions of TNTs with proteins. During the protein-loading process, the H2-TNTs not only enabled rapid protein adsorption, but also decreased the rate of protein elution compared with that of the air-TNTs. We found that the H2-TNTs exhibited better biocompatibility than the air-TNT and Ti groups. Both cell adhesion activity and alkaline phosphatase activity were significantly improved toward MG-63 human osteoblast-like cells as compared with the control groups (P<0.05).We conclude that hydrogenated TNTs could greatly improve the loading capacity of bioactive molecules and MG-63 cell proliferation.

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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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.

Mason, 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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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.

Mehmood, A, Nouman-Ul-Haq, Zameer, A, Ling, SH & Raja, MAZ 2018, 'Design of neuro-computing paradigms for nonlinear nanofluidic systems of MHD Jeffery-Hamel flow', JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS, vol. 91, pp. 57-85.
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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.

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, ATL, 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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© 2018, The Author(s). Rapidly 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).

Montanaro, T, Nguyen, DT, Keall, PJ, Booth, J, Caillet, V, Eade, T, Haddad, C & Shieh, C-C 2018, 'A comparison of gantry-mounted x-ray-based real-time target tracking methods.', Medical physics, vol. 45, no. 3, pp. 1222-1232.
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Most modern radiotherapy machines are built with a 2D kV imaging system. Combining this imaging system with a 2D-3D inference method would allow for a ready-made option for real-time 3D tumor tracking. This work investigates and compares the accuracy of four existing 2D-3D inference methods using both motion traces inferred from external surrogates and measured internally from implanted beacons.Tumor motion data from 160 fractions (46 thoracic/abdominal patients) of Synchrony traces (inferred traces), and 28 fractions (7 lung patients) of Calypso traces (internal traces) from the LIGHT SABR trial (NCT02514512) were used in this study. The motion traces were used as the ground truth. The ground truth trajectories were used in silico to generate 2D positions projected on the kV detector. These 2D traces were then passed to the 2D-3D inference methods: interdimensional correlation, Gaussian probability density function (PDF), arbitrary-shape PDF, and the Kalman filter. The inferred 3D positions were compared with the ground truth to determine tracking errors. The relationships between tracking error and motion magnitude, interdimensional correlation, and breathing periodicity index (BPI) were also investigated.Larger tracking errors were observed from the Calypso traces, with RMS and 95th percentile 3D errors of 0.84-1.25 mm and 1.72-2.64 mm, compared to 0.45-0.68 mm and 0.74-1.13 mm from the Synchrony traces. The Gaussian PDF method was found to be the most accurate, followed by the Kalman filter, the interdimensional correlation method, and the arbitrary-shape PDF method. Tracking error was found to strongly and positively correlate with motion magnitude for both the Synchrony and Calypso traces and for all four methods. Interdimensional correlation and BPI were found to negatively correlate with tracking error only for the Synchrony traces. The Synchrony traces exhibited higher interdimensional correlation than the Calypso traces especially in the anterior-poster...

Moshksayan, K, Kashaninejad, N, Warkiani, ME, Lock, JG, Moghadas, H, Firoozabadi, B, Saidi, MS & Nguyen, NT 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.
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© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Nature 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.

Nguyen, DT, Booth, JT, Caillet, V, Hardcastle, N, Briggs, A, Haddad, C, Eade, T, O'Brien, R & Keall, PJ 2018, 'An augmented correlation framework for the estimation of tumour translational and rotational motion during external beam radiotherapy treatments using intermittent monoscopic x-ray imaging and an external respiratory signal.', Physics in medicine and biology, vol. 63, no. 20, pp. 205003-205003.
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Increasing evidence shows that intrafraction tumour motion monitoring must include both six degrees of freedom (6DoF): 3D translations and 3D rotations. Existing real-time algorithms for 6DoF target motion estimation require continuous intrafraction fluoroscopic imaging at high frequency, thereby exposing patients to additional high imaging dose. This paper presents the first method capable of 6DoF motion monitoring using intermittent 2D kV imaging and a continuous external respiratory signal. Our approach is to optimise a state-augmented linear correlation model between an external signal and internal 6DoF motion. In standard treatments, the model can be built using information obtained during pre-treatment cone beam CT (CBCT). Real-time 6DoF tumor motion can then be estimated using just the external signal. Intermittent intrafraction kV images are used to update the model parameters, accounting for changes in correlation and baseline shifts. The method was evaluated in silico using data from 6 lung SABR patients, with the internal tumour motion recorded with electromagnetic beacons and the external signal from a bellows belt. Projection images from CBCT (10 Hz) and intermittent kV images were simulated by projecting the 3D Calypso beacon positions onto an imager. IMRT and VMAT treatments were simulated with increasing imaging update intervals: 0.1 s, 1 s, 3 s, 10 s and 30 s. For all the tested clinical scenarios, translational motion estimates with our method had sub-mm accuracy (mean) and precision (standard deviation) while rotational motion estimates were accurate to  <[Formula: see text] and precise to [Formula: see text]. Motion estimation errors increased as the imaging update interval increased. With the largest imaging update interval (30 s), the errors were [Formula: see text] mm, [Formula: see text] mm and [Formula: see text] mm for translation in the left-right, superior-inferior and anterior-posterior directions, respectively, and [Formula: see text...

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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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, 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 : the official journal of the American Society for Bone and Mineral Research, vol. 33, no. 3, pp. 386-388.
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Ooi, CY, Carter, DR, Liu, B, Mayoh, C, Beckers, A, Lalwani, A, Nagy, Z, De Brouwer, S, Decaesteker, B, Hung, TT, 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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© 2018 American Association for Cancer Research. 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.Onthe basis of a Bayesian learning network model in which wecompared pretumor ganglia from TH-MYCN+/+ mice to age-matched wildtype 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.

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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Wear 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.

Pham, TT, Nguyen, D, Dutkiewicz, E, Center, JR, Eisman, JA & Nguyen, T 2018, 'A Profiling analysis of contributions of cigarette smoking, dietary calcium intakes, and physical activity to fragility fracture in the elderly', Nature Scientific Reports, vol. 8, no. 1.
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Phukpattaranont, P, Thongpanja, S, Anam, K, Al-Jumaily, A & Limsakul, C 2018, 'Evaluation of feature extraction techniques and classifiers for finger movement recognition using surface electromyography signal', MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, vol. 56, no. 12, pp. 2259-2271.
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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.

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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© The Author(s) 2017. 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, M, Li, L & Su, S 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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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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IEEE The distribution power sub-systems 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 sub-optimal local gain. Furthermore, the convergence of the proposed schemed is analysed 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 and IEEE 57-bus power system. 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. Consequently, this work is valuable for the design of smart energy management system and will be able to easily implement control strategies when the system state is now available.

Razavi Bazaz, S, Mehrizi, AA, Ghorbani, S, Vasilescu, S, Asadnia, M & Ebrahimi Warkiani, M 2018, 'A hybrid micromixer with planar mixing units', RSC Advances, vol. 8, no. 58, pp. 33103-33120.
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© The Royal Society of Chemistry. The application of microfluidic systems in chemical and biological assays has progressed dramatically in recent years. One of the fundamental operations that microfluidic devices must achieve is a high mixing index. Of particular importance is the role of planar mixing units with repetitive obstacles (MURO) in the formation of micromixers. To date, a myriad of planar passive micromixers has been proposed. However, a strategy for the combination of these units to find an efficient planar mixer has not been investigated. As such, five different MURO have been selected to form a “hybrid micromixer,” and their combination was evaluated via numerical and experimental methods. These mixing units include ellipse-like, Tesla, nozzle and pillar, teardrop, and obstruction in a curved mixing unit. Since these units have distinctive dimensions, dynamic and geometric similarities were used to scale and connect them. Afterwards, six slots were designated to house each mixing unit. Since the evaluation of all possible unit configurations is not feasible, the design of experiment method is applied to reduce the total number of experiments from 15 625 to 25. Following this procedure, the “hybrid” micromixer proposed here, comprising Tesla, nozzle and pillar, and obstruction units, shows improved performance for a wide range of Re (i.e., mixing index of >90% for Re 0.001-0.1, 22-45) over existing designs. The use of velocity profiles, concentration diagrams, vorticity and circulation plots assist in the analysis of each unit. Comparison of the proposed “hybrid” micromixer with other obstacle-based planar micromixers demonstrates improved performance, indicating the combination of planar mixing units is a useful strategy for building high-performance micromixers.

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.

Scheltema, MJ, Chang, JI, van den Bos, W, Gielchinsky, I, Nguyen, TV, de Reijke, TM, Siriwardana, AR, Bohm, M, de la Rosette, JJ & Stricker, PD 2018, 'Impact on genitourinary function and quality of life following focal irreversible electroporation of different prostate segments', DIAGNOSTIC AND INTERVENTIONAL RADIOLOGY, vol. 24, no. 5, pp. 268-275.
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Shao, J, Zheng, WX, Huang, TZ & Bishop, AN 2018, 'On Leader-Follower Consensus with Switching Topologies: An Analysis Inspired by Pigeon Hierarchies', IEEE Transactions on Automatic Control, vol. 63, no. 10, pp. 3588-3593.
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© 1963-2012 IEEE. Inspired by the interesting findings regarding the hierarchy and coordination of pigeons in Nagy et al. [Nature, 2010], we revisit the discrete-time leader-follower consensus problem with switching topologies. The purpose of this paper is to investigate the impact of hierarchical topologies and followers' self-loops on the convergence performance of leader-follower consensus, including the convergence rate and robustness to switching topologies. We first study the fixed topology case, and show that the followers converge to the leader's state in finite time if and only if each follower has no self-loops and the topology is hierarchical. However, we show via counterexample, that leader-follower consensus may not be achieved when some followers have no self-loops and the topology is switching; even if each interaction graph has a spanning tree rooted at the leader. With the aid of binary relation theory, we further develop a new approach to present a novel sufficient condition for leader-follower consensus with switching topologies and with some followers having no self-loops. We prove that when no followers have self-loops and the same hierarchical organization is kept under the switching topologies, then the fastest rate of convergence in leader-follower consensus can be achieved; even in the presence of complex dynamic topologies. This is consistent with the natural phenomena found in pigeons by Nagy et al.

Sofela, S, Sahloul, S, Rafeie, M, Kwon, T, Han, J, Warkiani, ME & Song, YA 2018, 'High-throughput sorting of eggs for synchronization of: C. elegans in a microfluidic spiral chip', Lab on a Chip, vol. 18, no. 4, pp. 679-687.
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© 2018 The Royal Society of Chemistry. In this study, we report the use of a high-throughput microfluidic spiral chip to screen out eggs from a mixed age nematode population, which can subsequently be cultured to a desired developmental stage. For the sorting of a mixture containing three different developmental stages, eggs, L1 and L4, we utilized a microfluidic spiral chip with a trapezoidal channel to obtain a sorting efficiency of above 97% and a sample purity (SP) of above 80% for eggs at different flow rates up to 10 mL min -1 . The result demonstrated a cost-effective, simple, and highly efficient method for synchronizing C. elegans at a high throughput (∼4200 organisms per min at 6 mL min -1 ), while eliminating challenges such as clogging and non-reusability of membrane-based filtration. Due to its simplicity, our method can be easily adopted in the C. elegans research community.

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.

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 (Cambridge, England), vol. 54, no. 31, pp. 3851-3854.
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An efficient surface modification for upconversion nanoparticles (UCNPs) is reported via supramolecular host-guest self-assembly. Cucurbit[7]uril (CB) can provide a hydrophilic surface and cavities for most biomolecules. High biological efficiency, activity and versatility of the approach enable UCNPs to be significantly applied in bio-imaging, early disease detection, and bio-sensing.

Suñer, S, Gowland, N, Craven, R, Joffe, R, Emami, N & Tipper, JL 2018, 'Ultra high 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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In 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.

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.

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 and 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.

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 and metabolism, vol. 103, no. 9, pp. 3205-3214.
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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.

Tran, TS & Nguyen, TV 2018, 'Association Between Alendronate and All-Cause Mortality and Cardiovascular Mortality Among Hip Fracture: An Alternative Explanation.', Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research, vol. 33, no. 10, pp. 1906-1907.
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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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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.

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.
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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 suggest that LM is a stronger determinant of BMD than f...

Wang, Y, Cui, W, Chou, J, Wen, S, Sun, Y & Zhang, H 2018, 'Electrospun nanosilicates-based organic/inorganic nanofibers for potential bone tissue engineering.', Colloids and surfaces. B, Biointerfaces, vol. 172, pp. 90-97.
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Although growth factors and drugs (BMP-2, dexamethasone, etc.) have been widely used for bone tissue engineering, they have unignored limits such as adverse effects at high concentrations and easy inactivation in vivo. Accordingly, more osteoinductive supplements without side effects should be considered as alternatives in the design of bone tissue engineering scaffolds. Nanosilicate is a bioactive inorganic nanomaterial consisting of hydrous sodium lithium magnesium silicate, which is recently found to be safe and effective for bone induction. In this study, a range of organic/inorganic nanofibrous scaffolds with varied nanosilicate concentrations (0%, 1%, 5%, and 10% w/w to PCL matrix) were successfully fabricated via electrospinning. The tensile properties of the nanofibers were enhanced at low nanosilicate concentrations, and the incorporation of nanosilicates had no influence on cytocompatibility. Besides, in vitro osteogenesis experiments showed that nanosilicates-doped nanofibers were capable of inducing bone formation better than pure PCL nanofiber samples. More importantly, the results of histological and immunohistochemical assessments further revealed that the nanosilicates-enriched nanofibers had a significant potential of ectopic bone formation in vivo, while the pure PCL samples only induced limited osteogenic cues. All these results indicate that the nanosilicates-based organic/inorganic nanofibers may be potentially efficient for bone tissue engineering.

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.

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.
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© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim While 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, SH 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.

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...

Yu, H, Ye, L, Naik, GR, Song, R, Nguyen, HT & Su, S 2018, 'Nonparametric Dynamical Model of Cardiorespiratory Responses at the Onset and Offset of Treadmill Exercises', Medical and Biological Engineering and Computing, vol. 56, no. 12, pp. 2337-2351.
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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.

Al-Kaysi, AM, Al-Ani, A, Galvez, V, Colleen Loo, K, Ling, S & Tjeerd Boonstra, W 2018, 'Estimating The Quality of Electroconvulsive Therapy Induced Seizures Using Decision Tree and Fuzzy Inference System Classifiers.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Honolulu, HI, USA, pp. 3677-3680.
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Electroconvulsive therapy (ECT) is an effective and widely used treatment for major depressive disorder, in which a brief electric current is passed through the brain to trigger a brief seizure. This study aims to identify seizure quality rating by utilizing a set of seizure parameters. We used 750 ECT EEG recordings in this experiment. Four seizure related parameters, (time of slowing, regularity, stereotypy and post-ictal suppression) are used as inputs to two classifiers, decision tree and fuzzy inference system (FIS), to predict seizure quality ratings. The two classifiers produced encouraging results with error rate of 0.31 and 0.25 for FIS and decision tree, respectively. The classification results show that the four seizure parameters provide relevant information about the rating of seizure quality. Automatic scoring of seizure quality may be beneficial to clinicians working in this field.

Almansor, EH & Al-Ani, A 2018, 'A hybrid neural machine translation technique for translating low resource languages', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Machine Learning and Data Mining in Pattern Recognition, New York. USA, pp. 347-356.
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© Springer International Publishing AG, part of Springer Nature 2018. Neural machine translation (NMT) has produced very promising results on various high resource languages that have sizeable parallel datasets. However, low resource languages that lack sufficient parallel datasets face challenges in the automated translation filed. The main part of NMT is a recurrent neural network, which can work with sequential data at word and sentence levels, given that sequences are not too long. Due to the large number of word and sequence combinations, a parallel dataset is required, which unfortunately is not always available, particularly for low resource languages. Therefore, we adapted a character neural translation model that was based on a combined structure of recurrent neural network and convolutional neural network. This model was trained on the IWSLT 2016 Arabic—English and the IWSLT 2015 English—Vietnamese datasets. The model produced encouraging results particularly on the Arabic datasets, where Arabic is considered a rich morphological language.

Al-Taee, AA & Al-Jumaily, A 2018, 'Optimal feature set for finger movement classification based on sEMG.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Honolulu, HI, USA, pp. 5228-5231.
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One of the most important electrophysiological signal is the Electromyography (EMG) signal, which is widely used in medical and engineering studies. This signal contains a wealth of information about muscle functions. Therefore, the EMG signal is becoming increasingly important and has started to be used in many applications like finger movement rehabilitation. However, an advanced EMG signal analysis method is required for efficient usage of such applications. This signal analysis can include signal detection, decomposition, processing, and classification. There are many approaches in studying the EMG signals, however, one of the important factor of analyzing is to get the most efficient and effective features that can be extracted from the raw signal. This paper presents the best feature extraction set compared to previous studies. Where eighteen well-known features algorithm has been tested using the sequential forward searching (SFS) method to get excellent classification accuracy in a minimum processing time. Among these novel features only four combinations have been selected with perfect results, which are; Hjorth Time Domain parameters (HTD), Mean Absolute Value (MAV), Root Mean Square (RMS) and Wavelet Packet Transform (WPT). The superiority of this feature set has been proven experimentally, and the results show that the classification accuracy could reach up to 99% to recognize the individual and combined for ten classes of finger movements using only two EMG channels.

Alwidyan, F, Al-Ani, A, Kirchner, N & Zeibots, ME 2017, 'An effort-based evaluation of pedestrian route choice behaviour', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE Conference on Industrial Electronics and Applications, IEEE, Siem Reap, Cambodia.
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Route Choice is one of the main challenging problems from theoretical and practical viewpoints in the realm of pedestrian behaviour. A prime underlying concern of researchers in this field is to identify criteria or discover principles that pedestrians use to select their routes based on. Despite the fact that there are infinite possible routes between two given destinations in space, pedestrians in real situations tend to choose a certain finite number of available trajectories. As a consequence, there is a high demand for theoretical framework and models to describe route choice. The fundamental assumption is that pedestrians follow a route over which Effort is optimized. The existing criteria in the literature to predict route choice of pedestrians are mainly related to route length and travel time. In this paper, we consider physical effort as a new criterion, which indicates the pedestrian's metabolic energy expenditure that pedestrians may consume during their walking from origin to destination. A case study is included to illustrate the pertinent concepts and ideas introduced. Our discussion concludes with an overview of how this reconceptualization builds the foundations for a model that will enable improved operations, planning, and design of public transport facilities.

Al-Zubi, MM, Sanagavarapu, A & Ling, S 2018, 'Comparison of Reception Mechanisms for Molecular Communication via Diffusion', 2018 9th International Conference on Information and Communication Systems (ICICS), International Conference on Information & Communication Systems, IEEE, Irbid, Jordan, pp. 1-5.
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Molecular communication paradigm enables nanomachines or biological cells at nano/micro scales to communicate using chemical molecules. In this paper, we study different reception mechanisms in an unbounded 3-D biological medium for diffusion-based molecular communication system and compare their performances. The number of received molecules (i.e., number of activated receptors) is first analytically evaluated and then validated using a particle-based simulator developed by us. We address various receiver models, viz., passive, irreversible partially or fully absorptive, and a more general reversible receivers. The peak amplitude and peak time for passive and fully absorptive receivers are evaluated. The impact of various parameters, e.g., diffusion coefficient, separation distance, forward/backward reaction rates, on the received signal are examined.

Al-Zubi, MM, Sanagavarapu, A & Ling, S 2018, 'Impact of Reactive Obstacle on Molecular Communication between Nanomachines', 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), International Engineering in Medicine and Biology Conference, IEEE, Honolulu, Hawaii, USA, pp. 4468-4471.
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Molecular communication is an emerging technology for communication between bio-nanomachines in an aqueous environment. In this paper, we examine the effect of a reactive obstacle, which is placed in the diffusive molecular communication channel, on the expected number of the received molecules at the receiver. We develop a particle-based simulator that can predict the number of the received molecules for both passive and absorptive receivers by considering the impact of the reactive obstacle within the communication channel. The impacts of the reaction probability and radius of the obstacle on the received signal are examined and compared with the case of absence of the obstacle. The results show significant impact for the obstacle on the received signal, particularly, for obstacle with high reaction probability and large size.

Argha, A, Su, SW & Celler, B 2018, 'Optimal Sparsely Distributed Static Output Feedback for Publisher/Subscriber Networked Systems with Parametric Uncertainties', Proceedings of the American Control Conference, pp. 2617-2622.
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© 2018 AACC. This paper develops a framework for the design of H2-based block row/column-sparse distributed static output feedback controllers for interconnected systems with polytopic uncertainties. The application of the proposed method will be in the networked systems using publisher/subscriber communication scheme in order to optimally select a subset of available publishers and/or subscribers in the network. We propose to incorporate two additional terms, that penalise the number of publishers and subscribers, into the optimisation index function, and then employ an explicit scheme and an iterative process to deal with this problem. A numerical example is used to demonstrate the effectiveness of the proposed approach in the simultaneous identification of favourable networks topologies and design of controller strategy.

Argha, A, Su, SW, Savkin, A & Celler, BG 2018, 'A Novel Optimal Sliding Mode Control for Multiple Time-Delay Systems', Proceedings of the American Control Conference, Annual American Control Conference, IEEE, Milwaukee, WI, USA, pp. 4081-4086.
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© 2018 AACC. This paper considers the problem of delay-independent optimal sliding mode control design for uncertain systems with multiple constant delays. An improved delay-independent framework for the design of SMC is established in terms of a linear matrix inequality for time-delay systems, in which multi-channel H 2 performances of the closed-loop system are under control. Unlike most of the existing methods, the required level of control effort to maintain sliding will be taken into account in this new framework. Our two-stage SMC is constructed as follows. Firstly, a certain state feedback gain is designed while assigning some of the closed-loop eigenvalues precisely to a predetermined stable location as well as ensuring a prescribed multi-channel H 2 performance level of the closed-loop system. In the second stage, we will find the optimal switching surface associated with the gain designed in the first stage via a novel approach developed for this goal while ensuring the stability of the reduced-order dynamics.

Ghorbani, S, Razavi Bazaz, S, Ebrahimi Warkiani, M, Soleimani, M & Abouei Mehrizi, A 2018, 'Evaluation of Nanofiber PLA Scaffolds Using Dry- and Wet-Electrospinning Methods', 2017 24th Iranian Conference on Biomedical Engineering and 2017 2nd International Iranian Conference on Biomedical Engineering, ICBME 2017.
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© 2017 IEEE. Investigating the fabrication of a favorable scaffold is a continuing sconcern and an essential step within tissue engineering. An ideal scaffold should mimic the structure of extracellular matrix (ECM) which has considerable impacts on its function. To meet this demands, in this study, three-dimensional scaffolds by polylactic acid (PLA) polymer 10%, 13%, 15%, 17% and 20% (w/v) with a novel architecture produced by a wet-electrospinning process have been fabricated and compared with dry-electrospun scaffolds that have been developed for tissue engineering applications. In the wet-electrospinning method, an aqueous solution of sodium hydroxide (NaOH) (pH∼13) has been used as the coagulation bath instead of the aluminum collector which is used in the dry method. Comparing with usual nanofiber non-woven PLA fabric prepared by a conventional electrospinning method, wet-electrospun spongiform PLA nanofiber scaffolds have low apparent density and high porosity. The porosity of the scaffolds has been examined in this two methods and their mechanical properties as well as their morphology are investigated. All in all, it is shown that the novel nanofiber fabrication system would be amazingly useful for the structure control of the nanofiber fabric.

Hao, L, Ling, SH & Jiang, F 2018, 'Classification of Cardiovascular Disease via A New SoftMax Model.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Honolulu, USA, pp. 486-489.
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Cardiovascular disease clinical diagnosis is an essentially problem of pattern recognition. In the traditional intelligent diagnosis, the evaluation of classification algorithm is based on the final accuracy of the disease diagnosis. In this paper, a new classification method called Softmax regression model is proposed and it uses the known state data of two-layer neural network structure of the Softmax regression model for training and learning, and then calculate the probability of reclassification data belonging to each category. These categories are corresponding to the maximum probability and the classification result of the data to be classified. It provides a new method for classification of disease with higher speed and higher accuracy. Experiment is designed to compare with the K-nearest neighbours and BP neural networks, and also verify the classification accuracy of Softmax regression model. ECG data from MIT-BIH open database is considered for the experiment. The correct classification rate of the diagnosis reaches 94.44% which outperforms than K- nearest neighbor method (77.78%) and BP neural network (72.27%) in regards to the detection of the Cardiovascular disease.

Ho-Le, TP, Center, JR, Eisman, JA, Nguyen, HT & Nguyen, TV 2018, 'Assessing Clinical Utility of Genetic Profiling in Fracture Risk Assessment: A Decision Curve Analysis', JOURNAL OF BONE AND MINERAL RESEARCH, Annual Meeting of the American-Society-for-Bone-and-Mineral-Research, WILEY, Montreal, CANADA, pp. 79-80.

Ho-Le, TP, Tran, TS, Center, JR, Eisman, JA & Nguyen, TV 2018, 'Contribution of Multimorbility to Post-Fracture Mortality: Result of a Long Term Population Based Study', JOURNAL OF BONE AND MINERAL RESEARCH, Annual Meeting of the American-Society-for-Bone-and-Mineral-Research, WILEY, Montreal, CANADA, pp. 271-271.

Islam, SMS, Mahmood, H, Al-Jumaily, AA & Claxton, S 2018, 'Deep Learning of Facial Depth Maps for Obstructive Sleep Apnea Prediction', 2018 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND DATA ENGINEERING (ICMLDE 2018), International Conference on Machine Learning and Data Engineering (iCMLDE), IEEE, Sydney, AUSTRALIA, pp. 154-157.
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Islam, SMS, Raza, SK, Moniruzzamn, M, Janjua, N, Lavery, P & Al-Jumaily, A 2017, 'Automatic seagrass detection: A survey', 2017, International Conference on Electrical and Computing Technologies and Applications, IEEE, Ras Al Khaimah, United Arab Emirates, pp. 1-5.
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© 2017 IEEE. Seagrass is an important component of the marine ecosystem and plays a vital role in preserving the water quality. The traditional approaches for sea grass identification are either manual or semi-automated, resulting in costlier, time consuming and tedious solutions. There has been an increasing interest in the automatic identification of seagrasses and this article provides a survey of automatic classification techniques that are based on machine learning, fuzzy synthetic evaluation model and maximum likelihood classifier along with their performance. The article classifies the existing approaches on the basis of image types (i.e. aerial, satellite, and underwater digital), outlines the current challenges and provides future research directions.

Jing, D, Huang, Y, Liu, X, Sia, K, Poulos, RC, Span, M, Zhang, C, Mi, J, Wong, JWH, Beck, D, Pimanda, JE & Lock, RB 2018, 'Lymphocyte-specific chromatin accessibility predetermines glucocorticoid resistance in acute lymphoblastic leukemia', CANCER RESEARCH, Annual Meeting of the American-Association-for-Cancer-Research (AACR), AMER ASSOC CANCER RESEARCH, Chicago, IL.
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Khushaba, RN, Krasoulis, A, Al-Jumaily, A & Nazarpour, K 2018, 'Spatio-Temporal Inertial Measurements Feature Extraction Improves Hand Movement Pattern Recognition without Electromyography.', 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, HI, USA, pp. 2108-2111.
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Recent studies indicate the limited clinical acceptance of myoelectric prostheses, as upper extremity amputees need improved functionality and more intuitive, effective, and coordinated control of their artificial limbs. Rather than exclusively classifying the electromyogram (EMG) signals, it has been shown that inertial measurements (IMs) can form an excellent complementary signal to the EMG signals to improve the prosthetic control robustness. We present an investigation into the possibility of replacing, rather than complementing, the EMG signals with IMs. We hypothesize that the enhancements achieved by the combined use of the EMG and IM signals may not be significantly different from that achieved by the use of Magnetometer (MAG) or Accelerometer (ACC) signals only, when the temporal and spatial information aspects are considered. A large dataset comprising recordings with 20 ablebodied and two amputee participants, executing 40 movements, was collected. A systematic performance comparison across a number of feature extraction methods was carried out to test our hypothesis. Results suggest that, individually, each of the ACC and MMG signals can form an excellent and potentially independent source of control signal for upper-limb prostheses, with an average classification accuracy of $\approx 93$% across all subjects. This study suggests the feasibility of moving from surface EMG to IM signals as a main source for upper-limb prosthetic control in real-life applications.

Kottapalli, AGP, Asadnia, M, Karavitaki, KD, Warkiani, ME, Miao, J, Corey, DP & Triantafyllou, M 2017, 'Engineering biomimetic hair bundle sensors for underwater sensing applications', AIP Conference Proceedings, Mechanics of Hearing Workshop, AIP, St Catharines, Canada, pp. 160003-1-160003-7.
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© 2018 Author(s). We present the fabrication of an artificial MEMS hair bundle sensor designed to approximate the structural and functional principles of the flow-sensing bundles found in fish neuromast hair cells. The sensor consists of micro-pillars of graded height connected with piezoelectric nanofiber "tip-links" and encapsulated by a hydrogel cupula-like structure. Fluid drag force actuates the hydrogel cupula and deflects the micro-pillar bundle, stretching the nanofibers and generating electric charges. These biomimetic sensors achieve an ultrahigh sensitivity of 0.286 mV/(mm/s) and an extremely low threshold detection limit of 8.24 μm/s. A complete version of this paper has been published [1].

Lai, J, Feng, B, Zeng, Q & Su, S 2018, 'A Dual-Band Dual-Polarized Omnidirectional Antenna for 2G/3G/LTE Indoor System Applications', 2018 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2018, IEEE International Conference on Signal Processing, Communications and Computing, IEEE, Qingdao, China, pp. 1-3.
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© 2018 IEEE. In this paper, we presented a dual-band dual-polarized (DP) omnidirectional antenna for 2G/3G/Long Term Evolution (LTE) indoor communication systems. Two modified cones compose the vertical polarized (VP) unit, which exhibits good omnidirectional radiation performance and achieves a wide impedance bandwidth. The loop antenna and the printed circular dipole arm arrays are arranged on the top end and middle end of the VP unit, respectively. They are connected by a commercial diplexer as the horizontal polarized (HP) units. Simulated results indicated that an impedance bandwidth of 790 MHz-1.14 GHz and 1.72-3.51GHz can be achieved for VP while another one of 806-980 MHz and 1.68-2.99 GHz is also obtained for HP. In the azimuth plane, omnidirectional radiation patterns for both VP and HP are achieved. For the lower and upper frequency bandsmore than 1 dBi and 3 dBi antenna gain are realized for both of the VP and HP radiations, respectively. Better port-to-port isolation, low cross polarization and little gain variation are also acquired.

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', International Conference on Genome Informatics, Kunming, Yunnan, China.
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Li, X, Al-Ani, A & Ling, SH 2018, 'Feature Selection for the Detection of Sleep Apnea using Multi-Bio Signals from Overnight Polysomnography.', The 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society proceedings, Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS) Conference, IEEE, USA, pp. 1444-1447.
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Patients with sleep apnea (SA) are at increased risk of stroke and cardiovascular disease. Diagnosis of sleep apnea depends on the standard overnight polysomnography (PSG). In this study, the DREAM Apnea Database was used to evaluate the importance of the various features proposed in the literature for the analysis of sleep apnea. Various timeand frequency- domain features that include wavelet and power spectral density were extracted from ECG, EMG, EEG, airflow, SaO2, abdominal and thoracic recordings. Evaluation measures of one-way analysis of variance (ANOVA) and Rank-Sum test were used to test the performance of different features. The selected feature subset indicated that frequency-domain features outperform time-domain ones. This study will help in enhancing the detection accuracy of sleep apnea for the various polysomnography signals.

Lyu, J & Ling, SH 2018, 'Using Multi-level Convolutional Neural Network for Classification of Lung Nodules on CT images.', Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Honolulu, HI, USA, pp. 686-689.
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Lung cancer is one of the four major cancers in the world. Accurate diagnosing of lung cancer in the early stage plays an important role to increase the survival rate. Computed Tomography (CT)is an effective method to help the doctor to detect the lung cancer. In this paper, we developed a multi-level convolutional neural network (ML-CNN)to investigate the problem of lung nodule malignancy classification. ML-CNN consists of three CNNs for extracting multi-scale features in lung nodule CT images. Furthermore, we flatten the output of the last pooling layer into a one-dimensional vector for every level and then concatenate them. This strategy can help to improve the performance of our model. The ML-CNN is applied to ternary classification of lung nodules (benign, indeterminate and malignant lung nodules). The experimental results show that our ML-CNN achieves 84.81\% accuracy without any additional hand-craft preprocessing algorithm. It is also indicated that our model achieves the best result in ternary classification.

Naji, M, Abdelhalim, S, Al-Ani, A & Al-Kilidar, H 2017, 'Airport security screening process: A review', CICTP 2017: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation - Proceedings of the 17th COTA International Conference of Transportation Professionals, COTA International Conference of Transportation Professionals, Shanghai, China, pp. 3978-3988.
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© 2018 American Society of Civil Engineers (ASCE). All rights reserved. Airport security screening processes are essential to ensure the safety of passengers and the aviation industry. The level of airport security is continuously improving with the help of advanced technology and trained security officers. However, airports have witnessed a significant increase in the number of passengers, which makes optimal security screening processes costly to implement for airport operations, and time-consuming for passengers and airlines. Different methods have been proposed to optimise the queueing process, reduce processing time, and strike a balance between security and time delay. This paper reviews the existing methods used to optimise the security process at airports, the technology being used, the importance of experienced security officers, and the impact of the screening process on passengers and the economy.

Stephenson, RM, Chai, R & Eager, D 2018, 'Isometric Finger Pose Recognition with Sparse Channel SpatioTemporal EMG Imaging.', 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society Proceedings, Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS) Conference, IEEE, USA, pp. 5232-5235.
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High fidelity myoelectric control of prostheses and orthoses isparamount to restoring lost function to amputees and neuro-muscular disease sufferers. In this study we prove that patio-temporal imaging can be used to allow convolutional neural networks to classify sparse channel EMG samples from a consumer-grade device with over 94 % accuracy. 10,572 images are generated from 960 samples of simple and complex isometric finger poses recorded from 4 fully intact subjects. Real-time classification of 12 poses is achieved with a 250ms continuous overlapping window.

Tran, VP & Al-Jumaily, AA 2018, 'Non-contact Doppler radar based prediction of nocturnal body orientations using deep neural network for chronic heart failure patients', 2017 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2017, International Conference on Electrical and Computing Technologies and Applications, IEEE, Ras Al Khaimah, United Arab Emirates, pp. 1-5.
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© 2017 IEEE. Sleep is crucial in our daily life as it plays a key role in our physical and mental health. It is important to monitor the sleep body orientations and movements due to its relationships to particular diseases, e.g., obstructive sleep apnea, insomnia or periodic limb movement disorder. Analyzing sleep body orientations also helps in determining sleep quality and irregular sleeping patterns. However, the current non-invasive sleep body orientations monitoring technologies are not well suited for long-term continuous monitoring due to its restrictions in mobility and comfort. This paper proposes a system that applies a features extraction process, utilizing wavelet packet decomposition, to extract features that describe the non-contact Doppler radar signatures caused by the body orientations. A database consisting of 24 chronic heart failure patients is selected for the training, validation and test of the non-contact body orientations prediction. These patients are diagnosed with New York Heart Association heart failure classification Class II & III and underwent full polysomnography analysis for the diagnosis of sleep apnea, disordered sleep, or both. The patients' data are randomly concatenated and partitioned into the ratio of 50% for 'Training', 15% for 'Validation' and 35% for 'Test. Across the 'Test dataset with total sleep duration of 65 hours, the body orientations prediction accuracy achieved a correct classification rate of 99.2% for 5 classes of 'Prone', 'Upright', 'Supine', 'Right and 'Left body orientations. The misclassification rate is 0.8%. A potential application would be non-contact continuous monitoring of nocturnal body orientations in the home.

Zhang, W, Liu, T, Zhang, M, Zhang, Y, Li, H, Ueland, M, Forbes, SL, Rosalind Wang, X & Su, SW 2018, 'NOS.E: A New Fast Response Electronic Nose Health Monitoring System.', 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, USA, pp. 4977-4980.
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We present a practical electronic nose (e-nose) sys-tem, NOS.E, for the rapid detection and identification of human health conditions. By detecting the changes in the composition of an individual's respiratory gases, which have been shown to be linked to changes in metabolism, e-nose systems can be used to characterize the physical health condition. We demonstrated our system's viability with a simple data set consists of breath collected under three different scenarios from one volunteer. Our preliminary results show the popular classifier SVM can discriminate NOS.E's responses under the three scenarios with high performance. In future work, we will aim to gather a more varied data set to test NOS.E's abilities.

Zhang, Y, Yang, Q, Pang, W, Argha, A, Xu, P, Su, S & Yao, D 2018, 'Congestive Heart Failure Detection Via Short-Time Electrocardiographic Monitoring For Fast Reference Advice In Urgent Medical Conditions.', Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Honolulu, HI, USA, pp. 2256-2259.
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This study proposed a detection approach for the congestive heart failure (CHF) by short-time electrocardiographic monitoring. Recent literature only reported that RR intervals and Heart Rate Variability (HRV) indicated key hidden information to discriminate CHF groups from healthy controls. However whether it was possible to find certain short-time electrocardiographic monitoring duration for CHF clinical diagnoses, has not been well addressed. In the study, databases of 54 normal subjects and 15 CHF patients from PhysioNet were introduced. Signals were classified into variable assessment lengths. Based on R-R intervals in the assessment length, raw R-R intervals, mean and standard deviation (STD) of R-R intervals, and clinically standard features of shortterm (5-min) Heart Rate Variability (HRV), were comparatively analyzed, while combining with classifiers of Recurrent Neural Network (RNN), Random Forest (RF), and Support Vector Machine (SVM). The Leave-one-out Cross-Validation (LOOCV) was adopted for performance verification, by which the model extracted from certain assessment length was utilized to test measured data of a subject with the same length. Results showed that based on testing databases, a specific 30-minute duration can be achieved by choosing HRV features in full with sensitivity of 88.55% and specificity of 94.81%. It was believed that a short-time electrocardiographic monitoring for the CHF detection could be feasible if standard HRV features together with the classifier of RF or RNN are adopted. It implied that a short-time electrocardiographic monitoring can be applied for fast reference advice of CHF in urgent medical conditions.

Heng, J, Bishop, AN, Deligiannidis, G & Doucet, A 2018, 'Controlled Sequential Monte Carlo'.
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Sequential Monte Carlo methods, also known as particle methods, are a popular set of techniques to approximate high-dimensional probability distributions and their normalizing constants. They have found numerous applications in statistics and related fields as they can be applied to perform state estimation for non-linear non-Gaussian state space models and Bayesian inference for complex static models. Like many Monte Carlo sampling schemes, they rely on proposal distributions which have a crucial impact on their performance. We introduce here a class of controlled sequential Monte Carlo algorithms, where the proposal distributions are determined by approximating the solution to an associated optimal control problem using an iterative scheme. We provide theoretical analysis of our proposed methodology and demonstrate significant gains over state-of-the-art methods at a fixed computational complexity on a variety of applications.