Automated segmentation of mouse OCT volumes (ASiMOV): Validation & clinical study of a light damage model
- Antony, Bhavna, Kim, Byung-Jin, Lang, Andrew, Carass, Aaron, Prince, Jerry, Zack, Donald
- Authors: Antony, Bhavna , Kim, Byung-Jin , Lang, Andrew , Carass, Aaron , Prince, Jerry , Zack, Donald
- Date: 2017
- Type: Text , Journal article
- Relation: PLoS One Vol. 12, no. 8 (2017), p. e0181059-e0181059
- Full Text:
- Reviewed:
- Description: The use of spectral-domain optical coherence tomography (SD-OCT) is becoming commonplace for the in vivo longitudinal study of murine models of ophthalmic disease. Longitudinal studies, however, generate large quantities of data, the manual analysis of which is very challenging due to the time-consuming nature of generating delineations. Thus, it is of importance that automated algorithms be developed to facilitate accurate and timely analysis of these large datasets. Furthermore, as the models target a variety of diseases, the associated structural changes can also be extremely disparate. For instance, in the light damage (LD) model, which is frequently used to study photoreceptor degeneration, the outer retina appears dramatically different from the normal retina. To address these concerns, we have developed a flexible graph-based algorithm for the automated segmentation of mouse OCT volumes (ASiMOV). This approach incorporates a machine-learning component that can be easily trained for different disease models. To validate ASiMOV, the automated results were compared to manual delineations obtained from three raters on healthy and BALB/cJ mice post LD. It was also used to study a longitudinal LD model, where five control and five LD mice were imaged at four timepoints post LD. The total retinal thickness and the outer retina (comprising the outer nuclear layer, and inner and outer segments of the photoreceptors) were unchanged the day after the LD, but subsequently thinned significantly (p < 0.01). The retinal nerve fiber-ganglion cell complex and the inner plexiform layers, however, remained unchanged for the duration of the study.
- Authors: Antony, Bhavna , Kim, Byung-Jin , Lang, Andrew , Carass, Aaron , Prince, Jerry , Zack, Donald
- Date: 2017
- Type: Text , Journal article
- Relation: PLoS One Vol. 12, no. 8 (2017), p. e0181059-e0181059
- Full Text:
- Reviewed:
- Description: The use of spectral-domain optical coherence tomography (SD-OCT) is becoming commonplace for the in vivo longitudinal study of murine models of ophthalmic disease. Longitudinal studies, however, generate large quantities of data, the manual analysis of which is very challenging due to the time-consuming nature of generating delineations. Thus, it is of importance that automated algorithms be developed to facilitate accurate and timely analysis of these large datasets. Furthermore, as the models target a variety of diseases, the associated structural changes can also be extremely disparate. For instance, in the light damage (LD) model, which is frequently used to study photoreceptor degeneration, the outer retina appears dramatically different from the normal retina. To address these concerns, we have developed a flexible graph-based algorithm for the automated segmentation of mouse OCT volumes (ASiMOV). This approach incorporates a machine-learning component that can be easily trained for different disease models. To validate ASiMOV, the automated results were compared to manual delineations obtained from three raters on healthy and BALB/cJ mice post LD. It was also used to study a longitudinal LD model, where five control and five LD mice were imaged at four timepoints post LD. The total retinal thickness and the outer retina (comprising the outer nuclear layer, and inner and outer segments of the photoreceptors) were unchanged the day after the LD, but subsequently thinned significantly (p < 0.01). The retinal nerve fiber-ganglion cell complex and the inner plexiform layers, however, remained unchanged for the duration of the study.
A systematic review of Lean in healthcare : a global prospective
- Antony, Jiju, Sunder, Vijaya, Sreedharan, Raja, Chakraborty, Ayon, Gunasekaran, Angappa
- Authors: Antony, Jiju , Sunder, Vijaya , Sreedharan, Raja , Chakraborty, Ayon , Gunasekaran, Angappa
- Date: 2019
- Type: Text , Journal article , Review
- Relation: International Journal of Quality and Reliability Management Vol. 36, no. 8 (2019), p. 1370-1391
- Full Text:
- Reviewed:
- Description: Purpose: Fostered by a rapid spread beyond the manufacturing sector, Lean philosophy for continuous improvement has been widely used in service organizations, primarily in the healthcare sector. However, there is a limited research on the motivating factors, challenges and benefits of implementing Lean in healthcare. Taking this as a valuable opportunity, the purpose of this paper is to present the key motivating factors, limitations or challenges of Lean deployment, benefits of Lean in healthcare and key gaps in the literature as an agenda for future research. Design/methodology/approach: The authors used the secondary data from the literature (peer-reviewed journal articles) published between 2000 and 2016 to understand the state of the art. The systematic review identified 101 articles across 88 journals recognized by the Association of Business Schools ranking guide 2015. Findings: The systematic review helped the authors to identify the evolution, current trends, research gaps and an agenda for future research for Lean in healthcare. A bouquet of motivating factors, challenges/limitations and benefits of Lean in healthcare are presented. Practical implications: The implications of this work include directions for managers and healthcare professionals in healthcare organizations to embark on a focused Lean journey aligned with the strategic objectives. This work could serve as a valuable resource to both practitioners and researchers for learning, investigating and rightly adapting the Lean in the healthcare sector. Originality/value: This study is perhaps one of the comprehensive systematic literature reviews covering an important agenda of Lean in Healthcare. All the text, figures and tables featured here are original work carried by five authors in collaboration (from three countries, namely, India, the USA and the UK). © 2019, Emerald Publishing Limited.
- Authors: Antony, Jiju , Sunder, Vijaya , Sreedharan, Raja , Chakraborty, Ayon , Gunasekaran, Angappa
- Date: 2019
- Type: Text , Journal article , Review
- Relation: International Journal of Quality and Reliability Management Vol. 36, no. 8 (2019), p. 1370-1391
- Full Text:
- Reviewed:
- Description: Purpose: Fostered by a rapid spread beyond the manufacturing sector, Lean philosophy for continuous improvement has been widely used in service organizations, primarily in the healthcare sector. However, there is a limited research on the motivating factors, challenges and benefits of implementing Lean in healthcare. Taking this as a valuable opportunity, the purpose of this paper is to present the key motivating factors, limitations or challenges of Lean deployment, benefits of Lean in healthcare and key gaps in the literature as an agenda for future research. Design/methodology/approach: The authors used the secondary data from the literature (peer-reviewed journal articles) published between 2000 and 2016 to understand the state of the art. The systematic review identified 101 articles across 88 journals recognized by the Association of Business Schools ranking guide 2015. Findings: The systematic review helped the authors to identify the evolution, current trends, research gaps and an agenda for future research for Lean in healthcare. A bouquet of motivating factors, challenges/limitations and benefits of Lean in healthcare are presented. Practical implications: The implications of this work include directions for managers and healthcare professionals in healthcare organizations to embark on a focused Lean journey aligned with the strategic objectives. This work could serve as a valuable resource to both practitioners and researchers for learning, investigating and rightly adapting the Lean in the healthcare sector. Originality/value: This study is perhaps one of the comprehensive systematic literature reviews covering an important agenda of Lean in Healthcare. All the text, figures and tables featured here are original work carried by five authors in collaboration (from three countries, namely, India, the USA and the UK). © 2019, Emerald Publishing Limited.
Introduced birds in urban remnant vegetation: Does remnant size really matter?
- Antos, Mark, Fitzsimons, John, Palmer, Grant, White, James
- Authors: Antos, Mark , Fitzsimons, John , Palmer, Grant , White, James
- Date: 2006
- Type: Text , Journal article
- Relation: Austral Ecology Vol. 31, no. 2 (2006), p. 254-261
- Full Text:
- Reviewed:
- Description: Introduced birds are a pervasive and dominant element of urban ecosystems. We examined the richness and relative abundance of introduced bird species in small (1-5 ha) medium (6-15 ha) and large (>15 ha) remnants of native vegetation within an urban matrix. Transects were surveyed during breeding and non-breeding seasons. There was a significant relationship between introduced species richness and remnant size with larger remnants supporting more introduced species. There was no significant difference in relative abundance of introduced species in remnants of different sizes. Introduced species, as a proportion of the relative abundance of the total avifauna (native and introduced species), did not vary significantly between remnants of differing sizes. There were significant differences in the composition of introduced bird species between the different remnant sizes, with large remnants supporting significantly different assemblages than medium and small remnants. Other variables also have substantial effects on the abundance of introduced bird species. The lack of significant differences in abundance between remnant sizes suggests they were all equally susceptible to invasion. No patches in the urban matrix are likely to be unaffected by introduced species. The effective long-term control of introduced bird species is difficult and resources may be better spent managing habitat in a way which renders it less suitable for introduced species (e.g. reducing areas of disturbed ground and weed dominated areas).
- Description: C1
- Description: 2003001638
- Authors: Antos, Mark , Fitzsimons, John , Palmer, Grant , White, James
- Date: 2006
- Type: Text , Journal article
- Relation: Austral Ecology Vol. 31, no. 2 (2006), p. 254-261
- Full Text:
- Reviewed:
- Description: Introduced birds are a pervasive and dominant element of urban ecosystems. We examined the richness and relative abundance of introduced bird species in small (1-5 ha) medium (6-15 ha) and large (>15 ha) remnants of native vegetation within an urban matrix. Transects were surveyed during breeding and non-breeding seasons. There was a significant relationship between introduced species richness and remnant size with larger remnants supporting more introduced species. There was no significant difference in relative abundance of introduced species in remnants of different sizes. Introduced species, as a proportion of the relative abundance of the total avifauna (native and introduced species), did not vary significantly between remnants of differing sizes. There were significant differences in the composition of introduced bird species between the different remnant sizes, with large remnants supporting significantly different assemblages than medium and small remnants. Other variables also have substantial effects on the abundance of introduced bird species. The lack of significant differences in abundance between remnant sizes suggests they were all equally susceptible to invasion. No patches in the urban matrix are likely to be unaffected by introduced species. The effective long-term control of introduced bird species is difficult and resources may be better spent managing habitat in a way which renders it less suitable for introduced species (e.g. reducing areas of disturbed ground and weed dominated areas).
- Description: C1
- Description: 2003001638
Investigating lebanese primary school teachers’ perceptions of gifted and highly able students
- Antoun, Maya, Kronborg, Leonie, Plunkett, Margaret
- Authors: Antoun, Maya , Kronborg, Leonie , Plunkett, Margaret
- Date: 2020
- Type: Text , Journal article
- Relation: Gifted and Talented International Vol. 35, no.1 (2020), p. 39-57
- Full Text:
- Reviewed:
- Description: This article outlines findings of a study that investigated perceptions of Lebanese primary school teachers in relation to gifted/highly able students. While there are no specific policy or formal school practices for gifted students in Lebanon, education is nonetheless highly regarded. The aim of the study was to determine whether there were cultural differences in the way giftedness in students was perceived and supported by teachers at the primary school level in comparison to Western conceptualizations and provisions. A study utilizing qualitative and quantitative methods underpinned the gathering of data from 281 teachers across three governorates of Lebanon. Of the 281 teachers who completed the survey, 12 also participated in the qualitative component, which involved individual semistructured interviews. Findings suggested a generally positive attitude by teachers but also an acknowledgment of limited awareness of evidence based on Western understandings and practices associated with gifted education. The resultant data provided insights regarding the implementation of effective teacher education and concomitant support to improve identification. © 2020, © 2020 World Council for Gifted and Talented Children.
- Authors: Antoun, Maya , Kronborg, Leonie , Plunkett, Margaret
- Date: 2020
- Type: Text , Journal article
- Relation: Gifted and Talented International Vol. 35, no.1 (2020), p. 39-57
- Full Text:
- Reviewed:
- Description: This article outlines findings of a study that investigated perceptions of Lebanese primary school teachers in relation to gifted/highly able students. While there are no specific policy or formal school practices for gifted students in Lebanon, education is nonetheless highly regarded. The aim of the study was to determine whether there were cultural differences in the way giftedness in students was perceived and supported by teachers at the primary school level in comparison to Western conceptualizations and provisions. A study utilizing qualitative and quantitative methods underpinned the gathering of data from 281 teachers across three governorates of Lebanon. Of the 281 teachers who completed the survey, 12 also participated in the qualitative component, which involved individual semistructured interviews. Findings suggested a generally positive attitude by teachers but also an acknowledgment of limited awareness of evidence based on Western understandings and practices associated with gifted education. The resultant data provided insights regarding the implementation of effective teacher education and concomitant support to improve identification. © 2020, © 2020 World Council for Gifted and Talented Children.
Secure big data ecosystem architecture : challenges and solutions
- Anwar, Memoona, Gill, Asif, Hussain, Farookh, Imran, Muhammad
- Authors: Anwar, Memoona , Gill, Asif , Hussain, Farookh , Imran, Muhammad
- Date: 2021
- Type: Text , Journal article , Review
- Relation: Eurasip Journal on Wireless Communications and Networking Vol. 2021, no. 1 (2021), p.
- Full Text:
- Reviewed:
- Description: Big data ecosystems are complex data-intensive, digital–physical systems. Data-intensive ecosystems offer a number of benefits; however, they present challenges as well. One major challenge is related to the privacy and security. A number of privacy and security models, techniques and algorithms have been proposed over a period of time. The limitation is that these solutions are primarily focused on an individual or on an isolated organizational context. There is a need to study and provide complete end-to-end solutions that ensure security and privacy throughout the data lifecycle across the ecosystem beyond the boundary of an individual system or organizational context. The results of current study provide a review of the existing privacy and security challenges and solutions using the systematic literature review (SLR) approach. Based on the SLR approach, 79 applicable articles were selected and analyzed. The information from these articles was extracted to compile a catalogue of security and privacy challenges in big data ecosystems and to highlight their interdependencies. The results were categorized from theoretical viewpoint using adaptive enterprise architecture and practical viewpoint using DAMA framework as guiding lens. The findings of this research will help to identify the research gaps and draw novel research directions in the context of privacy and security in big data-intensive ecosystems. © 2021, The Author(s).
- Authors: Anwar, Memoona , Gill, Asif , Hussain, Farookh , Imran, Muhammad
- Date: 2021
- Type: Text , Journal article , Review
- Relation: Eurasip Journal on Wireless Communications and Networking Vol. 2021, no. 1 (2021), p.
- Full Text:
- Reviewed:
- Description: Big data ecosystems are complex data-intensive, digital–physical systems. Data-intensive ecosystems offer a number of benefits; however, they present challenges as well. One major challenge is related to the privacy and security. A number of privacy and security models, techniques and algorithms have been proposed over a period of time. The limitation is that these solutions are primarily focused on an individual or on an isolated organizational context. There is a need to study and provide complete end-to-end solutions that ensure security and privacy throughout the data lifecycle across the ecosystem beyond the boundary of an individual system or organizational context. The results of current study provide a review of the existing privacy and security challenges and solutions using the systematic literature review (SLR) approach. Based on the SLR approach, 79 applicable articles were selected and analyzed. The information from these articles was extracted to compile a catalogue of security and privacy challenges in big data ecosystems and to highlight their interdependencies. The results were categorized from theoretical viewpoint using adaptive enterprise architecture and practical viewpoint using DAMA framework as guiding lens. The findings of this research will help to identify the research gaps and draw novel research directions in the context of privacy and security in big data-intensive ecosystems. © 2021, The Author(s).
Regulation of the rabbit's once-daily pattern of nursing : A circadian or hourglass-dependent process?
- Apel, Sabine, Hudson, Robyn, Coleman, Grahame, Rodel, Heiko, Kennedy, Gerard
- Authors: Apel, Sabine , Hudson, Robyn , Coleman, Grahame , Rodel, Heiko , Kennedy, Gerard
- Date: 2020
- Type: Text , Journal article
- Relation: Chronobiology International Vol. 37, no. 8 (2020), p. 1151-1162
- Full Text:
- Reviewed:
- Description: The European rabbitOryctolagus cuniculushas an unusual pattern of nursing behavior. After giving birth in a nursery burrow (or laboratory nest box), the mother immediately leaves the young and only returns to nurse for a few minutes once approximately every 24 h. It has been assumed this schedule, like a variety of other functions in the rabbit, is under circadian control. This assumption has been largely based on findings from mothers only permitted restricted access to their young once every 24 h. However, in nature and in the laboratory, mothers with free access to young show nursing visits with a periodicity shorter than 24 h, that does not correspond to other behavioral and physiological rhythms entrained to the prevailing 24 h light/dark (LD) cycle. To investigate how this unusual, apparently non-circadian pattern might be regulated, we conducted two experiments using female Dutch-belted rabbits housed individually in cages designed to automatically register feeding activity and nest box visits. In Experiment 1 we recorded the behavior of 17 mothers with free access to their young under five different LD cycles with long photo and short scotoperiods, spanning the limits of entrainment of the rabbit's circadian system. Whereas feeding rhythms were entrained by LD cycles within the rabbit's circadian range of entrainment, nursing visits showed a consistently shorter periodicity regardless of the LD regimen, largely independent of the circadian system. In Experiment 2 we tested further 12 mothers under more conventional LD 16:8 cycles but "trained" by having access to the nest box restricted to 1 h at the same time each day for the first 7 d of nursing. Mothers were then allowed free access either when their young were left in the box (n= 6), or when the litter had been permanently removed (n= 6). Mothers with pups still present returned to nurse them on the following days according to a similarly advancing pattern to the mothers of Experiment 1 despite the previous 7 d of "training" to an experimentally enforced 24 h nursing schedule as commonly used in previous studies of rabbit maternal behavior. Mothers whose pups had been removed entered the box repeatedly several times on the first day of unrestricted access, but on subsequent days did so only rarely, and at times of day apparently unrelated to the previously scheduled access. We conclude that the pattern of the rabbit's once-daily nursing visits has a periodicity largely independent of the circadian system, and that this is reset at each nursing. When nursing fails to occur nest box visits cease abruptly, with mothers making few or no subsequent visits. Together, these findings suggest that the rabbit's once-daily pattern of nursing is regulated by an hourglass-type process with a period less than 24 h that is reset at each nursing, rather than by a circadian oscillator. Such a mechanism might be particularly adaptive for rhythms of short duration that should end abruptly with a sudden change in context such as death or weaning of the young.
- Description: This work was supported by the Australian Federal Government via a Postgraduate PhD Scholarship for Sabibe Apel [APA SA 1].
- Authors: Apel, Sabine , Hudson, Robyn , Coleman, Grahame , Rodel, Heiko , Kennedy, Gerard
- Date: 2020
- Type: Text , Journal article
- Relation: Chronobiology International Vol. 37, no. 8 (2020), p. 1151-1162
- Full Text:
- Reviewed:
- Description: The European rabbitOryctolagus cuniculushas an unusual pattern of nursing behavior. After giving birth in a nursery burrow (or laboratory nest box), the mother immediately leaves the young and only returns to nurse for a few minutes once approximately every 24 h. It has been assumed this schedule, like a variety of other functions in the rabbit, is under circadian control. This assumption has been largely based on findings from mothers only permitted restricted access to their young once every 24 h. However, in nature and in the laboratory, mothers with free access to young show nursing visits with a periodicity shorter than 24 h, that does not correspond to other behavioral and physiological rhythms entrained to the prevailing 24 h light/dark (LD) cycle. To investigate how this unusual, apparently non-circadian pattern might be regulated, we conducted two experiments using female Dutch-belted rabbits housed individually in cages designed to automatically register feeding activity and nest box visits. In Experiment 1 we recorded the behavior of 17 mothers with free access to their young under five different LD cycles with long photo and short scotoperiods, spanning the limits of entrainment of the rabbit's circadian system. Whereas feeding rhythms were entrained by LD cycles within the rabbit's circadian range of entrainment, nursing visits showed a consistently shorter periodicity regardless of the LD regimen, largely independent of the circadian system. In Experiment 2 we tested further 12 mothers under more conventional LD 16:8 cycles but "trained" by having access to the nest box restricted to 1 h at the same time each day for the first 7 d of nursing. Mothers were then allowed free access either when their young were left in the box (n= 6), or when the litter had been permanently removed (n= 6). Mothers with pups still present returned to nurse them on the following days according to a similarly advancing pattern to the mothers of Experiment 1 despite the previous 7 d of "training" to an experimentally enforced 24 h nursing schedule as commonly used in previous studies of rabbit maternal behavior. Mothers whose pups had been removed entered the box repeatedly several times on the first day of unrestricted access, but on subsequent days did so only rarely, and at times of day apparently unrelated to the previously scheduled access. We conclude that the pattern of the rabbit's once-daily nursing visits has a periodicity largely independent of the circadian system, and that this is reset at each nursing. When nursing fails to occur nest box visits cease abruptly, with mothers making few or no subsequent visits. Together, these findings suggest that the rabbit's once-daily pattern of nursing is regulated by an hourglass-type process with a period less than 24 h that is reset at each nursing, rather than by a circadian oscillator. Such a mechanism might be particularly adaptive for rhythms of short duration that should end abruptly with a sudden change in context such as death or weaning of the young.
- Description: This work was supported by the Australian Federal Government via a Postgraduate PhD Scholarship for Sabibe Apel [APA SA 1].
To remain, migrate abroad or resettle : a complex dynamic process affecting Pakistani physicians' career decisions
- Arif, Muhammad, Cruickshank, Mary, Fraser, John
- Authors: Arif, Muhammad , Cruickshank, Mary , Fraser, John
- Date: 2019
- Type: Text , Journal article
- Relation: Asia Pacific Journal of Health Management Vol. 14, no. 3 (2019), p.
- Full Text:
- Reviewed:
- Description: OBJECTIVE This study investigated Pakistani physicians' decision-making concerning their decisions to stay in Pakistan, migrate abroad, or resettle back into their country after working abroad. METHODS This qualitative study employed a phenomenological research design. Thirteen Pakistani physicians characterised as 'stayers', 'leavers' and 'resettlers' were interviewed via telephone to explore their lived experience in 2008-2009. RESULTS Results show a dynamic nature of the physicians' career decision-making depending on their constant weighing of complex personal, family, professional and societal factors. Stayers, leavers and resettlers are not mutually exclusive groups but rather individual physicians' can move between these groups at different stages of career and life. Physicians vary in their decision making. Stayers and resettlers place more emphasis on personal and family reasons and societal factors providing there is a permanent job for them. Leavers focus on health system problems and recent societal problems of personal and societal insecurity. CONCLUSIONS The findings of this study indicates that physician migration, retention and resettlement is a complex issue and there are multiple personal, social, political and economic factors that affect their decisions to stay, move abroad or resettle back into their countries. Therefore, it is recommended that future research focusing on health workers retention, migration and resettlement issues look at it from a holistic perspective rather than focusing only on the economic and professional imperatives. The findings of this study have international implications for health care managers dealing with a highly mobile international medical workforce. Strategies considering different stages of the physician career/ life cycle need to highlight the importance of identity, belonging and place as doctors weigh this with career goals. © 2019 Asia Pacific Journal of Health Management. All Rights Reserved.
- Authors: Arif, Muhammad , Cruickshank, Mary , Fraser, John
- Date: 2019
- Type: Text , Journal article
- Relation: Asia Pacific Journal of Health Management Vol. 14, no. 3 (2019), p.
- Full Text:
- Reviewed:
- Description: OBJECTIVE This study investigated Pakistani physicians' decision-making concerning their decisions to stay in Pakistan, migrate abroad, or resettle back into their country after working abroad. METHODS This qualitative study employed a phenomenological research design. Thirteen Pakistani physicians characterised as 'stayers', 'leavers' and 'resettlers' were interviewed via telephone to explore their lived experience in 2008-2009. RESULTS Results show a dynamic nature of the physicians' career decision-making depending on their constant weighing of complex personal, family, professional and societal factors. Stayers, leavers and resettlers are not mutually exclusive groups but rather individual physicians' can move between these groups at different stages of career and life. Physicians vary in their decision making. Stayers and resettlers place more emphasis on personal and family reasons and societal factors providing there is a permanent job for them. Leavers focus on health system problems and recent societal problems of personal and societal insecurity. CONCLUSIONS The findings of this study indicates that physician migration, retention and resettlement is a complex issue and there are multiple personal, social, political and economic factors that affect their decisions to stay, move abroad or resettle back into their countries. Therefore, it is recommended that future research focusing on health workers retention, migration and resettlement issues look at it from a holistic perspective rather than focusing only on the economic and professional imperatives. The findings of this study have international implications for health care managers dealing with a highly mobile international medical workforce. Strategies considering different stages of the physician career/ life cycle need to highlight the importance of identity, belonging and place as doctors weigh this with career goals. © 2019 Asia Pacific Journal of Health Management. All Rights Reserved.
An exploratory study of factors influencing pakistani physicians' retention and resettlement career decisions
- Arif, Muhammad, Fraser, John, Cruickshank, Mary
- Authors: Arif, Muhammad , Fraser, John , Cruickshank, Mary
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Ayub Medical College, Abbottabad : JAMC Vol. 34 , no. 3 (2022), p. S649-S659
- Full Text:
- Reviewed:
- Description: Background: The recruitment, retention and migration of health workers is a global phenomenon. The literature shows push factors associated with leaving rural areas and developing countries in general are explored in depth. However importantly, some health workers behave differently and decide to stay in or return to a developing country. Less is known about the reasons/ pull factors of this groups' decision making. Methods: This paper aims to explore the perceptions of Pakistani physicians regarding their career decisions to remain in their country, or resettle back after working abroad for some time. Thirteen Pakistani physicians were interviewed via telephones who were working in Pakistan and Australia. Results: The motivation for Pakistani physicians to remain or resettle back into their country stems from the perceived better quality of life in Pakistan compared to the better standard of life overseas. Other reasons include a perceived differentiation between locals and non-locals abroad and the availability of a permanent job in Pakistan. Conclusion: The main factors that contributed to Pakistani physicians' retention and resettlement decisions were mostly personal and family or societal factors and there was a minimal role for professional or health system related factors in their career decisions, except for the availability of permanent jobs in Pakistan.
- Authors: Arif, Muhammad , Fraser, John , Cruickshank, Mary
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Ayub Medical College, Abbottabad : JAMC Vol. 34 , no. 3 (2022), p. S649-S659
- Full Text:
- Reviewed:
- Description: Background: The recruitment, retention and migration of health workers is a global phenomenon. The literature shows push factors associated with leaving rural areas and developing countries in general are explored in depth. However importantly, some health workers behave differently and decide to stay in or return to a developing country. Less is known about the reasons/ pull factors of this groups' decision making. Methods: This paper aims to explore the perceptions of Pakistani physicians regarding their career decisions to remain in their country, or resettle back after working abroad for some time. Thirteen Pakistani physicians were interviewed via telephones who were working in Pakistan and Australia. Results: The motivation for Pakistani physicians to remain or resettle back into their country stems from the perceived better quality of life in Pakistan compared to the better standard of life overseas. Other reasons include a perceived differentiation between locals and non-locals abroad and the availability of a permanent job in Pakistan. Conclusion: The main factors that contributed to Pakistani physicians' retention and resettlement decisions were mostly personal and family or societal factors and there was a minimal role for professional or health system related factors in their career decisions, except for the availability of permanent jobs in Pakistan.
Investigating smart home security : is blockchain the answer?
- Arif, Samrah, Khan, M. Arif, Rehman, Sabih, Kabir, Muhammad, Imran, Muhammad
- Authors: Arif, Samrah , Khan, M. Arif , Rehman, Sabih , Kabir, Muhammad , Imran, Muhammad
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 117802-117816
- Full Text:
- Reviewed:
- Description: Smart Home automation is increasingly gaining popularity among current applications of Internet of Things (IoT) due to the convenience and facilities it provides to the home owners. Sensors are employed within the home appliances via wireless connectivity to be accessible remotely by home owners to operate these devices. With the exponential increase of smart home IoT devices in the marketplace such as door locks, light bulbs, power switches etc, numerous security concerns are arising due to limited storage and processing power of such devices, making these devices vulnerable to several attacks. Due to this reason, security implementations in the deployment of these devices has gained popularity among researchers as a critical research area. Moreover, the adoption of traditional security schemes has failed to address the unique security concerns associated with these devices. Blockchain, a decentralised database based on cryptographic techniques, is gaining enormous attention to assure security of IoT systems. The blockchain framework within an IoT system is a fascinating substitute to the traditional centralised models, which has some significant concerns in fulfilling the demand of smart homes security. In this article, we aim to examine the security of smart homes by instigating the adoption of blockchain and exploring some of the currently proposed smart home architectures using blockchain technology. To present our findings, we describe a simple secure smart home framework based on a refined version of blockchain called Consortium blockchain. We highlight the limitations and opportunities of adopting such an architecture. We further evaluate our model and conclude with the results by designing an experimental testbed using a few household IoT devices commonly available in the marketplace. © 2013 IEEE.
- Authors: Arif, Samrah , Khan, M. Arif , Rehman, Sabih , Kabir, Muhammad , Imran, Muhammad
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 117802-117816
- Full Text:
- Reviewed:
- Description: Smart Home automation is increasingly gaining popularity among current applications of Internet of Things (IoT) due to the convenience and facilities it provides to the home owners. Sensors are employed within the home appliances via wireless connectivity to be accessible remotely by home owners to operate these devices. With the exponential increase of smart home IoT devices in the marketplace such as door locks, light bulbs, power switches etc, numerous security concerns are arising due to limited storage and processing power of such devices, making these devices vulnerable to several attacks. Due to this reason, security implementations in the deployment of these devices has gained popularity among researchers as a critical research area. Moreover, the adoption of traditional security schemes has failed to address the unique security concerns associated with these devices. Blockchain, a decentralised database based on cryptographic techniques, is gaining enormous attention to assure security of IoT systems. The blockchain framework within an IoT system is a fascinating substitute to the traditional centralised models, which has some significant concerns in fulfilling the demand of smart homes security. In this article, we aim to examine the security of smart homes by instigating the adoption of blockchain and exploring some of the currently proposed smart home architectures using blockchain technology. To present our findings, we describe a simple secure smart home framework based on a refined version of blockchain called Consortium blockchain. We highlight the limitations and opportunities of adopting such an architecture. We further evaluate our model and conclude with the results by designing an experimental testbed using a few household IoT devices commonly available in the marketplace. © 2013 IEEE.
Real-time big data processing for anomaly detection : a survey
- Ariyaluran Habeeb, Riyaz, Nasaruddin, Fariza, Gani, Abdullah, Targio Hashem, Ibrahim, Ahmed, Ejaz, Imran, Muhammad
- Authors: Ariyaluran Habeeb, Riyaz , Nasaruddin, Fariza , Gani, Abdullah , Targio Hashem, Ibrahim , Ahmed, Ejaz , Imran, Muhammad
- Date: 2019
- Type: Text , Journal article , Review
- Relation: International Journal of Information Management Vol. 45, no. (2019), p. 289-307
- Full Text:
- Reviewed:
- Description: The advent of connected devices and omnipresence of Internet have paved way for intruders to attack networks, which leads to cyber-attack, financial loss, information theft in healthcare, and cyber war. Hence, network security analytics has become an important area of concern and has gained intensive attention among researchers, off late, specifically in the domain of anomaly detection in network, which is considered crucial for network security. However, preliminary investigations have revealed that the existing approaches to detect anomalies in network are not effective enough, particularly to detect them in real time. The reason for the inefficacy of current approaches is mainly due the amassment of massive volumes of data though the connected devices. Therefore, it is crucial to propose a framework that effectively handles real time big data processing and detect anomalies in networks. In this regard, this paper attempts to address the issue of detecting anomalies in real time. Respectively, this paper has surveyed the state-of-the-art real-time big data processing technologies related to anomaly detection and the vital characteristics of associated machine learning algorithms. This paper begins with the explanation of essential contexts and taxonomy of real-time big data processing, anomalous detection, and machine learning algorithms, followed by the review of big data processing technologies. Finally, the identified research challenges of real-time big data processing in anomaly detection are discussed. © 2018 Elsevier Ltd
- Authors: Ariyaluran Habeeb, Riyaz , Nasaruddin, Fariza , Gani, Abdullah , Targio Hashem, Ibrahim , Ahmed, Ejaz , Imran, Muhammad
- Date: 2019
- Type: Text , Journal article , Review
- Relation: International Journal of Information Management Vol. 45, no. (2019), p. 289-307
- Full Text:
- Reviewed:
- Description: The advent of connected devices and omnipresence of Internet have paved way for intruders to attack networks, which leads to cyber-attack, financial loss, information theft in healthcare, and cyber war. Hence, network security analytics has become an important area of concern and has gained intensive attention among researchers, off late, specifically in the domain of anomaly detection in network, which is considered crucial for network security. However, preliminary investigations have revealed that the existing approaches to detect anomalies in network are not effective enough, particularly to detect them in real time. The reason for the inefficacy of current approaches is mainly due the amassment of massive volumes of data though the connected devices. Therefore, it is crucial to propose a framework that effectively handles real time big data processing and detect anomalies in networks. In this regard, this paper attempts to address the issue of detecting anomalies in real time. Respectively, this paper has surveyed the state-of-the-art real-time big data processing technologies related to anomaly detection and the vital characteristics of associated machine learning algorithms. This paper begins with the explanation of essential contexts and taxonomy of real-time big data processing, anomalous detection, and machine learning algorithms, followed by the review of big data processing technologies. Finally, the identified research challenges of real-time big data processing in anomaly detection are discussed. © 2018 Elsevier Ltd
Performance assessment of a solar dryer system using small parabolic dish and alumina/oil nanofluid : simulation and experimental study
- Arkian, Amir, Najafi, Gholamhassan, Gorjian, Shiva, Loni, Reyhaneh, Bellos, Evangelos, Yusaf, Talal
- Authors: Arkian, Amir , Najafi, Gholamhassan , Gorjian, Shiva , Loni, Reyhaneh , Bellos, Evangelos , Yusaf, Talal
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 24 (Dec 2019), p. 22
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- Description: In this study, a small dish concentrator with a cylindrical cavity receiver was experimentally investigated as the heat source of a dryer. The system was examined for operation with pure thermal oil and Al2O3/oil nanofluid as the working fluids in the solar system. Moreover, the design, the development, and the evaluation of the dried mint plant are presented in this work. Also, the solar dryer system was simulated by the SolidWorks and ANSYS CFX software. On the other side, the color histogram of the wet and dried mint samples based on the RGB method was considered. The results revealed that the different temperatures of the solar working fluids at the inlet and outlet of the cavity receiver showed similar trend data compared to the variation of the solar radiation during the experimental test. Moreover, it is found that the cavity heat gain and thermal efficiency of the solar system was improved by using the nanofluid as the solar working fluid. Furthermore, the required time for mint drying had decreased by increasing the drying temperature and increasing air speed. The highest drying time was measured equal to 320 min for the condition of the air speed equal to 0.5 m/s and the drying temperature of 30 degrees C. A good agreement was observed between the calculated numerical results and measured experimental data. Finally, based on the color histogram of the wet and dried mint samples, it was concluded that intensity amount of the red color of the mint increased with the drying process compared to intensity amount of the red color of the wet mint sample.
- Authors: Arkian, Amir , Najafi, Gholamhassan , Gorjian, Shiva , Loni, Reyhaneh , Bellos, Evangelos , Yusaf, Talal
- Date: 2019
- Type: Text , Journal article
- Relation: Energies Vol. 12, no. 24 (Dec 2019), p. 22
- Full Text:
- Reviewed:
- Description: In this study, a small dish concentrator with a cylindrical cavity receiver was experimentally investigated as the heat source of a dryer. The system was examined for operation with pure thermal oil and Al2O3/oil nanofluid as the working fluids in the solar system. Moreover, the design, the development, and the evaluation of the dried mint plant are presented in this work. Also, the solar dryer system was simulated by the SolidWorks and ANSYS CFX software. On the other side, the color histogram of the wet and dried mint samples based on the RGB method was considered. The results revealed that the different temperatures of the solar working fluids at the inlet and outlet of the cavity receiver showed similar trend data compared to the variation of the solar radiation during the experimental test. Moreover, it is found that the cavity heat gain and thermal efficiency of the solar system was improved by using the nanofluid as the solar working fluid. Furthermore, the required time for mint drying had decreased by increasing the drying temperature and increasing air speed. The highest drying time was measured equal to 320 min for the condition of the air speed equal to 0.5 m/s and the drying temperature of 30 degrees C. A good agreement was observed between the calculated numerical results and measured experimental data. Finally, based on the color histogram of the wet and dried mint samples, it was concluded that intensity amount of the red color of the mint increased with the drying process compared to intensity amount of the red color of the wet mint sample.
Feasibility of ANFIS model for prediction of ground vibrations resulting from quarry blasting
- Armaghani, Danial, Momeni, Ehsan, Abad, Seyed, Khandelwal, Manoj
- Authors: Armaghani, Danial , Momeni, Ehsan , Abad, Seyed , Khandelwal, Manoj
- Date: 2015
- Type: Text , Journal article
- Relation: Environmental Earth Sciences Vol. 74, no. 4 (2015), p. 2845-2860
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- Description: One of the most significant environmental issues of blasting operations is ground vibration, which can cause damage to the surrounding residents and structures. Hence, it is a major concern to predict and subsequently control the ground vibration due to blasting. This paper presents two artificial intelligence techniques, namely, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network for the prediction of ground vibration in quarry blasting site. For this purpose, blasting parameters as well as ground vibrations of 109 blasting operations were measured in ISB granite quarry, Johor, Malaysia. Moreover, an empirical equation was also proposed based on the measured data. Several AI-based models were trained and tested using the measured data to determine the optimum models. Each model involved two inputs (maximum charge per delay and distance from the blast-face) and one output (ground vibration). To control capacity performances of the predictive models, the values of root mean squared error (RMSE), value account for (VAF), and coefficient of determination (R2) were computed for each model. It was found that the ANFIS model can provide better performance capacity in predicting ground vibration in comparison with other predictive techniques. The values of 0.973, 0.987 and 97.345 for R2, RMSE and VAF, respectively, reveal that the ANFIS model is capable to predict ground vibration with high degree of accuracy. © 2015, Springer-Verlag Berlin Heidelberg.
- Authors: Armaghani, Danial , Momeni, Ehsan , Abad, Seyed , Khandelwal, Manoj
- Date: 2015
- Type: Text , Journal article
- Relation: Environmental Earth Sciences Vol. 74, no. 4 (2015), p. 2845-2860
- Full Text:
- Reviewed:
- Description: One of the most significant environmental issues of blasting operations is ground vibration, which can cause damage to the surrounding residents and structures. Hence, it is a major concern to predict and subsequently control the ground vibration due to blasting. This paper presents two artificial intelligence techniques, namely, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network for the prediction of ground vibration in quarry blasting site. For this purpose, blasting parameters as well as ground vibrations of 109 blasting operations were measured in ISB granite quarry, Johor, Malaysia. Moreover, an empirical equation was also proposed based on the measured data. Several AI-based models were trained and tested using the measured data to determine the optimum models. Each model involved two inputs (maximum charge per delay and distance from the blast-face) and one output (ground vibration). To control capacity performances of the predictive models, the values of root mean squared error (RMSE), value account for (VAF), and coefficient of determination (R2) were computed for each model. It was found that the ANFIS model can provide better performance capacity in predicting ground vibration in comparison with other predictive techniques. The values of 0.973, 0.987 and 97.345 for R2, RMSE and VAF, respectively, reveal that the ANFIS model is capable to predict ground vibration with high degree of accuracy. © 2015, Springer-Verlag Berlin Heidelberg.
Pathogen genomics in public health
- Armstrong, Gregory, MacCannell, Duncan, Taylor, Jill, Carleton, Heather, Neuhaus, Elizabeth, Bradbury, Richard, Posey, James, Gwinn, Marta
- Authors: Armstrong, Gregory , MacCannell, Duncan , Taylor, Jill , Carleton, Heather , Neuhaus, Elizabeth , Bradbury, Richard , Posey, James , Gwinn, Marta
- Date: 2019
- Type: Text , Journal article
- Relation: New England Journal of Medicine Vol. 381, no. 26 (2019), p. 2569-2580
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- Authors: Armstrong, Gregory , MacCannell, Duncan , Taylor, Jill , Carleton, Heather , Neuhaus, Elizabeth , Bradbury, Richard , Posey, James , Gwinn, Marta
- Date: 2019
- Type: Text , Journal article
- Relation: New England Journal of Medicine Vol. 381, no. 26 (2019), p. 2569-2580
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Burnout, stress and resilience of an Australian regional hospital during COVID-19 : a longitudinal study
- Armstrong, Samantha, Porter, Joanne, Larkins, Jo-Ann, Mesagno, Christopher
- Authors: Armstrong, Samantha , Porter, Joanne , Larkins, Jo-Ann , Mesagno, Christopher
- Date: 2022
- Type: Text , Journal article
- Relation: BMC Health Services Research Vol. 22, no. 1 (2022), p.
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- Description: Coronavirus disease 2019 (COVID-19) has placed huge strain on hospital staff around the world. The aim of the current longitudinal study was to investigate the resilience, stress and burnout of hospital staff located at a large, regional hospital in Victoria, Australia during the COVID-19 pandemic over time via cross-sectional surveys. The surveys were disseminated six times from August 2020 to March 2021, with the first three data collection points distributed during a state-wide lockdown. A total of 558 responses from various professional roles within the hospital over the survey period were included in the sample. Analysis of variance indicated significant main effects for the psychological variables across time, age, and workload. Hospital staff reported an increase in burnout levels throughout the eight-months. Significant negative relationships were observed between resilience and burnout, and between resilience and stress. A backward regression highlighted the contribution of resilience, stress, age, and nursing roles on burnout. Hierarchical regression analysis indicated that resilience contributed to the stress-burnout relationship. This study strengthens the evidence between resilience and burnout among healthcare workers and hospital staff and highlights the need for psychological wellbeing programs to be implemented for hospital staff impacted by a prolonged worldwide pandemic. © 2022, The Author(s).
- Authors: Armstrong, Samantha , Porter, Joanne , Larkins, Jo-Ann , Mesagno, Christopher
- Date: 2022
- Type: Text , Journal article
- Relation: BMC Health Services Research Vol. 22, no. 1 (2022), p.
- Full Text:
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- Description: Coronavirus disease 2019 (COVID-19) has placed huge strain on hospital staff around the world. The aim of the current longitudinal study was to investigate the resilience, stress and burnout of hospital staff located at a large, regional hospital in Victoria, Australia during the COVID-19 pandemic over time via cross-sectional surveys. The surveys were disseminated six times from August 2020 to March 2021, with the first three data collection points distributed during a state-wide lockdown. A total of 558 responses from various professional roles within the hospital over the survey period were included in the sample. Analysis of variance indicated significant main effects for the psychological variables across time, age, and workload. Hospital staff reported an increase in burnout levels throughout the eight-months. Significant negative relationships were observed between resilience and burnout, and between resilience and stress. A backward regression highlighted the contribution of resilience, stress, age, and nursing roles on burnout. Hierarchical regression analysis indicated that resilience contributed to the stress-burnout relationship. This study strengthens the evidence between resilience and burnout among healthcare workers and hospital staff and highlights the need for psychological wellbeing programs to be implemented for hospital staff impacted by a prolonged worldwide pandemic. © 2022, The Author(s).
Burnout, stress and resilience of an Australian regional hospital during COVID-19: a longitudinal study
- Armstrong, Samantha, Porter, Joanne, Larkins, Jo-Ann, Mesagno, Christopher
- Authors: Armstrong, Samantha , Porter, Joanne , Larkins, Jo-Ann , Mesagno, Christopher
- Date: 2022
- Type: Text , Journal article
- Relation: BMC health services research Vol. 22, no. 1 (2022), p. 1-1115
- Full Text:
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- Description: Abstract Coronavirus disease 2019 (COVID-19) has placed huge strain on hospital staff around the world. The aim of the current longitudinal study was to investigate the resilience, stress and burnout of hospital staff located at a large, regional hospital in Victoria, Australia during the COVID-19 pandemic over time via cross-sectional surveys. The surveys were disseminated six times from August 2020 to March 2021, with the first three data collection points distributed during a state-wide lockdown. A total of 558 responses from various professional roles within the hospital over the survey period were included in the sample. Analysis of variance indicated significant main effects for the psychological variables across time, age, and workload. Hospital staff reported an increase in burnout levels throughout the eight-months. Significant negative relationships were observed between resilience and burnout, and between resilience and stress. A backward regression highlighted the contribution of resilience, stress, age, and nursing roles on burnout. Hierarchical regression analysis indicated that resilience contributed to the stress-burnout relationship. This study strengthens the evidence between resilience and burnout among healthcare workers and hospital staff and highlights the need for psychological wellbeing programs to be implemented for hospital staff impacted by a prolonged worldwide pandemic.
- Authors: Armstrong, Samantha , Porter, Joanne , Larkins, Jo-Ann , Mesagno, Christopher
- Date: 2022
- Type: Text , Journal article
- Relation: BMC health services research Vol. 22, no. 1 (2022), p. 1-1115
- Full Text:
- Reviewed:
- Description: Abstract Coronavirus disease 2019 (COVID-19) has placed huge strain on hospital staff around the world. The aim of the current longitudinal study was to investigate the resilience, stress and burnout of hospital staff located at a large, regional hospital in Victoria, Australia during the COVID-19 pandemic over time via cross-sectional surveys. The surveys were disseminated six times from August 2020 to March 2021, with the first three data collection points distributed during a state-wide lockdown. A total of 558 responses from various professional roles within the hospital over the survey period were included in the sample. Analysis of variance indicated significant main effects for the psychological variables across time, age, and workload. Hospital staff reported an increase in burnout levels throughout the eight-months. Significant negative relationships were observed between resilience and burnout, and between resilience and stress. A backward regression highlighted the contribution of resilience, stress, age, and nursing roles on burnout. Hierarchical regression analysis indicated that resilience contributed to the stress-burnout relationship. This study strengthens the evidence between resilience and burnout among healthcare workers and hospital staff and highlights the need for psychological wellbeing programs to be implemented for hospital staff impacted by a prolonged worldwide pandemic.
Global impact of tobacco control policies on smokeless tobacco use: A systematic review protocol
- Arora, Monika, Chugh, Aastha, Jain, Neha, Mishu, Masuma, Rahman, Muhammad Aziz
- Authors: Arora, Monika , Chugh, Aastha , Jain, Neha , Mishu, Masuma , Rahman, Muhammad Aziz
- Date: 2020
- Type: Text , Journal article
- Relation: BMJ Open Vol. 10, no. 12 (2020), p.
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- Description: Introduction Smokeless tobacco (ST) was consumed by 356 million people globally in 2017. Recent evidence shows that ST consumption is responsible for an estimated 652 494 all-cause deaths across the globe annually. The WHO Framework Convention on Tobacco Control (FCTC) was negotiated in 2003 and ratified in 2005 to implement effective tobacco control measures. While the policy measures enacted through various tobacco control laws have been effective in reducing the incidence and prevalence of smoking, the impact of ST-related policies (within WHO FCTC and beyond) on ST use is under-researched and not collated. Methods and analysis A systematic review will be conducted to collate all available ST-related policies implemented across various countries and assess their impact on ST use. The following databases will be searched: Medline, EMBASE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Scopus, EconLit, ISI Web of Science, Cochrane Library (CENTRAL), African Index Medicus, LILACS, Scientific Electronic Library Online, Index Medicus for the Eastern Mediterranean Region, Index Medicus for South-East Asia Region, Western Pacific Region Index Medicus and WHO Library Database, as well as Google search engine and country-specific government websites. All ST-related policy documents (FCTC and non-FCTC) will be included. Results will be limited to literature published since 2005 in English and regional languages (Bengali, Hindi and Urdu). Two reviewers will independently employ two-stage screening to determine inclusion. The Effective Public Health Practice Project's 'Quality Assessment Tool for Quantitative Studies' will be used to record ratings of quality and risk of bias among studies selected for inclusion. Data will be extracted using a standardised form. Meta-analysis and narrative synthesis will be used. Ethics and dissemination Permission for ethics exemption of the review was obtained from the Centre for Chronic Disease Control's Institutional Ethics Committee, India (CCDC-IEC-06-2020; dated 16 April 2020). The results will be disseminated through publications in a peer-reviewed journal and will be presented in national and international conferences. PROSPERO registration number CRD42020191946. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Aziz Rahman” is provided in this record**
- Authors: Arora, Monika , Chugh, Aastha , Jain, Neha , Mishu, Masuma , Rahman, Muhammad Aziz
- Date: 2020
- Type: Text , Journal article
- Relation: BMJ Open Vol. 10, no. 12 (2020), p.
- Full Text:
- Reviewed:
- Description: Introduction Smokeless tobacco (ST) was consumed by 356 million people globally in 2017. Recent evidence shows that ST consumption is responsible for an estimated 652 494 all-cause deaths across the globe annually. The WHO Framework Convention on Tobacco Control (FCTC) was negotiated in 2003 and ratified in 2005 to implement effective tobacco control measures. While the policy measures enacted through various tobacco control laws have been effective in reducing the incidence and prevalence of smoking, the impact of ST-related policies (within WHO FCTC and beyond) on ST use is under-researched and not collated. Methods and analysis A systematic review will be conducted to collate all available ST-related policies implemented across various countries and assess their impact on ST use. The following databases will be searched: Medline, EMBASE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Scopus, EconLit, ISI Web of Science, Cochrane Library (CENTRAL), African Index Medicus, LILACS, Scientific Electronic Library Online, Index Medicus for the Eastern Mediterranean Region, Index Medicus for South-East Asia Region, Western Pacific Region Index Medicus and WHO Library Database, as well as Google search engine and country-specific government websites. All ST-related policy documents (FCTC and non-FCTC) will be included. Results will be limited to literature published since 2005 in English and regional languages (Bengali, Hindi and Urdu). Two reviewers will independently employ two-stage screening to determine inclusion. The Effective Public Health Practice Project's 'Quality Assessment Tool for Quantitative Studies' will be used to record ratings of quality and risk of bias among studies selected for inclusion. Data will be extracted using a standardised form. Meta-analysis and narrative synthesis will be used. Ethics and dissemination Permission for ethics exemption of the review was obtained from the Centre for Chronic Disease Control's Institutional Ethics Committee, India (CCDC-IEC-06-2020; dated 16 April 2020). The results will be disseminated through publications in a peer-reviewed journal and will be presented in national and international conferences. PROSPERO registration number CRD42020191946. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Aziz Rahman” is provided in this record**
The relationship between smoking status and smoking cessation practice for health workers in Surabaya
- Artanti, Kurnia, Martini, Santi, Mahmudah, Mahmudah, Widati, Sri, Adila, Diva, Rahman, Muhammad Aziz
- Authors: Artanti, Kurnia , Martini, Santi , Mahmudah, Mahmudah , Widati, Sri , Adila, Diva , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Public Health in Africa Vol. 14, no. S2 (2023), p.
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- Description: Background. Indonesia is one of the countries that have a high smoker prevalence globally. Therefore, a smoking cessation pro- gram is key to reducing the smoking prevalence in Indonesia. The role of health workers is necessary for smoking cessation pro-grams. However, smoking behavior among health workers could limit smoking cessation practices for patients. Objective. This study aims to analyze smoking behavior and 5A smoking cessation (Ask, Advice, Assess, Assist, and Arrange) practices among health workers. Materials and Methods. This study design is cross-sectional with a simple random sampling from the population of health workers in Surabaya. The total sample of this study counted 60 health workers. The data were analyzed in univariate and bivariate using SPSS 18 application. Bivariate analysis using a chi-square or Fisher exact test was conducted to analyze the relationship between smoking status and 5A smoking cessation practice. Results. Report of main outcomes or findings, including (where relevant) levels of statistical significance and confidence intervals. The result of this study shows that the asking practice was the most practiced item in the 5A model among health workers (98.3%). There was no significant association between smoking behavior and 5A implementation among health workers (PR=0.40; 95%CI: 0.52-5.30; P=1.67). Conclusions. There was no significant association between respondents’ characteristics, smoking cessation training, and pro-fessional roles with 5A implementation. © the Author(s), 2023.
- Authors: Artanti, Kurnia , Martini, Santi , Mahmudah, Mahmudah , Widati, Sri , Adila, Diva , Rahman, Muhammad Aziz
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Public Health in Africa Vol. 14, no. S2 (2023), p.
- Full Text:
- Reviewed:
- Description: Background. Indonesia is one of the countries that have a high smoker prevalence globally. Therefore, a smoking cessation pro- gram is key to reducing the smoking prevalence in Indonesia. The role of health workers is necessary for smoking cessation pro-grams. However, smoking behavior among health workers could limit smoking cessation practices for patients. Objective. This study aims to analyze smoking behavior and 5A smoking cessation (Ask, Advice, Assess, Assist, and Arrange) practices among health workers. Materials and Methods. This study design is cross-sectional with a simple random sampling from the population of health workers in Surabaya. The total sample of this study counted 60 health workers. The data were analyzed in univariate and bivariate using SPSS 18 application. Bivariate analysis using a chi-square or Fisher exact test was conducted to analyze the relationship between smoking status and 5A smoking cessation practice. Results. Report of main outcomes or findings, including (where relevant) levels of statistical significance and confidence intervals. The result of this study shows that the asking practice was the most practiced item in the 5A model among health workers (98.3%). There was no significant association between smoking behavior and 5A implementation among health workers (PR=0.40; 95%CI: 0.52-5.30; P=1.67). Conclusions. There was no significant association between respondents’ characteristics, smoking cessation training, and pro-fessional roles with 5A implementation. © the Author(s), 2023.
Prediction of blast-induced ground vibration at a limestone quarry : an artificial intelligence approach
- Arthur, Clement, Bhatawdekar, Ramesh, Mohamad, Edy, Sabri, Mohanad, Bohra, Manish, Khandelwal, Manoj, Kwon, Sangki
- Authors: Arthur, Clement , Bhatawdekar, Ramesh , Mohamad, Edy , Sabri, Mohanad , Bohra, Manish , Khandelwal, Manoj , Kwon, Sangki
- Date: 2022
- Type: Text , Journal article
- Relation: Applied Sciences (Switzerland) Vol. 12, no. 18 (2022), p.
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- Reviewed:
- Description: Ground vibration is one of the most unfavourable environmental effects of blasting activities, which can cause serious damage to neighboring homes and structures. As a result, effective forecasting of their severity is critical to controlling and reducing their recurrence. There are several conventional vibration predictor equations available proposed by different researchers but most of them are based on only two parameters, i.e., explosive charge used per delay and distance between blast face to the monitoring point. It is a well-known fact that blasting results are influenced by a number of blast design parameters, such as burden, spacing, powder factor, etc. but these are not being considered in any of the available conventional predictors and due to that they show a high error in predicting blast vibrations. Nowadays, artificial intelligence has been widely used in blast engineering. Thus, three artificial intelligence approaches, namely Gaussian process regression (GPR), extreme learning machine (ELM) and backpropagation neural network (BPNN) were used in this study to estimate ground vibration caused by blasting in Shree Cement Ras Limestone Mine in India. To achieve that aim, 101 blasting datasets with powder factor, average depth, distance, spacing, burden, charge weight, and stemming length as input parameters were collected from the mine site. For comparison purposes, a simple multivariate regression analysis (MVRA) model as well as, a nonparametric regression-based technique known as multivariate adaptive regression splines (MARS) was also constructed using the same datasets. This study serves as a foundational study for the comparison of GPR, BPNN, ELM, MARS and MVRA to ascertain their respective predictive performances. Eighty-one (81) datasets representing 80% of the total blasting datasets were used to construct and train the various predictive models while 20 data samples (20%) were utilized for evaluating the predictive capabilities of the developed predictive models. Using the testing datasets, major indicators of performance, namely mean squared error (MSE), variance accounted for (VAF), correlation coefficient (R) and coefficient of determination (R2) were compared as statistical evaluators of model performance. This study revealed that the GPR model exhibited superior predictive capability in comparison to the MARS, BPNN, ELM and MVRA. The GPR model showed the highest VAF, R and R2 values of 99.1728%, 0.9985 and 0.9971 respectively and the lowest MSE of 0.0903. As a result, the blast engineer can employ GPR as an effective and appropriate method for forecasting blast-induced ground vibration. © 2022 by the authors.
- Authors: Arthur, Clement , Bhatawdekar, Ramesh , Mohamad, Edy , Sabri, Mohanad , Bohra, Manish , Khandelwal, Manoj , Kwon, Sangki
- Date: 2022
- Type: Text , Journal article
- Relation: Applied Sciences (Switzerland) Vol. 12, no. 18 (2022), p.
- Full Text:
- Reviewed:
- Description: Ground vibration is one of the most unfavourable environmental effects of blasting activities, which can cause serious damage to neighboring homes and structures. As a result, effective forecasting of their severity is critical to controlling and reducing their recurrence. There are several conventional vibration predictor equations available proposed by different researchers but most of them are based on only two parameters, i.e., explosive charge used per delay and distance between blast face to the monitoring point. It is a well-known fact that blasting results are influenced by a number of blast design parameters, such as burden, spacing, powder factor, etc. but these are not being considered in any of the available conventional predictors and due to that they show a high error in predicting blast vibrations. Nowadays, artificial intelligence has been widely used in blast engineering. Thus, three artificial intelligence approaches, namely Gaussian process regression (GPR), extreme learning machine (ELM) and backpropagation neural network (BPNN) were used in this study to estimate ground vibration caused by blasting in Shree Cement Ras Limestone Mine in India. To achieve that aim, 101 blasting datasets with powder factor, average depth, distance, spacing, burden, charge weight, and stemming length as input parameters were collected from the mine site. For comparison purposes, a simple multivariate regression analysis (MVRA) model as well as, a nonparametric regression-based technique known as multivariate adaptive regression splines (MARS) was also constructed using the same datasets. This study serves as a foundational study for the comparison of GPR, BPNN, ELM, MARS and MVRA to ascertain their respective predictive performances. Eighty-one (81) datasets representing 80% of the total blasting datasets were used to construct and train the various predictive models while 20 data samples (20%) were utilized for evaluating the predictive capabilities of the developed predictive models. Using the testing datasets, major indicators of performance, namely mean squared error (MSE), variance accounted for (VAF), correlation coefficient (R) and coefficient of determination (R2) were compared as statistical evaluators of model performance. This study revealed that the GPR model exhibited superior predictive capability in comparison to the MARS, BPNN, ELM and MVRA. The GPR model showed the highest VAF, R and R2 values of 99.1728%, 0.9985 and 0.9971 respectively and the lowest MSE of 0.0903. As a result, the blast engineer can employ GPR as an effective and appropriate method for forecasting blast-induced ground vibration. © 2022 by the authors.
Managing the resource allocation for the COVID-19 pandemic in healthcare institutions : a pluralistic perspective
- Arunmozhi, Manimuthu, Persis, Jinil, Sreedharan, V., Chakraborty, Ayon, Zouadi, Tarik, Khamlichi, Hanane
- Authors: Arunmozhi, Manimuthu , Persis, Jinil , Sreedharan, V. , Chakraborty, Ayon , Zouadi, Tarik , Khamlichi, Hanane
- Date: 2022
- Type: Text , Journal article
- Relation: International Journal of Quality and Reliability Management Vol. 39, no. 9 (2022), p. 2184-2204
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- Description: Purpose: As COVID-19 outbreak has created a global crisis, treating patients with minimum resources and traditional methods has become a hectic task. In this technological era, the rapid growth of coronavirus has affected the countries in lightspeed manner. Therefore, the present study proposes a model to analyse the resource allocation for the COVID-19 pandemic from a pluralistic perspective. Design/methodology/approach: The present study has combined data analytics with the K-mean clustering and probability queueing theory (PQT) and analysed the evolution of COVID-19 all over the world from the data obtained from public repositories. By using K-mean clustering, partitioning of patients’ records along with their status of hospitalization can be mapped and clustered. After K-mean analysis, cluster functions are trained and modelled along with eigen vectors and eigen functions. Findings: After successful iterative training, the model is programmed using R functions and given as input to Bayesian filter for predictive model analysis. Through the proposed model, disposal rate; PPE (personal protective equipment) utilization and recycle rate for different countries were calculated. Research limitations/implications: Using probabilistic queueing theory and clustering, the study was able to predict the resource allocation for patients. Also, the study has tried to model the failure quotient ratio upon unsuccessful delivery rate in crisis condition. Practical implications: The study has gathered epidemiological and clinical data from various government websites and research laboratories. Using these data, the study has identified the COVID-19 impact in various countries. Further, effective decision-making for resource allocation in pluralistic setting has being evaluated for the practitioner's reference. Originality/value: Further, the proposed model is a two-stage approach for vulnerability mapping in a pandemic situation in a healthcare setting for resource allocation and utilization. © 2021, Emerald Publishing Limited.
- Authors: Arunmozhi, Manimuthu , Persis, Jinil , Sreedharan, V. , Chakraborty, Ayon , Zouadi, Tarik , Khamlichi, Hanane
- Date: 2022
- Type: Text , Journal article
- Relation: International Journal of Quality and Reliability Management Vol. 39, no. 9 (2022), p. 2184-2204
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- Description: Purpose: As COVID-19 outbreak has created a global crisis, treating patients with minimum resources and traditional methods has become a hectic task. In this technological era, the rapid growth of coronavirus has affected the countries in lightspeed manner. Therefore, the present study proposes a model to analyse the resource allocation for the COVID-19 pandemic from a pluralistic perspective. Design/methodology/approach: The present study has combined data analytics with the K-mean clustering and probability queueing theory (PQT) and analysed the evolution of COVID-19 all over the world from the data obtained from public repositories. By using K-mean clustering, partitioning of patients’ records along with their status of hospitalization can be mapped and clustered. After K-mean analysis, cluster functions are trained and modelled along with eigen vectors and eigen functions. Findings: After successful iterative training, the model is programmed using R functions and given as input to Bayesian filter for predictive model analysis. Through the proposed model, disposal rate; PPE (personal protective equipment) utilization and recycle rate for different countries were calculated. Research limitations/implications: Using probabilistic queueing theory and clustering, the study was able to predict the resource allocation for patients. Also, the study has tried to model the failure quotient ratio upon unsuccessful delivery rate in crisis condition. Practical implications: The study has gathered epidemiological and clinical data from various government websites and research laboratories. Using these data, the study has identified the COVID-19 impact in various countries. Further, effective decision-making for resource allocation in pluralistic setting has being evaluated for the practitioner's reference. Originality/value: Further, the proposed model is a two-stage approach for vulnerability mapping in a pandemic situation in a healthcare setting for resource allocation and utilization. © 2021, Emerald Publishing Limited.
Global lessons from successful rhinoceros conservation in Nepal
- Aryal, Achyut, Acharya, Krishna, Shrestha, Uttam Babu, Dhakal, Maheshwar, Raubenhiemer, David, Wright, Wendy
- Authors: Aryal, Achyut , Acharya, Krishna , Shrestha, Uttam Babu , Dhakal, Maheshwar , Raubenhiemer, David , Wright, Wendy
- Date: 2017
- Type: Text , Journal article
- Relation: Conservation Biology Vol. 31, no. 6 (2017), p. 1494-1497
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- Authors: Aryal, Achyut , Acharya, Krishna , Shrestha, Uttam Babu , Dhakal, Maheshwar , Raubenhiemer, David , Wright, Wendy
- Date: 2017
- Type: Text , Journal article
- Relation: Conservation Biology Vol. 31, no. 6 (2017), p. 1494-1497
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