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Assessing the conservation and enhancement value of revegetated strips on arthropod assemblages in a pasture landscape

- O'Donnell, Peter, Wright, Wendy

  • Authors: O'Donnell, Peter , Wright, Wendy
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Journal of Environmental Management Vol. 278, no. (2021), p.
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  • Description: Examining population dynamics of arthropod communities in habitats neighboring arable lands is essential to understanding how agroecosystems can be engineered to enhance ecosystem services and contribute to sustainable intensification. Arthropods comprise the bulk of faunal biomass on farms, are taxonomically diverse, and are the main drivers of many ecosystem functions. This study aimed to compare arthropod assemblages in revegetated strips of native plants and exotic pastures, and examine taxa of beneficial arthropods in revegetated strips and adjacent pasture in early spring (September 2009) and mid-summer (December 2009–January 2010) on two farms in southeastern Gippsland, Victoria, Australia. Arthropod community assemblages were distinctly different between revegetated strips and adjacent pasture with the exception of functional groups in early spring. Several taxa of beneficial arthropods including Carabidae (ground beetles) and Syrphidae (hoverflies) were of similar abundance in the two habitats. Only Formicidae (ants) were of higher abundances in revegetated strips compared to adjacent pasture in both seasons. Five of the 10 ant genera present, seven spider families and Dolichopodidae flies (long-legged flies) were found exclusively in revegetated strips. Apidae (bees) and Tachinidae (tachinid flies) had higher abundances in revegetated strips compared to 80 m into the adjacent pasture in mid-summer. Lycosidae (wolf spiders) were more abundant along the edge of revegetated strips and 20 m into adjacent pasture compared to the center (core) of revegetated strips and 80 m into pasture. These results illustrate that beneficial arthropods use revegetated strips as refugia and that revegetated strips clearly enhanced biological conservation of arthropods in pasturelands. Relevance of findings to enhanced biological control is also discussed. © 2020 Elsevier Ltd

Generalised rational approximation and its application to improve deep learning classifiers

- Peiris, V, Sharon, Nir, Sukhorukova, Nadezda, Ugon, Julien

  • Authors: Peiris, V , Sharon, Nir , Sukhorukova, Nadezda , Ugon, Julien
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Applied Mathematics and Computation Vol. 389, no. (2021), p.
  • Relation: http://purl.org/au-research/grants/arc/DP180100602
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  • Description: A rational approximation (that is, approximation by a ratio of two polynomials) is a flexible alternative to polynomial approximation. In particular, rational functions exhibit accurate estimations to nonsmooth and non-Lipschitz functions, where polynomial approximations are not efficient. We prove that the optimisation problems appearing in the best uniform rational approximation and its generalisation to a ratio of linear combinations of basis functions are quasiconvex even when the basis functions are not restricted to monomials. Then we show how this fact can be used in the development of computational methods. This paper presents a theoretical study of the arising optimisation problems and provides results of several numerical experiments. We apply our approximation as a preprocessing step to deep learning classifiers and demonstrate that the classification accuracy is significantly improved compared to the classification of the raw signals. © 2020
  • Description: This research was supported by the Australian Research Council (ARC), Solving hard Chebyshev approximation problems through nonsmooth analysis (Discovery Project DP180100602 ).  This research was partially sponsored by Tel Aviv-Swinburne Research Collaboration Grant (2019).

Model predictive control of microgrids – An overview

- Hu, Jiefeng, Shan, Yinghao, Guerrero, Josep, Ioinovici, Adrian, Chan, Ka, Rodriguez, Jose

  • Authors: Hu, Jiefeng , Shan, Yinghao , Guerrero, Josep , Ioinovici, Adrian , Chan, Ka , Rodriguez, Jose
  • Date: 2021
  • Type: Text , Journal article , Review
  • Relation: Renewable and Sustainable Energy Reviews Vol. 136, no. (2021), p.
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  • Description: The development of microgrids is an advantageous option for integrating rapidly growing renewable energies. However, the stochastic nature of renewable energies and variable power demand have created many challenges like unstable voltage/frequency and complicated power management and interaction with the utility grid. Recently, predictive control with its fast transient response and flexibility to accommodate different constraints has presented huge potentials in microgrid applications. This paper provides a comprehensive review of model predictive control (MPC) in individual and interconnected microgrids, including both converter-level and grid-level control strategies applied to three layers of the hierarchical control architecture. This survey shows that MPC is at the beginning of the application in microgrids and that it emerges as a competitive alternative to conventional methods in voltage regulation, frequency control, power flow management and economic operation optimization. Also, some of the most important trends in MPC development have been highlighted and discussed as future perspectives. © 2020 Elsevier Ltd
  • Description: This work was supported by School of Engineering, IT and Physical Sciences, Federation University Australia , under Project RGS20-5 .

Risk assessment of SARS-CoV-2 in Antarctic wildlife

- Barbosa, Andres, Varsani, Arvind, Morandini, Virginia, Grimaldi, Wray, Vanstreels, Ralph, Diaz, Julia, Boulinier, Thierry, Dewar, Meagan, González-Acuña, Daniel, Gray, Rachael, McMahon, Clive, Miller, Gary, Power, Michelle, Gamble, Amandine, Wille, Michelle

  • Authors: Barbosa, Andres , Varsani, Arvind , Morandini, Virginia , Grimaldi, Wray , Vanstreels, Ralph , Diaz, Julia , Boulinier, Thierry , Dewar, Meagan , González-Acuña, Daniel , Gray, Rachael , McMahon, Clive , Miller, Gary , Power, Michelle , Gamble, Amandine , Wille, Michelle
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Science of the Total Environment Vol. 755, no. 2 (2021), p. 1-8
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  • Description: The coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This pathogen has spread rapidly across the world, causing high numbers of deaths and significant social and economic impacts. SARS-CoV-2 is a novel coronavirus with a suggested zoonotic origin with the potential for cross-species transmission among animals. Antarctica can be considered the only continent free of SARS-CoV-2. Therefore, concerns have been expressed regarding the potential human introduction of this virus to the continent through the activities of research or tourism to minimise the effects on human health, and the potential for virus transmission to Antarctic wildlife. We assess the reverse-zoonotic transmission risk to Antarctic wildlife by considering the available information on host susceptibility, dynamics of the infection in humans, and contact interactions between humans and Antarctic wildlife. The environmental conditions in Antarctica seem to be favourable for the virus stability. Indoor spaces such as those at research stations, research vessels or tourist cruise ships could allow for more transmission among humans and depending on their movements between different locations the virus could be spread across the continent. Among Antarctic wildlife previous in silico analyses suggested that cetaceans are at greater risk of infection whereas seals and birds appear to be at a low infection risk. However, caution needed until further research is carried out and consequently, the precautionary principle should be applied. Field researchers handling animals are identified as the human group posing the highest risk of transmission to animals while tourists and other personnel pose a significant risk only when in close proximity (< 5 m) to Antarctic fauna. We highlight measures to reduce the risk as well as identify of knowledge gaps related to this issue. © 2020 The Authors

Slope stability analysis using deterministic and probabilistic approaches for poorly defined stratigraphies

- Ghadrdan, Moshen, Dyson, Ashley, Shaghaghi, Tahereh, Tolooiyan, Ali

  • Authors: Ghadrdan, Moshen , Dyson, Ashley , Shaghaghi, Tahereh , Tolooiyan, Ali
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Geomechanics and Geophysics for Geo-Energy and Geo-Resources Vol. 7, no. 1 (2021), p.
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  • Description: The stability of slopes directly affects human lives, the environment, and the economy. Inaccurate geological profiles within numerical slope stability models can lead to potentially catastrophic consequences when model conditions do not appropriately reflect real-life stratigraphy. In cases where localised deposits are prevalent, probabilistic methods are often necessary to accommodate for unknown or poorly defined stratigraphies. Currently, there are no commercial geotechnical software packages that simulate probabilistic constitutive behaviour of materials within finite element methods for large-scale stratigraphic analysis. Instead, commercially available probabilistic methods such as the random limit equilibrium method are incapable of incorporating non-linear constitutive soil behaviour. For this reason, advanced constitutive models are seldom coupled with probabilistically varying soil layers or spatially variable soil parameters. The objective of this research is the implementation of a simplified method for probabilistic stratigraphic analysis within a commercially available FE environment, providing a technique to assess the effects of stratigraphic uncertainty on slope stability. The proposed method is presented, highlighting the impact of localised thin layers of soft material as well as their frequency and location on the slope of an operational open-pit mine. The significance of these stratigraphic effects is presented through a case study of Australia’s second-largest open-pit mine, at which the stability of a collapsed coal slope is analysed. To improve the reliability of the finite element method for slope stability assessment, the Monte Carlo approach has been incorporated to consider varying shear strength distributions for models incorporating advanced constitutive behaviour. Thicker probabilistically generated deposits of silty material resulted in increased slope Factors of Safety. Similarly, greater proportions of silty deposits within a predominantly clayey interseam produced larger safety factors than slopes without localised thin silty layers. Stratigraphic analysis indicated that the Factor of Safety was most sensitive to localised silt layers at depths greater than 83 m below ground level. © 2020, Springer Nature Switzerland AG.

Trustworthiness of self-driving vehicles for intelligent transportation systems in industry applications

- Chowdhury, Abdullahi, Karmakar, Gour, Kamruzzaman, Joarder, Islam, Syed

  • Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Islam, Syed
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Informatics Vol. 17, no. 2 (2021), p. 961-970
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  • Description: To enhance industrial production and automation, rapid and faster transportation of raw materials and finished products to and from distributed factories, warehouses and outlets are essential. To reduce cost with increased efficiency, this will increasingly see the use of connected and self-driving commercial vehicles fitted with industrial grade sensors on roads, shared with normal and self-driving passenger vehicles. For its wide adoption, the trustworthiness of self-driving vehicles in the intelligent transportation system (ITS) is pivotal. In this article, we introduce a novel model to measure the overall trustworthiness of a self-driving vehicle considering on-Board unit (OBU) components, GPS data and safety messages. In calculating the trustworthiness of individual OBU components, CertainLogic and beta distribution function (BDF) are used. Those trust values are fused using both the dempster-Shafer Theory (DST) and a logical operator of CertainLogic. Results of our simulation show that our proposed method can effectively determine the trust of self-driving vehicles. © 2005-2012 IEEE.

2020 International Society of Hypertension global hypertension practice guidelines

- Unger, Thomas, Borghi, Claudio, Charchar, Fadi, Khan, Nadia, Poulter, Neil, Prabhakaran, Dorairaj, Ramirez, Agustin, Schlaich, Markus, Stergiou, George, Tomaszewski, Maciej, Wainford, Richard, Williams, Bryan, Schutte, Aletta

A combined virtual element method and the scaled boundary finite element method for linear elastic fracture mechanics

- Adak, Dibyendu, Pramod, ALN, Ooi, Ean Tat, Natarajan, Sundararajan

  • Authors: Adak, Dibyendu , Pramod, ALN , Ooi, Ean Tat , Natarajan, Sundararajan
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Engineering Analysis with Boundary Elements Vol. 113, no. (2020), p. 9-16
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  • Description: In this paper, we propose a framework that combines the recently introduced virtual element method (VEM) and the scaled boundary finite element method (SBFEM) to evaluate the fracture parameters. The domain is discretized with arbitrary polygons and the element that contains the crack tip is treated within the framework of the SBFEM. This facilitates a semi-analytical treatment of the crack tip singularity allowing the fracture parameters are estimated directly from the definition. The VEM is employed for the rest of the domain. The salient feature of the VEM is that the terms in the stiffness matrix are computed without requiring higher order quadrature schemes. As both the methods satisfy partition of unity and the compatibility condition, the matrices are assembled as in the conventional FEM. The accuracy of the proposed formulation is demonstrated with two standard benchmark examples. The proposed VEM-SBFEM framework yields accurate results. © 2019 Elsevier Ltd

A comprehensive analyses of aging characteristics of oil-paper insulation system in HVDC converter transformers

- Cui, Huize, Yang, Liuqing, Zhu, Yuanwei, Li, Shengtao, Abu-Siada, A., Islam, Syed

  • Authors: Cui, Huize , Yang, Liuqing , Zhu, Yuanwei , Li, Shengtao , Abu-Siada, A. , Islam, Syed
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 27, no. 5 (2020), p. 1707-1714
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  • Description: This paper investigates the dissolved gases evolution in transformer oil under combined DC/AC electrical-Thermal stress. Dissolved gases detected in transformer aged insulation oil reveal that oil under AC electric field combined with thermal stress can produce more dissolved gases than oil under DC electric field with thermal stress but less than the gases produced in oil under distorted AC or combined AC/DC voltage stress. This is attributed to the divergent migration properties of the charged components under different types of electric fields. To further understand this behavior, carrier recombination coefficient is proposed to explain the oil DGA results under various aging stresses. Results show that diagnostic parameters such as breakdown voltage, oil interfacial tension, and moisture content in pressboard should be used along with DGA results in order to accurately diagnose the insulation condition within converter transformers that impose a combined AC/DC voltage stress on the insulation system. © 1994-2012 IEEE.
  • Description: This work has been supported by the National Key Research and Development Program of China (2017YFB0902705), State Key Laboratory of Electrical Insulation and Power Equipment (EIPE20210), the National Natural Science Foundation of China (51907148), the Youth Fund of State Key Laboratory of Electrical Insulation and Power Equipment (EIPE19308), the Foundation Project of State Grid in Shaanxi province section, China (SGSNKY00SPJS1900302). The authors thank the Natural Science Basic Research Plan in Shaanxi Province of China (2019JQ-070).

A cross-sectional survey of nursing students' patient safety knowledge

- Levett-Jones, Tracy, Andersen, Patrea, Bogossian, Fiona, Cooper, Simon, Guinea, Stephen, Hopmans, Ruben, McKenna, Lisa, Pich, Jacqui, Reid-Searl, Kerry, Seaton, Philippa

  • Authors: Levett-Jones, Tracy , Andersen, Patrea , Bogossian, Fiona , Cooper, Simon , Guinea, Stephen , Hopmans, Ruben , McKenna, Lisa , Pich, Jacqui , Reid-Searl, Kerry , Seaton, Philippa
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Nurse Education Today Vol. 88, no. (2020), p.
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  • Description: Background: Knowledge provides a foundation for safe and effective nursing practice. However, most previous studies have focused on exploring nursing students' self-reported perceptions of, or confidence in, their level of patient safety knowledge, rather than examining their actual levels of knowledge. Objective: The overarching objective of this study was to examine final year nursing students' levels of knowledge about key patient safety concepts. Design: A cross-sectional design was used for this study. Data collection was undertaken during 2018 using a web-based patient safety quiz with 45 multiple choice questions informed by the Patient Safety Competency Framework for Nursing Students. A Modified Angoff approach was used to establish a pass mark or ‘cut score’ for the quiz. Setting and participants: Nursing students enrolled in the final year of a pre-registration nursing program in Australia or New Zealand were invited to participate in the study. Results: In total, 2011 final year nursing students from 23 educational institutions completed the quiz. Mean quiz scores were 29.35/45 or 65.23% (SD 5.63). Participants achieved highest scores in the domains of person-centred care and therapeutic communication, and lowest scores for infection prevention and control and medication safety. Based on the pass mark of 67.3% determined by the Modified Angoff procedure, 44.7% of students (n = 899) demonstrated passing performance on the quiz. For eight of the institutions, less than half of their students achieved a passing mark. Conclusions: Given the pivotal role that nurses play in maintaining patient safety, the results from this quiz raise important questions about the preparation of nursing students for safe and effective clinical practice. The institutional results also suggest the need for increased curricula attention to patient safety. © 2020 Elsevier Ltd

A distributed and anonymous data collection framework based on multilevel edge computing architecture

- Usman, Muhammad, Jan, Mian, Jolfaei, Alireza, Xu, Min, He, Xiangjian, Chen, Jinjun

  • Authors: Usman, Muhammad , Jan, Mian , Jolfaei, Alireza , Xu, Min , He, Xiangjian , Chen, Jinjun
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Industrial Informatics Vol. 16, no. 9 (2020), p. 6114-6123
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  • Description: Industrial Internet of Things applications demand trustworthiness in terms of quality of service (QoS), security, and privacy, to support the smooth transmission of data. To address these challenges, in this article, we propose a distributed and anonymous data collection (DaaC) framework based on a multilevel edge computing architecture. This framework distributes captured data among multiple level-one edge devices (LOEDs) to improve the QoS and minimize packet drop and end-to-end delay. Mobile sinks are used to collect data from LOEDs and upload to cloud servers. Before data collection, the mobile sinks are registered with a level-two edge-device to protect the underlying network. The privacy of mobile sinks is preserved through group-based signed data collection requests. Experimental results show that our proposed framework improves QoS through distributed data transmission. It also helps in protecting the underlying network through a registration scheme and preserves the privacy of mobile sinks through group-based data collection requests. © 2005-2012 IEEE.

A DNA toolbox for non-invasive genetic studies of sambar deer (Rusa unicolor)

- Davies, Chris, Wright, Wendy, Wedrowicz, Faye, Hogan, Fiona

  • Authors: Davies, Chris , Wright, Wendy , Wedrowicz, Faye , Hogan, Fiona
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Australian Mammalogy Vol. 42, no. 1 (2020), p. 58-66
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  • Description: Invasive sambar deer (Rusa unicolor) are having significant detrimental impacts on natural environments in south-eastern Australia. Little, however, is known about their ecology, limiting evidence-based management strategies directed at reducing deer impacts. Genetic data, generated from DNA isolated from deer scats, can be used to fill ecological knowledge gaps. This study outlines a non-invasive genetic sampling strategy by which good-quality DNA from a single deer scat can be used to determine (1) species of origin, (2) sex and (3) a unique DNA profile. DNA from deer tissue and sambar deer scat samples were used to develop and optimise molecular methods to collect reliable genetic information. A DNA toolbox is presented that describes how to find, collect and store scat samples, isolate DNA and use molecular markers to generate informative genetic data. Generating genetic data using this approach will support studies aimed at acquiring ecological knowledge about sambar deer. Such knowledge will be critical for developing evidence-based recommendations to improve on-ground management decisions for sambar deer.

A dual scaled boundary finite element formulation over arbitrary faceted star convex polyhedra

- Ooi, Ean Tat, Saputra, Albert, Natarajan, Sundararajan, Ooi, Ean Hin, Song, Chongmin

  • Authors: Ooi, Ean Tat , Saputra, Albert , Natarajan, Sundararajan , Ooi, Ean Hin , Song, Chongmin
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Computational Mechanics Vol. 66, no. 1 (2020), p. 27-47
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  • Description: A novel technique to formulate arbritrary faceted polyhedral elements in three-dimensions is presented. The formulation is applicable for arbitrary faceted polyhedra, provided that a scaling requirement is satisfied and the polyhedron facets are planar. A triangulation process can be applied to non-planar facets to generate an admissible geometry. The formulation adopts two separate scaled boundary coordinate systems with respect to: (i) a scaling centre located within a polyhedron and; (ii) a scaling centre on a polyhedron’s facets. The polyhedron geometry is scaled with respect to both the scaling centres. Polygonal shape functions are derived using the scaled boundary finite element method on the polyhedron facets. The stiffness matrix of a polyhedron is obtained semi-analytically. Numerical integration is required only for the line elements that discretise the polyhedron boundaries. The new formulation passes the patch test. Application of the new formulation in computational solid mechanics is demonstrated using a few numerical benchmarks. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

A guide to the short, long and circular RNAs in hypertension and cardiovascular disease

- Prestes, Priscilla, Maier, Michelle, Woods, Bradley, Charchar, Fadi

  • Authors: Prestes, Priscilla , Maier, Michelle , Woods, Bradley , Charchar, Fadi
  • Date: 2020
  • Type: Text , Journal article , Review
  • Relation: International Journal of Molecular Sciences Vol. 21, no. 10 (2020)
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  • Description: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in adults in developed countries. CVD encompasses many diseased states, including hypertension, coronary artery disease and atherosclerosis. Studies in animal models and human studies have elucidated the contribution of many genetic factors, including non-coding RNAs. Non-coding RNAs are RNAs not translated into protein, involved in gene expression regulation post-transcriptionally and implicated in CVD. Of these, circular RNAs (circRNAs) and microRNAs are relevant. CircRNAs are created by the back-splicing of pre-messenger RNA and have been underexplored as contributors to CVD. These circRNAs may also act as biomarkers of human disease, as they can be extracted from whole blood, plasma, saliva and seminal fluid. CircRNAs have recently been implicated in various disease processes, including hypertension and other cardiovascular disease. This review article will explore the promising and emerging roles of circRNAs as potential biomarkers and therapeutic targets in CVD, in particular hypertension. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

A low-complexity equalizer for video broadcasting in cyber-physical social systems through handheld mobile devices

- Solyman, Ahmad, Attar, Hani, Khosravi, Mohammad, Menon, Varun, Jolfaei, Alireza, Balasubramanian, Venki, Selvaraj, Buvana, Tavallali, Pooya

  • Authors: Solyman, Ahmad , Attar, Hani , Khosravi, Mohammad , Menon, Varun , Jolfaei, Alireza , Balasubramanian, Venki , Selvaraj, Buvana , Tavallali, Pooya
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 67591-67602
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  • Description: In Digital Video Broadcasting-Handheld (DVB-H) devices for cyber-physical social systems, the Discrete Fractional Fourier Transform-Orthogonal Chirp Division Multiplexing (DFrFT-OCDM) has been suggested to enhance the performance over Orthogonal Frequency Division Multiplexing (OFDM) systems under time and frequency-selective fading channels. In this case, the need for equalizers like the Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF) arises, though it is excessively complex due to the need for a matrix inversion, especially for DVB-H extensive symbol lengths. In this work, a low complexity equalizer, Least-Squares Minimal Residual (LSMR) algorithm, is used to solve the matrix inversion iteratively. The paper proposes the LSMR algorithm for linear and nonlinear equalizers with the simulation results, which indicate that the proposed equalizer has significant performance and reduced complexity over the classical MMSE equalizer and other low complexity equalizers, in time and frequency-selective fading channels. © 2013 IEEE.

A machine learning approach for prediction of pregnancy outcome following IVF treatment

- Hassan, Md Rafiul, Al-Insaif, Sadiq, Hossain, Muhammad, Kamruzzaman, Joarder

  • Authors: Hassan, Md Rafiul , Al-Insaif, Sadiq , Hossain, Muhammad , Kamruzzaman, Joarder
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Neural Computing and Applications Vol. 32, no. 7 (2020), p. 2283-2297
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  • Description: Infertility affects one out of seven couples around the world. Therefore, the best possible management of the in vitro fertilization (IVF) treatment and patient advice is crucial for both patients and medical practitioners. The ultimate concern of the patients is the success of an IVF procedure, which depends on a number of influencing attributes. Without any automated tool, it is hard for the practitioners to assess any influencing trend of the attributes and factors that might lead to a successful IVF pregnancy. This paper proposes a hill climbing feature (attribute) selection algorithm coupled with automated classification using machine learning techniques with the aim to analyze and predict IVF pregnancy in greater accuracy. Using 25 attributes, we assessed the prediction ability of IVF pregnancy success for five different machine learning models, namely multilayer perceptron (MLP), support vector machines (SVM), C4.5, classification and regression trees (CART) and random forest (RF). The prediction ability was measured in terms of widely used performance metrics, namely accuracy rate, F-measure and AUC. Feature selection algorithm reduced the number of most influential attributes to nineteen for MLP, sixteen for RF, seventeen for SVM, twelve for C4.5 and eight for CART. Overall, the most influential attributes identified are: ‘age’, ‘indication’ of fertility factor, ‘Antral Follicle Counts (AFC)’, ‘NbreM2’, ‘method of sperm collection’, ‘Chamotte’, ‘Fertilization rate in vitro’, ‘Follicles on day 14’ and ‘Embryo transfer day.’ The machine learning models trained with the selected set of features significantly improved the prediction accuracy of IVF pregnancy success to a level considerably higher than those reported in the current literature. © 2018, The Natural Computing Applications Forum.

A narrative review of pharmacotherapy treatment for opioid addiction and application in a community-based model in Victoria, Australia

- Vishwanath, Tejaswini, Cash, Penelope, Penney, Wendy, Cant, Robyn

  • Authors: Vishwanath, Tejaswini , Cash, Penelope , Penney, Wendy , Cant, Robyn
  • Date: 2020
  • Type: Text , Journal article
  • Relation: International Journal of Mental Health and Addiction Vol. 18, no. 1 (2020), p. 66-76
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  • Description: To review the literature regarding the value and consumer focus of research on opioid replacement therapy (ORT) programs, relevant to the Australian rural context and community pharmacy. We conducted a narrative review of literature published between 1995 and 2015, searching EBSCOhost, PubMed and Google Scholar. Three authors collaborated to screen and synthesise studies. Effectiveness, cost affordability, diversion and retention benefits were reported from pharmacological or prescribers’ or dispensers’ standpoint. Research was fragmented and evaluated contributions of these individual types of stakeholders with less discussion of consumers, or consumers’ everyday experiences of ORT. No studies took into account consumers’ psychosocial aspects or power discourses. We found ORT as a beneficial treatment for opioid dependence is well researched, although overall Australian program evaluation was lacking. A gap within ORT literature should be addressed by making consumer experiences central in designs for future research and for program evaluation. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

A new coupling structure and position detection method for segmented control dynamic wireless power transfer systems

- Li, Xiaofei, Hu, Jiefeng, Wang, Heshou, Dai, Xin, Sun, Yue

  • Authors: Li, Xiaofei , Hu, Jiefeng , Wang, Heshou , Dai, Xin , Sun, Yue
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Transactions on Power Electronics Vol. 35, no. 7 (2020), p. 6741-6745
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  • Description: In this letter, a new coupling structure for dynamic wireless power transfer (DWPT) systems is proposed. Bipolar coils are symmetrically placed on the transmitter unipolar coils, resulting in natural decoupling between the bipolar coils and the unipolar coils. This special structure can mitigate the self-couplings between the adjacent unipolar transmitter coils and hence facilitate the design of the compensation circuit. Another remarkable advantage of this design is that it can lead to a stable mutual coupling between the transmitter array and the receiver when the receiver moves along the transmitter, making it a natural fit for DWPT applications. Furthermore, to reduce the electromagnetic interference and power loss, an automatic segmented control scheme is implemented, and a position detection method by monitoring the primary current is developed. The feasibility of the proposed coupling structure and the position detection method are verified on a laboratory prototype with 72-V output voltage. The experimental results show that the power fluctuation is within ±2.5%, and system efficiency is around 90%. (This letter is accompanied by a video demonstrating the experimental test). © 2020 IEEE.

A new data driven long-term solar yield analysis model of photovoltaic power plants

- Ray, Biplob, Shah, Rakibuzzaman, Islam, Md Rabiul, Islam, Syed

  • Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
  • Date: 2020
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
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  • Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.

A note on primal-dual stability in infinite linear programming

- Goberna, Miguel, López, Marco, Ridolfi, Andrea, Vera de Serio, Virginia

  • Authors: Goberna, Miguel , López, Marco , Ridolfi, Andrea , Vera de Serio, Virginia
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Optimization Letters Vol. 14, no. 8 (2020), p. 2247-2263
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  • Description: In this note we analyze the simultaneous preservation of the consistency (and of the inconsistency) of linear programming problems posed in infinite dimensional Banach spaces, and their corresponding dual problems, under sufficiently small perturbations of the data. We consider seven different scenarios associated with the different possibilities of perturbations of the data (the objective functional, the constraint functionals, and the right hand-side function), i.e., which of them are known, and remain fixed, and which ones can be perturbed because of their uncertainty. The obtained results allow us to give sufficient and necessary conditions for the coincidence of the optimal values of both problems and for the stability of the duality gap under the same type of perturbations. There appear substantial differences with the finite dimensional case due to the distinct topological properties of cones in finite and infinite dimensional Banach spaces. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
  • Description: Funding details: Australian Research Council, ARC, DP180100602: http://purl.org/au-research/grants/arc/DP180100602