Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer's dec...Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer's decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. "The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.展开更多
In rapid socio-economic developme nt,the process of concentration and dispersal of various elements tends to be more dramatic,tremendously in fluencing the shaping and transform ation of the space in metropolitan area...In rapid socio-economic developme nt,the process of concentration and dispersal of various elements tends to be more dramatic,tremendously in fluencing the shaping and transform ation of the space in metropolitan area.Survey of spatial concentration and decent ralization has thus become a basic me thod in examining metropolitan spatial evolution.In this research,three elements were selected as the essential indicato rs of the process:demographic density distribu-tion,employment density distribut ion and business office location.Performance of these elements in Nanji ng City was exam-ined historically.As Nanjing City c ould be regarded as a representative of metropolitan areas in China,its s ituation large-ly suggestes the general characteristics in similar areas of China.Hence based on the investigation of Nanji ng City,four general implications were highligh ted.First,metropolitan areas inChina are in a violentprocess and shift of spatialconcentra-tion and decentralization.Second,from now to at least the near future,c oncentration will continue to be the central fea-ture.Third,the landscape of metrop olitan areas basically exhibits a dual structure character.The gap in en vironmental and ecological qualities among different districts will continue for a l ong time.Fourth,Central Business District(CBD)is playing an important role in helpi ng to convert the traditionally single-centered city structure into a polycentric one.展开更多
Federated learning is a distributed learning framework which trains global models by passing model parameters instead of raw data.However,the training mechanism for passing model parameters is still threatened by grad...Federated learning is a distributed learning framework which trains global models by passing model parameters instead of raw data.However,the training mechanism for passing model parameters is still threatened by gradient inversion,inference attacks,etc.With a lightweight encryption overhead,function encryption is a viable secure aggregation technique in federation learning,which is often used in combination with differential privacy.The function encryption in federal learning still has the following problems:a)Traditional function encryption usually requires a trust third party(TTP)to assign the keys.If a TTP colludes with a server,the security aggregation mechanism can be compromised.b)When using differential privacy in combination with function encryption,the evaluation metrics of incentive mechanisms in the traditional federal learning become invisible.In this paper,we propose a hybrid privacy-preserving scheme for federated learning,called Fed-DFE.Specifically,we present a decentralized multi-client function encryption algorithm.It replaces the TTP in traditional function encryption with an interactive key generation algorithm,avoiding the problem of collusion.Then,an embedded incentive mechanism is designed for function encryption.It models the real parameters in federated learning and finds a balance between privacy preservation and model accuracy.Subsequently,we implemented a prototype of Fed-DFE and evaluated the performance of decentralized function encryption algorithm.The experimental results demonstrate the effectiveness and efficiency of our scheme.展开更多
Background: The integration of relevant high-quality research evidence into the health decision and policy formulation process is a key strategy for improving health systems especially in developing countries such as ...Background: The integration of relevant high-quality research evidence into the health decision and policy formulation process is a key strategy for improving health systems especially in developing countries such as Zambia. However, the lack of capacity to understand and value research evidence by policy and decision makers makes it difficult for them to find and use research evidence in a timely manner even when motivated to do so. This study aimed to establish the views, attitudes and practices of policy makers on the use of research evidence in policy and decision-making process in Zambia. Methodology: This descriptive cross-sectional study was conducted in Lusaka, Zambia among selected public health decision and policy making institutions. A purposive sample of 21 consenting policy makers who were working in different positions in the Ministry of Health Headquarters, Provincial and District Health Offices, Health Professions Regulatory Bodies, United Nations Agencies, International Non-Governmental Organizations and University Deans from the University of Zambia participated in the study. A self-administered questionnaire was used to collect data. The IBM? SPSS? Statistics for Windows Version 20.0 was used for data analysis. Results: The concept of Evidence Informed Health Policy was not well understood such that only less than half (47.5%) of the participants reported having heard specifically about Evidence Informed Health Policy meanwhile almost two thirds (61.9%) reported that they used research evidence in decision making and policy formulation. Similar discrepancy was expressed in the understanding of and use of rapid response mechanisms such that although (47.6%) of the participants reported having heard about it, (57%) had never used rapid response mechanisms for deci-sion-making. With regard to the sources of information, about half (52.3) of the participants reported scholarly articles as their main source of evidence. Con-clusion and Recommendations: There is need for more sensitization and ca-pacity building among the decision and policy makers on the importance of using research evidence in decision and policy making process as incorporation of relevant high-quality research evidence into the health policy making pro-cess is a key strategy for improving health systems.展开更多
Key technologies as well as their principles were discussed for a decentralized control platform capable of dynamic evolution. The primary content includes the automatic decision-making mechanism and the algorithm of ...Key technologies as well as their principles were discussed for a decentralized control platform capable of dynamic evolution. The primary content includes the automatic decision-making mechanism and the algorithm of the control center migration, the principle and technology of system self-monitoring, the principle and technology of the switch-mode of remote control station, the information transmission technology, and the data consistency technology. These key technologies have shown a series of advanced characteristics for decentralized control platform.展开更多
Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examini...Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.展开更多
This article provides a coherent framework within which to understand China’s development model,as well as the successes and the failures of China’s decentralization approach to reform.The combination of political c...This article provides a coherent framework within which to understand China’s development model,as well as the successes and the failures of China’s decentralization approach to reform.The combination of political centralization and economic decentralization provide local government with enough incentives to develop local economies,in particular incentives to promote market privatisation locally.However,the relative evaluation-based incentive schemes lead to inter- regional market segmentation,increasing inter-regional development gaps and the unequal provision of certain public goods.The success of early-stage reform can be attributed to the benefits of the decentralization approach.The next stage reform should however focus on minimizing the associated costs.China’s gradualist reform can be seen as a mechanism design issue under the control of central government.Therefore,it is essential to take both the costs and benefits of the decentralization approach into account in the design of the next-stage reform package.展开更多
基金supported by the National Laboratory of Cognitive Neuroscience and Learning at Beijing Normal University (the 973 program),No. 2010CB8339004the National Natural Science Foundation of China,No. 30970911+1 种基金the Fundamental Research Fund for the Central Universities,No.SWJTU11BR192the Humanity and Social Science Youth foundation of Ministry of Education of China,No. 12YJC630317
文摘Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer's decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. "The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.
文摘In rapid socio-economic developme nt,the process of concentration and dispersal of various elements tends to be more dramatic,tremendously in fluencing the shaping and transform ation of the space in metropolitan area.Survey of spatial concentration and decent ralization has thus become a basic me thod in examining metropolitan spatial evolution.In this research,three elements were selected as the essential indicato rs of the process:demographic density distribu-tion,employment density distribut ion and business office location.Performance of these elements in Nanji ng City was exam-ined historically.As Nanjing City c ould be regarded as a representative of metropolitan areas in China,its s ituation large-ly suggestes the general characteristics in similar areas of China.Hence based on the investigation of Nanji ng City,four general implications were highligh ted.First,metropolitan areas inChina are in a violentprocess and shift of spatialconcentra-tion and decentralization.Second,from now to at least the near future,c oncentration will continue to be the central fea-ture.Third,the landscape of metrop olitan areas basically exhibits a dual structure character.The gap in en vironmental and ecological qualities among different districts will continue for a l ong time.Fourth,Central Business District(CBD)is playing an important role in helpi ng to convert the traditionally single-centered city structure into a polycentric one.
基金This work was supported in part by the National Key R&D Program of China(No.2018YFB2100400)in part by the National Natural Science Foundation of China(No.62002077,61872100)+2 种基金in part by the China Postdoctoral Science Foundation(No.2020M682657)in part by Guangdong Basic and Applied Basic Research Foundation(No.2020A1515110385)in part by Zhejiang Lab(No.2020NF0AB01),in part by Guangzhou Science and Technology Plan Project(202102010440).
文摘Federated learning is a distributed learning framework which trains global models by passing model parameters instead of raw data.However,the training mechanism for passing model parameters is still threatened by gradient inversion,inference attacks,etc.With a lightweight encryption overhead,function encryption is a viable secure aggregation technique in federation learning,which is often used in combination with differential privacy.The function encryption in federal learning still has the following problems:a)Traditional function encryption usually requires a trust third party(TTP)to assign the keys.If a TTP colludes with a server,the security aggregation mechanism can be compromised.b)When using differential privacy in combination with function encryption,the evaluation metrics of incentive mechanisms in the traditional federal learning become invisible.In this paper,we propose a hybrid privacy-preserving scheme for federated learning,called Fed-DFE.Specifically,we present a decentralized multi-client function encryption algorithm.It replaces the TTP in traditional function encryption with an interactive key generation algorithm,avoiding the problem of collusion.Then,an embedded incentive mechanism is designed for function encryption.It models the real parameters in federated learning and finds a balance between privacy preservation and model accuracy.Subsequently,we implemented a prototype of Fed-DFE and evaluated the performance of decentralized function encryption algorithm.The experimental results demonstrate the effectiveness and efficiency of our scheme.
文摘Background: The integration of relevant high-quality research evidence into the health decision and policy formulation process is a key strategy for improving health systems especially in developing countries such as Zambia. However, the lack of capacity to understand and value research evidence by policy and decision makers makes it difficult for them to find and use research evidence in a timely manner even when motivated to do so. This study aimed to establish the views, attitudes and practices of policy makers on the use of research evidence in policy and decision-making process in Zambia. Methodology: This descriptive cross-sectional study was conducted in Lusaka, Zambia among selected public health decision and policy making institutions. A purposive sample of 21 consenting policy makers who were working in different positions in the Ministry of Health Headquarters, Provincial and District Health Offices, Health Professions Regulatory Bodies, United Nations Agencies, International Non-Governmental Organizations and University Deans from the University of Zambia participated in the study. A self-administered questionnaire was used to collect data. The IBM? SPSS? Statistics for Windows Version 20.0 was used for data analysis. Results: The concept of Evidence Informed Health Policy was not well understood such that only less than half (47.5%) of the participants reported having heard specifically about Evidence Informed Health Policy meanwhile almost two thirds (61.9%) reported that they used research evidence in decision making and policy formulation. Similar discrepancy was expressed in the understanding of and use of rapid response mechanisms such that although (47.6%) of the participants reported having heard about it, (57%) had never used rapid response mechanisms for deci-sion-making. With regard to the sources of information, about half (52.3) of the participants reported scholarly articles as their main source of evidence. Con-clusion and Recommendations: There is need for more sensitization and ca-pacity building among the decision and policy makers on the importance of using research evidence in decision and policy making process as incorporation of relevant high-quality research evidence into the health policy making pro-cess is a key strategy for improving health systems.
基金The National Innovation Fund ( No.00C262251211336)
文摘Key technologies as well as their principles were discussed for a decentralized control platform capable of dynamic evolution. The primary content includes the automatic decision-making mechanism and the algorithm of the control center migration, the principle and technology of system self-monitoring, the principle and technology of the switch-mode of remote control station, the information transmission technology, and the data consistency technology. These key technologies have shown a series of advanced characteristics for decentralized control platform.
文摘Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.
基金This paper is one of the research results of China Centre for Economic Studies at Fudan University and also one of the research results of Fudan University 985 China International Economic Competitiveness Research and Innovation Institution.The authors gratefully acknowledge the helpful comments of many domestic and foreign scholars on this paper.
文摘This article provides a coherent framework within which to understand China’s development model,as well as the successes and the failures of China’s decentralization approach to reform.The combination of political centralization and economic decentralization provide local government with enough incentives to develop local economies,in particular incentives to promote market privatisation locally.However,the relative evaluation-based incentive schemes lead to inter- regional market segmentation,increasing inter-regional development gaps and the unequal provision of certain public goods.The success of early-stage reform can be attributed to the benefits of the decentralization approach.The next stage reform should however focus on minimizing the associated costs.China’s gradualist reform can be seen as a mechanism design issue under the control of central government.Therefore,it is essential to take both the costs and benefits of the decentralization approach into account in the design of the next-stage reform package.