Objective:This study has the objective to offer a thorough overview of the current state and future research possibilities regarding the social stigma of tuberculosis(TB).Given the growing volume and variety of resear...Objective:This study has the objective to offer a thorough overview of the current state and future research possibilities regarding the social stigma of tuberculosis(TB).Given the growing volume and variety of research in this field,a quantitative approach is essential for mapping existing themes and pinpointing potential areas for further investigation.To accomplish this,a bibliometric and content analysis was performed to explore the current literature and emphasize key themes and future directions.Methods:The study examines 770 bibliographic records from Scopus and visualizes the results of the bibliometric analysis using co-occurrence and thematic map analyses with VOSviewer and Tableau Public software.Additionally,a content analysis was conducted based on the findings from the co-occurrence analysis.Results:The findings indicate a notable rise in publications and citations related to the social stigma of TB,with prominent research topics including healthcare workers,social support,mobile health technology(mHealth),nursing,and attitudes.Emerging areas of research encompass epidemiology,public health,patient delays,multidrug-resistant TB(MDR-TB),corona virus disease 2019,and mHealth.Future studies might concentrate on the factors leading to patient delays,as well as the development of diagnostic tools and effective treatment regimens for MDR-TB cases.Conclusion:This study offers important insights into the current state of social stigma in TB research and identifies promising areas for future investigation.By addressing these research gaps and refining methodological approaches,researchers can strengthen initiatives to combat TB stigma,ultimately resulting in more effective treatments and improved adherence among TB patients.展开更多
For a non-relativistic particle that freely moves on a curved surface, the fundamental commutation relations between positions and momenta are insufficient to uniquely determine the operator form of the momenta. With ...For a non-relativistic particle that freely moves on a curved surface, the fundamental commutation relations between positions and momenta are insufficient to uniquely determine the operator form of the momenta. With introduc- tion of more commutation relations between positions and Hamiltonian and those between momenta and Hamiltonian, our recent sequential studies imply that the Cartesian system of coordinates is physically preferable, consistent with Dirae＇s observation. In present paper, we study quantization problem of the motion constrained on the two-dimensional sphere and develop a discriminant that can be used to show how the quantization within the intrinsic geometry is im- proper. Two kinds of parameterization of the spherical surface are explicitly invoked to investigate the quantization problem within the intrinsic geometry.展开更多
This research addresses the design of intensity-curvature functional(ICF)based digital high pass filter(HPF).ICF is calculated from bivariate cubic B-spline model polynomial function and is called ICF-based HPF.In ord...This research addresses the design of intensity-curvature functional(ICF)based digital high pass filter(HPF).ICF is calculated from bivariate cubic B-spline model polynomial function and is called ICF-based HPF.In order to calculate ICF,the model function needs to be second order differentiable and to have non-null classic-curvature calculated at the origin(0,0)of the pixel coordinate system.The theoretical basis of this research is called intensitycurvature concept.The concept envisions to replace signal intensity with the product between signal intensity and sum of second order partial derivatives of the model function.Extrapolation of the concept in two-dimensions(2D)makes it possible to calculate the ICF of an image.Theoretical treatise is presented to demonstrate the hypothesis that ICF is HPF signal.Empirical evidence then validates the assumption and also extends the comparison between ICF-based HPF and ten different HPFs among which is traditional HPF and particle swarm optimization(PSO)based HPF.Through comparison of image space and k-space magnitude,results indicate that HPFs behave differently.Traditional HPF filtering and ICF-based filtering are superior to PSO-based filtering.Images filtered with traditional HPF are sharper than images filtered with ICF-based filter.The contribution of this research can be summarized as follows:(1)Math description of the constraints that ICF need to obey to in order to function as HPF;(2)Math of ICF-based HPF of bivariate cubic B-spline;(3)Image space comparisons between HPFs;(4)K-space magnitude comparisons between HPFs.This research provides confirmation on the math procedure to use in order to design 2D HPF from a model bivariate polynomial function.展开更多
Purpose: This paper relates the definition of data quality procedures for knowledge organizations such as Higher Education Institutions. The main purpose is to present the flexible approach developed for monitoring th...Purpose: This paper relates the definition of data quality procedures for knowledge organizations such as Higher Education Institutions. The main purpose is to present the flexible approach developed for monitoring the data quality of the European Tertiary Education Register(ETER) database, illustrating its functioning and highlighting the main challenges that still have to be faced in this domain.Design/methodology/approach: The proposed data quality methodology is based on two kinds of checks, one to assess the consistency of cross-sectional data and the other to evaluate the stability of multiannual data. This methodology has an operational and empirical orientation. This means that the proposed checks do not assume any theoretical distribution for the determination of the threshold parameters that identify potential outliers, inconsistencies, and errors in the data. Findings: We show that the proposed cross-sectional checks and multiannual checks are helpful to identify outliers, extreme observations and to detect ontological inconsistencies not described in the available meta-data. For this reason, they may be a useful complement to integrate the processing of the available information.Research limitations: The coverage of the study is limited to European Higher Education Institutions. The cross-sectional and multiannual checks are not yet completely integrated.Practical implications: The consideration of the quality of the available data and information is important to enhance data quality-aware empirical investigations, highlighting problems, and areas where to invest for improving the coverage and interoperability of data in future data collection initiatives.Originality/value: The data-driven quality checks proposed in this paper may be useful as a reference for building and monitoring the data quality of new databases or of existing databases available for other countries or systems characterized by high heterogeneity and complexity of the units of analysis without relying on pre-specified theoretical distributions.展开更多
Mobbing has been defined as a chronic asymmetric pattern of power relations and a consequent conflict transformed into a systematic discrimination or mistreatment at workplace which is expressed through unethical or a...Mobbing has been defined as a chronic asymmetric pattern of power relations and a consequent conflict transformed into a systematic discrimination or mistreatment at workplace which is expressed through unethical or aggressive communication （Leynman, 1996）. Mobbing occurs when an employee in the workplace is steadily subjected to aggressive behavior from more than one colleague or supervisor over a period of time, in a situation where the target finds it difficult to defend him/herself to escape this dire situation. Such a long term incivility tends to stigmatize the mobbed victim and may cause severe psychological trauma since （s）he is metaphorically in a straitjacket. In this double-bind and double-squeeze condition where （s）he can neither get out of the situation nor endure the ordeal, a positive outcome is unlikely. How do we differentiate mobbing from conflict in organizations and how are disputes converted into mobbing behavior, and if one may even do research on mobbing in a culture of＂organizational silence＂ and ＂obedience/submission＂ in a developing country will be the first theoretical research question. Whether systemic silence as a collective level phenomenon is not only an obstacle to healthy organizational communication and relationships, but also a serious barrier to development, participation and learning from malpractices is another relevant question. Most researches investigating the background of mobbing are based on either experiences of targets as victims or the critical cases including the perpetrators as mobber; Therefore, the findings are often at individual level and subjective. They are often ＂ex post facto＂ analysis of psychological dimensions （e.g., personality characteristics of mostly of mobbed victims and rarely of mobbers） or legal dimensions. There are few ＂ex ante＂ analyses of organizational culture dimensions so that preventive measures may be taken prior to any serious mobbing case is reported. This paper＇s objective is to approach mobbing as a function of group conflict and rumor that is uncontrolled for a long time. By exploring the background of mobbing in ten companies from service sector in IstanbuI-Turkey, this view is assessed. The findings confirmed that mobbing is a function of relational conflict and gossip particularly in companies with high positional power distance and highly centralized decision-making where high power imbalance between supervisors and subordinates are salient. Such organizations seem to be more conducive to concealed mobbing and survival than to development and participation of employees as ＂modus operandi＂.展开更多
Big data is a term that refers to a set of data that,due to its largeness or complexity,cannot be stored or processed with one of the usual tools or applications for data management,and it has become a prominent word ...Big data is a term that refers to a set of data that,due to its largeness or complexity,cannot be stored or processed with one of the usual tools or applications for data management,and it has become a prominent word in recent years for the massive development of technology.Almost immediately thereafter,the term“big data mining”emerged,i.e.,mining from big data even as an emerging and interconnected field of research.Classification is an important stage in data mining since it helps people make better decisions in a variety of situations,including scientific endeavors,biomedical research,and industrial applications.The probabilistic neural network(PNN)is a commonly used and successful method for handling classification and pattern recognition issues.In this study,the authors proposed to combine the probabilistic neural network(PPN),which is one of the data mining techniques,with the vibrating particles system(VPS),which is one of the metaheuristic algorithms named“VPS-PNN”,to solve classi-fication problems more effectively.The data set is eleven common benchmark medical datasets from the machine-learning library,the suggested method was tested.The suggested VPS-PNN mechanism outperforms the PNN,biogeography-based optimization,enhanced-water cycle algorithm(E-WCA)and the firefly algorithm(FA)in terms of convergence speed and classification accuracy.展开更多
Objective Decision fatigue(DF)can lead to impaired judgement,decreased diagnostic accuracy and increased likelihood of medical errors.Research on DF is scarce,and little is known about its nature in the clinical conte...Objective Decision fatigue(DF)can lead to impaired judgement,decreased diagnostic accuracy and increased likelihood of medical errors.Research on DF is scarce,and little is known about its nature in the clinical context.The objective of the present review was to provide a comprehensive framework to understand how the construct of DF in medical settings has been defined and measured.This review aimed to understand DF determinants and consequences and capture motivational factors overlooked in the existing reviews.Design Systematic and scoping review(ScR)with meta-synthesis.Eligibility criteria Empirical and non-empirical papers on clinical DF or related constructs directly impacting clinical decision-making were considered,with doctors of all ages,sexes and nationalities as participants.The Preferred Reporting Item for Systematic Reviews and Meta-analyses scoping review checklist has been applied and checked.Information sources Six databases were systematically searched by two independent researchers according to a predefined set of keywords.Results 43 papers were included,of which 25 were empirical.The quantitative studies outnumber the qualitative ones and primarily involved residents in Europe/UK and North America.Internal medicine and primary care were the most studied disciplines.Only one sequential cross-sectional study measured DF in the medical setting,and all other studies addressed the construct indirectly.A conceptual analysis of clinical DF,including narrative contributions,a thematic analysis of the data extracted and a meta-synthesis,is provided.Clinical DF was investigated mostly by individual risk factors analysed through multiple intertwined determinants involving cognitive,emotional,behavioural,social and ethical aspects.Relevant risks,protective factors and negative outcomes circularly increasing DF are outlined.Conclusions The review gives solid arguments for developing a clear and coherent definition of clinical DF that allows the implementation of preventive targeted intervention.展开更多
文摘Objective:This study has the objective to offer a thorough overview of the current state and future research possibilities regarding the social stigma of tuberculosis(TB).Given the growing volume and variety of research in this field,a quantitative approach is essential for mapping existing themes and pinpointing potential areas for further investigation.To accomplish this,a bibliometric and content analysis was performed to explore the current literature and emphasize key themes and future directions.Methods:The study examines 770 bibliographic records from Scopus and visualizes the results of the bibliometric analysis using co-occurrence and thematic map analyses with VOSviewer and Tableau Public software.Additionally,a content analysis was conducted based on the findings from the co-occurrence analysis.Results:The findings indicate a notable rise in publications and citations related to the social stigma of TB,with prominent research topics including healthcare workers,social support,mobile health technology(mHealth),nursing,and attitudes.Emerging areas of research encompass epidemiology,public health,patient delays,multidrug-resistant TB(MDR-TB),corona virus disease 2019,and mHealth.Future studies might concentrate on the factors leading to patient delays,as well as the development of diagnostic tools and effective treatment regimens for MDR-TB cases.Conclusion:This study offers important insights into the current state of social stigma in TB research and identifies promising areas for future investigation.By addressing these research gaps and refining methodological approaches,researchers can strengthen initiatives to combat TB stigma,ultimately resulting in more effective treatments and improved adherence among TB patients.
基金Supported by the National Natural Science Foundation of China under Grant No.11175063
文摘For a non-relativistic particle that freely moves on a curved surface, the fundamental commutation relations between positions and momenta are insufficient to uniquely determine the operator form of the momenta. With introduc- tion of more commutation relations between positions and Hamiltonian and those between momenta and Hamiltonian, our recent sequential studies imply that the Cartesian system of coordinates is physically preferable, consistent with Dirae＇s observation. In present paper, we study quantization problem of the motion constrained on the two-dimensional sphere and develop a discriminant that can be used to show how the quantization within the intrinsic geometry is im- proper. Two kinds of parameterization of the spherical surface are explicitly invoked to investigate the quantization problem within the intrinsic geometry.
文摘This research addresses the design of intensity-curvature functional(ICF)based digital high pass filter(HPF).ICF is calculated from bivariate cubic B-spline model polynomial function and is called ICF-based HPF.In order to calculate ICF,the model function needs to be second order differentiable and to have non-null classic-curvature calculated at the origin(0,0)of the pixel coordinate system.The theoretical basis of this research is called intensitycurvature concept.The concept envisions to replace signal intensity with the product between signal intensity and sum of second order partial derivatives of the model function.Extrapolation of the concept in two-dimensions(2D)makes it possible to calculate the ICF of an image.Theoretical treatise is presented to demonstrate the hypothesis that ICF is HPF signal.Empirical evidence then validates the assumption and also extends the comparison between ICF-based HPF and ten different HPFs among which is traditional HPF and particle swarm optimization(PSO)based HPF.Through comparison of image space and k-space magnitude,results indicate that HPFs behave differently.Traditional HPF filtering and ICF-based filtering are superior to PSO-based filtering.Images filtered with traditional HPF are sharper than images filtered with ICF-based filter.The contribution of this research can be summarized as follows:(1)Math description of the constraints that ICF need to obey to in order to function as HPF;(2)Math of ICF-based HPF of bivariate cubic B-spline;(3)Image space comparisons between HPFs;(4)K-space magnitude comparisons between HPFs.This research provides confirmation on the math procedure to use in order to design 2D HPF from a model bivariate polynomial function.
基金support of the European Commission ETER Project (No. 934533-2017-AO8-CH)H2020 RISIS 2 project (No. 824091)。
文摘Purpose: This paper relates the definition of data quality procedures for knowledge organizations such as Higher Education Institutions. The main purpose is to present the flexible approach developed for monitoring the data quality of the European Tertiary Education Register(ETER) database, illustrating its functioning and highlighting the main challenges that still have to be faced in this domain.Design/methodology/approach: The proposed data quality methodology is based on two kinds of checks, one to assess the consistency of cross-sectional data and the other to evaluate the stability of multiannual data. This methodology has an operational and empirical orientation. This means that the proposed checks do not assume any theoretical distribution for the determination of the threshold parameters that identify potential outliers, inconsistencies, and errors in the data. Findings: We show that the proposed cross-sectional checks and multiannual checks are helpful to identify outliers, extreme observations and to detect ontological inconsistencies not described in the available meta-data. For this reason, they may be a useful complement to integrate the processing of the available information.Research limitations: The coverage of the study is limited to European Higher Education Institutions. The cross-sectional and multiannual checks are not yet completely integrated.Practical implications: The consideration of the quality of the available data and information is important to enhance data quality-aware empirical investigations, highlighting problems, and areas where to invest for improving the coverage and interoperability of data in future data collection initiatives.Originality/value: The data-driven quality checks proposed in this paper may be useful as a reference for building and monitoring the data quality of new databases or of existing databases available for other countries or systems characterized by high heterogeneity and complexity of the units of analysis without relying on pre-specified theoretical distributions.
文摘Mobbing has been defined as a chronic asymmetric pattern of power relations and a consequent conflict transformed into a systematic discrimination or mistreatment at workplace which is expressed through unethical or aggressive communication （Leynman, 1996）. Mobbing occurs when an employee in the workplace is steadily subjected to aggressive behavior from more than one colleague or supervisor over a period of time, in a situation where the target finds it difficult to defend him/herself to escape this dire situation. Such a long term incivility tends to stigmatize the mobbed victim and may cause severe psychological trauma since （s）he is metaphorically in a straitjacket. In this double-bind and double-squeeze condition where （s）he can neither get out of the situation nor endure the ordeal, a positive outcome is unlikely. How do we differentiate mobbing from conflict in organizations and how are disputes converted into mobbing behavior, and if one may even do research on mobbing in a culture of＂organizational silence＂ and ＂obedience/submission＂ in a developing country will be the first theoretical research question. Whether systemic silence as a collective level phenomenon is not only an obstacle to healthy organizational communication and relationships, but also a serious barrier to development, participation and learning from malpractices is another relevant question. Most researches investigating the background of mobbing are based on either experiences of targets as victims or the critical cases including the perpetrators as mobber; Therefore, the findings are often at individual level and subjective. They are often ＂ex post facto＂ analysis of psychological dimensions （e.g., personality characteristics of mostly of mobbed victims and rarely of mobbers） or legal dimensions. There are few ＂ex ante＂ analyses of organizational culture dimensions so that preventive measures may be taken prior to any serious mobbing case is reported. This paper＇s objective is to approach mobbing as a function of group conflict and rumor that is uncontrolled for a long time. By exploring the background of mobbing in ten companies from service sector in IstanbuI-Turkey, this view is assessed. The findings confirmed that mobbing is a function of relational conflict and gossip particularly in companies with high positional power distance and highly centralized decision-making where high power imbalance between supervisors and subordinates are salient. Such organizations seem to be more conducive to concealed mobbing and survival than to development and participation of employees as ＂modus operandi＂.
文摘Big data is a term that refers to a set of data that,due to its largeness or complexity,cannot be stored or processed with one of the usual tools or applications for data management,and it has become a prominent word in recent years for the massive development of technology.Almost immediately thereafter,the term“big data mining”emerged,i.e.,mining from big data even as an emerging and interconnected field of research.Classification is an important stage in data mining since it helps people make better decisions in a variety of situations,including scientific endeavors,biomedical research,and industrial applications.The probabilistic neural network(PNN)is a commonly used and successful method for handling classification and pattern recognition issues.In this study,the authors proposed to combine the probabilistic neural network(PPN),which is one of the data mining techniques,with the vibrating particles system(VPS),which is one of the metaheuristic algorithms named“VPS-PNN”,to solve classi-fication problems more effectively.The data set is eleven common benchmark medical datasets from the machine-learning library,the suggested method was tested.The suggested VPS-PNN mechanism outperforms the PNN,biogeography-based optimization,enhanced-water cycle algorithm(E-WCA)and the firefly algorithm(FA)in terms of convergence speed and classification accuracy.
文摘Objective Decision fatigue(DF)can lead to impaired judgement,decreased diagnostic accuracy and increased likelihood of medical errors.Research on DF is scarce,and little is known about its nature in the clinical context.The objective of the present review was to provide a comprehensive framework to understand how the construct of DF in medical settings has been defined and measured.This review aimed to understand DF determinants and consequences and capture motivational factors overlooked in the existing reviews.Design Systematic and scoping review(ScR)with meta-synthesis.Eligibility criteria Empirical and non-empirical papers on clinical DF or related constructs directly impacting clinical decision-making were considered,with doctors of all ages,sexes and nationalities as participants.The Preferred Reporting Item for Systematic Reviews and Meta-analyses scoping review checklist has been applied and checked.Information sources Six databases were systematically searched by two independent researchers according to a predefined set of keywords.Results 43 papers were included,of which 25 were empirical.The quantitative studies outnumber the qualitative ones and primarily involved residents in Europe/UK and North America.Internal medicine and primary care were the most studied disciplines.Only one sequential cross-sectional study measured DF in the medical setting,and all other studies addressed the construct indirectly.A conceptual analysis of clinical DF,including narrative contributions,a thematic analysis of the data extracted and a meta-synthesis,is provided.Clinical DF was investigated mostly by individual risk factors analysed through multiple intertwined determinants involving cognitive,emotional,behavioural,social and ethical aspects.Relevant risks,protective factors and negative outcomes circularly increasing DF are outlined.Conclusions The review gives solid arguments for developing a clear and coherent definition of clinical DF that allows the implementation of preventive targeted intervention.
