On estimating the variance of maximum entropy median for odd sample size
- Bani-Mustafa, Ahmed, Al-Nasser, Amjad D.
- Authors: Bani-Mustafa, Ahmed , Al-Nasser, Amjad D.
- Date: 2008
- Type: Text , Journal article
- Relation: Pakistan Journal of Statistics Vol. 24, no. 1 (2008), p. 1-10
- Full Text: false
- Reviewed:
- Description: The estimation of Maximum Entropy (ME) median variance based on odd samples is discussed. The estimated variance is given in a form that depends on an incomplete beta function. We show that the ME-median is more efficient than the sample median for small samples.
- Description: C1
- Charchar, Fadi, Tomaszewski, Maciej, Barnes, Timothy, Wang, Y., Brouilette, S. W., Codd, Veryan, Bani-Mustafa, Ahmed, Padmanabhan, Sandosh, Dominiczak, Anna, Ford, I., Samani, Nilesh
- Authors: Charchar, Fadi , Tomaszewski, Maciej , Barnes, Timothy , Wang, Y. , Brouilette, S. W. , Codd, Veryan , Bani-Mustafa, Ahmed , Padmanabhan, Sandosh , Dominiczak, Anna , Ford, I. , Samani, Nilesh
- Date: 2009
- Type: Text , Conference paper
- Relation: , p. S448-S448
- Full Text: false
Automatic sleep stage identification: difficulties and possible solutions
- Sukhorukova, Nadezda, Stranieri, Andrew, Ofoghi, Bahadorreza, Vamplew, Peter, Saleem, Muhammad Saad, Ma, Liping, Ugon, Adrien, Ugon, Julien, Muecke, Nial, Amiel, Hélène, Philippe, Carole, Bani-Mustafa, Ahmed, Huda, Shamsul, Bertoli, Marcello, Levy, P, Ganascia, J.G
- Authors: Sukhorukova, Nadezda , Stranieri, Andrew , Ofoghi, Bahadorreza , Vamplew, Peter , Saleem, Muhammad Saad , Ma, Liping , Ugon, Adrien , Ugon, Julien , Muecke, Nial , Amiel, Hélène , Philippe, Carole , Bani-Mustafa, Ahmed , Huda, Shamsul , Bertoli, Marcello , Levy, P , Ganascia, J.G
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: The diagnosis of many sleep disorders is a labour intensive task that involves the specialised interpretation of numerous signals including brain wave, breath and heart rate captured in overnight polysomnogram sessions. The automation of diagnoses is challenging for data mining algorithms because the data sets are extremely large and noisy, the signals are complex and specialist's analyses vary. This work reports on the adaptation of approaches from four fields; neural networks, mathematical optimisation, financial forecasting and frequency domain analysis to the problem of automatically determing a patient's stage of sleep. Results, though preliminary, are promising and indicate that combined approaches may prove more fruitful than the reliance on a approach.
- Authors: Sukhorukova, Nadezda , Stranieri, Andrew , Ofoghi, Bahadorreza , Vamplew, Peter , Saleem, Muhammad Saad , Ma, Liping , Ugon, Adrien , Ugon, Julien , Muecke, Nial , Amiel, Hélène , Philippe, Carole , Bani-Mustafa, Ahmed , Huda, Shamsul , Bertoli, Marcello , Levy, P , Ganascia, J.G
- Date: 2010
- Type: Text , Conference proceedings
- Full Text:
- Description: The diagnosis of many sleep disorders is a labour intensive task that involves the specialised interpretation of numerous signals including brain wave, breath and heart rate captured in overnight polysomnogram sessions. The automation of diagnoses is challenging for data mining algorithms because the data sets are extremely large and noisy, the signals are complex and specialist's analyses vary. This work reports on the adaptation of approaches from four fields; neural networks, mathematical optimisation, financial forecasting and frequency domain analysis to the problem of automatically determing a patient's stage of sleep. Results, though preliminary, are promising and indicate that combined approaches may prove more fruitful than the reliance on a approach.
Sport-specific factors predicting player retention in junior cricket
- Talpey, Scott, Croucher, Tom, Bani-Mustafa, Ahmed, Finch, Caroline
- Authors: Talpey, Scott , Croucher, Tom , Bani-Mustafa, Ahmed , Finch, Caroline
- Date: 2017
- Type: Text , Journal article
- Relation: European Journal of Sport Science Vol. 17, no. 3 (2017), p. 264-270
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Relation: http://purl.org/au-research/grants/nhmrc/1058737
- Full Text: false
- Reviewed:
- Description: Understanding factors that motivate young athletes to continue participation in sport can help key stakeholders cultivate an environment that fosters long-term participation. This investigation sought to determine the performance and participation factors that influenced continued participation in junior cricket. Administration-level data were collected each annual season across a seven-year period by a community-level junior cricket association in Australia and analysed to identify the performance and participation-based predictors of player retention. All players were males aged <16 years. Players were categorised according to whether they remained in (or departed from) the association at the end of each playing season. A multivariate logistic regression model with a stepwise variable selection was employed to identify significant independent predictors of player retention. The number of innings batted and overs bowled were significant participation-related contributors to junior cricket player retention. Performance factors such as the number of wickets taken and the number of runs scored also significantly influenced player retention. Finally, team age group, the number of previous seasons played and age were also significant factors in player retention. This demonstrates that sufficient opportunity for children to participate in the game and expression of skills competence are key factors for retention in cricket.
- Description: Understanding factors that motivate young athletes to continue participation in sport can help key stakeholders cultivate an environment that fosters long-term participation. This investigation sought to determine the performance and participation factors that influenced continued participation in junior cricket. Administration-level data were collected each annual season across a seven-year period by a community-level junior cricket association in Australia and analysed to identify the performance and participation-based predictors of player retention. All players were males aged <16 years. Players were categorised according to whether they remained in (or departed from) the association at the end of each playing season. A multivariate logistic regression model with a stepwise variable selection was employed to identify significant independent predictors of player retention. The number of innings batted and overs bowled were significant participation-related contributors to junior cricket player retention. Performance factors such as the number of wickets taken and the number of runs scored also significantly influenced player retention. Finally, team age group, the number of previous seasons played and age were also significant factors in player retention. This demonstrates that sufficient opportunity for children to participate in the game and expression of skills competence are key factors for retention in cricket. © 2016 European College of Sport Science.
Marginal longitudinal curves estimated via Bayesian penalized splines
- Al Kadiri, Mohammad, Bani-Mustafa, Ahmed, Finch, Caroline
- Authors: Al Kadiri, Mohammad , Bani-Mustafa, Ahmed , Finch, Caroline
- Date: 2010
- Type: Text , Conference paper
- Relation: Australian Statistical Conference 2010 , 6th December, 2010 Fremantle Published in Statistics & Probability Letters Vol. 80 Issue 15-16 Vol. 80, p. 1-19
- Full Text: false
- Reviewed:
- Description: The six cities air pollution is used to estimate and investigate the marginal curve of a function describing lung growth for set of children in a longitudinal study. This article proposes penalized regression spline technqiue based ona semiparametric mixed models (MM) framework for an additive model. This smoothing approach fits marginal models for longitudinal unbalanced measurements by using a Bayesian inference approach, implemented using a Markov chain Monte Carlo approach with the Gibbs sampler. The unbalanced case in which missing or different number of measurements for a set of subjects is more practical and common in real life studies. This methodology makes it possible to establish a straightforward approach to similar models using R programming, when it is not possible to do so using existing codes.
Robust extreme ranked set sampling
- Al-Nasser, Amjad D., Bani-Mustafa, Ahmed
- Authors: Al-Nasser, Amjad D. , Bani-Mustafa, Ahmed
- Date: 2009
- Type: Text , Journal article
- Relation: Journal of Statistical Computation & Simulation Vol. 79, no. 7 (2009), p. 859-867
- Full Text: false
- Reviewed:
- Description: In this paper, a robust extreme ranked set sampling (RERSS) procedure for estimating the population mean is introduced. It is shown that the proposed method gives an unbiased estimator with smaller variance, provided the underlying distribution is symmetric. However, for asymmetric distributions a weighted mean is given, where the optimal weights are computed by using Shannon's entropy. The performance of the population mean estimator is discussed along with its properties. Monte Carlo simulations are used to demonstrate the performance of the RERSS estimator relative to the simple random sample (SRS), ranked set sampling (RSS) and extreme ranked set sampling (ERSS) estimators. The results indicate that the proposed estimator is more efficient than the estimators based on the traditional sampling methods. [ABSTRACT FROM AUTHOR]
Soil moisture, organic carbon, and nitrogen content prediction with hyperspectral data using regression models
- Datta, Dristi, Paul, Manoranjan, Murshed, Manzur, Teng, Shyh Wei, Schmidtke, Leigh
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
- Full Text:
- Reviewed:
- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
- Full Text:
- Reviewed:
- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
Inheritance of coronary artery disease in men : An analysis of the role of the y chromosome
- Charchar, Fadi, Bloomer, Lisa, Barnes, Timothy, Cowley, Mark, Nelson, Christopher, Wang, Yanzhong, Denniff, Matthew, Debiec, Radoslaw, Christofidou, Paraskevi, Nankervis, Scott, Dominiczak, Anna, Bani-Mustafa, Ahmed, Balmforth, Anthony, Hall, Alistair, Erdmann, Jeanette, Cambien, Francois, Deloukas, Panos, Hengstenberg, Christian, Packard, Chris, Schunkert, Heribert, Ouwehand, Willem, Ford, Ian, Goodall, Alison, Jobling, Mark, Samani, Nilesh, Tomaszewski, Maciej
- Authors: Charchar, Fadi , Bloomer, Lisa , Barnes, Timothy , Cowley, Mark , Nelson, Christopher , Wang, Yanzhong , Denniff, Matthew , Debiec, Radoslaw , Christofidou, Paraskevi , Nankervis, Scott , Dominiczak, Anna , Bani-Mustafa, Ahmed , Balmforth, Anthony , Hall, Alistair , Erdmann, Jeanette , Cambien, Francois , Deloukas, Panos , Hengstenberg, Christian , Packard, Chris , Schunkert, Heribert , Ouwehand, Willem , Ford, Ian , Goodall, Alison , Jobling, Mark , Samani, Nilesh , Tomaszewski, Maciej
- Date: 2012
- Type: Text , Journal article
- Relation: The Lancet Vol. 379, no. 9819 (2012), p. 915-922
- Relation: http://purl.org/au-research/grants/nhmrc/1009490
- Full Text: false
- Reviewed:
- Description: Background: A sexual dimorphism exists in the incidence and prevalence of coronary artery disease - men are more commonly affected than are age-matched women. We explored the role of the Y chromosome in coronary artery disease in the context of this sexual inequity. Methods: We genotyped 11 markers of the male-specific region of the Y chromosome in 3233 biologically unrelated British men from three cohorts: the British Heart Foundation Family Heart Study (BHF-FHS), West of Scotland Coronary Prevention Study (WOSCOPS), and Cardiogenics Study. On the basis of this information, each Y chromosome was tracked back into one of 13 ancient lineages defined as haplogroups. We then examined associations between common Y chromosome haplogroups and the risk of coronary artery disease in cross-sectional BHF-FHS and prospective WOSCOPS. Finally, we undertook functional analysis of Y chromosome effects on monocyte and macrophage transcriptome in British men from the Cardiogenics Study. Findings: Of nine haplogroups identified, two (R1b1b2 and I) accounted for roughly 90 of the Y chromosome variants among British men. Carriers of haplogroup I had about a 50 higher age-adjusted risk of coronary artery disease than did men with other Y chromosome lineages in BHF-FHS (odds ratio 1·75, 95 CI 1·20-2·54, p=0·004), WOSCOPS (1·45, 1·08-1·95, p=0·012), and joint analysis of both populations (1·56, 1·24-1·97, p=0·0002). The association between haplogroup I and increased risk of coronary artery disease was independent of traditional cardiovascular and socioeconomic risk factors. Analysis of macrophage transcriptome in the Cardiogenics Study revealed that 19 molecular pathways showing strong differential expression between men with haplogroup I and other lineages of the Y chromosome were interconnected by common genes related to inflammation and immunity, and that some of them have a strong relevance to atherosclerosis. Interpretation: The human Y chromosome is associated with risk of coronary artery disease in men of European ancestry, possibly through interactions of immunity and inflammation. Funding: British Heart Foundation; UK National Institute for Health Research; LEW Carty Charitable Fund; National Health and Medical Research Council of Australia; European Union 6th Framework Programme; Wellcome Trust. © 2012 Elsevier Ltd.
- Cook, Kay, Albury, Kath, Savic, Milovan, Zirakbash, Farnaz, Al Mahmud, Abdullah, Ahmed, Ashir, Martin, Jennifer, Fordyce, Robbie, Mackelprang, Jessica, Bano, Muneera, Schneider, Jean-Guy
- Authors: Cook, Kay , Albury, Kath , Savic, Milovan , Zirakbash, Farnaz , Al Mahmud, Abdullah , Ahmed, Ashir , Martin, Jennifer , Fordyce, Robbie , Mackelprang, Jessica , Bano, Muneera , Schneider, Jean-Guy
- Date: 2019
- Type: Text , Technical report , Report
- Full Text: false
A novel generalized concept for three phase cascaded multilevel inverter topologies
- Hasan,Md Mubashwar, Abu-Siada, Ahmed, Islam, Syed, Muyeen, S
- Authors: Hasan,Md Mubashwar , Abu-Siada, Ahmed , Islam, Syed , Muyeen, S
- Date: 2017
- Type: Text , Conference proceedings
- Relation: 9th Annual IEEE Green Technologies Conference (GreenTech 2017); Denver, CO; 29th-21st March, 2017 p. 110-117
- Full Text: false
- Reviewed:
- Description: Many new cascaded multilevel inverter (MLI) topologies have recently been proposed and published in the literature. All proposed topologies demand significant amount of semiconductor components and input dc supplies, which is considered the main drawback for the implementation of three phase cascaded MLIs. This paper proposes a new generalized concept that could be employed within any existing cascaded MLI topology in order to reduce its size in terms of device count including semiconductor switches, diodes, and dc power supplies. The new generalized concept involves two stages namely, cascaded stage (CS) and phase generator stage (PGS). The PGS stage is a combination of conventional three phase two level inverter (CTPTLI) and three bidirectional (BD) switches, while the cascaded stage can be modified using any existing cascaded topology. The proposed concept is validated through extensive simulation and experimental analyses. Results show the capability of the proposed technique in reducing device count of the existing topologies while maintaining its performance.
Comparative analysis of machine and deep learning models for soil properties prediction from hyperspectral visual band
- Datta, Dristi, Paul, Manoranjan, Murshed, Manzur, Teng, Shyh Wei, Schmidtke, Leigh
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
- Full Text:
- Reviewed:
- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2023
- Type: Text , Journal article
- Relation: Environments Vol. 10, no. 5 (2023), p. 77
- Full Text:
- Reviewed:
- Description: Estimating various properties of soil, including moisture, carbon, and nitrogen, is crucial for studying their correlation with plant health and food production. However, conventional methods such as oven-drying and chemical analysis are laborious, expensive, and only feasible for a limited land area. With the advent of remote sensing technologies like multi/hyperspectral imaging, it is now possible to predict soil properties non-invasive and cost-effectively for a large expanse of bare land. Recent research shows the possibility of predicting those soil contents from a wide range of hyperspectral data using good prediction algorithms. However, these kinds of hyperspectral sensors are expensive and not widely available. Therefore, this paper investigates different machine and deep learning techniques to predict soil nutrient properties using only the red (R), green (G), and blue (B) bands data to propose a suitable machine/deep learning model that can be used as a rapid soil test. Another objective of this research is to observe and compare the prediction accuracy in three cases i. hyperspectral band ii. full spectrum of the visual band, and iii. three-channel of RGB band and provide a guideline to the user on which spectrum information they should use to predict those soil properties. The outcome of this research helps to develop a mobile application that is easy to use for a quick soil test. This research also explores learning-based algorithms with significant feature combinations and their performance comparisons in predicting soil properties from visual band data. For this, we also explore the impact of dimensional reduction (i.e., principal component analysis) and transformations (i.e., empirical mode decomposition) of features. The results show that the proposed model can comparably predict the soil contents from the three-channel RGB data.
Factors associated with chronic kidney disease in patients with type 2 diabetes in Bangladesh
- Islam, Sheikh, Salehin, Masudus, Zaman, Sojib, Tansi, Tania, Gupta, Rajat
- Authors: Islam, Sheikh , Salehin, Masudus , Zaman, Sojib , Tansi, Tania , Gupta, Rajat
- Date: 2021
- Type: Text , Journal article
- Relation: International Journal of Environmental Research and Public Health Vol. 18, no. 23 (2021), p.
- Full Text:
- Reviewed:
- Description: Diabetes and chronic kidney disease (CKD) are a major public health burden in low- and middle-income countries. This study aimed to explore factors associated with CKD in patients with type 2 diabetes (T2D) in Bangladesh. A cross-sectional study was conducted among 315 adults with T2D presenting at the outpatient department of Bangladesh Institute of Health Sciences (BIHS) hospital between July 2013 to December 2013. CKD was diagnosed based on the estimated glomerular filtration rate using the ‘Modification of Diet in Renal Disease’ equations and the presence of albu-minuria estimated by the albumin-to-creatinine ratio. Multivariate logistic regression analysis was used to determine the factors associated with CKD. The overall prevalence of CKD among patients with T2D was 21.3%. In the unadjusted model, factors associated with CKD included age 40–49 years (OR: 5.7, 95% CI: 1.3–25.4), age 50–59 years (7.0, 1.6–39), age ≥60 years (7.6, 1.7–34), being female (2.2, 1.2–3.8), being hypertensive (1.9, 1.1–3.5), and household income between 10,001 and 20,000 Bangladeshi taka, BDT (2.9, 1.0–8.2) compared with income ≤10,000 BDT. However, after ad-justment of other covariates, only the duration of hypertension and household income (10,001– 20,000 BDT) remained statistically significant. There is a need to implement policies and programs for early detection and management of hypertension and CKD in T2D patients in Bangladesh. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Masudus Salehin” is provided in this record**
- Authors: Islam, Sheikh , Salehin, Masudus , Zaman, Sojib , Tansi, Tania , Gupta, Rajat
- Date: 2021
- Type: Text , Journal article
- Relation: International Journal of Environmental Research and Public Health Vol. 18, no. 23 (2021), p.
- Full Text:
- Reviewed:
- Description: Diabetes and chronic kidney disease (CKD) are a major public health burden in low- and middle-income countries. This study aimed to explore factors associated with CKD in patients with type 2 diabetes (T2D) in Bangladesh. A cross-sectional study was conducted among 315 adults with T2D presenting at the outpatient department of Bangladesh Institute of Health Sciences (BIHS) hospital between July 2013 to December 2013. CKD was diagnosed based on the estimated glomerular filtration rate using the ‘Modification of Diet in Renal Disease’ equations and the presence of albu-minuria estimated by the albumin-to-creatinine ratio. Multivariate logistic regression analysis was used to determine the factors associated with CKD. The overall prevalence of CKD among patients with T2D was 21.3%. In the unadjusted model, factors associated with CKD included age 40–49 years (OR: 5.7, 95% CI: 1.3–25.4), age 50–59 years (7.0, 1.6–39), age ≥60 years (7.6, 1.7–34), being female (2.2, 1.2–3.8), being hypertensive (1.9, 1.1–3.5), and household income between 10,001 and 20,000 Bangladeshi taka, BDT (2.9, 1.0–8.2) compared with income ≤10,000 BDT. However, after ad-justment of other covariates, only the duration of hypertension and household income (10,001– 20,000 BDT) remained statistically significant. There is a need to implement policies and programs for early detection and management of hypertension and CKD in T2D patients in Bangladesh. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Masudus Salehin” is provided in this record**
Missing health data pattern matching technique for continuous remote patient monitoring
- Arora, Teena, Balasubramanian, Venki, Stranieri, Andrew
- Authors: Arora, Teena , Balasubramanian, Venki , Stranieri, Andrew
- Date: 2023
- Type: Text , Conference paper
- Relation: 20th International Conference on Smart Living and Public Health, ICOST 2023, Wonju, Korea, 7-8 July 2023, Digital Health Transformation, Smart Ageing, and Managing Disability, 20th International Conference, ICOST 2023, Wonju, South Korea, July 7–8, 2023, Proceedings Vol. 14237 LNCS, p. 130-143
- Full Text:
- Reviewed:
- Description: Remote patient monitoring (RPM) has been gaining popularity recently. However, health data acquisition is a significant challenge associated with patient monitoring. In continuous RPM, health data acquisition may miss health data during transmission. Missing data compromises the quality and reliability of patient risk assessment. Several studies suggested techniques for analyzing missing data; however, many are unsuitable for RPM. These techniques neglect the variability of missing data and provide biased results with imputation. Therefore, a holistic approach must consider the correlation and variability of the various vitals and avoid biased imputation. This paper proposes a coherent computation pattern-matching technique to identify and predict missing data patterns. The performance of the proposed approach is evaluated using data collected from a field trial. Results show that the technique can effectively identify and predict missing patterns. © 2023, The Author(s).
- Authors: Arora, Teena , Balasubramanian, Venki , Stranieri, Andrew
- Date: 2023
- Type: Text , Conference paper
- Relation: 20th International Conference on Smart Living and Public Health, ICOST 2023, Wonju, Korea, 7-8 July 2023, Digital Health Transformation, Smart Ageing, and Managing Disability, 20th International Conference, ICOST 2023, Wonju, South Korea, July 7–8, 2023, Proceedings Vol. 14237 LNCS, p. 130-143
- Full Text:
- Reviewed:
- Description: Remote patient monitoring (RPM) has been gaining popularity recently. However, health data acquisition is a significant challenge associated with patient monitoring. In continuous RPM, health data acquisition may miss health data during transmission. Missing data compromises the quality and reliability of patient risk assessment. Several studies suggested techniques for analyzing missing data; however, many are unsuitable for RPM. These techniques neglect the variability of missing data and provide biased results with imputation. Therefore, a holistic approach must consider the correlation and variability of the various vitals and avoid biased imputation. This paper proposes a coherent computation pattern-matching technique to identify and predict missing data patterns. The performance of the proposed approach is evaluated using data collected from a field trial. Results show that the technique can effectively identify and predict missing patterns. © 2023, The Author(s).
- Barton, Andrew, Mala-Jetmarova, Helena, Nuamat, Alia Mari Al, Bagirov, Adil, Sultanova, Nargiz, Ahmed, Shams
- Authors: Barton, Andrew , Mala-Jetmarova, Helena , Nuamat, Alia Mari Al , Bagirov, Adil , Sultanova, Nargiz , Ahmed, Shams
- Date: 2012
- Type: Text , Conference paper
- Relation: 34th Hydrology and Water Resources Symposium, HWRS 2012; Sydney, Australia; 19th-22nd November 2012; p. 1298-1305
- Relation: http://purl.org/au-research/grants/arc/LP0990908
- Full Text: false
- Reviewed:
- Description: The operation of a water distribution system is a complex task which involves scheduling of pumps, regulating water levels of storages, and providing satisfactory water quality to customers at required flow and pressure. Pump scheduling is one of the most important tasks of the operation of a water distribution system as it represents the major part of its operating costs. In this paper, a novel approach for modeling of pump scheduling to minimize energy consumption by pumps is introduced which uses pump's start/end run times. We separate two types of pumps, one is operated based on the water level in a storage and another one is operated based on downstream pressure. For the first type of pumps both the explicit and implicit pump scheduling can be used, whereas the second type pumps can be optimized only using implicit pump scheduling. The problem is formulated as an optimization problem and an algorithm is developed for its solution. The performance of the algorithm is evaluated using a literature test problem applying the hydraulic simulation model EPANet.
- Authors: Mestrom, Sanne
- Date: 2012
- Type: Text , Visual art work
- Full Text:
Tumour microenvironment and metabolic plasticity in cancer and cancer stem cells : Perspectives on metabolic and immune regulatory signatures in chemoresistant ovarian cancer stem cells
- Ahmed, Nuzhat, Escalona, Ruth, Leung, Dilys, Chan, Emily, Kannourakis, George
- Authors: Ahmed, Nuzhat , Escalona, Ruth , Leung, Dilys , Chan, Emily , Kannourakis, George
- Date: 2018
- Type: Text , Journal article , Review
- Relation: Seminars in Cancer Biology Vol. 53, no. (2018), p. 265-281
- Full Text:
- Reviewed:
- Description: Cancer stem cells (CSCs) are a sub-population of tumour cells, which are responsible to drive tumour growth, metastasis and therapy resistance. It has recently been proposed that enhanced glucose metabolism and immune evasion by tumour cells are linked, and are modulated by the changing tumour microenvironment (TME) that creates a competition for nutrient consumption between tumour and different sub-types of cells attracted to the TME. To facilitate efficient nutrient distribution, oncogene-induced inflammatory milieu in the tumours facilitate adaptive metabolic changes in the surrounding non-malignant cells to secrete metabolites that are used as alternative nutrient sources by the tumours to sustain its increasing energy needs for growth and anabolic functions. This scenario also affects CSCs residing at the primary or metastatic niches. This review summarises recent advances in our understanding of the metabolic phenotypes of cancer cells and CSCs and how these processes are affected by the TME. We also discuss how the evolving TME modulates tumour cells and CSCs in cancer progression. Using previously described proteomic and genomic platforms, ovarian cancer cell lines and a mouse xenograft model we highlight the existence of metabolic and immune regulatory signatures in chemoresistant ovarian CSCs, and discuss how these processes may affect recurrence in ovarian tumours. We propose that progress in cancer control and eradication may depend not only on the elimination of highly chemoresistant CSCs, but also in designing novel strategies which would intervene with the tumour-promoting TME factors.
- Authors: Ahmed, Nuzhat , Escalona, Ruth , Leung, Dilys , Chan, Emily , Kannourakis, George
- Date: 2018
- Type: Text , Journal article , Review
- Relation: Seminars in Cancer Biology Vol. 53, no. (2018), p. 265-281
- Full Text:
- Reviewed:
- Description: Cancer stem cells (CSCs) are a sub-population of tumour cells, which are responsible to drive tumour growth, metastasis and therapy resistance. It has recently been proposed that enhanced glucose metabolism and immune evasion by tumour cells are linked, and are modulated by the changing tumour microenvironment (TME) that creates a competition for nutrient consumption between tumour and different sub-types of cells attracted to the TME. To facilitate efficient nutrient distribution, oncogene-induced inflammatory milieu in the tumours facilitate adaptive metabolic changes in the surrounding non-malignant cells to secrete metabolites that are used as alternative nutrient sources by the tumours to sustain its increasing energy needs for growth and anabolic functions. This scenario also affects CSCs residing at the primary or metastatic niches. This review summarises recent advances in our understanding of the metabolic phenotypes of cancer cells and CSCs and how these processes are affected by the TME. We also discuss how the evolving TME modulates tumour cells and CSCs in cancer progression. Using previously described proteomic and genomic platforms, ovarian cancer cell lines and a mouse xenograft model we highlight the existence of metabolic and immune regulatory signatures in chemoresistant ovarian CSCs, and discuss how these processes may affect recurrence in ovarian tumours. We propose that progress in cancer control and eradication may depend not only on the elimination of highly chemoresistant CSCs, but also in designing novel strategies which would intervene with the tumour-promoting TME factors.
Coalition of Oct4A and β1 integrins in facilitating metastasis in ovarian cancer
- Samardzija, Chantel, Luwor, Rodney, Quinn, Michael, Kannourakis, George, Findlay, Jock, Ahmed, Nuzhat
- Authors: Samardzija, Chantel , Luwor, Rodney , Quinn, Michael , Kannourakis, George , Findlay, Jock , Ahmed, Nuzhat
- Date: 2016
- Type: Text , Journal article
- Relation: BMC Cancer Vol. 16, no. 1 (2016), p. 1-16
- Full Text:
- Reviewed:
- Description: Background: Ovarian cancer is a metastatic disease and one of the leading causes of gynaecology malignancy-related deaths in women. Cancer stem cells (CSCs) are key contributors of cancer metastasis and relapse. Integrins are a family of cell surface receptors which allow interactions between cells and their surrounding microenvironment and play a fundamental role in promoting metastasis. This study investigates the molecular mechanism which associates CSCs and integrins in ovarian cancer metastasis. Methods: The expression of Oct4A in high-grade serous ovarian tumors and normal ovaries was determined by immunofluorescence analysis. The functional role of Oct4A was evaluated by generating stable knockdown (KD) of Oct4A clones in an established ovarian cancer cell line HEY using shRNA-mediated silencing. The expression of integrins in cell lines was evaluated by flow cytometry. Spheroid forming ability, adhesion and the activities of matrix metalloproteinases 9/2 (MMP-9/2) was measured by in vitro functional assays and gelatin zymography. These observations were further validated in in vivo mouse models using Balb/c nu/nu mice. Results: We report significantly elevated expression of Oct4A in high-grade serous ovarian tumors compared to normal ovarian tissues. The expression of Oct4A in ovarian cancer cell lines correlated with their CSC-related sphere forming abilities. The suppression of Oct4A in HEY cells resulted in a significant diminution of integrin β1 expression and associated α5 and α2 subunits compared to vector control cells. This was associated with a reduced adhesive ability on collagen and fibronectin and decreased secretion of pro-MMP2 in Oct4A KD cells compared to vector control cells. In vivo, Oct4A knock down (KD) cells produced tumors which were significantly smaller in size and weight compared to tumors derived from vector control cells. Immunohistochemical analyses of Oct4A KD tumor xenografts demonstrated a significant loss of cytokeratin 7 (CK7), Glut-1 as well as CD34 and CD31 compared to vector control cell-derived xenografts. Conclusion: The expression of Oct4A may be crucial to promote and sustain integrin-mediated extracellular matrix (ECM) remodeling requisite for tumor metastasis in ovarian cancer patients. © 2016 The Author(s).
- Authors: Samardzija, Chantel , Luwor, Rodney , Quinn, Michael , Kannourakis, George , Findlay, Jock , Ahmed, Nuzhat
- Date: 2016
- Type: Text , Journal article
- Relation: BMC Cancer Vol. 16, no. 1 (2016), p. 1-16
- Full Text:
- Reviewed:
- Description: Background: Ovarian cancer is a metastatic disease and one of the leading causes of gynaecology malignancy-related deaths in women. Cancer stem cells (CSCs) are key contributors of cancer metastasis and relapse. Integrins are a family of cell surface receptors which allow interactions between cells and their surrounding microenvironment and play a fundamental role in promoting metastasis. This study investigates the molecular mechanism which associates CSCs and integrins in ovarian cancer metastasis. Methods: The expression of Oct4A in high-grade serous ovarian tumors and normal ovaries was determined by immunofluorescence analysis. The functional role of Oct4A was evaluated by generating stable knockdown (KD) of Oct4A clones in an established ovarian cancer cell line HEY using shRNA-mediated silencing. The expression of integrins in cell lines was evaluated by flow cytometry. Spheroid forming ability, adhesion and the activities of matrix metalloproteinases 9/2 (MMP-9/2) was measured by in vitro functional assays and gelatin zymography. These observations were further validated in in vivo mouse models using Balb/c nu/nu mice. Results: We report significantly elevated expression of Oct4A in high-grade serous ovarian tumors compared to normal ovarian tissues. The expression of Oct4A in ovarian cancer cell lines correlated with their CSC-related sphere forming abilities. The suppression of Oct4A in HEY cells resulted in a significant diminution of integrin β1 expression and associated α5 and α2 subunits compared to vector control cells. This was associated with a reduced adhesive ability on collagen and fibronectin and decreased secretion of pro-MMP2 in Oct4A KD cells compared to vector control cells. In vivo, Oct4A knock down (KD) cells produced tumors which were significantly smaller in size and weight compared to tumors derived from vector control cells. Immunohistochemical analyses of Oct4A KD tumor xenografts demonstrated a significant loss of cytokeratin 7 (CK7), Glut-1 as well as CD34 and CD31 compared to vector control cell-derived xenografts. Conclusion: The expression of Oct4A may be crucial to promote and sustain integrin-mediated extracellular matrix (ECM) remodeling requisite for tumor metastasis in ovarian cancer patients. © 2016 The Author(s).
COVID-19 : factors associated with the psychological distress, fear and resilient coping strategies among community members in Saudi Arabia
- Alharbi, Talal, Alqurashi, Alaa, Mahmud, Ilias, Alharbi, Rayan, Islam, Sheikh, Almustanyir, Sami, Maklad, Ahmed, AlSarraj, Ahmad, Mughaiss, Lujain, Al-Tawfiq, Jaffar, Ahmed, Ahmed, Barry, Mazin, Ghozy, Sherief, Alabdan, Lulwah, Alif, Sheikh, Sultana, Farhana, Salehin, Masudus, Banik, Biswajit, Cross, Wendy, Rahman, Muhammad Aziz
- Authors: Alharbi, Talal , Alqurashi, Alaa , Mahmud, Ilias , Alharbi, Rayan , Islam, Sheikh , Almustanyir, Sami , Maklad, Ahmed , AlSarraj, Ahmad , Mughaiss, Lujain , Al-Tawfiq, Jaffar , Ahmed, Ahmed , Barry, Mazin , Ghozy, Sherief , Alabdan, Lulwah , Alif, Sheikh , Sultana, Farhana , Salehin, Masudus , Banik, Biswajit , Cross, Wendy , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Healthcare (Switzerland) Vol. 11, no. 8 (2023), p.
- Full Text:
- Reviewed:
- Description: (1) Background: COVID-19 caused the worst international public health crisis, accompanied by major global economic downturns and mass-scale job losses, which impacted the psychosocial wellbeing of the worldwide population, including Saudi Arabia. Evidence of the high-risk groups impacted by the pandemic has been non-existent in Saudi Arabia. Therefore, this study examined factors associated with psychosocial distress, fear of COVID-19 and coping strategies among the general population in Saudi Arabia. (2) Methods: A cross-sectional study was conducted in healthcare and community settings in the Saudi Arabia using an anonymous online questionnaire. The Kessler Psychological Distress Scale (K-10), Fear of COVID-19 Scale (FCV-19S) and Brief Resilient Coping Scale (BRCS) were used to assess psychological distress, fear and coping strategies, respectively. Multivariate logistic regressions were used, and an Adjusted Odds Ratio (AOR) with 95% Confidence Intervals (CIs) was reported. (3) Results: Among 803 participants, 70% (n = 556) were females, and the median age was 27 years; 35% (n = 278) were frontline or essential service workers; and 24% (n = 195) reported comorbid conditions including mental health illness. Of the respondents, 175 (21.8%) and 207 (25.8%) reported high and very high psychological distress, respectively. Factors associated with moderate to high levels of psychological distress were: youth, females, non-Saudi nationals, those experiencing a change in employment or a negative financial impact, having comorbidities, and current smoking. A high level of fear was reported by 89 participants (11.1%), and this was associated with being ex-smokers (3.72, 1.14–12.14, 0.029) and changes in employment (3.42, 1.91–6.11, 0.000). A high resilience was reported by 115 participants (14.3%), and 333 participants (41.5%) had medium resilience. Financial impact and contact with known/suspected cases (1.63, 1.12–2.38, 0.011) were associated with low, medium, to high resilient coping. (4) Conclusions: People in Saudi Arabia were at a higher risk of psychosocial distress along with medium-high resilience during the COVID-19 pandemic, warranting urgent attention from healthcare providers and policymakers to provide specific mental health support strategies for their current wellbeing and to avoid a post-pandemic mental health crisis. © 2023 by the authors.
- Authors: Alharbi, Talal , Alqurashi, Alaa , Mahmud, Ilias , Alharbi, Rayan , Islam, Sheikh , Almustanyir, Sami , Maklad, Ahmed , AlSarraj, Ahmad , Mughaiss, Lujain , Al-Tawfiq, Jaffar , Ahmed, Ahmed , Barry, Mazin , Ghozy, Sherief , Alabdan, Lulwah , Alif, Sheikh , Sultana, Farhana , Salehin, Masudus , Banik, Biswajit , Cross, Wendy , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Healthcare (Switzerland) Vol. 11, no. 8 (2023), p.
- Full Text:
- Reviewed:
- Description: (1) Background: COVID-19 caused the worst international public health crisis, accompanied by major global economic downturns and mass-scale job losses, which impacted the psychosocial wellbeing of the worldwide population, including Saudi Arabia. Evidence of the high-risk groups impacted by the pandemic has been non-existent in Saudi Arabia. Therefore, this study examined factors associated with psychosocial distress, fear of COVID-19 and coping strategies among the general population in Saudi Arabia. (2) Methods: A cross-sectional study was conducted in healthcare and community settings in the Saudi Arabia using an anonymous online questionnaire. The Kessler Psychological Distress Scale (K-10), Fear of COVID-19 Scale (FCV-19S) and Brief Resilient Coping Scale (BRCS) were used to assess psychological distress, fear and coping strategies, respectively. Multivariate logistic regressions were used, and an Adjusted Odds Ratio (AOR) with 95% Confidence Intervals (CIs) was reported. (3) Results: Among 803 participants, 70% (n = 556) were females, and the median age was 27 years; 35% (n = 278) were frontline or essential service workers; and 24% (n = 195) reported comorbid conditions including mental health illness. Of the respondents, 175 (21.8%) and 207 (25.8%) reported high and very high psychological distress, respectively. Factors associated with moderate to high levels of psychological distress were: youth, females, non-Saudi nationals, those experiencing a change in employment or a negative financial impact, having comorbidities, and current smoking. A high level of fear was reported by 89 participants (11.1%), and this was associated with being ex-smokers (3.72, 1.14–12.14, 0.029) and changes in employment (3.42, 1.91–6.11, 0.000). A high resilience was reported by 115 participants (14.3%), and 333 participants (41.5%) had medium resilience. Financial impact and contact with known/suspected cases (1.63, 1.12–2.38, 0.011) were associated with low, medium, to high resilient coping. (4) Conclusions: People in Saudi Arabia were at a higher risk of psychosocial distress along with medium-high resilience during the COVID-19 pandemic, warranting urgent attention from healthcare providers and policymakers to provide specific mental health support strategies for their current wellbeing and to avoid a post-pandemic mental health crisis. © 2023 by the authors.
Age–sex differences in the global burden of lower respiratory infections and risk factors, 1990–2019 : results from the Global Burden of Disease Study 2019
- Kyu, Hmwe, Vongpradith, Avina, Sirota, Sarah, Novotney, Amanda, Troeger, Christopher, Doxey, Matthew, Bender, Rose, Ledesma, Jorge, Biehl, Molly, Albertson, Samuel, Frostad, Joseph, Burkart, Katrin, Bennitt, Fiona, Zhao, Jeff, Gardner, William, Hagins, Hailey, Bryazka, Dana, Dominguez, Regina, Abate, Semagn, Abdelmasseh, Michael, Abdoli, Amir, Abdoli, Gholamreza, Abedi, Aidin, Abedi, Vida, Abegaz, Tadesse, Abidi, Hassan, Aboagye, Richard, Nguyen, Huy, Rahman, Muhammad Aziz
- Authors: Kyu, Hmwe , Vongpradith, Avina , Sirota, Sarah , Novotney, Amanda , Troeger, Christopher , Doxey, Matthew , Bender, Rose , Ledesma, Jorge , Biehl, Molly , Albertson, Samuel , Frostad, Joseph , Burkart, Katrin , Bennitt, Fiona , Zhao, Jeff , Gardner, William , Hagins, Hailey , Bryazka, Dana , Dominguez, Regina , Abate, Semagn , Abdelmasseh, Michael , Abdoli, Amir , Abdoli, Gholamreza , Abedi, Aidin , Abedi, Vida , Abegaz, Tadesse , Abidi, Hassan , Aboagye, Richard , Nguyen, Huy , Rahman, Muhammad Aziz
- Date: 2022
- Type: Text , Journal article
- Relation: The Lancet Infectious Diseases Vol. 22, no. 11 (2022), p. 1626-1647
- Full Text:
- Reviewed:
- Description: Background: The global burden of lower respiratory infections (LRIs) and corresponding risk factors in children older than 5 years and adults has not been studied as comprehensively as it has been in children younger than 5 years. We assessed the burden and trends of LRIs and risk factors across all age groups by sex, for 204 countries and territories. Methods: In this analysis of data for the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we used clinician-diagnosed pneumonia or bronchiolitis as our case definition for LRIs. We included International Classification of Diseases 9th edition codes 079.6, 466–469, 470.0, 480–482.8, 483.0–483.9, 484.1–484.2, 484.6–484.7, and 487–489 and International Classification of Diseases 10th edition codes A48.1, A70, B97.4–B97.6, J09–J15.8, J16–J16.9, J20–J21.9, J91.0, P23.0–P23.4, and U04–U04.9. We used the Cause of Death Ensemble modelling strategy to analyse 23 109 site-years of vital registration data, 825 site-years of sample vital registration data, 1766 site-years of verbal autopsy data, and 681 site-years of mortality surveillance data. We used DisMod-MR 2.1, a Bayesian meta-regression tool, to analyse age–sex-specific incidence and prevalence data identified via systematic reviews of the literature, population-based survey data, and claims and inpatient data. Additionally, we estimated age–sex-specific LRI mortality that is attributable to the independent effects of 14 risk factors. Findings: Globally, in 2019, we estimated that there were 257 million (95% uncertainty interval [UI] 240–275) LRI incident episodes in males and 232 million (217–248) in females. In the same year, LRIs accounted for 1·30 million (95% UI 1·18–1·42) male deaths and 1·20 million (1·07–1·33) female deaths. Age-standardised incidence and mortality rates were 1·17 times (95% UI 1·16–1·18) and 1·31 times (95% UI 1·23–1·41) greater in males than in females in 2019. Between 1990 and 2019, LRI incidence and mortality rates declined at different rates across age groups and an increase in LRI episodes and deaths was estimated among all adult age groups, with males aged 70 years and older having the highest increase in LRI episodes (126·0% [95% UI 121·4–131·1]) and deaths (100·0% [83·4–115·9]). During the same period, LRI episodes and deaths in children younger than 15 years were estimated to have decreased, and the greatest decline was observed for LRI deaths in males younger than 5 years (–70·7% [–77·2 to –61·8]). The leading risk factors for LRI mortality varied across age groups and sex. More than half of global LRI deaths in children younger than 5 years were attributable to child wasting (population attributable fraction [PAF] 53·0% [95% UI 37·7–61·8] in males and 56·4% [40·7–65·1] in females), and more than a quarter of LRI deaths among those aged 5–14 years were attributable to household air pollution (PAF 26·0% [95% UI 16·6–35·5] for males and PAF 25·8% [16·3–35·4] for females). PAFs of male LRI deaths attributed to smoking were 20·4% (95% UI 15·4–25·2) in those aged 15–49 years, 30·5% (24·1–36·9) in those aged 50–69 years, and 21·9% (16·8–27·3) in those aged 70 years and older. PAFs of female LRI deaths attributed to household air pollution were 21·1% (95% UI 14·5–27·9) in those aged 15–49 years and 18·2% (12·5–24·5) in those aged 50–69 years. For females aged 70 years and older, the leading risk factor, ambient particulate matter, was responsible for 11·7% (95% UI 8·2–15·8) of LRI deaths. Interpretation: The patterns and progress in reducing the burden of LRIs and key risk factors for mortality varied across age groups and sexes. The progress seen in children younger than 5 years was clearly a result of targeted interventions, such as vaccination and reduction of exposure to risk factors. Similar interventions for other age groups could contribute to the achievement of multiple Sustainable Development Goals targets, including promoting well eing at all ages and reducing health inequalities. Interventions, including addressing risk factors such as child wasting, smoking, ambient particulate matter pollution, and household air pollution, would prevent deaths and reduce health disparities. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Muhammad Aziz Rahman and Huy Nguyen” is provided in this record**
- Authors: Kyu, Hmwe , Vongpradith, Avina , Sirota, Sarah , Novotney, Amanda , Troeger, Christopher , Doxey, Matthew , Bender, Rose , Ledesma, Jorge , Biehl, Molly , Albertson, Samuel , Frostad, Joseph , Burkart, Katrin , Bennitt, Fiona , Zhao, Jeff , Gardner, William , Hagins, Hailey , Bryazka, Dana , Dominguez, Regina , Abate, Semagn , Abdelmasseh, Michael , Abdoli, Amir , Abdoli, Gholamreza , Abedi, Aidin , Abedi, Vida , Abegaz, Tadesse , Abidi, Hassan , Aboagye, Richard , Nguyen, Huy , Rahman, Muhammad Aziz
- Date: 2022
- Type: Text , Journal article
- Relation: The Lancet Infectious Diseases Vol. 22, no. 11 (2022), p. 1626-1647
- Full Text:
- Reviewed:
- Description: Background: The global burden of lower respiratory infections (LRIs) and corresponding risk factors in children older than 5 years and adults has not been studied as comprehensively as it has been in children younger than 5 years. We assessed the burden and trends of LRIs and risk factors across all age groups by sex, for 204 countries and territories. Methods: In this analysis of data for the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we used clinician-diagnosed pneumonia or bronchiolitis as our case definition for LRIs. We included International Classification of Diseases 9th edition codes 079.6, 466–469, 470.0, 480–482.8, 483.0–483.9, 484.1–484.2, 484.6–484.7, and 487–489 and International Classification of Diseases 10th edition codes A48.1, A70, B97.4–B97.6, J09–J15.8, J16–J16.9, J20–J21.9, J91.0, P23.0–P23.4, and U04–U04.9. We used the Cause of Death Ensemble modelling strategy to analyse 23 109 site-years of vital registration data, 825 site-years of sample vital registration data, 1766 site-years of verbal autopsy data, and 681 site-years of mortality surveillance data. We used DisMod-MR 2.1, a Bayesian meta-regression tool, to analyse age–sex-specific incidence and prevalence data identified via systematic reviews of the literature, population-based survey data, and claims and inpatient data. Additionally, we estimated age–sex-specific LRI mortality that is attributable to the independent effects of 14 risk factors. Findings: Globally, in 2019, we estimated that there were 257 million (95% uncertainty interval [UI] 240–275) LRI incident episodes in males and 232 million (217–248) in females. In the same year, LRIs accounted for 1·30 million (95% UI 1·18–1·42) male deaths and 1·20 million (1·07–1·33) female deaths. Age-standardised incidence and mortality rates were 1·17 times (95% UI 1·16–1·18) and 1·31 times (95% UI 1·23–1·41) greater in males than in females in 2019. Between 1990 and 2019, LRI incidence and mortality rates declined at different rates across age groups and an increase in LRI episodes and deaths was estimated among all adult age groups, with males aged 70 years and older having the highest increase in LRI episodes (126·0% [95% UI 121·4–131·1]) and deaths (100·0% [83·4–115·9]). During the same period, LRI episodes and deaths in children younger than 15 years were estimated to have decreased, and the greatest decline was observed for LRI deaths in males younger than 5 years (–70·7% [–77·2 to –61·8]). The leading risk factors for LRI mortality varied across age groups and sex. More than half of global LRI deaths in children younger than 5 years were attributable to child wasting (population attributable fraction [PAF] 53·0% [95% UI 37·7–61·8] in males and 56·4% [40·7–65·1] in females), and more than a quarter of LRI deaths among those aged 5–14 years were attributable to household air pollution (PAF 26·0% [95% UI 16·6–35·5] for males and PAF 25·8% [16·3–35·4] for females). PAFs of male LRI deaths attributed to smoking were 20·4% (95% UI 15·4–25·2) in those aged 15–49 years, 30·5% (24·1–36·9) in those aged 50–69 years, and 21·9% (16·8–27·3) in those aged 70 years and older. PAFs of female LRI deaths attributed to household air pollution were 21·1% (95% UI 14·5–27·9) in those aged 15–49 years and 18·2% (12·5–24·5) in those aged 50–69 years. For females aged 70 years and older, the leading risk factor, ambient particulate matter, was responsible for 11·7% (95% UI 8·2–15·8) of LRI deaths. Interpretation: The patterns and progress in reducing the burden of LRIs and key risk factors for mortality varied across age groups and sexes. The progress seen in children younger than 5 years was clearly a result of targeted interventions, such as vaccination and reduction of exposure to risk factors. Similar interventions for other age groups could contribute to the achievement of multiple Sustainable Development Goals targets, including promoting well eing at all ages and reducing health inequalities. Interventions, including addressing risk factors such as child wasting, smoking, ambient particulate matter pollution, and household air pollution, would prevent deaths and reduce health disparities. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Muhammad Aziz Rahman and Huy Nguyen” is provided in this record**
Efficient data gathering in 3D linear underwater wireless sensor networks using sink mobility
- Akbar, Mariam, Javaid, Nadeem, Khan, Ayesha, Imran, Muhammad, Shoaib, Muhammad, Vasilakos, Athanasios
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
- Full Text:
- Reviewed:
- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
- Authors: Akbar, Mariam , Javaid, Nadeem , Khan, Ayesha , Imran, Muhammad , Shoaib, Muhammad , Vasilakos, Athanasios
- Date: 2016
- Type: Text , Journal article
- Relation: Sensors (Switzerland) Vol. 16, no. 3 (2016), p.
- Full Text:
- Reviewed:
- Description: Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. © 2016 by the authors; licensee MDPI, Basel, Switzerland.