The River Chief System (RCS) has evolved from local innovative practices to a national water governance strategy to address the current challenges in China’s water environmental management. In contrast to existing re...The River Chief System (RCS) has evolved from local innovative practices to a national water governance strategy to address the current challenges in China’s water environmental management. In contrast to existing research that focuses on the strengths, weaknesses, and improvements of RCS, this study uses literature study to reveal the dynamic evolution of RCS through three phases, with RCS spreading from developed coastal areas to central and western inland regions. RCS’s diffusion path involves vertical diffusion between central and local levels and horizontal diffusion among local governments. Moreover, RCS has also achieved conceptual spillover, gradually expanding into other governance domains, such as the Lake Chief System, the Field Chief System, the Forestry Chief System, and the integration of multiple chief roles. However, it is essential to scrutinize the phenomenon of applying similar governance mechanisms to different areas, as it may result in challenges such as overburdening local governments, insufficient public participation, oversimplification of differences in natural resource endowments, and limited applicability. This study also provides suggestions on how to address these challenges. The study contributes theoretical insights and policy implications, providing a foundation for practical policy innovation.展开更多
Universal access to China＇s social welfare system involves a process of diffusion from localities to the whole country on the basis of social policy innovations in which intergovernmental relations play a key role as...Universal access to China＇s social welfare system involves a process of diffusion from localities to the whole country on the basis of social policy innovations in which intergovernmental relations play a key role as a facilitator. The rapid establishment of the urban subsistence allowance system in more than 200 cities throughout the country in seven years （1993-1999） serves as a case for our empirical analysis of the diffusion mechanism of social policy innovations at different levels of government. Our findings show, firstly, that in adopting a new social policy, city governments have to respond to the social desire of local citizens while keeping fiscal constraints in mind; at the same time, they are affected by administrative orders from higher-level governments and the vertical fiscal relations between governments at different levels, and are also subject to competitive pressures from other cities at the same level. Secondly, city governments＇ policy innovations offer an opportunity for higher levels of government to learn from their experience. Thirdly, central government orders exert both a direct and indirect influence upon city governments, with provincial orders acting as intermediaries. And lastly, there is a clear difference in the time lag effect of orders from the central government and those at provincial level upon city governments＇ policy adoption.展开更多
Anthropomorphic hand manipulation is a quintessential example of embodied intelligence in robotics,presenting a notable challenge due to its high degrees of freedom and complex inter-joint coupling.Though recent advan...Anthropomorphic hand manipulation is a quintessential example of embodied intelligence in robotics,presenting a notable challenge due to its high degrees of freedom and complex inter-joint coupling.Though recent advancements in reinforcement learning(RL)have led to substantial progress in this field,existing methods often overlook the detailed structural properties of anthropomorphic hands.To address this,we propose a novel deep RL approach,Bionic-Constrained Diffusion Policy(Bio-CDP),which integrates knowledge of human hand control with a powerful diffusion policy representation.Our bionic constraint modifies the action space of anthropomorphic hand control,while the diffusion policy enhances the expressibility of the policy in high-dimensional continuous control tasks.Bio-CDP has been evaluated in the simulation environment,where it has shown superior performance and data efficiency compared to state-of-the-art RL approaches.Furthermore,our method is resilient to task complexity and robust in performance,making it a promising tool for advanced control in robotics.展开更多
文摘The River Chief System (RCS) has evolved from local innovative practices to a national water governance strategy to address the current challenges in China’s water environmental management. In contrast to existing research that focuses on the strengths, weaknesses, and improvements of RCS, this study uses literature study to reveal the dynamic evolution of RCS through three phases, with RCS spreading from developed coastal areas to central and western inland regions. RCS’s diffusion path involves vertical diffusion between central and local levels and horizontal diffusion among local governments. Moreover, RCS has also achieved conceptual spillover, gradually expanding into other governance domains, such as the Lake Chief System, the Field Chief System, the Forestry Chief System, and the integration of multiple chief roles. However, it is essential to scrutinize the phenomenon of applying similar governance mechanisms to different areas, as it may result in challenges such as overburdening local governments, insufficient public participation, oversimplification of differences in natural resource endowments, and limited applicability. This study also provides suggestions on how to address these challenges. The study contributes theoretical insights and policy implications, providing a foundation for practical policy innovation.
文摘Universal access to China＇s social welfare system involves a process of diffusion from localities to the whole country on the basis of social policy innovations in which intergovernmental relations play a key role as a facilitator. The rapid establishment of the urban subsistence allowance system in more than 200 cities throughout the country in seven years （1993-1999） serves as a case for our empirical analysis of the diffusion mechanism of social policy innovations at different levels of government. Our findings show, firstly, that in adopting a new social policy, city governments have to respond to the social desire of local citizens while keeping fiscal constraints in mind; at the same time, they are affected by administrative orders from higher-level governments and the vertical fiscal relations between governments at different levels, and are also subject to competitive pressures from other cities at the same level. Secondly, city governments＇ policy innovations offer an opportunity for higher levels of government to learn from their experience. Thirdly, central government orders exert both a direct and indirect influence upon city governments, with provincial orders acting as intermediaries. And lastly, there is a clear difference in the time lag effect of orders from the central government and those at provincial level upon city governments＇ policy adoption.
基金supported by the National Nature Science Foundation of China under grants 91748131,6200629,61771471,and 62073324in part by the InnoHK Project.
文摘Anthropomorphic hand manipulation is a quintessential example of embodied intelligence in robotics,presenting a notable challenge due to its high degrees of freedom and complex inter-joint coupling.Though recent advancements in reinforcement learning(RL)have led to substantial progress in this field,existing methods often overlook the detailed structural properties of anthropomorphic hands.To address this,we propose a novel deep RL approach,Bionic-Constrained Diffusion Policy(Bio-CDP),which integrates knowledge of human hand control with a powerful diffusion policy representation.Our bionic constraint modifies the action space of anthropomorphic hand control,while the diffusion policy enhances the expressibility of the policy in high-dimensional continuous control tasks.Bio-CDP has been evaluated in the simulation environment,where it has shown superior performance and data efficiency compared to state-of-the-art RL approaches.Furthermore,our method is resilient to task complexity and robust in performance,making it a promising tool for advanced control in robotics.
