ADHD symptoms among adolescents : measurement invariance across mother and adolescent self-ratings
- Gomez, Rapson, Houghton, Stephen
- Authors: Gomez, Rapson , Houghton, Stephen
- Date: 2023
- Type: Text , Journal article
- Relation: Personality and Individual Differences Vol. 213, no. (2023), p.
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- Description: This study employed confirmatory factor analysis (CFA) to examine measurement invariance (configural, metric, and scalar) across mother and adolescent self-ratings of ADHD symptoms [inattention (IA), hyperactivity (HY), and impulsivity (IM)] as presented in the Disruptive Behavior Rating Scale (DBRS; Barkley & Murphy, 1998). The ADHD model used for this analysis was the ICD-10 3-factor model, with factors for IA, HY and IM. Findings supported configural invariance. Of the 18 ADHD symptoms, 4 symptoms (three of which were IA symptoms) lacked metric invariance. Nine thresholds (1 IA symptom, 6 HY symptoms, and 2 IM symptoms) lacked scalar invariance, with six being for the first thresholds. The psychometric and practical implications of the findings are discussed. © 2023 The Authors
- Authors: Gomez, Rapson , Houghton, Stephen
- Date: 2023
- Type: Text , Journal article
- Relation: Personality and Individual Differences Vol. 213, no. (2023), p.
- Full Text:
- Reviewed:
- Description: This study employed confirmatory factor analysis (CFA) to examine measurement invariance (configural, metric, and scalar) across mother and adolescent self-ratings of ADHD symptoms [inattention (IA), hyperactivity (HY), and impulsivity (IM)] as presented in the Disruptive Behavior Rating Scale (DBRS; Barkley & Murphy, 1998). The ADHD model used for this analysis was the ICD-10 3-factor model, with factors for IA, HY and IM. Findings supported configural invariance. Of the 18 ADHD symptoms, 4 symptoms (three of which were IA symptoms) lacked metric invariance. Nine thresholds (1 IA symptom, 6 HY symptoms, and 2 IM symptoms) lacked scalar invariance, with six being for the first thresholds. The psychometric and practical implications of the findings are discussed. © 2023 The Authors
- Davis, Christal, Gizer, Ian, Lynskey, Michael, Statham, Dixie, Heath, Andrew, Martin, Nicholas, Slutske, Wendy
- Authors: Davis, Christal , Gizer, Ian , Lynskey, Michael , Statham, Dixie , Heath, Andrew , Martin, Nicholas , Slutske, Wendy
- Date: 2023
- Type: Text , Journal article
- Relation: Addiction Vol. 118, no. 1 (2023), p. 167-176
- Full Text: false
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- Description: Background and Aims: Previous studies have demonstrated associations between substance use and reduced educational attainment; however, many were unable to account for potential confounding factors like genetics and the rearing environment. In the few studies that controlled for these factors, the substances assessed were limited to alcohol, cannabis, and tobacco. To address these limitations, we examined the relationship between adolescent use of seven kinds of substances, the number of additional substances used, and high school noncompletion within a large sample of Australian twins. Design: A series of two-level generalized mixed effects logistic regressions were conducted to examine associations between adolescent substance use and high school noncompletion. Setting: Australia. Participants: A total of 9579 adult Australian twins from two cohorts of the Australian Twin Registry. Measurements: Assessments of high school completion, childhood major depression, conduct disorder symptoms, substance use initiation, demographics, and parental educational attainment using the Australian version of the Semi-Structured Assessment for the Genetics of Alcoholism. Findings: There were unique within-twin-pair effects of use of sedatives (odds ratio [OR] = 22.39 [95% confidence interval (CI) = 1.18–423.48]) and inhalants/solvents (OR = 10.46 [95% CI = 1.30–84.16]) on high school noncompletion. The number of substances used in adolescence was strongly associated with high school noncompletion across all discordant twin models (ORs from 1.50–2.32, Ps < 0.03). Conclusions: In Australia, adolescent substance use appears to be associated with early school dropout, with the effects of any given substance largely because of the confounding factors of parental education, childhood conduct disorder symptoms, and use of other substances. Sedatives and inhalants/solvents have effects on high school noncompletion that cannot be explained by polysubstance use or familial factors. © 2022 Society for the Study of Addiction.
- Gates, Trevor, Ross, Dyann, Bennett, Bindi
- Authors: Gates, Trevor , Ross, Dyann , Bennett, Bindi
- Date: 2023
- Type: Text , Journal article
- Relation: Adult learning Vol. 34, no. 4 (2023), p. 209-219
- Full Text: false
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- Description: Critical events in Leonard Matlovich’s life depict a reluctant activist for lesbian, gay, bisexual, transgender/gender diverse, and queer+ (LGBTQ+) equality. He served in the US military and subsequently came to personify the broad social challenges to the military’s homophobic culture and recruitment practices. Matlovich’s experience of a series of life metamorphoses made a difference beyond the individual. His example inspired multitudes of other concerned citizens in how to undertake their metamorphoses to challenge institutionalized homophobia. Breakthrough learning experiences in Matlovich’s life are presented to explore and refine aspects of transformative learning theory by applying Jane Martin’s metamorphosis model. The learning nexus between individuals and society is shown to be a dynamic interaction where both aspects of Matlovich’s story and his influence are explored in the context of today’s LGBTQ+ equality struggles. The article shows the conducive personal and societal conditions that enabled his various metamorphoses as whole-of-individual identity and sociocultural crossings toward transformational change. Additionally, the implications of Martin’s educational metamorphosis are discussed. Adult educators are encouraged to emphasize learning located in the learner’s life circumstances, exemplary case studies to inspire cultural crossings against injustice, and transformations as being about grasping in situ learning opportunities in the cross-influence between the whole person and their socio-historical context. Matlovich’s experiences show how relevant dimensions of Martin’s theoretical approach, coupled with support from allies, can contribute to personal agency and can build a groundswell of learning needed to support activism for social justice movements.
Aerosol delivery of palivizumab in a neonatal lamb model of respiratory syncytial virus infection
- Edirisinghe, Hasindu, Rajapaksa, Anushi, Royce, Simon, Sourial, Magdy, Bischof, Robert, Anderson, Jeremy, Sarila, Gulcan, Nguyen, Cattram, Mulholland, Kim, Do, Lien, Licciardi, Paul
- Authors: Edirisinghe, Hasindu , Rajapaksa, Anushi , Royce, Simon , Sourial, Magdy , Bischof, Robert , Anderson, Jeremy , Sarila, Gulcan , Nguyen, Cattram , Mulholland, Kim , Do, Lien , Licciardi, Paul
- Date: 2023
- Type: Text , Journal article
- Relation: Viruses Vol. 15, no. 11 (2023), p.
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- Description: (1) Background: Palivizumab has been an approved preventative monoclonal antibody for respiratory syncytial virus (RSV) infection for over two decades. However, due to its high cost and requirement for multiple intramuscular injections, its use has been limited mostly to high-income countries. Following our previous study showing the successful lung deposition of aerosolised palivizumab in lambs, this current study evaluated the “proof-of-principle” effect of aerosolised palivizumab delivered as a therapeutic to neonatal lambs following RSV infection. (2) Methods: Neonatal lambs were intranasally inoculated with RSV-A2 on day 0 (day 3 post-birth) and treated with aerosolised palivizumab 3 days later (day 3 post-inoculation). Clinical symptoms, RSV viral load and inflammatory response were measured post-inoculation. (3) Results: Aerosolised therapeutic delivery of palivizumab did not reduce RSV viral loads in the nasopharynx nor the bronchoalveolar lavage fluid, but resulted in a modest reduction in inflammatory response at day 6 post-inoculation compared with untreated lambs. (4) Conclusions: This proof-of-principle study shows some evidence of aerosolised palivizumab reducing RSV inflammation, but further studies using optimized protocols are needed in order to validate these findings. © 2023 by the authors.
- Authors: Edirisinghe, Hasindu , Rajapaksa, Anushi , Royce, Simon , Sourial, Magdy , Bischof, Robert , Anderson, Jeremy , Sarila, Gulcan , Nguyen, Cattram , Mulholland, Kim , Do, Lien , Licciardi, Paul
- Date: 2023
- Type: Text , Journal article
- Relation: Viruses Vol. 15, no. 11 (2023), p.
- Full Text:
- Reviewed:
- Description: (1) Background: Palivizumab has been an approved preventative monoclonal antibody for respiratory syncytial virus (RSV) infection for over two decades. However, due to its high cost and requirement for multiple intramuscular injections, its use has been limited mostly to high-income countries. Following our previous study showing the successful lung deposition of aerosolised palivizumab in lambs, this current study evaluated the “proof-of-principle” effect of aerosolised palivizumab delivered as a therapeutic to neonatal lambs following RSV infection. (2) Methods: Neonatal lambs were intranasally inoculated with RSV-A2 on day 0 (day 3 post-birth) and treated with aerosolised palivizumab 3 days later (day 3 post-inoculation). Clinical symptoms, RSV viral load and inflammatory response were measured post-inoculation. (3) Results: Aerosolised therapeutic delivery of palivizumab did not reduce RSV viral loads in the nasopharynx nor the bronchoalveolar lavage fluid, but resulted in a modest reduction in inflammatory response at day 6 post-inoculation compared with untreated lambs. (4) Conclusions: This proof-of-principle study shows some evidence of aerosolised palivizumab reducing RSV inflammation, but further studies using optimized protocols are needed in order to validate these findings. © 2023 by the authors.
Aerosol exposure of live bird market workers to viable influenza A/H5N1 and A/H9N2 viruses, Cambodia
- Horwood, Paul, Horm, Srey, Yann, Sokhoun, Tok, Songha, Chan, Malen, Suttie, Annika, Phalla, Y, Rith, Sareth, Siegers, Jurre, San, Sorn, Davun, Holl, Tum, Sothyra, Ly, Sowath, Tarantola, Arnaud, Dussart, Philippe, Karlsson, Erik
- Authors: Horwood, Paul , Horm, Srey , Yann, Sokhoun , Tok, Songha , Chan, Malen , Suttie, Annika , Phalla, Y , Rith, Sareth , Siegers, Jurre , San, Sorn , Davun, Holl , Tum, Sothyra , Ly, Sowath , Tarantola, Arnaud , Dussart, Philippe , Karlsson, Erik
- Date: 2023
- Type: Text , Journal article
- Relation: Zoonoses and Public Health Vol. 70, no. 2 (2023), p. 171-175
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- Description: Live bird markets (LBMs) have been identified as key factors in the spread, persistence and evolution of avian influenza viruses (AIVs). In addition, these settings have been associated with human infections with AIVs of pandemic concern. Exposure to aerosolised AIVs by workers in a Cambodian LBM was assessed using aerosol impact samplers. LBM vendors were asked to wear an air sampler for 30 min per day for 1 week while continuing their usual activities in the LBM during a period of high AIV circulation (February) and a period of low circulation (May). During the period of high circulation, AIV RNA was detected from 100% of the air samplers using molecular methods and viable AIV (A/H5N1 and/or A/H9N2) was isolated from 50% of air samplers following inoculation into embryonated chicken eggs. In contrast, AIV was not detected by molecular methods or successfully isolated during the period of low circulation. This study demonstrates the increased risk of aerosol exposure of LBM workers to AIVs during periods of high circulation and highlights the need for interventions during these high-risk periods. Novel approaches, such as environmental sampling, should be further explored at key high-risk interfaces as a potentially cost-effective alternative for monitoring pandemic threats. © 2022 The Authors. Zoonoses and Public Health published by Wiley-VCH GmbH.
Aerosol exposure of live bird market workers to viable influenza A/H5N1 and A/H9N2 viruses, Cambodia
- Authors: Horwood, Paul , Horm, Srey , Yann, Sokhoun , Tok, Songha , Chan, Malen , Suttie, Annika , Phalla, Y , Rith, Sareth , Siegers, Jurre , San, Sorn , Davun, Holl , Tum, Sothyra , Ly, Sowath , Tarantola, Arnaud , Dussart, Philippe , Karlsson, Erik
- Date: 2023
- Type: Text , Journal article
- Relation: Zoonoses and Public Health Vol. 70, no. 2 (2023), p. 171-175
- Full Text:
- Reviewed:
- Description: Live bird markets (LBMs) have been identified as key factors in the spread, persistence and evolution of avian influenza viruses (AIVs). In addition, these settings have been associated with human infections with AIVs of pandemic concern. Exposure to aerosolised AIVs by workers in a Cambodian LBM was assessed using aerosol impact samplers. LBM vendors were asked to wear an air sampler for 30 min per day for 1 week while continuing their usual activities in the LBM during a period of high AIV circulation (February) and a period of low circulation (May). During the period of high circulation, AIV RNA was detected from 100% of the air samplers using molecular methods and viable AIV (A/H5N1 and/or A/H9N2) was isolated from 50% of air samplers following inoculation into embryonated chicken eggs. In contrast, AIV was not detected by molecular methods or successfully isolated during the period of low circulation. This study demonstrates the increased risk of aerosol exposure of LBM workers to AIVs during periods of high circulation and highlights the need for interventions during these high-risk periods. Novel approaches, such as environmental sampling, should be further explored at key high-risk interfaces as a potentially cost-effective alternative for monitoring pandemic threats. © 2022 The Authors. Zoonoses and Public Health published by Wiley-VCH GmbH.
Age management for the common good
- Taylor, Philip, Earl, Catherine
- Authors: Taylor, Philip , Earl, Catherine
- Date: 2023
- Type: Text , Journal article
- Relation: Economic and Labour Relations Review Vol. 34, no. 1 (2023), p. 179-188
- Full Text: false
- Reviewed:
- Description: In the aftermath of the COVID-19 pandemic and amid the present reconfiguring of corporate purpose, there is an opportunity to realign actions focused on prolonging working lives. We put forward a transformative agenda concerned with workforce ageing that aligns with contemporary expectations regarding sustainability, inequality, and emerging conceptualisations of management. In this article, the new concept of Common Good human resource management (HRM) is utilised as a potential means of encouraging business responses focused on grand challenges such as population ageing. We suggest how these principles might be applied to the issue of managing age in workplaces, to recast debate about issues of age and work, to be used as an advocacy tool encouraging employer engagement, while providing a framework that might direct organisational leadership. © The Author(s), 2023. Published by Cambridge University Press on behalf of UNSW Canberra.
Agile ageing : implementation considerations for a walking basketball program
- Talpey, Scott, Pascoe, Deborah, Wallen, Mathew
- Authors: Talpey, Scott , Pascoe, Deborah , Wallen, Mathew
- Date: 2023
- Type: Text , Journal article
- Relation: Activities, Adaptation and Aging Vol. 47, no. 3 (2023), p. 301-314
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- Description: Physical activity generally declines with increasing age and lack of enjoyment is a noted barrier to older adults participating in traditional exercise programs. Walking basketball is a modified version of basketball designed to align with the physical capabilities of older adults, where participants are required to walk rather than run and body contact is not allowed. A walking basketball program provides participants with an opportunity to obtain the physical, mental and social health benefits of exercise in a competitive and social context. Due to the dynamic environment of a walking basketball program, participants are exposed to a unique stimulus combining both physical and cognitive demands, that is unmatched by traditional exercise programs. However, an increased risk of injury coincides with the unique demands of the activity. Therefore, the purpose of this manuscript is to provide practical applications for sporting organization that wish to implement a walking basketball program. © 2022 Taylor & Francis Group, LLC.
- Authors: Talpey, Scott , Pascoe, Deborah , Wallen, Mathew
- Date: 2023
- Type: Text , Journal article
- Relation: Activities, Adaptation and Aging Vol. 47, no. 3 (2023), p. 301-314
- Full Text:
- Reviewed:
- Description: Physical activity generally declines with increasing age and lack of enjoyment is a noted barrier to older adults participating in traditional exercise programs. Walking basketball is a modified version of basketball designed to align with the physical capabilities of older adults, where participants are required to walk rather than run and body contact is not allowed. A walking basketball program provides participants with an opportunity to obtain the physical, mental and social health benefits of exercise in a competitive and social context. Due to the dynamic environment of a walking basketball program, participants are exposed to a unique stimulus combining both physical and cognitive demands, that is unmatched by traditional exercise programs. However, an increased risk of injury coincides with the unique demands of the activity. Therefore, the purpose of this manuscript is to provide practical applications for sporting organization that wish to implement a walking basketball program. © 2022 Taylor & Francis Group, LLC.
AI apology : interactive multi-objective reinforcement learning for human-aligned AI
- Harland, Hadassah, Dazeley, Richard, Nakisa, Bahareh, Cruz, Francisco, Vamplew, Peter
- Authors: Harland, Hadassah , Dazeley, Richard , Nakisa, Bahareh , Cruz, Francisco , Vamplew, Peter
- Date: 2023
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 35, no. 23 (2023), p. 16917-16930
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- Description: For an Artificially Intelligent (AI) system to maintain alignment between human desires and its behaviour, it is important that the AI account for human preferences. This paper proposes and empirically evaluates the first approach to aligning agent behaviour to human preference via an apologetic framework. In practice, an apology may consist of an acknowledgement, an explanation and an intention for the improvement of future behaviour. We propose that such an apology, provided in response to recognition of undesirable behaviour, is one way in which an AI agent may both be transparent and trustworthy to a human user. Furthermore, that behavioural adaptation as part of apology is a viable approach to correct against undesirable behaviours. The Act-Assess-Apologise framework potentially could address both the practical and social needs of a human user, to recognise and make reparations against prior undesirable behaviour and adjust for the future. Applied to a dual-auxiliary impact minimisation problem, the apologetic agent had a near perfect determination and apology provision accuracy in several non-trivial configurations. The agent subsequently demonstrated behaviour alignment with success that included up to complete avoidance of the impacts described by these objectives in some scenarios. © 2023, The Author(s).
- Authors: Harland, Hadassah , Dazeley, Richard , Nakisa, Bahareh , Cruz, Francisco , Vamplew, Peter
- Date: 2023
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 35, no. 23 (2023), p. 16917-16930
- Full Text:
- Reviewed:
- Description: For an Artificially Intelligent (AI) system to maintain alignment between human desires and its behaviour, it is important that the AI account for human preferences. This paper proposes and empirically evaluates the first approach to aligning agent behaviour to human preference via an apologetic framework. In practice, an apology may consist of an acknowledgement, an explanation and an intention for the improvement of future behaviour. We propose that such an apology, provided in response to recognition of undesirable behaviour, is one way in which an AI agent may both be transparent and trustworthy to a human user. Furthermore, that behavioural adaptation as part of apology is a viable approach to correct against undesirable behaviours. The Act-Assess-Apologise framework potentially could address both the practical and social needs of a human user, to recognise and make reparations against prior undesirable behaviour and adjust for the future. Applied to a dual-auxiliary impact minimisation problem, the apologetic agent had a near perfect determination and apology provision accuracy in several non-trivial configurations. The agent subsequently demonstrated behaviour alignment with success that included up to complete avoidance of the impacts described by these objectives in some scenarios. © 2023, The Author(s).
AI grey box model for alum sludge as a soil stabilizer : an accurate predictive tool
- Baghbani, Abolfazl, Nguyen, Minh, Kafle, Bidur, Baghbani, Hasan, Shirani Faradonbeh, Roohollah
- Authors: Baghbani, Abolfazl , Nguyen, Minh , Kafle, Bidur , Baghbani, Hasan , Shirani Faradonbeh, Roohollah
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Geotechnical Engineering Vol. 17, no. 5 (2023), p. 480-494
- Full Text: false
- Reviewed:
- Description: By using a grey box AI model, a comprehensive study is presented on the behaviour prediction of alum sludge as a soil stabilizer. To creat models for predicting the California bearing rtio (CBR) of alum sludge as a soil stabilizer, the study employs statistical models, including multiple linear regression (MLR) and Partial least squares (PLS), and advanced artificial intelligence, including classificatoin and regression random forests (CRRF) and classification and regression trees (CART). Results show that CRRF and CART models accurately predict CBR values better than MLR and PLS models. For predicting the behaviour of alum sludge in soil stablization, the compaction number of hammer and sludge content were the most significant parameters. Gs and optimum moisture content of soil were the least important parameters. Study results provide valuable insights into alum sludge’s behaviour as a soil stablizer, which could reduce waste and promote sustainable practice. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
An agriprecision decision support system for weed management in pastures
- Chegini, Hossein, Naha, Ranesh, Mahanti, Aniket, Gong, Mingwei, Passi, Kalpdrum
- Authors: Chegini, Hossein , Naha, Ranesh , Mahanti, Aniket , Gong, Mingwei , Passi, Kalpdrum
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 92660-92675
- Full Text:
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- Description: Pastures are a vital source of dairy products and cattle nutrition, and as such, play a significant role in New Zealand's agricultural economy. However, weeds can be a major problem for pastures, making it a challenge for dairy farmers to monitor and control them. Currently, most of the tasks for weed management are done manually, and farmers lack persistent technology for weed control. This motivated us to design, implement, and evaluate a Decision Support System (DSS) to detect weeds in pastures and provide decisions for the cleanup of weeds. Our proposed system uses two primary inputs: weeds and bare patches. We created a synthetic dataset to train a weed detection model and designed a fuzzy inference system to assess a pasture. We also used a neuro-fuzzy system in our DSS to evaluate our fuzzy model and tune its parameters for better functioning and accuracy. Our work aims to assist dairy farmers in better weed monitoring, as well as to provide 2D maps of weed density and yield score, which can be of significant value when no digital and meaningful images of pastures exist. The system can also support farmers in scheduling, recommending prohibitive tasks, and storing historical data for pasture analysis, collaborated by stakeholders. © 2013 IEEE.
- Authors: Chegini, Hossein , Naha, Ranesh , Mahanti, Aniket , Gong, Mingwei , Passi, Kalpdrum
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 92660-92675
- Full Text:
- Reviewed:
- Description: Pastures are a vital source of dairy products and cattle nutrition, and as such, play a significant role in New Zealand's agricultural economy. However, weeds can be a major problem for pastures, making it a challenge for dairy farmers to monitor and control them. Currently, most of the tasks for weed management are done manually, and farmers lack persistent technology for weed control. This motivated us to design, implement, and evaluate a Decision Support System (DSS) to detect weeds in pastures and provide decisions for the cleanup of weeds. Our proposed system uses two primary inputs: weeds and bare patches. We created a synthetic dataset to train a weed detection model and designed a fuzzy inference system to assess a pasture. We also used a neuro-fuzzy system in our DSS to evaluate our fuzzy model and tune its parameters for better functioning and accuracy. Our work aims to assist dairy farmers in better weed monitoring, as well as to provide 2D maps of weed density and yield score, which can be of significant value when no digital and meaningful images of pastures exist. The system can also support farmers in scheduling, recommending prohibitive tasks, and storing historical data for pasture analysis, collaborated by stakeholders. © 2013 IEEE.
An annotated checklist of the Collembola (Hexapoda) from Iran
- Mayvan, Mahmood, Greenslade, Penelope, Sadeghi-Namaghi, Hussein
- Authors: Mayvan, Mahmood , Greenslade, Penelope , Sadeghi-Namaghi, Hussein
- Date: 2023
- Type: Text , Journal article
- Relation: Zootaxa Vol. 5275, no. 1 (2023), p.
- Full Text: false
- Reviewed:
- Description: Based on available literature sources, we have listed the genera and species of springtails (Collembola) of Iran located in Southwest Asia. In total, 301 named species of Collembola are listed in catalogue. This includes 286 described species in 109 genera from 20 families recorded from Iran. Of them, 15 species are also considered as dubious species. It also includes 15 genera whose species are still unknown. Information about biology, geographical distribution, ecology, authorship records for different provinces, and bibliographical data of Iranian Collembola are included. Copyright © 2023 Magnolia Press.
An educator's anthology of virtual simulation applications for nursing curricula : a mapping review
- Authors: Cant, Robyn , Ryan, Colleen
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Clinical Simulation in Nursing Vol. 74, no. (2023), p. 87-97
- Full Text: false
- Reviewed:
- Description: Virtual (screen-based) simulations have been utilized to help progress pre-licensure nursing students’ remote clinical learning during the recent pandemic. This mapping review, reports an anthology of virtual simulation technology sources from simulation education web sites and library sources. Two authors verified available sources and categorized these based on cost; either open access, or subscription-based. A list of 40 virtual simulation sources including virtual simulations, virtual reality simulations and virtual games, is presented. These provide faculty with a choice of virtual simulation modalities for various levels of nurse learners. Numerous virtual simulation technology applications are available for educators to utilize in teaching nursing students. Results from this review meet a need for educators to access virtual simulation applications to include in their education curricula. © 2022
An effective solution to the optimal power flow problem using meta-heuristic algorithms
- Aurangzeb, Khursheed, Shafiq, Sundas, Alhussein, Musaed, Pamir, Javaid, Nadeem, Imran, Muhammad
- Authors: Aurangzeb, Khursheed , Shafiq, Sundas , Alhussein, Musaed , Pamir , Javaid, Nadeem , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Energy Research Vol. 11, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Financial loss in power systems is an emerging problem that needs to be resolved. To tackle the mentioned problem, energy generated from various generation sources in the power network needs proper scheduling. In order to determine the best settings for the control variables, this study formulates and solves an optimal power flow (OPF) problem. In the proposed work, the bird swarm algorithm (BSA), JAYA, and a hybrid of both algorithms, termed as HJBSA, are used for obtaining the settings of optimum variables. We perform simulations by considering the constraints of voltage stability and line capacity, and generated reactive and active power. In addition, the used algorithms solve the problem of OPF and minimize carbon emission generated from thermal systems, fuel cost, voltage deviations, and losses in generation of active power. The suggested approach is evaluated by putting it into use on two separate IEEE testing systems, one with 30 buses and the other with 57 buses. The simulation results show that for the 30-bus system, the minimization in cost by HJBSA, JAYA, and BSA is 860.54 $/h, 862.31, $/h and 900.01 $/h, respectively, while for the 57-bus system, it is 5506.9 $/h, 6237.4, $/h and 7245.6 $/h for HJBSA, JAYA, and BSA, respectively. Similarly, for the 30-bus system, the power loss by HJBSA, JAYA, and BSA is 9.542 MW, 10.102 MW, and 11.427 MW, respectively, while for the 57-bus system, the value of power loss is 13.473 MW, 20.552, MW and 18.638 MW for HJBSA, JAYA, and BSA, respectively. Moreover, HJBSA, JAYA, and BSA cause reduction in carbon emissions by 4.394 ton/h, 4.524, ton/h and 4.401 ton/h, respectively, with the 30-bus system. With the 57-bus system, HJBSA, JAYA, and BSA cause reduction in carbon emissions by 26.429 ton/h, 27.014, ton/h and 28.568 ton/h, respectively. The results show the outperformance of HJBSA. Copyright © 2023 Aurangzeb, Shafiq, Alhussein, Pamir, Javaid and Imran.
- Authors: Aurangzeb, Khursheed , Shafiq, Sundas , Alhussein, Musaed , Pamir , Javaid, Nadeem , Imran, Muhammad
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Energy Research Vol. 11, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Financial loss in power systems is an emerging problem that needs to be resolved. To tackle the mentioned problem, energy generated from various generation sources in the power network needs proper scheduling. In order to determine the best settings for the control variables, this study formulates and solves an optimal power flow (OPF) problem. In the proposed work, the bird swarm algorithm (BSA), JAYA, and a hybrid of both algorithms, termed as HJBSA, are used for obtaining the settings of optimum variables. We perform simulations by considering the constraints of voltage stability and line capacity, and generated reactive and active power. In addition, the used algorithms solve the problem of OPF and minimize carbon emission generated from thermal systems, fuel cost, voltage deviations, and losses in generation of active power. The suggested approach is evaluated by putting it into use on two separate IEEE testing systems, one with 30 buses and the other with 57 buses. The simulation results show that for the 30-bus system, the minimization in cost by HJBSA, JAYA, and BSA is 860.54 $/h, 862.31, $/h and 900.01 $/h, respectively, while for the 57-bus system, it is 5506.9 $/h, 6237.4, $/h and 7245.6 $/h for HJBSA, JAYA, and BSA, respectively. Similarly, for the 30-bus system, the power loss by HJBSA, JAYA, and BSA is 9.542 MW, 10.102 MW, and 11.427 MW, respectively, while for the 57-bus system, the value of power loss is 13.473 MW, 20.552, MW and 18.638 MW for HJBSA, JAYA, and BSA, respectively. Moreover, HJBSA, JAYA, and BSA cause reduction in carbon emissions by 4.394 ton/h, 4.524, ton/h and 4.401 ton/h, respectively, with the 30-bus system. With the 57-bus system, HJBSA, JAYA, and BSA cause reduction in carbon emissions by 26.429 ton/h, 27.014, ton/h and 28.568 ton/h, respectively. The results show the outperformance of HJBSA. Copyright © 2023 Aurangzeb, Shafiq, Alhussein, Pamir, Javaid and Imran.
An efficient framework for mining outlying aspects
- Authors: Samariya, Durgesh
- Date: 2023
- Type: Text , Thesis , PhD
- Full Text:
- Description: In the era of big data, an immense volume of information is being continuously generated. It is common to encounter errors or anomalies within datasets. These anomalies can arise due to system malfunctions or human errors, resulting in data points that deviate from expected patterns or values. Anomaly detection algorithms have been developed to identify such anomalies effectively from the data. However, these algorithms often fall short in providing insights into why a particular data point is considered as an anomaly. They cannot explain the specific feature subset(s) in which a,data point significantly differs from the majority of the data. To address this limitation, researchers have recently turned their attention,to a new research area called outlying aspect mining. This area focuses on discovering feature subset(s), known as aspects or subspaces, in which anomalous data points exhibit significant deviations from the remaining set of data. Outlying aspect mining algorithms aim to provide a more detailed,understanding of the characteristics that make a data point anomalous. Although outlying aspect mining is an emerging area of research only a few studies have been published so far. One of the key challenges in this field is scaling up these algorithms to handle large datasets, characterised by,either a large data size or high dimensionality. Many existing outlying aspect mining algorithms are not well-suited for such datasets, as they exhaustively enumerate all possible subspaces and utilise density or distance-based anomaly scores to rank subspaces. As a result, most of these algorithms struggle to handle datasets with dimensions exceeding 20. Addressing the scalability issue and developing efficient algorithms for outlying aspect mining in large datasets remain active area of research. The ability to identify and understand the specific feature subsets contributing to anomalies in big data holds great potential for various applications, including fraud detection, network intrusion detection, and anomaly-based decision support systems. Existing outlying aspect mining methods are suffering from three main problems. Firstly, these measures often rely on distance or density-based calculations, which can be biased toward high-dimensional spaces. As the dimensionality of the subspace increases, the density tends to decrease, making it difficult to assess the outlyingness of data points within specific subspaces accurately. Secondly, distances or density-based measures are computationally expensive, especially when dealing with large-scale datasets that contain millions of data points. As distance and density-based measures require computing pairwise distance, it makes them computationally expensive. In addition to that, existing work uses Z-Score normalisation to make density-based scoring measure dimensionally unbias. However, it adds additional computational overload on already computationally expensive measures. Lastly, existing outlying aspect mining uses brute-force methods to search subspaces. Thus, it is essential to tackle this efficiency issue because when the dimensionality of the data is high – candidate subspace grows exponentially, which is beyond computational resources. This research project aims to solve this challenge by developing efficient and effective methods for mining outlying aspects in high-dimensional and large datasets. I have explored and designed different scoring measures to find the outlyingness of a given data point in each subspace. The effectiveness and efficiency of these proposed measures have been verified with extensive experiments on synthetic and real-world datasets. To overcome the first problem, this thesis first identifies and analyses the condition under which Z-Score based normalisation scoring measure fails to find the most outlying aspects and proposes two different approaches called HMass and sGrid++, both measures are dimensionally unbiased in their raw form, which means they do not require any additional normalisation. sGrid++ is a simpler version of sGrid that is not only efficient and effective but also dimensionality unbiased. It does not require Z-score normalisation. HMass is a simple but effective and efficient histogram-based solution to rank outlying aspects of a given query in each subspace. In addition to detecting anomalies, HMass provides explanations on why the points are anomalous. Both sGrid++ and HMass do not require pair-wise calculation like distance or density-based measures; therefore, sGrid++ and HMass are computationally faster than distance and density-based measures, which solves the second issue of existing work. The effectiveness and efficiency of both sGrid++ and HMass are evaluated using synthetic and real-world datasets. In addition to that, I presented an exciting application of outlying aspect mining in the cybersecurity domain. To tackle the third problem, this thesis proposes an efficient and effective outlying aspect mining framework named OIMiner (for Outlying - Inlying Aspect Miner). It introduces a new scoring measure to compute outlying degree, called Simple Isolation score using Nearest Neighbor Ensemble (SiNNE), which not only detects the outliers but also provides an explanation on why the selected point is an outlier. SiNNE is a dimensionally unbias measure in its raw form, which means the scores produced by SiNNE are compared directly with subspaces having different dimensions. Thus, it does not require any normalisation to make the score unbiased. Our experimental results on synthetic and publicly available real-world datasets revealed that (i) SiNNE produces better or at least the same results as existing scores. (ii) It improves the run time of the existing outlying aspect mining algorithm based on beam search by at least two orders of magnitude. SiNNE allows the existing outlying aspect mining algorithm to run in datasets with hundreds of thousands of instances and thousands of dimensions, which was not possible before.
- Description: Doctor of Philosophy
- Authors: Samariya, Durgesh
- Date: 2023
- Type: Text , Thesis , PhD
- Full Text:
- Description: In the era of big data, an immense volume of information is being continuously generated. It is common to encounter errors or anomalies within datasets. These anomalies can arise due to system malfunctions or human errors, resulting in data points that deviate from expected patterns or values. Anomaly detection algorithms have been developed to identify such anomalies effectively from the data. However, these algorithms often fall short in providing insights into why a particular data point is considered as an anomaly. They cannot explain the specific feature subset(s) in which a,data point significantly differs from the majority of the data. To address this limitation, researchers have recently turned their attention,to a new research area called outlying aspect mining. This area focuses on discovering feature subset(s), known as aspects or subspaces, in which anomalous data points exhibit significant deviations from the remaining set of data. Outlying aspect mining algorithms aim to provide a more detailed,understanding of the characteristics that make a data point anomalous. Although outlying aspect mining is an emerging area of research only a few studies have been published so far. One of the key challenges in this field is scaling up these algorithms to handle large datasets, characterised by,either a large data size or high dimensionality. Many existing outlying aspect mining algorithms are not well-suited for such datasets, as they exhaustively enumerate all possible subspaces and utilise density or distance-based anomaly scores to rank subspaces. As a result, most of these algorithms struggle to handle datasets with dimensions exceeding 20. Addressing the scalability issue and developing efficient algorithms for outlying aspect mining in large datasets remain active area of research. The ability to identify and understand the specific feature subsets contributing to anomalies in big data holds great potential for various applications, including fraud detection, network intrusion detection, and anomaly-based decision support systems. Existing outlying aspect mining methods are suffering from three main problems. Firstly, these measures often rely on distance or density-based calculations, which can be biased toward high-dimensional spaces. As the dimensionality of the subspace increases, the density tends to decrease, making it difficult to assess the outlyingness of data points within specific subspaces accurately. Secondly, distances or density-based measures are computationally expensive, especially when dealing with large-scale datasets that contain millions of data points. As distance and density-based measures require computing pairwise distance, it makes them computationally expensive. In addition to that, existing work uses Z-Score normalisation to make density-based scoring measure dimensionally unbias. However, it adds additional computational overload on already computationally expensive measures. Lastly, existing outlying aspect mining uses brute-force methods to search subspaces. Thus, it is essential to tackle this efficiency issue because when the dimensionality of the data is high – candidate subspace grows exponentially, which is beyond computational resources. This research project aims to solve this challenge by developing efficient and effective methods for mining outlying aspects in high-dimensional and large datasets. I have explored and designed different scoring measures to find the outlyingness of a given data point in each subspace. The effectiveness and efficiency of these proposed measures have been verified with extensive experiments on synthetic and real-world datasets. To overcome the first problem, this thesis first identifies and analyses the condition under which Z-Score based normalisation scoring measure fails to find the most outlying aspects and proposes two different approaches called HMass and sGrid++, both measures are dimensionally unbiased in their raw form, which means they do not require any additional normalisation. sGrid++ is a simpler version of sGrid that is not only efficient and effective but also dimensionality unbiased. It does not require Z-score normalisation. HMass is a simple but effective and efficient histogram-based solution to rank outlying aspects of a given query in each subspace. In addition to detecting anomalies, HMass provides explanations on why the points are anomalous. Both sGrid++ and HMass do not require pair-wise calculation like distance or density-based measures; therefore, sGrid++ and HMass are computationally faster than distance and density-based measures, which solves the second issue of existing work. The effectiveness and efficiency of both sGrid++ and HMass are evaluated using synthetic and real-world datasets. In addition to that, I presented an exciting application of outlying aspect mining in the cybersecurity domain. To tackle the third problem, this thesis proposes an efficient and effective outlying aspect mining framework named OIMiner (for Outlying - Inlying Aspect Miner). It introduces a new scoring measure to compute outlying degree, called Simple Isolation score using Nearest Neighbor Ensemble (SiNNE), which not only detects the outliers but also provides an explanation on why the selected point is an outlier. SiNNE is a dimensionally unbias measure in its raw form, which means the scores produced by SiNNE are compared directly with subspaces having different dimensions. Thus, it does not require any normalisation to make the score unbiased. Our experimental results on synthetic and publicly available real-world datasets revealed that (i) SiNNE produces better or at least the same results as existing scores. (ii) It improves the run time of the existing outlying aspect mining algorithm based on beam search by at least two orders of magnitude. SiNNE allows the existing outlying aspect mining algorithm to run in datasets with hundreds of thousands of instances and thousands of dimensions, which was not possible before.
- Description: Doctor of Philosophy
An empirical study into the use of 7 quality control tools in Higher Education Institutions (HEIs)
- Mathur, Swati, Antony, Jiju, Olivia, McDermott, Fabiane Letícia, Lizarelli, Shreeranga, Bhat, Raja, Jayaraman, Ayon, Chakraborty
- Authors: Mathur, Swati , Antony, Jiju , Olivia, McDermott , Fabiane Letícia, Lizarelli , Shreeranga, Bhat , Raja, Jayaraman , Ayon, Chakraborty
- Date: 2023
- Type: Text , Journal article
- Relation: TQM Journal Vol. 35, no. 7 (2023), p. 1777-1798
- Full Text:
- Reviewed:
- Description: Purpose: The main purpose of this study is to revisit Ishikawa's statement: “95% of problems in processes can be accomplished using the original 7 Quality Control (QC) tools”. The paper critically investigates the validity of this statement in higher education institutions (HEIs). It involves analysis of the usage of the 7 QC tools and identifying the barriers, benefits, challenges and critical success factors (CSFs) for the application of the 7 QC tools in a HEI setting. Design/methodology/approach: An online survey instrument was developed, and as this is a global study, survey participants were contacted via social networks such as LinkedIn. Target respondents were HEIs educators or professionals who are knowledgeable about the 7 QC tools promulgated by Dr Ishikawa. Professionals who work in administrative sectors, such as libraries, information technology and human resources were included in the study. A number of academics who teach the 7 basic tools of QC were also included in the study. The survey link was sent to over 200 educators and professionals and 76 complete responses were obtained. Findings: The primary finding of this study shows that the diffusion of seven QC tools is not widespread in the context of HEIs. Less than 8% of the respondents believe that more than 90% of process problems can be solved by applying the 7 QC tools. These numbers show that modern-quality problems may need more than the 7 basic QC basic tools and there may be a need to revisit the role and contribution of these tools to solve problems in the higher education sector. Tools such as Pareto chart and cause and effect diagram have been widely used in the context of HEIs. The most important barriers highlighted are related to the lack of knowledge about the benefits and about how and when to apply these tools. Among the challenges are the “lack of knowledge of the tools and their applications” and “lack of training in the use of the tools”. The main benefits mentioned by the respondents were “the identification of areas for improvement, problem definition, measurement, and analysis”. According to this study, the most important factors critical for the success of the initiative were “management support”, “widespread training” and “having a continuous improvement program in place”. Research limitations/implications: The exploratory study provides an initial understanding about the 7 QC tools application in HEIs, and their benefits, challenges and critical success factors, which can act as guidelines for implementation in HEIs. Surveys alone cannot provide deeper insights into the status of the application of 7 QC tools in HEIs, and therefore qualitative studies in the form of semi-structured interviews should be carried out in the future. Originality/value: This article contributes with an exploratory empirical study on the extent of the use of 7 QC tools in the university processes. The authors claim that this is the first empirical study looking into the use of the 7 QC tools in the university sector. © 2022, Emerald Publishing Limited.
- Authors: Mathur, Swati , Antony, Jiju , Olivia, McDermott , Fabiane Letícia, Lizarelli , Shreeranga, Bhat , Raja, Jayaraman , Ayon, Chakraborty
- Date: 2023
- Type: Text , Journal article
- Relation: TQM Journal Vol. 35, no. 7 (2023), p. 1777-1798
- Full Text:
- Reviewed:
- Description: Purpose: The main purpose of this study is to revisit Ishikawa's statement: “95% of problems in processes can be accomplished using the original 7 Quality Control (QC) tools”. The paper critically investigates the validity of this statement in higher education institutions (HEIs). It involves analysis of the usage of the 7 QC tools and identifying the barriers, benefits, challenges and critical success factors (CSFs) for the application of the 7 QC tools in a HEI setting. Design/methodology/approach: An online survey instrument was developed, and as this is a global study, survey participants were contacted via social networks such as LinkedIn. Target respondents were HEIs educators or professionals who are knowledgeable about the 7 QC tools promulgated by Dr Ishikawa. Professionals who work in administrative sectors, such as libraries, information technology and human resources were included in the study. A number of academics who teach the 7 basic tools of QC were also included in the study. The survey link was sent to over 200 educators and professionals and 76 complete responses were obtained. Findings: The primary finding of this study shows that the diffusion of seven QC tools is not widespread in the context of HEIs. Less than 8% of the respondents believe that more than 90% of process problems can be solved by applying the 7 QC tools. These numbers show that modern-quality problems may need more than the 7 basic QC basic tools and there may be a need to revisit the role and contribution of these tools to solve problems in the higher education sector. Tools such as Pareto chart and cause and effect diagram have been widely used in the context of HEIs. The most important barriers highlighted are related to the lack of knowledge about the benefits and about how and when to apply these tools. Among the challenges are the “lack of knowledge of the tools and their applications” and “lack of training in the use of the tools”. The main benefits mentioned by the respondents were “the identification of areas for improvement, problem definition, measurement, and analysis”. According to this study, the most important factors critical for the success of the initiative were “management support”, “widespread training” and “having a continuous improvement program in place”. Research limitations/implications: The exploratory study provides an initial understanding about the 7 QC tools application in HEIs, and their benefits, challenges and critical success factors, which can act as guidelines for implementation in HEIs. Surveys alone cannot provide deeper insights into the status of the application of 7 QC tools in HEIs, and therefore qualitative studies in the form of semi-structured interviews should be carried out in the future. Originality/value: This article contributes with an exploratory empirical study on the extent of the use of 7 QC tools in the university processes. The authors claim that this is the first empirical study looking into the use of the 7 QC tools in the university sector. © 2022, Emerald Publishing Limited.
An evaluation of low and high intensity digital mental health treatment models for anxiety and depression : an adaptive treatment randomized clinical trial
- Authors: Andrews, Brooke
- Date: 2023
- Type: Text , Thesis , PhD
- Full Text:
- Description: Doctor of Philsophy
- Authors: Andrews, Brooke
- Date: 2023
- Type: Text , Thesis , PhD
- Full Text:
- Description: Doctor of Philsophy
An evidence theoretic approach for traffic signal intrusion detection
- Chowdhury, Abdullahi, Karmakar, Gour, Kamruzzaman, Joarder, Das, Rajkumar, Newaz, Shah
- Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Das, Rajkumar , Newaz, Shah
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 10 (2023), p. 4646
- Full Text:
- Reviewed:
- Description: The increasing attacks on traffic signals worldwide indicate the importance of intrusion detection. The existing traffic signal Intrusion Detection Systems (IDSs) that rely on inputs from connected vehicles and image analysis techniques can only detect intrusions created by spoofed vehicles. However, these approaches fail to detect intrusion from attacks on in-road sensors, traffic controllers, and signals. In this paper, we proposed an IDS based on detecting anomalies associated with flow rate, phase time, and vehicle speed, which is a significant extension of our previous work using additional traffic parameters and statistical tools. We theoretically modelled our system using the Dempster-Shafer decision theory, considering the instantaneous observations of traffic parameters and their relevant historical normal traffic data. We also used Shannon's entropy to determine the uncertainty associated with the observations. To validate our work, we developed a simulation model based on the traffic simulator called SUMO using many real scenarios and the data recorded by the Victorian Transportation Authority, Australia. The scenarios for abnormal traffic conditions were generated considering attacks such as jamming, Sybil, and false data injection attacks. The results show that the overall detection accuracy of our proposed system is 79.3% with fewer false alarms.
- Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Das, Rajkumar , Newaz, Shah
- Date: 2023
- Type: Text , Journal article
- Relation: Sensors Vol. 23, no. 10 (2023), p. 4646
- Full Text:
- Reviewed:
- Description: The increasing attacks on traffic signals worldwide indicate the importance of intrusion detection. The existing traffic signal Intrusion Detection Systems (IDSs) that rely on inputs from connected vehicles and image analysis techniques can only detect intrusions created by spoofed vehicles. However, these approaches fail to detect intrusion from attacks on in-road sensors, traffic controllers, and signals. In this paper, we proposed an IDS based on detecting anomalies associated with flow rate, phase time, and vehicle speed, which is a significant extension of our previous work using additional traffic parameters and statistical tools. We theoretically modelled our system using the Dempster-Shafer decision theory, considering the instantaneous observations of traffic parameters and their relevant historical normal traffic data. We also used Shannon's entropy to determine the uncertainty associated with the observations. To validate our work, we developed a simulation model based on the traffic simulator called SUMO using many real scenarios and the data recorded by the Victorian Transportation Authority, Australia. The scenarios for abnormal traffic conditions were generated considering attacks such as jamming, Sybil, and false data injection attacks. The results show that the overall detection accuracy of our proposed system is 79.3% with fewer false alarms.
An examination of physical exercise therapy on quality of life (QoL) and mortality in men diagnosed with Prostate Cancer (PCa)
- Authors: Khan, Nazib
- Date: 2023
- Type: Text , Thesis , PhD
- Full Text:
- Description: Prostate cancer (PCa) is the second most frequent malignancy in men worldwide, accounting for 27% of new cancer cases in men and responsible for 3.8% of worldwide male cancer deaths (2018). This risk is projected to double before 204, so it is surprising that there are no well- established modifiable risk factors for PCa diagnosis orr progression. Considering this, the following thesis consists of three original research studies that examined; (1) the moderating effect of physical activity and muscular strength on prostate cancer mortality; (2) the magnitude of effect from pooled therapeutic exercise studies to impact quality of life and adverse events in PCa patients following surgery; (3) the head-to-head comparative efficacy of individual exercise therapies to impact quality of life and adverse events following surgery. The sum of works presented in this thesis lead to the conclusion that 1) when PCa is the only lifetime cancer diagnosis, life expectancy is similar to lifetime cancer free counterparts whereas diagnosis of PCa with any other lifetime cancer is associated with a 30.2% lower life expectancy during 10-year follow-up. Physical activity has negligible effect on life-expectancy whereas handgrip strength accounts for ~4% of the difference in life-expectancy between PCa with any other lifetime cancer compared with controls; 2) Pooled evidence from randomised controlled trials (n=999 participants) identifies that perioperative exercise therapy (aerobic, resistance, pelvic floor, mind-body exercise, or mixed exercise (combined aerobic and resistance) has a positive impact on patient quality of life and adverse events in PCa patients undergoing surgery which is predominant in perceptions of symptom related QoL (SMD: 0.56, 111 95% CI’s [0.22-0.89]) more so than health related quality of life (HRQoL) (SMD: 0.02, 95% 112 CI’s [-0.16-0.20]; 3) Comparison of head-to-head efficacy of different therapeutic exercise interventions [Aerobic, resistance, pelvic floor, mind-body exercise or mixed exercise (combined aerobic and resistance)] identified pelvic floor muscle exercise to be the most favorable exercise therapy to maintain QoL in PCa patients undergoing surgery, partly due to the current lack of evidence to support other exercise therapies. These findings provide new knowledge to support the effective treatment of PCa patients.
- Description: Doctor of Philosophy
- Authors: Khan, Nazib
- Date: 2023
- Type: Text , Thesis , PhD
- Full Text:
- Description: Prostate cancer (PCa) is the second most frequent malignancy in men worldwide, accounting for 27% of new cancer cases in men and responsible for 3.8% of worldwide male cancer deaths (2018). This risk is projected to double before 204, so it is surprising that there are no well- established modifiable risk factors for PCa diagnosis orr progression. Considering this, the following thesis consists of three original research studies that examined; (1) the moderating effect of physical activity and muscular strength on prostate cancer mortality; (2) the magnitude of effect from pooled therapeutic exercise studies to impact quality of life and adverse events in PCa patients following surgery; (3) the head-to-head comparative efficacy of individual exercise therapies to impact quality of life and adverse events following surgery. The sum of works presented in this thesis lead to the conclusion that 1) when PCa is the only lifetime cancer diagnosis, life expectancy is similar to lifetime cancer free counterparts whereas diagnosis of PCa with any other lifetime cancer is associated with a 30.2% lower life expectancy during 10-year follow-up. Physical activity has negligible effect on life-expectancy whereas handgrip strength accounts for ~4% of the difference in life-expectancy between PCa with any other lifetime cancer compared with controls; 2) Pooled evidence from randomised controlled trials (n=999 participants) identifies that perioperative exercise therapy (aerobic, resistance, pelvic floor, mind-body exercise, or mixed exercise (combined aerobic and resistance) has a positive impact on patient quality of life and adverse events in PCa patients undergoing surgery which is predominant in perceptions of symptom related QoL (SMD: 0.56, 111 95% CI’s [0.22-0.89]) more so than health related quality of life (HRQoL) (SMD: 0.02, 95% 112 CI’s [-0.16-0.20]; 3) Comparison of head-to-head efficacy of different therapeutic exercise interventions [Aerobic, resistance, pelvic floor, mind-body exercise or mixed exercise (combined aerobic and resistance)] identified pelvic floor muscle exercise to be the most favorable exercise therapy to maintain QoL in PCa patients undergoing surgery, partly due to the current lack of evidence to support other exercise therapies. These findings provide new knowledge to support the effective treatment of PCa patients.
- Description: Doctor of Philosophy
- Soldatenko, Daria, Zentveld, Elisa, Morgan, Damian
- Authors: Soldatenko, Daria , Zentveld, Elisa , Morgan, Damian
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Tourism Cities Vol. 9, no. 3 (2023), p. 572-597
- Full Text: false
- Reviewed:
- Description: Purpose: To succeed in a competitive tourist market and attract more foreign tourists, it is essential to have a clear understanding of what travellers are seeking and endeavour to meet those needs, as well as key influential factors in their travel decision-making process. The purpose of the study is to develop and examine tourists’ pre-trip motivational model using the push–pull theory. Design/methodology/approach: A tourists’ pre-trip motivational model was developed and then tested based on a sample of 320 Chinese and non-Chinese visitors to Melbourne, Australia, to assess the suitability of the new model. Data were analysed by descriptive and inferential statistical techniques, such as principal component analysis and independent T-tests. Findings: The analysis revealed statistically significant differences between studied samples in terms of the push and pull factors. In comparison with non-Chinese tourists, Chinese visitors to Melbourne assigned higher importance to resting and relaxing opportunities, family-oriented activities, as well as safety and a high level of service. The identified differences should be reflected in marketing and promotional activities provided to Chinese and non-Chinese travellers. Practical implications: The study provides useful information for Destination Marketing Organisations in tourism cities wanting to develop specifically customised tourist products, services and promotion programs tailored to each market. Originality/value: The proposed extended push–pull model represents a holistic and complex model of the travel decision-making process with the multiple linkages between motivations for travelling, preferences of destination attributes, information source usage, trip expectations, possible constraints for travelling and evaluation of destination choice criteria. Understanding all these factors, their relationship and their influence on the final destination choice is a prerequisite for effective and successful actions on attraction and retention of visitors for all tourist destinations. The developed tourists’ pre-trip motivational model may be used as a conceptual framework to guide subsequent motivational studies in tourism. © 2023, International Tourism Studies Association.
An exploration into early childhood physical literacy programs : a systematic literature review
- Porter, Joanne, Dabkowski, Elissa, Prokopiv, Val, Missen, Karen, Barbagallo, Michael, James, Michelle
- Authors: Porter, Joanne , Dabkowski, Elissa , Prokopiv, Val , Missen, Karen , Barbagallo, Michael , James, Michelle
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Australasian Journal of Early Childhood Vol. 48, no. 1 (2023), p. 34-49
- Full Text: false
- Reviewed:
- Description: This review explored the impact of physical literacy programs designed to engage two- to five-year-old preschool children. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was used. Six EBSCO host databases were searched for the period 2011 to April 2021 using the search terms “physical literacy,” “early childhood,” and “impact.” Articles were excluded if physical literacy was not the focal intervention. The final data set consisted of seven-peer reviewed articles meeting the eligibility criteria and quality assessment for this review. Three themes were created using Braun and Clark’s (2006) approach to thematic analysis: Holistic benefits of physical literacy, Barriers to physical literacy and Education begins at home. Early childhood physical literacy programs provide holistic benefits for children; however, further research is needed in an Australian context. Families and community members working in the early childhood sector could benefit from further education and training to improve physical literacy awareness. © The Author(s) 2022.