The Experts below are selected from a list of 442818 Experts worldwide ranked by ideXlab platform
Michele Williams - One of the best experts on this subject based on the ideXlab platform.
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building genuine trust through interpersonal emotion management a threat Regulation Model of trust and collaboration across boundaries
Academy of Management Review, 2007Co-Authors: Michele WilliamsAbstract:I introduce the construct of threat Regulation as an agentic interpersonal process for building and maintaining trust. I examine threat Regulation as a specific dimension of interpersonal emotion management that fosters trust and effective cooperation by allowing individuals to understand and mitigate the harm that their counterparts associate with cooperating—in particular, harm from opportunism, identity damage, and neglect of their interests. To explicate the microprocesses of threat Regulation, I draw on social cognitive theory, symbolic interactionism, and the psychology of emotion Regulation.
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building genuine trust through interpersonal emotion management a threat Regulation Model of trust and cooperation across boundaries
Social Science Research Network, 2004Co-Authors: Michele WilliamsAbstract:This article explores active influences on trust in an effort to create a broader understanding of interpersonal trust across boundaries. In contrast to more passive Models of trust development, we introduce the construct of threat Regulation as an agentic interpersonal process for building and maintaining trust. We examine threat Regulation as a specific dimension of interpersonal emotion management that fosters trust and effective cooperation by allowing individuals to understand and mitigate the harm that their counterparts associate with cooperating - in particular, harm from opportunism, identity damage, and neglect of their interests. To explicate the micro-processes of threat Regulation, we draw on social-cognitive theory, symbolic interactionism, and the psychology of emotion Regulation.
Pamela K Keel - One of the best experts on this subject based on the ideXlab platform.
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revisiting the affect Regulation Model of binge eating a meta analysis of studies using ecological momentary assessment
Psychological Bulletin, 2011Co-Authors: Alissa A Haedtmatt, Pamela K KeelAbstract:The affect Regulation Model of binge eating, which posits that patients binge eat to reduce negative affect (NA), has received support from cross-sectional and laboratory-based studies. Ecological momentary assessment (EMA) involves momentary ratings and repeated assessments over time and is ideally suited to identify temporal antecedents and consequences of binge eating. This meta-analytic review includes EMA studies of affect and binge eating. Electronic database and manual searches produced 36 EMA studies with N = 968 participants (89% Caucasian women). Meta-analyses examined changes in affect before and after binge eating using within-subjects standardized mean gain effect sizes (ESs). Results supported greater NA preceding binge eating relative to average affect (ES = 0.63) and affect before regular eating (ES = 0.68). However, NA increased further following binge episodes (ES = 0.50). Preliminary findings suggested that NA decreased following purging in bulimia nervosa (ES = -0.46). Moderators included diagnosis (with significantly greater elevations of NA prior to bingeing in binge eating disorder compared to bulimia nervosa) and binge definition (with significantly smaller elevations of NA before binge vs. regular eating episodes for the Diagnostic and Statistical Manual of Mental Disorders definition compared to lay definitions of binge eating). Overall, results fail to support the affect Regulation Model of binge eating and challenge reductions in NA as a maintenance factor for binge eating. However, limitations of this literature include unidimensional analyses of NA and inadequate examination of affect during binge eating, as binge eating may regulate only specific facets of affect or may reduce NA only during the episode.
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revisiting the affect Regulation Model of binge eating a meta analysis of studies using ecological momentary assessment
Psychological Bulletin, 2011Co-Authors: Alissa A Haedtmatt, Pamela K KeelAbstract:The affect Regulation Model of binge eating, which posits that patients binge eat to reduce negative affect (NA), has received support from cross-sectional and laboratory-based studies. Ecological momentary assessment (EMA) involves momentary ratings and repeated assessments over time and is ideally suited to identify temporal antecedents and consequences of binge eating. This meta-analytic review includes EMA studies of affect and binge eating. Electronic database and manual searches produced 36 EMA studies with N = 968 participants (89% Caucasian women). Meta-analyses examined changes in affect before and after binge eating using within-subjects standardized mean gain effect sizes (ES). Results supported greater NA preceding binge eating relative to average affect (ES = .63) and affect before regular eating (ES = .68). However, NA increased further following binge episodes (ES = .50). Preliminary findings suggested that NA decreased following purging in Bulimia Nervosa (ES = −.46). Moderators included diagnosis (with significantly greater elevations of NA prior to bingeing in Binge Eating Disorder compared to Bulimia Nervosa) and binge definition (with significantly smaller elevations of NA before binge versus regular eating episodes for the DSM definition compared to lay definitions of binge eating). Overall, results fail to support the affect Regulation Model of binge eating and challenge reductions in NA as a maintenance factor for binge eating. However, limitations of this literature include unidimensional analyses of NA and inadequate examination of affect during binge eating as binge eating may regulate only specific facets of affect or may reduce NA only during the episode.
Yang Cao - One of the best experts on this subject based on the ideXlab platform.
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stiffness detection and reduction in discrete stochastic simulation of biochemical systems
Journal of Chemical Physics, 2011Co-Authors: Layne T Watson, Yang CaoAbstract:Typical multiscale biochemical Models contain fast-scale and slow-scale reactions, where “fast” reactions fire much more frequently than “slow” ones. This feature often causes stiffness in discrete stochastic simulation methods such as Gillespie's algorithm and the Tau-Leaping method leading to inefficient simulation. This paper proposes a new strategy to automatically detect stiffness and identify species that cause stiffness for the Tau-Leaping method, as well as two stiffness reduction methods. Numerical results on a stiff decaying dimerization Model and a heat shock protein Regulation Model demonstrate the efficiency and accuracy of the proposed methods for multiscale biochemical systems.
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stiffness detection and reduction in discrete stochastic simulation of biochemical systems
Spring Simulation Multiconference, 2010Co-Authors: Layne T Watson, Yang CaoAbstract:Typical multiscale biochemical Models contain fast-scale and slow-scale reactions, where "fast" reactions fire much more frequently than "slow" ones. This feature often causes stiffness in discrete stochastic simulation methods such as Gillespie's algorithm and tau-leaping methods leading to inefficient simulation. This paper proposes a new strategy to automatically detect stiffness and identify species that cause stiffness. Stiffness reduction methods are also discussed. Numerical results on a heat shock protein Regulation Model demonstrate the efficiency and accuracy of the proposed method for multiscale biochemical systems.
Cheuk Ming Mak - One of the best experts on this subject based on the ideXlab platform.
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Development of a multi-nodal thermal Regulation and comfort Model for the outdoor environment assessment
Building and Environment, 2020Co-Authors: Yongxin Xie, Jianlei Niu, Hui Zhang, Sijie Liu, Jianlin Liu, Taiyang Huang, Cheuk Ming MakAbstract:Abstract The growing need for planning eco-cities is calling on a tool that can give better prediction of the thermal comfort conditions for a specific microclimate. A multi-nodal thermal Regulation Model can potentially factor in the impacts of the transient and asymmetric thermal conditions on human subjects. In this study, Human subjects were invited to experience various kinds of urban open spaces and to express their thermal feelings, while skin temperatures of 17 local body segments were measured. We tested the multi-nodal thermal Regulation Model developed by UC Berkeley by comparing its predictions of human body skin temperature, thermal sensation vote (TSV), and thermal comfort vote (TCV) with our onsite human subject measurements and questionnaire survey, in order to identify the causes of the errors between the prediction and measurements. Corresponding to the thermal neutral status, the field-measured data recorded wider local skin temperature ranges than the simulated ones. We proposed using a “null zone” instead of “set-point” in the thermal comfort Model to accommodate the possible adaptation of human subjects to the highly fluctuating wind environment in open spaces. It was proposed that the forehead was counted as one of the dominant local body parts when defining the overall thermal sensation. The correlation coefficient R 2 between the prediction and the field measured TSV improved to 93.7% for the revised Model from 76.2% of the original Model.
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Evaluation of a multi-nodal thermal Regulation Model for assessment of outdoor thermal comfort: Sensitivity to wind speed and solar radiation
Building and Environment, 2018Co-Authors: Yongxin Xie, Jianlei Niu, Jianlin Liu, Taiyang Huang, Cheuk Ming Mak, Zhang LinAbstract:Abstract People's outdoor thermal sensation varies from that indoors. The highly asymmetric solar radiation and transient wind environment are the main causes. The University of California-Berkeley developed a multi-nodal human body thermal Regulation Model (the UCB Model) to predict human thermal sensation and comfort in asymmetric and transient indoor environments. However, few studies compared its predictions with the survey responses outdoors. In this study, subjects' thermal sensations outdoors were surveyed and compared with the UCB Model predictions. Meteorological parameters were monitored using a microclimate station, and over a thousand human subjects were surveyed. Results point out that subjects were highly sensitive to the changes in wind speed, especially under low-radiation conditions. However, the UCB Model failed to predict such a high sensitivity. Besides, subjects had a higher tolerance to high air temperatures in outdoor environments when the solar radiation was acceptable, but the UCB Model over-predicted the TSV (thermal sensation vote) in such conditions. Both the on-site results and the predictions by UCB Model showed that subjects were more sensitive to wind speed in hotter environments while they were least sensitive to solar radiation in neutral thermal conditions. This study helps to reveal the potential of a multi-nodal thermal Regulation Model to address the asymmetric and transient features of outdoor environments and indicates the need to further refine the Model for better quantitative prediction of outdoor thermal sensations.
Yongxin Xie - One of the best experts on this subject based on the ideXlab platform.
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Development of a multi-nodal thermal Regulation and comfort Model for the outdoor environment assessment
Building and Environment, 2020Co-Authors: Yongxin Xie, Jianlei Niu, Hui Zhang, Sijie Liu, Jianlin Liu, Taiyang Huang, Cheuk Ming MakAbstract:Abstract The growing need for planning eco-cities is calling on a tool that can give better prediction of the thermal comfort conditions for a specific microclimate. A multi-nodal thermal Regulation Model can potentially factor in the impacts of the transient and asymmetric thermal conditions on human subjects. In this study, Human subjects were invited to experience various kinds of urban open spaces and to express their thermal feelings, while skin temperatures of 17 local body segments were measured. We tested the multi-nodal thermal Regulation Model developed by UC Berkeley by comparing its predictions of human body skin temperature, thermal sensation vote (TSV), and thermal comfort vote (TCV) with our onsite human subject measurements and questionnaire survey, in order to identify the causes of the errors between the prediction and measurements. Corresponding to the thermal neutral status, the field-measured data recorded wider local skin temperature ranges than the simulated ones. We proposed using a “null zone” instead of “set-point” in the thermal comfort Model to accommodate the possible adaptation of human subjects to the highly fluctuating wind environment in open spaces. It was proposed that the forehead was counted as one of the dominant local body parts when defining the overall thermal sensation. The correlation coefficient R 2 between the prediction and the field measured TSV improved to 93.7% for the revised Model from 76.2% of the original Model.
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Evaluation of a multi-nodal thermal Regulation Model for assessment of outdoor thermal comfort: Sensitivity to wind speed and solar radiation
Building and Environment, 2018Co-Authors: Yongxin Xie, Jianlei Niu, Jianlin Liu, Taiyang Huang, Cheuk Ming Mak, Zhang LinAbstract:Abstract People's outdoor thermal sensation varies from that indoors. The highly asymmetric solar radiation and transient wind environment are the main causes. The University of California-Berkeley developed a multi-nodal human body thermal Regulation Model (the UCB Model) to predict human thermal sensation and comfort in asymmetric and transient indoor environments. However, few studies compared its predictions with the survey responses outdoors. In this study, subjects' thermal sensations outdoors were surveyed and compared with the UCB Model predictions. Meteorological parameters were monitored using a microclimate station, and over a thousand human subjects were surveyed. Results point out that subjects were highly sensitive to the changes in wind speed, especially under low-radiation conditions. However, the UCB Model failed to predict such a high sensitivity. Besides, subjects had a higher tolerance to high air temperatures in outdoor environments when the solar radiation was acceptable, but the UCB Model over-predicted the TSV (thermal sensation vote) in such conditions. Both the on-site results and the predictions by UCB Model showed that subjects were more sensitive to wind speed in hotter environments while they were least sensitive to solar radiation in neutral thermal conditions. This study helps to reveal the potential of a multi-nodal thermal Regulation Model to address the asymmetric and transient features of outdoor environments and indicates the need to further refine the Model for better quantitative prediction of outdoor thermal sensations.
