101 research outputs found

    Effects of electrojet turbulence on a magnetosphere-ionosphere simulation of a geomagnetic storm

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    Ionospheric conductance plays an important role in regulating the response of the magnetosphere‐ionosphere system to solar wind driving. Typically, models of magnetosphere‐ionosphere coupling include changes to ionospheric conductance driven by extreme ultraviolet ionization and electron precipitation. This paper shows that effects driven by the Farley‐Buneman instability can also create significant enhancements in the ionospheric conductance, with substantial impacts on geospace. We have implemented a method of including electrojet turbulence (ET) effects into the ionospheric conductance model utilized within geospace simulations. Our particular implementation is tested with simulations of the Lyon‐Fedder‐Mobarry global magnetosphere model coupled with the Rice Convection Model of the inner magnetosphere. We examine the impact of including ET‐modified conductances in a case study of the geomagnetic storm of 17 March 2013. Simulations with ET show a 13% reduction in the cross polar cap potential at the beginning of the storm and up to 20% increases in the Pedersen and Hall conductance. These simulation results show better agreement with Defense Meteorological Satellite Program observations, including capturing features of subauroral polarization streams. The field‐aligned current (FAC) patterns show little differences during the peak of storm and agree well with Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) reconstructions. Typically, the simulated FAC densities are stronger and at slightly higher latitudes than shown by AMPERE. The inner magnetospheric pressures derived from Tsyganenko‐Sitnov empirical magnetic field model show that the inclusion of the ET effects increases the peak pressure and brings the results into better agreement with the empirical model.This material is based upon work supported by NASA grants NNX14AI13G, NNX13AF92G, and NNX16AB80G. The National Center for Atmospheric Research is sponsored by the National Science Foundation. This work used the XSEDE and TACC computational facilities, supported by National Science Foundation grant ACI-1053575. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. We thank the AMPERE team and the AMPERE Science Center for providing the Iridium derived data products. All model output, simulation codes, and analysis routines are being preserved on the NCAR High-Performance Storage System and will be made available upon written request to the lead author of this publication. (NNX14AI13G - NASA; NNX13AF92G - NASA; NNX16AB80G - NASA; National Science Foundation; ACI-1053575 - National Science Foundation

    A fibered description of the vector-valued spectrum

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    For Banach spaces X and Y we study the vector-valued spectrum (Formula presented.), that is the set of non null algebra homomorphisms from (Formula presented.) to (Formula presented.), which is naturally projected onto the closed unit ball of (Formula presented.). The aim of this article is to describe the fibers defined by this projection, searching for analytic balls and considering Gleason parts.Fil: Dimant, Veronica Isabel. Universidad de San Andrés. Departamento de Matemåticas y Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Singer, Joaquín Camilo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Matemåtica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemåticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemåticas "Luis A. Santaló"; Argentin

    The mediating effect of task presentation on collaboration and children's acquisition of scientific reasoning

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    There has been considerable research concerning peer interaction and the acquisition of children's scientific reasoning. This study investigated differences in collaborative activity between pairs of children working around a computer with pairs of children working with physical apparatus and related any differences to the development of children's scientific reasoning. Children aged between 9 and 10 years old (48 boys and 48 girls) were placed into either same ability or mixed ability pairs according to their individual, pre-test performance on a scientific reasoning task. These pairs then worked on either a computer version or a physical version of Inhelder and Piaget's (1958) chemical combination task. Type of presentation was found to mediate the nature and type of collaborative activity. The mixed-ability pairs working around the computer talked proportionally more about the task and management of the task; had proportionally more transactive discussions and used the record more productively than children working with the physical apparatus. Type of presentation was also found to mediated children's learning. Children in same ability pairs who worked with the physical apparatus improved significantly more than same ability pairs who worked around the computer. These findings were partially predicted from a socio-cultural theory and show the importance of tools for mediating collaborative activity and collaborative learning

    A synthesis of evidence for policy from behavioural science during COVID-19

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    Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

    A synthesis of evidence for policy from behavioural science during COVID-19

    Get PDF
    Scientific evidence regularly guides policy decisions 1, with behavioural science increasingly part of this process 2. In April 2020, an influential paper 3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

    Does emigration reduce corruption?

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    © 2017, The Author(s). We study the effects of emigration on bribery experience and attitudes towards corruption in the migrants’ countries of origin. Using data from the Gallup Balkan Monitor survey and instrumental variable analysis, we find that having relatives abroad reduces the likelihood of bribing public officials, renders bribe-taking behavior by public officials less acceptable, and reduces the likelihood of being asked for bribes by public officials. Receiving monetary remittances does not change the beneficial effects regarding bribe paying and attitudes toward corruption; however, remittances counteract the beneficial effect on bribe solicitations by public officials. Overall, our findings support the conjecture that migration contributes to the transfer of norms and practices from destination to source countries

    A synthesis of evidence for policy from behavioural science during COVID-19

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    Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

    A synthesis of evidence for policy from behavioural science during COVID-19

    Get PDF
    DATA AVAILABILITY : All data and study material are provided either in the Supplementary information or through the two online repositories (OSF and Tableau Public, both accessible via https://psyarxiv.com/58udn). No code was used for analyses in this work.Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.The National Science Foundation; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for the Support and Evaluation of Graduate Education); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for the Support and Evaluation of Graduate Education); the Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development); National Science Foundation grants; the European Research Council; the Canadian Institutes of Health Research.http://www.nature.com/naturehj2024Gordon Institute of Business Science (GIBS)Non
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