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.
- 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
- Full Text:
- Reviewed:
- 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 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.
- 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)
- Full Text:
- Reviewed:
- 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.
- 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
- Full Text:
- Reviewed:
- 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 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
- Full Text:
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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.
- 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
- Full Text:
- Reviewed:
- 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 pupil-positioning method based on the starburst model
- Yu, Pingping, Duan, Wenjie, Sun, Yi, Cao, Ning, Wang, Zhenzhou, Lu, Guojun
- Authors: Yu, Pingping , Duan, Wenjie , Sun, Yi , Cao, Ning , Wang, Zhenzhou , Lu, Guojun
- Date: 2020
- Type: Text , Journal article
- Relation: Cmc-Computers Materials & Continua Vol. 64, no. 2 (2020), p. 1199-1217
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- Description: Human eye detection has become an area of interest in the field of computer vision with an extensive range of applications in human-computer interaction, disease diagnosis, and psychological and physiological studies. Gaze-tracking systems are an important research topic in the human-computer interaction field. As one of the core modules of the head-mounted gaze-tracking system, pupil positioning affects the accuracy and stability of the system. By tracking eye movements to better locate the center of the pupil, this paper proposes a method for pupil positioning based on the starburst model. The method uses vertical and horizontal coordinate integral projections in the rectangular region of the human eye for accurate positioning and applies a linear interpolation method that is based on a circular model to the reflections in the human eye. In this paper, we propose a method for detecting the feature points of the pupil edge based on the starburst model, which clusters feature points and uses the RANdom SAmple Consensus (RANSAC) algorithm to perform ellipse fitting of the pupil edge to accurately locate the pupil center. Our experimental results show that the algorithm has higher precision, higher efficiency and more robustness than other algorithms and excellent accuracy even when the image of the pupil is incomplete.
- Description: Science and Technology Support Plan Project of Hebei Province (grant numbers 17210803D and 19273703D Science and Technology Spark Project of the Hebei Seismological Bureau (grant number DZ20180402056) Education Department of Hebei Province (grant number QN2018095) Polytechnic College of Hebei University of Science and Technology
- Authors: Yu, Pingping , Duan, Wenjie , Sun, Yi , Cao, Ning , Wang, Zhenzhou , Lu, Guojun
- Date: 2020
- Type: Text , Journal article
- Relation: Cmc-Computers Materials & Continua Vol. 64, no. 2 (2020), p. 1199-1217
- Full Text:
- Reviewed:
- Description: Human eye detection has become an area of interest in the field of computer vision with an extensive range of applications in human-computer interaction, disease diagnosis, and psychological and physiological studies. Gaze-tracking systems are an important research topic in the human-computer interaction field. As one of the core modules of the head-mounted gaze-tracking system, pupil positioning affects the accuracy and stability of the system. By tracking eye movements to better locate the center of the pupil, this paper proposes a method for pupil positioning based on the starburst model. The method uses vertical and horizontal coordinate integral projections in the rectangular region of the human eye for accurate positioning and applies a linear interpolation method that is based on a circular model to the reflections in the human eye. In this paper, we propose a method for detecting the feature points of the pupil edge based on the starburst model, which clusters feature points and uses the RANdom SAmple Consensus (RANSAC) algorithm to perform ellipse fitting of the pupil edge to accurately locate the pupil center. Our experimental results show that the algorithm has higher precision, higher efficiency and more robustness than other algorithms and excellent accuracy even when the image of the pupil is incomplete.
- Description: Science and Technology Support Plan Project of Hebei Province (grant numbers 17210803D and 19273703D Science and Technology Spark Project of the Hebei Seismological Bureau (grant number DZ20180402056) Education Department of Hebei Province (grant number QN2018095) Polytechnic College of Hebei University of Science and Technology
A role for MAIT cells in colorectal cancer
- Berzins, Stuart, Wallace, Morgan, Kannourakis, George, Kelly, Jason
- Authors: Berzins, Stuart , Wallace, Morgan , Kannourakis, George , Kelly, Jason
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Frontiers in Immunology Vol. 11, no. (2020), p.
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- Description: MAIT cells are MR1-restricted T cells that are well-known for their anti-microbial properties, but they have recently been associated with different forms of cancer. Several studies have reported activated MAIT cells within the microenvironment of colorectal tumors, but there is conjecture about the nature of their response and whether they are contributing to anti-tumor immunity, or to the progression of the disease. We have reviewed the current state of knowledge about the role of MAIT cells in colorectal cancer, including their likely influence when activated and potential sources of stimulation in the tumor microenvironment. The prospects for MAIT cells being used in clinical settings as biomarkers or as targets of new immunotherapies designed to harness their function are discussed. © Copyright © 2020 Berzins, Wallace, Kannourakis and Kelly.
- Authors: Berzins, Stuart , Wallace, Morgan , Kannourakis, George , Kelly, Jason
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Frontiers in Immunology Vol. 11, no. (2020), p.
- Full Text:
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- Description: MAIT cells are MR1-restricted T cells that are well-known for their anti-microbial properties, but they have recently been associated with different forms of cancer. Several studies have reported activated MAIT cells within the microenvironment of colorectal tumors, but there is conjecture about the nature of their response and whether they are contributing to anti-tumor immunity, or to the progression of the disease. We have reviewed the current state of knowledge about the role of MAIT cells in colorectal cancer, including their likely influence when activated and potential sources of stimulation in the tumor microenvironment. The prospects for MAIT cells being used in clinical settings as biomarkers or as targets of new immunotherapies designed to harness their function are discussed. © Copyright © 2020 Berzins, Wallace, Kannourakis and Kelly.
A shared bus profiling scheme for smart cities based on heterogeneous mobile crowdsourced data
- Kong, Xiangjie, Xia, Feng, Li, Jianxin, Hou, Mingliang, Li, Menglin, Xiang, Yong
- Authors: Kong, Xiangjie , Xia, Feng , Li, Jianxin , Hou, Mingliang , Li, Menglin , Xiang, Yong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 16, no. 2 (2020), p. 1436-1444
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- Description: Mobile crowdsourcing (MCS), as an effective and crucial technique of Industrial Internet of Things, is enabling smart city initiatives in the real world. It aims at incorporating the intelligence of dynamic crowds to collect and compute decentralized ubiquitous sensing data that can be used to solve major urbanization problems such as traffic congestion. The shared bus, as a neotype transportation mode, aims at improving the resource utilization rate and maintaining the advantages of convenience and economy. In this article, we provide a scheme to profile shared buses through heterogeneous mobile crowdsourced data (TRProfiling). First, we design an MCS-based shared bus data generation and collection solution to overcome the aforementioned data scarcity issue. Then, we propose a travel profiling to profile resident travel and design a method called multiconstraint evolution algorithm to optimize the routes. Experimental results demonstrate that TRProfiling has an excellent performance in satisfying passengers' travel requirements. © 2005-2012 IEEE.
- Authors: Kong, Xiangjie , Xia, Feng , Li, Jianxin , Hou, Mingliang , Li, Menglin , Xiang, Yong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 16, no. 2 (2020), p. 1436-1444
- Full Text:
- Reviewed:
- Description: Mobile crowdsourcing (MCS), as an effective and crucial technique of Industrial Internet of Things, is enabling smart city initiatives in the real world. It aims at incorporating the intelligence of dynamic crowds to collect and compute decentralized ubiquitous sensing data that can be used to solve major urbanization problems such as traffic congestion. The shared bus, as a neotype transportation mode, aims at improving the resource utilization rate and maintaining the advantages of convenience and economy. In this article, we provide a scheme to profile shared buses through heterogeneous mobile crowdsourced data (TRProfiling). First, we design an MCS-based shared bus data generation and collection solution to overcome the aforementioned data scarcity issue. Then, we propose a travel profiling to profile resident travel and design a method called multiconstraint evolution algorithm to optimize the routes. Experimental results demonstrate that TRProfiling has an excellent performance in satisfying passengers' travel requirements. © 2005-2012 IEEE.
A Survey on Behavioral Pattern Mining from Sensor Data in Internet of Things
- Rashid, Md Mamunur, Kamruzzaman, Joarder, Hassan, Mohammad, Shahriar Shafin, Sakib, Bhuiyan, Md Zakirul
- Authors: Rashid, Md Mamunur , Kamruzzaman, Joarder , Hassan, Mohammad , Shahriar Shafin, Sakib , Bhuiyan, Md Zakirul
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 33318-33341
- Full Text:
- Reviewed:
- Description: The deployment of large-scale wireless sensor networks (WSNs) for the Internet of Things (IoT) applications is increasing day-by-day, especially with the emergence of smart city services. The sensor data streams generated from these applications are largely dynamic, heterogeneous, and often geographically distributed over large areas. For high-value use in business, industry and services, these data streams must be mined to extract insightful knowledge, such as about monitoring (e.g., discovering certain behaviors over a deployed area) or network diagnostics (e.g., predicting faulty sensor nodes). However, due to the inherent constraints of sensor networks and application requirements, traditional data mining techniques cannot be directly used to mine IoT data streams efficiently and accurately in real-time. In the last decade, a number of works have been reported in the literature proposing behavioral pattern mining algorithms for sensor networks. This paper presents the technical challenges that need to be considered for mining sensor data. It then provides a thorough review of the mining techniques proposed in the recent literature to mine behavioral patterns from sensor data in IoT, and their characteristics and differences are highlighted and compared. We also propose a behavioral pattern mining framework for IoT and discuss possible future research directions in this area. © 2013 IEEE.
- Authors: Rashid, Md Mamunur , Kamruzzaman, Joarder , Hassan, Mohammad , Shahriar Shafin, Sakib , Bhuiyan, Md Zakirul
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 33318-33341
- Full Text:
- Reviewed:
- Description: The deployment of large-scale wireless sensor networks (WSNs) for the Internet of Things (IoT) applications is increasing day-by-day, especially with the emergence of smart city services. The sensor data streams generated from these applications are largely dynamic, heterogeneous, and often geographically distributed over large areas. For high-value use in business, industry and services, these data streams must be mined to extract insightful knowledge, such as about monitoring (e.g., discovering certain behaviors over a deployed area) or network diagnostics (e.g., predicting faulty sensor nodes). However, due to the inherent constraints of sensor networks and application requirements, traditional data mining techniques cannot be directly used to mine IoT data streams efficiently and accurately in real-time. In the last decade, a number of works have been reported in the literature proposing behavioral pattern mining algorithms for sensor networks. This paper presents the technical challenges that need to be considered for mining sensor data. It then provides a thorough review of the mining techniques proposed in the recent literature to mine behavioral patterns from sensor data in IoT, and their characteristics and differences are highlighted and compared. We also propose a behavioral pattern mining framework for IoT and discuss possible future research directions in this area. © 2013 IEEE.
Aberrant pregnancy-associated plasma protein-A expression in breast cancers prognosticates clinical outcomes
- Prithviraj, Prashanth, Anaka, Matthew, Thompson, Erik, Sharma, Revati, Walkiewicz, Marzena, Tutuka, Candani, Behren, Andreas, Kannourakis, George, Jayachandran, Aparna
- Authors: Prithviraj, Prashanth , Anaka, Matthew , Thompson, Erik , Sharma, Revati , Walkiewicz, Marzena , Tutuka, Candani , Behren, Andreas , Kannourakis, George , Jayachandran, Aparna
- Date: 2020
- Type: Text , Journal article
- Relation: Scientific Reports Vol. 10, no. 1 (2020), p.
- Full Text:
- Reviewed:
- Description: Elevated levels of pregnancy-associated plasma protein-A (PAPP-A) have been implicated in the pathogenesis of various malignancies, including breast cancers. Breast cancer is one of the most frequent carcinomas and is the second most common cancer type detected in women of child-bearing age. Throughout pregnancy PAPP-A is produced and secreted by the placental syncytiotrophoblast cells; co-incidentally pregnancy-associated breast cancers often have an aggressive clinical course. The components of the PAPP-A/IGF axis was assessed in a panel of breast cancer cell lines. Using neutralising antibodies the impact of PAPP-A/IGF axis on cell motility was evaluated. PAPP-A was expressed in four of the twelve breast cancer cell lines tested. Blocking PAPP-A and IGFBP4 with neutralising antibodies significantly decreased motiliy of MDA-MB-231 cells. Upregulation of PAPP-A expression in breast tumours resulted in a trend towards worse overall survival. Notably, PAPP-A expression also positively correlated with epithelial-to-mesenchymal transition markers. In conclusion, these results indicate that PAPP-A plays an important role in breast cancer progression and it may be a promising therapeutic target in breast cancer. © 2020, The Author(s).
- Authors: Prithviraj, Prashanth , Anaka, Matthew , Thompson, Erik , Sharma, Revati , Walkiewicz, Marzena , Tutuka, Candani , Behren, Andreas , Kannourakis, George , Jayachandran, Aparna
- Date: 2020
- Type: Text , Journal article
- Relation: Scientific Reports Vol. 10, no. 1 (2020), p.
- Full Text:
- Reviewed:
- Description: Elevated levels of pregnancy-associated plasma protein-A (PAPP-A) have been implicated in the pathogenesis of various malignancies, including breast cancers. Breast cancer is one of the most frequent carcinomas and is the second most common cancer type detected in women of child-bearing age. Throughout pregnancy PAPP-A is produced and secreted by the placental syncytiotrophoblast cells; co-incidentally pregnancy-associated breast cancers often have an aggressive clinical course. The components of the PAPP-A/IGF axis was assessed in a panel of breast cancer cell lines. Using neutralising antibodies the impact of PAPP-A/IGF axis on cell motility was evaluated. PAPP-A was expressed in four of the twelve breast cancer cell lines tested. Blocking PAPP-A and IGFBP4 with neutralising antibodies significantly decreased motiliy of MDA-MB-231 cells. Upregulation of PAPP-A expression in breast tumours resulted in a trend towards worse overall survival. Notably, PAPP-A expression also positively correlated with epithelial-to-mesenchymal transition markers. In conclusion, these results indicate that PAPP-A plays an important role in breast cancer progression and it may be a promising therapeutic target in breast cancer. © 2020, The Author(s).
Almost simplicial polytopes : the lower and upper bound theorems
- Nevo, Eran, Pineda-Villavicencio, Guillermo, Ugon, Julien, Yost, David
- Authors: Nevo, Eran , Pineda-Villavicencio, Guillermo , Ugon, Julien , Yost, David
- Date: 2020
- Type: Text , Journal article
- Relation: Canadian Journal of Mathematics Vol. 72, no. 2 (2020), p. 537-556
- Full Text:
- Reviewed:
- Description: We study -vertex -dimensional polytopes with at most one nonsimplex facet with, say, vertices, called almost simplicial polytopes. We provide tight lower and upper bound theorems for these polytopes as functions of, and, thus generalizing the classical Lower Bound Theorem by Barnette and the Upper Bound Theorem by McMullen, which treat the case where s = 0. We characterize the minimizers and provide examples of maximizers for any. Our construction of maximizers is a generalization of cyclic polytopes, based on a suitable variation of the moment curve, and is of independent interest. © 2018 Canadian Mathematical Society.
- Authors: Nevo, Eran , Pineda-Villavicencio, Guillermo , Ugon, Julien , Yost, David
- Date: 2020
- Type: Text , Journal article
- Relation: Canadian Journal of Mathematics Vol. 72, no. 2 (2020), p. 537-556
- Full Text:
- Reviewed:
- Description: We study -vertex -dimensional polytopes with at most one nonsimplex facet with, say, vertices, called almost simplicial polytopes. We provide tight lower and upper bound theorems for these polytopes as functions of, and, thus generalizing the classical Lower Bound Theorem by Barnette and the Upper Bound Theorem by McMullen, which treat the case where s = 0. We characterize the minimizers and provide examples of maximizers for any. Our construction of maximizers is a generalization of cyclic polytopes, based on a suitable variation of the moment curve, and is of independent interest. © 2018 Canadian Mathematical Society.
An application of high-dimensional statistics to predictive modeling of grade variability
- Hinz, Juri, Grigoryev, Igor, Novikov, Alexander
- Authors: Hinz, Juri , Grigoryev, Igor , Novikov, Alexander
- Date: 2020
- Type: Text , Journal article
- Relation: Geosciences (Switzerland) Vol. 10, no. 4 (2020), p.
- Full Text:
- Reviewed:
- Description: The economic viability of a mining project depends on its efficient exploration, which requires a prediction of worthwhile ore in a mine deposit. In this work, we apply the so-called LASSO methodology to estimate mineral concentration within unexplored areas. Our methodology outperforms traditional techniques not only in terms of logical consistency, but potentially also in costs reduction. Our approach is illustrated by a full source code listing and a detailed discussion of the advantages and limitations of our approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Hinz, Juri , Grigoryev, Igor , Novikov, Alexander
- Date: 2020
- Type: Text , Journal article
- Relation: Geosciences (Switzerland) Vol. 10, no. 4 (2020), p.
- Full Text:
- Reviewed:
- Description: The economic viability of a mining project depends on its efficient exploration, which requires a prediction of worthwhile ore in a mine deposit. In this work, we apply the so-called LASSO methodology to estimate mineral concentration within unexplored areas. Our methodology outperforms traditional techniques not only in terms of logical consistency, but potentially also in costs reduction. Our approach is illustrated by a full source code listing and a detailed discussion of the advantages and limitations of our approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
An application of high-dimensional statistics to predictive modeling of grade variability
- Hinz, Juri, Grigoryev, Igor, Novikov, Alexander
- Authors: Hinz, Juri , Grigoryev, Igor , Novikov, Alexander
- Date: 2020
- Type: Text , Journal article
- Relation: Geosciences (Switzerland) Vol. 10, no. 4 (2020), p.
- Full Text:
- Reviewed:
- Description: The economic viability of a mining project depends on its efficient exploration, which requires a prediction of worthwhile ore in a mine deposit. In this work, we apply the so-called LASSO methodology to estimate mineral concentration within unexplored areas. Our methodology outperforms traditional techniques not only in terms of logical consistency, but potentially also in costs reduction. Our approach is illustrated by a full source code listing and a detailed discussion of the advantages and limitations of our approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Hinz, Juri , Grigoryev, Igor , Novikov, Alexander
- Date: 2020
- Type: Text , Journal article
- Relation: Geosciences (Switzerland) Vol. 10, no. 4 (2020), p.
- Full Text:
- Reviewed:
- Description: The economic viability of a mining project depends on its efficient exploration, which requires a prediction of worthwhile ore in a mine deposit. In this work, we apply the so-called LASSO methodology to estimate mineral concentration within unexplored areas. Our methodology outperforms traditional techniques not only in terms of logical consistency, but potentially also in costs reduction. Our approach is illustrated by a full source code listing and a detailed discussion of the advantages and limitations of our approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
An efficient 3-D model for remaining wall thicknesses of cast iron pipes in nondestructive testing
- Authors: Nguyen, Linh , Miro, Jaime
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Sensors Letters Vol. 4, no. 7 (2020), p.
- Full Text:
- Reviewed:
- Description: Over 50% of global pipes have been made of cast iron, and most of them are aging. In order to effectively estimate possibilities of their failures, which is paramount for efficiently managing asset infrastructures, it requires the remaining wall thickness (RWT) of a pipe to be known. In fact, RWT of the cast iron pipes can be primarily measured by the magnetism based nondestructive testing technologies though they are quite slow. To speed up the inspection process, it is proposed to sense RWT of a part of a pipe and then employ a model to predict RWT in the rest. Thus, this letter introduces a 3-D model to efficiently represent RWT of a pipe given measurements collected intermittently on the pipe's surface. The proposed model first transforms 3-D cylindrical coordinates to 3-D Cartesian coordinates before modeling RWT by Gaussian processes (GP). The transformation allows GP to work properly on RWT data gathered on a cylindrical pipe and effectively predict RWT at unmeasured locations. Moreover, periodicity of RWT along circumference of the pipe is naturally integrated. The effectiveness of the proposed approach is demonstrated by implementation in two real life inservice aging cast iron pipes, where the obtained results are highly promising. © 2017 IEEE.
- Authors: Nguyen, Linh , Miro, Jaime
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Sensors Letters Vol. 4, no. 7 (2020), p.
- Full Text:
- Reviewed:
- Description: Over 50% of global pipes have been made of cast iron, and most of them are aging. In order to effectively estimate possibilities of their failures, which is paramount for efficiently managing asset infrastructures, it requires the remaining wall thickness (RWT) of a pipe to be known. In fact, RWT of the cast iron pipes can be primarily measured by the magnetism based nondestructive testing technologies though they are quite slow. To speed up the inspection process, it is proposed to sense RWT of a part of a pipe and then employ a model to predict RWT in the rest. Thus, this letter introduces a 3-D model to efficiently represent RWT of a pipe given measurements collected intermittently on the pipe's surface. The proposed model first transforms 3-D cylindrical coordinates to 3-D Cartesian coordinates before modeling RWT by Gaussian processes (GP). The transformation allows GP to work properly on RWT data gathered on a cylindrical pipe and effectively predict RWT at unmeasured locations. Moreover, periodicity of RWT along circumference of the pipe is naturally integrated. The effectiveness of the proposed approach is demonstrated by implementation in two real life inservice aging cast iron pipes, where the obtained results are highly promising. © 2017 IEEE.
An enhancement to the spatial pyramid matching for image classification and retrieval
- Karmakar, Priyabrata, Teng, Shyh, Lu, Guojun, Zhang, Dengsheng
- Authors: Karmakar, Priyabrata , Teng, Shyh , Lu, Guojun , Zhang, Dengsheng
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 22463-22472
- Full Text:
- Reviewed:
- Description: Spatial pyramid matching (SPM) is one of the widely used methods to incorporate spatial information into the image representation. Despite its effectiveness, the traditional SPM is not rotation invariant. A rotation invariant SPM has been proposed in the literature but it has many limitations regarding the effectiveness. In this paper, we investigate how to make SPM robust to rotation by addressing those limitations. In an SPM framework, an image is divided into an increasing number of partitions at different pyramid levels. In this paper, our main focus is on how to partition images in such a way that the resulting structure can deal with image-level rotations. To do that, we investigate three concentric ring partitioning schemes. Apart from image partitioning, another important component of the SPM framework is a weight function. To apportion the contribution of each pyramid level to the final matching between two images, the weight function is needed. In this paper, we propose a new weight function which is suitable for the rotation-invariant SPM structure. Experiments based on image classification and retrieval are performed on five image databases. The detailed result analysis shows that we are successful in enhancing the effectiveness of SPM for image classification and retrieval. © 2013 IEEE.
- Authors: Karmakar, Priyabrata , Teng, Shyh , Lu, Guojun , Zhang, Dengsheng
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 22463-22472
- Full Text:
- Reviewed:
- Description: Spatial pyramid matching (SPM) is one of the widely used methods to incorporate spatial information into the image representation. Despite its effectiveness, the traditional SPM is not rotation invariant. A rotation invariant SPM has been proposed in the literature but it has many limitations regarding the effectiveness. In this paper, we investigate how to make SPM robust to rotation by addressing those limitations. In an SPM framework, an image is divided into an increasing number of partitions at different pyramid levels. In this paper, our main focus is on how to partition images in such a way that the resulting structure can deal with image-level rotations. To do that, we investigate three concentric ring partitioning schemes. Apart from image partitioning, another important component of the SPM framework is a weight function. To apportion the contribution of each pyramid level to the final matching between two images, the weight function is needed. In this paper, we propose a new weight function which is suitable for the rotation-invariant SPM structure. Experiments based on image classification and retrieval are performed on five image databases. The detailed result analysis shows that we are successful in enhancing the effectiveness of SPM for image classification and retrieval. © 2013 IEEE.
Anxiety and Depression After a Cardiac Event: Prevalence and Predictors
- Murphy, Barbara, Le Grande, Michael, Alvarenga, Marlies, Worcester, Marian, Jackson, Alun
- Authors: Murphy, Barbara , Le Grande, Michael , Alvarenga, Marlies , Worcester, Marian , Jackson, Alun
- Date: 2020
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 10, no. (2020), p.
- Full Text:
- Reviewed:
- Description: Introduction: Patients who are anxious or depressed after an acute cardiac event are at increased risk of a subsequent event and premature death. It is therefore important to identify these patients early in order to initiate supportive or even preventive measures. In the present study, we report on the prevalence of anxiety and depression during the first 12 months after an acute cardiac event, and the patient characteristics predictive of increased anxiety and depression risk in early and late convalescence. Methods: We recruited a sample of 911 patients with acute myocardial infarction (AMI), acute coronary syndrome (ACS), and/or unstable angina (UA), and/or undergoing coronary artery bypass graft surgery (CABGS). Patients completed the Hospital Anxiety and Depression Scale (HADS) close to the time of their event, and again during early (2–4 months post-event) and late (6–12 months post-event) convalescence. Using HADS-A and HADS-D cut-offs of 8+, prevalence rates for anxiety, depression, and comorbid anxiety and depression were determined for each timepoint. Chi-square tests and odds ratios were used to identify baseline patient characteristics associated with increased anxiety and depression risk over 12 months. Results: Anxiety rates were 43, 28, and 27% at the time of the event, early, and late convalescence. Depression rates were 22, 17, and 15%, respectively. Factors consistently associated with increased anxiety and depression risk were history of depression, financial strain, poor self-rated health, low socioeconomic status, younger age (<55 years), and smoking. Obesity, diabetes, and social isolation (living alone or being unpartnered) were identified as important albeit less significant risk factors. Neither sex nor event type were predictive of anxiety or depression. Conclusion: This large patient sample provided the opportunity to identify rates of anxiety and depression during the 12 months after a cardiac event and key patient characteristics for increased risk. These risk factors are easily identifiable at the time of the event, and could be used to guide the targeting of support programs for patients at risk. © Copyright © 2020 Murphy, Le Grande, Alvarenga, Worcester and Jackson.
- Authors: Murphy, Barbara , Le Grande, Michael , Alvarenga, Marlies , Worcester, Marian , Jackson, Alun
- Date: 2020
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 10, no. (2020), p.
- Full Text:
- Reviewed:
- Description: Introduction: Patients who are anxious or depressed after an acute cardiac event are at increased risk of a subsequent event and premature death. It is therefore important to identify these patients early in order to initiate supportive or even preventive measures. In the present study, we report on the prevalence of anxiety and depression during the first 12 months after an acute cardiac event, and the patient characteristics predictive of increased anxiety and depression risk in early and late convalescence. Methods: We recruited a sample of 911 patients with acute myocardial infarction (AMI), acute coronary syndrome (ACS), and/or unstable angina (UA), and/or undergoing coronary artery bypass graft surgery (CABGS). Patients completed the Hospital Anxiety and Depression Scale (HADS) close to the time of their event, and again during early (2–4 months post-event) and late (6–12 months post-event) convalescence. Using HADS-A and HADS-D cut-offs of 8+, prevalence rates for anxiety, depression, and comorbid anxiety and depression were determined for each timepoint. Chi-square tests and odds ratios were used to identify baseline patient characteristics associated with increased anxiety and depression risk over 12 months. Results: Anxiety rates were 43, 28, and 27% at the time of the event, early, and late convalescence. Depression rates were 22, 17, and 15%, respectively. Factors consistently associated with increased anxiety and depression risk were history of depression, financial strain, poor self-rated health, low socioeconomic status, younger age (<55 years), and smoking. Obesity, diabetes, and social isolation (living alone or being unpartnered) were identified as important albeit less significant risk factors. Neither sex nor event type were predictive of anxiety or depression. Conclusion: This large patient sample provided the opportunity to identify rates of anxiety and depression during the 12 months after a cardiac event and key patient characteristics for increased risk. These risk factors are easily identifiable at the time of the event, and could be used to guide the targeting of support programs for patients at risk. © Copyright © 2020 Murphy, Le Grande, Alvarenga, Worcester and Jackson.
Application of thermal fragmentation in Australian hard rock underground narrow-vein mining
- Drake, Bradley, Koroznikova, Larissa, Tuck, Michael, Durkin, Steve
- Authors: Drake, Bradley , Koroznikova, Larissa , Tuck, Michael , Durkin, Steve
- Date: 2020
- Type: Text , Journal article
- Relation: Mining, Metallurgy and Exploration Vol. 37, no. 1 (2020), p. 219-229
- Full Text:
- Reviewed:
- Description: This paper presents the results from the investigation of the application of thermal fragmentation in Australian hard rock underground narrow-vein mining. Two geologically similar samples from an underground narrow-vein hard rock gold mine were collected to obtain a measure of the technology’s ability to recover ore by the creation of large thermal openings to assess the applicability of the thermal method. Particle size distribution showed a higher generation of fine product, − 2 mm, by thermal fragmentation compared with selective blasting by 31%. The Bond work index for thermal ore (12.62 kWh/t) is half to that of the blasted ore value (25.32 kWh/t). The average grindability obtained for the thermal ore sample was greater than the blasted sample by a factor of 2.44, a higher value indicating a decrease in the energy required to grind. The thermal fragmentation method generates product with higher dissolution of gold in cyanide, by 14% for the − 9.5 + 2 mm size fraction samples. Additionally, the thermal fragmentation results in higher production of − 9.5 + 2 mm material by 15 % compared with selective blasting. © 2019, Society for Mining, Metallurgy & Exploration Inc.
- Authors: Drake, Bradley , Koroznikova, Larissa , Tuck, Michael , Durkin, Steve
- Date: 2020
- Type: Text , Journal article
- Relation: Mining, Metallurgy and Exploration Vol. 37, no. 1 (2020), p. 219-229
- Full Text:
- Reviewed:
- Description: This paper presents the results from the investigation of the application of thermal fragmentation in Australian hard rock underground narrow-vein mining. Two geologically similar samples from an underground narrow-vein hard rock gold mine were collected to obtain a measure of the technology’s ability to recover ore by the creation of large thermal openings to assess the applicability of the thermal method. Particle size distribution showed a higher generation of fine product, − 2 mm, by thermal fragmentation compared with selective blasting by 31%. The Bond work index for thermal ore (12.62 kWh/t) is half to that of the blasted ore value (25.32 kWh/t). The average grindability obtained for the thermal ore sample was greater than the blasted sample by a factor of 2.44, a higher value indicating a decrease in the energy required to grind. The thermal fragmentation method generates product with higher dissolution of gold in cyanide, by 14% for the − 9.5 + 2 mm size fraction samples. Additionally, the thermal fragmentation results in higher production of − 9.5 + 2 mm material by 15 % compared with selective blasting. © 2019, Society for Mining, Metallurgy & Exploration Inc.
Audit education in a socialist oriented market economy – the case of Vietnam
- Dang, Ky
- Authors: Dang, Ky
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: The objective of the research project is to contribute to the understanding of the auditing profession in Vietnam. In particular, it provides information on the challenges facing auditors in an emerging economy where economic transformation is in progress and where auditing, as a profession, is under development. Auditors operate in an environment of conflicting priorities where they must maintain independence and objectivity in discharging their responsibilities to stakeholders and society. In Vietnam, the audit profession only came into existence in 1986 when the country embarked on its new economic model. Whilst studies have been conducted on the status of current accounting practice in Vietnam, studies regarding the audit profession have been limited. In this research project an examination of the issues affecting audit quality in Vietnam are investigated and suggestions for changes to address the deficiencies are made. In particular, the project focuses on the relevance and appropriateness of the education of auditors. A national survey of accountants, auditors and accounting academics in Vietnam was undertaken. The survey results indicate that in Vietnam there are deficiencies in audit practices over and above those commonly observed in other countries. These deficiencies are the result of the unique history of Vietnam, the current stage of economic development and the education system for auditors. From an auditing perspective, the slow adaptation of the education system to the new economic environment is having negative effects on accounting graduates and their employment prospects. Although inadequate training was identified as the single most important factor affecting audit quality, the ineffective enforcement regime was also a contributing factor. This research project indicates that there is a need for an overhaul of the current education system in Vietnam and for universities to develop an accounting and auditing curriculum that meets the needs of employers while complying with government’s education objectives and international standards of auditing and accounting.
- Description: Doctor of Philosophy
- Authors: Dang, Ky
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: The objective of the research project is to contribute to the understanding of the auditing profession in Vietnam. In particular, it provides information on the challenges facing auditors in an emerging economy where economic transformation is in progress and where auditing, as a profession, is under development. Auditors operate in an environment of conflicting priorities where they must maintain independence and objectivity in discharging their responsibilities to stakeholders and society. In Vietnam, the audit profession only came into existence in 1986 when the country embarked on its new economic model. Whilst studies have been conducted on the status of current accounting practice in Vietnam, studies regarding the audit profession have been limited. In this research project an examination of the issues affecting audit quality in Vietnam are investigated and suggestions for changes to address the deficiencies are made. In particular, the project focuses on the relevance and appropriateness of the education of auditors. A national survey of accountants, auditors and accounting academics in Vietnam was undertaken. The survey results indicate that in Vietnam there are deficiencies in audit practices over and above those commonly observed in other countries. These deficiencies are the result of the unique history of Vietnam, the current stage of economic development and the education system for auditors. From an auditing perspective, the slow adaptation of the education system to the new economic environment is having negative effects on accounting graduates and their employment prospects. Although inadequate training was identified as the single most important factor affecting audit quality, the ineffective enforcement regime was also a contributing factor. This research project indicates that there is a need for an overhaul of the current education system in Vietnam and for universities to develop an accounting and auditing curriculum that meets the needs of employers while complying with government’s education objectives and international standards of auditing and accounting.
- Description: Doctor of Philosophy
Being a parent, but not : the role of foster and kinship carers in supporting children and young people
- Authors: Cooper, Kimberlea
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: Home-based carers play an important role in the lives of children and young people. In Victoria, Australia, home-based care is now the most common form of alternative care, reflecting national and international trends. However, home-based care does currently face some challenges, such as shortages of carers. Therefore, strengthening this form of care through the training and support of foster and kinship carers is a key priority of Victoria’s reforms of child and family services. In the context of a university-industry collaboration, the current research drew upon the expertise of sixteen foster and kinship carers in the Central Highlands region of Victoria. Using constructivist grounded theory, the research sought to understand how carers support children and young people and how they see their role. In addition, the research sought carers’ perspectives on their interactions with the Out-of-Home Care (OOHC) system, including what they find supportive and challenging. The research revealed that home-based carers see some elements of their role as parenting, and others as going beyond parenting. The carers utilise principles of trauma-informed care to support children and young people, but do not experience trauma-informed support from the OOHC system. This discrepancy suggests that the implementation of trauma-informed care has the potential to increase pressure on home-based carers if it is only encouraged at the interpersonal level between carers and children and does not incorporate associated systems-level change. Therefore, this research proposes that whilst micro-level support and training for carers is necessary and useful, it is crucial to move beyond such initiatives to make macro-level reform. This research also raises doubts regarding the capacity of home-based care to become fully trauma-informed due to potential incompatibilities with the current risk-averse and deficit-oriented paradigm of the child protection system.
- Description: Doctor of Philosophy
- Authors: Cooper, Kimberlea
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: Home-based carers play an important role in the lives of children and young people. In Victoria, Australia, home-based care is now the most common form of alternative care, reflecting national and international trends. However, home-based care does currently face some challenges, such as shortages of carers. Therefore, strengthening this form of care through the training and support of foster and kinship carers is a key priority of Victoria’s reforms of child and family services. In the context of a university-industry collaboration, the current research drew upon the expertise of sixteen foster and kinship carers in the Central Highlands region of Victoria. Using constructivist grounded theory, the research sought to understand how carers support children and young people and how they see their role. In addition, the research sought carers’ perspectives on their interactions with the Out-of-Home Care (OOHC) system, including what they find supportive and challenging. The research revealed that home-based carers see some elements of their role as parenting, and others as going beyond parenting. The carers utilise principles of trauma-informed care to support children and young people, but do not experience trauma-informed support from the OOHC system. This discrepancy suggests that the implementation of trauma-informed care has the potential to increase pressure on home-based carers if it is only encouraged at the interpersonal level between carers and children and does not incorporate associated systems-level change. Therefore, this research proposes that whilst micro-level support and training for carers is necessary and useful, it is crucial to move beyond such initiatives to make macro-level reform. This research also raises doubts regarding the capacity of home-based care to become fully trauma-informed due to potential incompatibilities with the current risk-averse and deficit-oriented paradigm of the child protection system.
- Description: Doctor of Philosophy
Blockchain leveraged decentralized IoT eHealth framework
- Uddin, Ashraf, Stranieri, Andrew, Gondal, Iqbal, Balasubramanian, Venki
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: Internet of Things Vol. 9, no. March 2020 p. 100159
- Full Text:
- Reviewed:
- Description: Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data.
- Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venki
- Date: 2020
- Type: Text , Journal article
- Relation: Internet of Things Vol. 9, no. March 2020 p. 100159
- Full Text:
- Reviewed:
- Description: Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data.
Cohort profile : the Australian genetics of depression study
- Byrne, Enda, Kirk, Katherine, Medland, Sarah, McGrath, John, Colodro-Conde, Lucia, Parker, Richard, Cross, Simone, Sullivan, Lenore, Statham, Dixie, Levinson, Douglas, Licinio, Julio, Wray, Naomi, Hickie, Ian, Martin, Nicholas
- Authors: Byrne, Enda , Kirk, Katherine , Medland, Sarah , McGrath, John , Colodro-Conde, Lucia , Parker, Richard , Cross, Simone , Sullivan, Lenore , Statham, Dixie , Levinson, Douglas , Licinio, Julio , Wray, Naomi , Hickie, Ian , Martin, Nicholas
- Date: 2020
- Type: Text , Journal article
- Relation: BMJ Open Vol. 10, no. 5 (2020), p.
- Full Text:
- Reviewed:
- Description: Purpose Depression is the most common psychiatric disorder and the largest contributor to global disability. The Australian Genetics of Depression study was established to recruit a large cohort of individuals who have been diagnosed with depression at some point in their lifetime. The purpose of establishing this cohort is to investigate genetic and environmental risk factors for depression and response to commonly prescribed antidepressants. Participants A total of 20 689 participants were recruited through the Australian Department of Human Services and a media campaign, 75% of whom were female. The average age of participants was 43 years±15 years. Participants completed an online questionnaire that consisted of a compulsory module that assessed self-reported psychiatric history, clinical depression using the Composite Interview Diagnostic Interview Short Form and experiences of using commonly prescribed antidepressants. Further voluntary modules assessed a wide range of traits of relevance to psychopathology. Participants who reported they were willing to provide a DNA sample (75%) were sent a saliva kit in the mail. Findings to date 95% of participants reported being given a diagnosis of depression by a medical practitioner and 88% met the criteria for a lifetime depressive episode. 68% of the sample report having been diagnosed with another psychiatric disorder in addition to depression. In line with findings from clinical trials, only 33% of the sample report responding well to the first antidepressant they were prescribed. Future plans A number of analyses to investigate the genetic architecture of depression and common comorbidities will be conducted. The cohort will contribute to the global effort to identify genetic variants that increase risk to depression. Furthermore, a thorough investigation of genetic and psychosocial predictors of antidepressant response and side effects is planned. © © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
- Authors: Byrne, Enda , Kirk, Katherine , Medland, Sarah , McGrath, John , Colodro-Conde, Lucia , Parker, Richard , Cross, Simone , Sullivan, Lenore , Statham, Dixie , Levinson, Douglas , Licinio, Julio , Wray, Naomi , Hickie, Ian , Martin, Nicholas
- Date: 2020
- Type: Text , Journal article
- Relation: BMJ Open Vol. 10, no. 5 (2020), p.
- Full Text:
- Reviewed:
- Description: Purpose Depression is the most common psychiatric disorder and the largest contributor to global disability. The Australian Genetics of Depression study was established to recruit a large cohort of individuals who have been diagnosed with depression at some point in their lifetime. The purpose of establishing this cohort is to investigate genetic and environmental risk factors for depression and response to commonly prescribed antidepressants. Participants A total of 20 689 participants were recruited through the Australian Department of Human Services and a media campaign, 75% of whom were female. The average age of participants was 43 years±15 years. Participants completed an online questionnaire that consisted of a compulsory module that assessed self-reported psychiatric history, clinical depression using the Composite Interview Diagnostic Interview Short Form and experiences of using commonly prescribed antidepressants. Further voluntary modules assessed a wide range of traits of relevance to psychopathology. Participants who reported they were willing to provide a DNA sample (75%) were sent a saliva kit in the mail. Findings to date 95% of participants reported being given a diagnosis of depression by a medical practitioner and 88% met the criteria for a lifetime depressive episode. 68% of the sample report having been diagnosed with another psychiatric disorder in addition to depression. In line with findings from clinical trials, only 33% of the sample report responding well to the first antidepressant they were prescribed. Future plans A number of analyses to investigate the genetic architecture of depression and common comorbidities will be conducted. The cohort will contribute to the global effort to identify genetic variants that increase risk to depression. Furthermore, a thorough investigation of genetic and psychosocial predictors of antidepressant response and side effects is planned. © © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.