Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊...Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd.cn/browse/al/al2019/。展开更多
This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis f...This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis framework for the Chengdu real estate market.By using the Adaptive Neuro-Fuzzy Inference System(ANFIS)prediction model,spatial GIS(Geographic Information System analysis)analysis,and interactive dashboards,this study reveals market differentiation,policy impacts,and changes in demand structure,thereby providing decision support for the government,enterprises,and homebuyers.展开更多
The 53rd issue of Financial Innovation(FIN),Volume 11,No.5(2025),features 21 papers that can be classified into four main themes:the Special Issue on The Anomie of Artificial Intelligence(AI)in Finance:Bridging the Ga...The 53rd issue of Financial Innovation(FIN),Volume 11,No.5(2025),features 21 papers that can be classified into four main themes:the Special Issue on The Anomie of Artificial Intelligence(AI)in Finance:Bridging the Gap Between Technical Power and Human Wisdom,and Financial Markets and Investments,Economic and Policy Analysis,Corporate Governance and Related Market Dynamics.展开更多
Relational theory represents a critical paradigm in understanding organizational dynamics,policy formation,and leadership effectiveness.This comprehensive literature review explores the theoretical foundations,practic...Relational theory represents a critical paradigm in understanding organizational dynamics,policy formation,and leadership effectiveness.This comprehensive literature review explores the theoretical foundations,practical implications,and organizational leadership applications of relational theory across diverse contextual frameworks.By synthesizing contemporary scholarly research,this review critically examines the theory’s epistemological underpinnings,methodological approaches,and transformative potential in organizational policy development.The analysis reveals complex interconnections between relational theory,organizational behavior,leadership strategies,and systemic policy implementation,highlighting both the theory’s significant potential and inherent limitations in contemporary organizational contexts.展开更多
Remarkable achievements of the new energy industry policy framework over the past two decades Over the past two decades,the industry policy framework centered on the Renewable Energy Law has effectively facilitated th...Remarkable achievements of the new energy industry policy framework over the past two decades Over the past two decades,the industry policy framework centered on the Renewable Energy Law has effectively facilitated the leapfrog development of China’s new energy sector.During this period,policy incentives were primarily focused on promoting the rational scaling of the industry,thereby driving rapid technological upgrades and iterations.This,in turn,enabled a significant reduc-tion in the cost of new energy power generation.In this process,policy played a pivotal role in two key areas:first,by providing per-kilowatt-hour subsidies to bridge the cost gap between new energy and conventional power sources;and second,by exempting the system cost of new energy grid-connected operation through a full guaranteed purchase system.展开更多
The increasing complexity of on-orbit tasks imposes great demands on the flexible operation of space robotic arms, prompting the development of space robots from single-arm manipulation to multi-arm collaboration. In ...The increasing complexity of on-orbit tasks imposes great demands on the flexible operation of space robotic arms, prompting the development of space robots from single-arm manipulation to multi-arm collaboration. In this paper, a combined approach of Learning from Demonstration (LfD) and Reinforcement Learning (RL) is proposed for space multi-arm collaborative skill learning. The combination effectively resolves the trade-off between learning efficiency and feasible solution in LfD, as well as the time-consuming pursuit of the optimal solution in RL. With the prior knowledge of LfD, space robotic arms can achieve efficient guided learning in high-dimensional state-action space. Specifically, an LfD approach with Probabilistic Movement Primitives (ProMP) is firstly utilized to encode and reproduce the demonstration actions, generating a distribution as the initialization of policy. Then in the RL stage, a Relative Entropy Policy Search (REPS) algorithm modified in continuous state-action space is employed for further policy improvement. More importantly, the learned behaviors can maintain and reflect the characteristics of demonstrations. In addition, a series of supplementary policy search mechanisms are designed to accelerate the exploration process. The effectiveness of the proposed method has been verified both theoretically and experimentally. Moreover, comparisons with state-of-the-art methods have confirmed the outperformance of the approach.展开更多
In recent years,reinforcement learning control theory has been well developed.However,model-free value iteration needs many iterations to achieve the desired precision,and modelfree policy iteration requires an initia...In recent years,reinforcement learning control theory has been well developed.However,model-free value iteration needs many iterations to achieve the desired precision,and modelfree policy iteration requires an initial stabilizing control policy.It is significant to propose a fast model-free algorithm to solve the continuous-time linear quadratic control problem without an initial stabilizing control policy.In this paper,we construct a homotopy path on which each point corresponds to an linear quadratic regulator problem.Based on policy iteration,model-based and model-free homotopy algorithms are proposed to solve the optimal control problem of continuous-time linear systems along the homotopy path.Our algorithms are speeded up using first-order differential information and do not require an initial stabilizing control policy.Finally,several practical examples are used to illustrate our results.展开更多
Mandate-based and market-based mechanisms represent two primary approaches to achieving policy objectives,yet the debate over their relative effectiveness remains unresolved.The mandate-based approach is exemplified b...Mandate-based and market-based mechanisms represent two primary approaches to achieving policy objectives,yet the debate over their relative effectiveness remains unresolved.The mandate-based approach is exemplified by pilot programs for low-carbon provinces and cities,referred to as“Low-Carbon Pilot Provinces/Cities”,while the market-based mechanism is reflected in pilot programs for carbon emissions trading markets,or“Carbon Trading Pilot Programs”.This paper employs event study analysis to compare the carbon emission reduction impacts of these two approaches.Our findings reveal that the Low-Carbon Pilot Provinces/Cities achieved emissions reduction primarily by curbing economic output,without significantly reducing carbon emissions intensity.In contrast,the Carbon Trading Pilot Programs led to an increase in total carbon emissions by driving economic growth,even as they reduced carbon emissions intensity.A heterogeneity analysis further indicates that the emissions reductions observed in the Low-Carbon Pilot Provinces/Cities were predominantly concentrated in economically less-developed regions,whereas the increase in carbon emissions associated with the Carbon Trading Pilot Programs was more significant in regions with lower initial carbon emissions intensity.Against the backdrop of China’s efforts to achieve its carbon peak and neutrality goals,this paper offers valuable insights for the design of effective climate policies.展开更多
Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights t...Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights that have been underrepresented in policy documents by leveraging extensive datasets from policy texts and scholarly publications.Design/methodology/approach:This article introduces a research framework aimed at excavating scientific insights that have been overlooked by policy,encompassing four integral parts:data acquisition and preprocessing,the identification of overlooked content through thematic analysis,the discovery of overlooked content via keyword analysis,and a comprehensive analysis and discussion of the overlooked content.Leveraging this framework,the research conducts an in-depth exploration of the scientific content overlooked by policies during the COVID-19 pandemic.Findings:During the COVID-19 pandemic,scientific information in four domains was overlooked by policy:psychological state of the populace,environmental issues,the role of computer technology,and public relations.These findings indicate a systematic underrepresentation of important scientific insights in policy.Research limitations:This study is subject to two key limitations.Firstly,the text analysis method—relying on pre-extracted keywords and thematic structures—may not fully capture the nuanced context and complexity of scientific insights in policy documents.Secondly,the focus on a limited set of case studies restricts the broader applicability of the conclusions across diverse situations.Practical implications:The study introduces a quantitative framework using text analysis to identify overlooked scientific content in policy,bridging the gap between science and policy.It also highlights overlooked scientific information during COVID-19,promoting more evidence-based and robust policies through improved science-policy integration.Originality/value:This paper provides new ideas and methods for excavating scientific information that has been overlooked by policy,further deepens the understanding of the interaction between policy and science during the COVID-19 period,and lays the foundation for the more rational use of scientific information in policy-making.展开更多
As urbanization accelerates globally,air pollution-particularly PM_(2.5)-is becoming an increasingly significant threat,not only to public health but also the environment.In-depth research on the impact of China’s Ze...As urbanization accelerates globally,air pollution-particularly PM_(2.5)-is becoming an increasingly significant threat,not only to public health but also the environment.In-depth research on the impact of China’s Zero Waste City pilot policy on PM_(2.5)concentration offers valuable insights into the policy’s effectiveness and provides a potential model for environmental governance worldwide.This study employs panel data from 293 Chinese cities from 2014 to 2022 to systematically analyze the impact of the Zero-Waste City policy on PM_(2.5)concentration using a difference-in-differences model.The findings indicate that the policy not only directly reduces PM_(2.5)concentration but also indirectly curbs PM_(2.5)emissions by enhancing green innovation and green economic efficiency.Moreover,the policy’s effects are found to be positively moderated by urban energy dependence and digital financial inclusion,while they are negatively moderated by the government debt ratio.Based on these findings,this study suggests that cities should actively develop their digital economy,reduce government debt,promote green innovation,and improve green economic efficiency,as doing so will enhance their implementation of environmental policies and promote sustainable urban development.展开更多
This study investigates the critical intersection of cyberpsychology and cybersecurity policy development in small and medium-sized enterprises (SMEs). Through a mixed-methods approach incorporating surveys of 523 emp...This study investigates the critical intersection of cyberpsychology and cybersecurity policy development in small and medium-sized enterprises (SMEs). Through a mixed-methods approach incorporating surveys of 523 employees across 78 SMEs, qualitative interviews, and case studies, the research examines how psychological factors influence cybersecurity behaviors and policy effectiveness. Key findings reveal significant correlations between psychological factors and security outcomes, including the relationship between self-efficacy and policy compliance (r = 0.42, p β = 0.37, p < 0.001). The study identifies critical challenges in risk perception, policy complexity, and organizational culture affecting SME cybersecurity implementation. Results demonstrate that successful cybersecurity initiatives require the integration of psychological principles with technical solutions. The research provides a framework for developing human-centric security policies that address both behavioral and technical aspects of cybersecurity in resource-constrained environments.展开更多
Exo-atmospheric vehicles are constrained by limited maneuverability,which leads to the contradiction between evasive maneuver and precision strike.To address the problem of Integrated Evasion and Impact(IEI)decision u...Exo-atmospheric vehicles are constrained by limited maneuverability,which leads to the contradiction between evasive maneuver and precision strike.To address the problem of Integrated Evasion and Impact(IEI)decision under multi-constraint conditions,a hierarchical intelligent decision-making method based on Deep Reinforcement Learning(DRL)was proposed.First,an intelligent decision-making framework of“DRL evasion decision”+“impact prediction guidance decision”was established:it takes the impact point deviation correction ability as the constraint and the maximum miss distance as the objective,and effectively solves the problem of poor decisionmaking effect caused by the large IEI decision space.Second,to solve the sparse reward problem faced by evasion decision-making,a hierarchical decision-making method consisting of maneuver timing decision and maneuver duration decision was proposed,and the corresponding Markov Decision Process(MDP)was designed.A detailed simulation experiment was designed to analyze the advantages and computational complexity of the proposed method.Simulation results show that the proposed model has good performance and low computational resource requirement.The minimum miss distance is 21.3 m under the condition of guaranteeing the impact point accuracy,and the single decision-making time is 4.086 ms on an STM32F407 single-chip microcomputer,which has engineering application value.展开更多
Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework f...Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.展开更多
Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊...Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd.cn/browse/al/al2019/。展开更多
Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊...Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd.cn/browse/al/al2019/。展开更多
Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊...Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd.cn/browse/al/al2019/。展开更多
Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊...Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd. cn/browse/al/al2019/。展开更多
Purpose:This study examines the impact of research policy changes on scientific retractions of publications authored by Romanian authors,focusing on national trends and the interplay between policy reforms and publish...Purpose:This study examines the impact of research policy changes on scientific retractions of publications authored by Romanian authors,focusing on national trends and the interplay between policy reforms and publishing practices.Design/methodology/approach:Using data from the Retraction Watch Database and Web of Science(WoS),188 unique retractions involving Romanian authors(2000-2022)were analyzed.The study compared retraction patterns before and after the 2016 reforms,which prioritized the publication of articles in WoS-indexed journals over non-WoS outputs.Findings:The analysis identified two key trends:(1)before the 2016 reforms,retractions predominantly involved non-WoS journals(99 non-WoS retractions to 38 WoS retractions),a trend that reversed post-reform(16 non-WoS to 35 WoS),and(2)while the total number of WoS-indexed retractions increased after the reforms,the retraction rates for WoS articles remained stable.Post-reform reliance on MDPI journals,which have low retraction rates,partially explains this stability.Excluding MDPI publications,retraction rates for articles and reviews increase by 14.91%,aligning with patterns seen elsewhere.Research limitations:The study focuses on retractions involving Romanian authors,limiting its generalizability.Furthermore,reliance on database records may not fully capture all retractions.Practical implications:These findings underscore the need for research policy reforms to consider a broader range of effects,and the need for nuanced interpretations of retraction data,which are influenced by a complex range of factors,including specific publisher practices.Originality/value:This research is the first to investigate the complex relationship between research policy reforms,publisher behavior,and retraction trends.展开更多
Background:Globally,the use of community pharmacies and pharmacists in the delivery of vaccination services has been hampered by several factors,laws,and regulations that do not support pharmacists to participate in t...Background:Globally,the use of community pharmacies and pharmacists in the delivery of vaccination services has been hampered by several factors,laws,and regulations that do not support pharmacists to participate in the delivery of vaccination services.With the advent of COVID-19 pandemic,many countries have included community pharmacists and pharmacies in vaccination services to improve coverage.This study described the delivery of vaccination services in community pharmacies using the COVID-19 experience and how their involvement impacted vaccination coverage in Nigeria.It also exposed how this experience can be used to support policy revisions to formally recognize pharmacists in immunization delivery.Methods:A descriptive cross-sectional study was conducted among 474 community pharmacists in two southwestern States in Nigeria,using a semi-structured questionnaire.It determines the number of community pharmacists who have been trained in the delivery of vaccination services,the types of vaccination services provided,and vaccines administered in their pharmacies.Data were analyzed with descriptive and inferential statistics and p-value at≤0.05.Results:Response rate was 86.7%.Less than half of the respondents(40.1%)had undergone vaccination training.Of the 129(31.4%)respondents that provide vaccination services,72(55.8%)administer vaccines in their pharmacies.Out of these 72 respondents;45(62.5%)were administering vaccines before their involvement in COVID-19 vaccine administration;57(79.2%)of the health personnel who administer vaccines were pharmacists;60(83.3%)of them administer vaccines on request;22(30.6%)administered COVID-19 vaccines only;and only 7(9.7%)of the respondents had administered over 500 doses of COVID-19 vaccines.Training in vaccination was associated with the vaccination services provided(p<0.05).Respondents suggested government support through legal framework and policy review,training and empowering pharmacists in vaccine administration,and recognition of community pharmacists as PHC providers.展开更多
文摘Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd.cn/browse/al/al2019/。
基金Chengdu City Philosophy and Social Sciences Research Center“artificial intelligence+urban communication”theory and Application Research Center Project“Chengdu real estate vertical market public opinion data visualization research”(Project No.RZCC2025017).
文摘This study integrates multiple sources of data(transaction data,policy text,public opinion data)with visualization techniques(such as heat maps,time-series trend charts,3D building brochures)to construct an analysis framework for the Chengdu real estate market.By using the Adaptive Neuro-Fuzzy Inference System(ANFIS)prediction model,spatial GIS(Geographic Information System analysis)analysis,and interactive dashboards,this study reveals market differentiation,policy impacts,and changes in demand structure,thereby providing decision support for the government,enterprises,and homebuyers.
文摘The 53rd issue of Financial Innovation(FIN),Volume 11,No.5(2025),features 21 papers that can be classified into four main themes:the Special Issue on The Anomie of Artificial Intelligence(AI)in Finance:Bridging the Gap Between Technical Power and Human Wisdom,and Financial Markets and Investments,Economic and Policy Analysis,Corporate Governance and Related Market Dynamics.
文摘Relational theory represents a critical paradigm in understanding organizational dynamics,policy formation,and leadership effectiveness.This comprehensive literature review explores the theoretical foundations,practical implications,and organizational leadership applications of relational theory across diverse contextual frameworks.By synthesizing contemporary scholarly research,this review critically examines the theory’s epistemological underpinnings,methodological approaches,and transformative potential in organizational policy development.The analysis reveals complex interconnections between relational theory,organizational behavior,leadership strategies,and systemic policy implementation,highlighting both the theory’s significant potential and inherent limitations in contemporary organizational contexts.
文摘Remarkable achievements of the new energy industry policy framework over the past two decades Over the past two decades,the industry policy framework centered on the Renewable Energy Law has effectively facilitated the leapfrog development of China’s new energy sector.During this period,policy incentives were primarily focused on promoting the rational scaling of the industry,thereby driving rapid technological upgrades and iterations.This,in turn,enabled a significant reduc-tion in the cost of new energy power generation.In this process,policy played a pivotal role in two key areas:first,by providing per-kilowatt-hour subsidies to bridge the cost gap between new energy and conventional power sources;and second,by exempting the system cost of new energy grid-connected operation through a full guaranteed purchase system.
基金co-supported by the National Natural Science Foundation of China(No.12372045)the Guangdong Basic and Applied Basic Research Foundation,China(No.2023B1515120018)the Shenzhen Science and Technology Program,China(No.JCYJ20220818102207015).
文摘The increasing complexity of on-orbit tasks imposes great demands on the flexible operation of space robotic arms, prompting the development of space robots from single-arm manipulation to multi-arm collaboration. In this paper, a combined approach of Learning from Demonstration (LfD) and Reinforcement Learning (RL) is proposed for space multi-arm collaborative skill learning. The combination effectively resolves the trade-off between learning efficiency and feasible solution in LfD, as well as the time-consuming pursuit of the optimal solution in RL. With the prior knowledge of LfD, space robotic arms can achieve efficient guided learning in high-dimensional state-action space. Specifically, an LfD approach with Probabilistic Movement Primitives (ProMP) is firstly utilized to encode and reproduce the demonstration actions, generating a distribution as the initialization of policy. Then in the RL stage, a Relative Entropy Policy Search (REPS) algorithm modified in continuous state-action space is employed for further policy improvement. More importantly, the learned behaviors can maintain and reflect the characteristics of demonstrations. In addition, a series of supplementary policy search mechanisms are designed to accelerate the exploration process. The effectiveness of the proposed method has been verified both theoretically and experimentally. Moreover, comparisons with state-of-the-art methods have confirmed the outperformance of the approach.
基金supported by the National Natural Science Foundation of China(62273320).
文摘In recent years,reinforcement learning control theory has been well developed.However,model-free value iteration needs many iterations to achieve the desired precision,and modelfree policy iteration requires an initial stabilizing control policy.It is significant to propose a fast model-free algorithm to solve the continuous-time linear quadratic control problem without an initial stabilizing control policy.In this paper,we construct a homotopy path on which each point corresponds to an linear quadratic regulator problem.Based on policy iteration,model-based and model-free homotopy algorithms are proposed to solve the optimal control problem of continuous-time linear systems along the homotopy path.Our algorithms are speeded up using first-order differential information and do not require an initial stabilizing control policy.Finally,several practical examples are used to illustrate our results.
文摘Mandate-based and market-based mechanisms represent two primary approaches to achieving policy objectives,yet the debate over their relative effectiveness remains unresolved.The mandate-based approach is exemplified by pilot programs for low-carbon provinces and cities,referred to as“Low-Carbon Pilot Provinces/Cities”,while the market-based mechanism is reflected in pilot programs for carbon emissions trading markets,or“Carbon Trading Pilot Programs”.This paper employs event study analysis to compare the carbon emission reduction impacts of these two approaches.Our findings reveal that the Low-Carbon Pilot Provinces/Cities achieved emissions reduction primarily by curbing economic output,without significantly reducing carbon emissions intensity.In contrast,the Carbon Trading Pilot Programs led to an increase in total carbon emissions by driving economic growth,even as they reduced carbon emissions intensity.A heterogeneity analysis further indicates that the emissions reductions observed in the Low-Carbon Pilot Provinces/Cities were predominantly concentrated in economically less-developed regions,whereas the increase in carbon emissions associated with the Carbon Trading Pilot Programs was more significant in regions with lower initial carbon emissions intensity.Against the backdrop of China’s efforts to achieve its carbon peak and neutrality goals,this paper offers valuable insights for the design of effective climate policies.
基金financially supported by the Ningbo University of Technology New Faculty Research Fundthe 2023 Interdisciplinary Innovation Research Cultivation Program of School of Interdisciplinary Studies,RUCKey Project of the National Social Science Foundation of China(21ATQ008)。
文摘Purpose:Policies have often,albeit inadvertently,overlooked certain scientific insights,especially in the handling of complex events.This study aims to systematically uncover and evaluate pivotal scientific insights that have been underrepresented in policy documents by leveraging extensive datasets from policy texts and scholarly publications.Design/methodology/approach:This article introduces a research framework aimed at excavating scientific insights that have been overlooked by policy,encompassing four integral parts:data acquisition and preprocessing,the identification of overlooked content through thematic analysis,the discovery of overlooked content via keyword analysis,and a comprehensive analysis and discussion of the overlooked content.Leveraging this framework,the research conducts an in-depth exploration of the scientific content overlooked by policies during the COVID-19 pandemic.Findings:During the COVID-19 pandemic,scientific information in four domains was overlooked by policy:psychological state of the populace,environmental issues,the role of computer technology,and public relations.These findings indicate a systematic underrepresentation of important scientific insights in policy.Research limitations:This study is subject to two key limitations.Firstly,the text analysis method—relying on pre-extracted keywords and thematic structures—may not fully capture the nuanced context and complexity of scientific insights in policy documents.Secondly,the focus on a limited set of case studies restricts the broader applicability of the conclusions across diverse situations.Practical implications:The study introduces a quantitative framework using text analysis to identify overlooked scientific content in policy,bridging the gap between science and policy.It also highlights overlooked scientific information during COVID-19,promoting more evidence-based and robust policies through improved science-policy integration.Originality/value:This paper provides new ideas and methods for excavating scientific information that has been overlooked by policy,further deepens the understanding of the interaction between policy and science during the COVID-19 period,and lays the foundation for the more rational use of scientific information in policy-making.
基金The authors declare that fund support was received from National Social Science Fund of China[Grant No.23BJL010].
文摘As urbanization accelerates globally,air pollution-particularly PM_(2.5)-is becoming an increasingly significant threat,not only to public health but also the environment.In-depth research on the impact of China’s Zero Waste City pilot policy on PM_(2.5)concentration offers valuable insights into the policy’s effectiveness and provides a potential model for environmental governance worldwide.This study employs panel data from 293 Chinese cities from 2014 to 2022 to systematically analyze the impact of the Zero-Waste City policy on PM_(2.5)concentration using a difference-in-differences model.The findings indicate that the policy not only directly reduces PM_(2.5)concentration but also indirectly curbs PM_(2.5)emissions by enhancing green innovation and green economic efficiency.Moreover,the policy’s effects are found to be positively moderated by urban energy dependence and digital financial inclusion,while they are negatively moderated by the government debt ratio.Based on these findings,this study suggests that cities should actively develop their digital economy,reduce government debt,promote green innovation,and improve green economic efficiency,as doing so will enhance their implementation of environmental policies and promote sustainable urban development.
文摘This study investigates the critical intersection of cyberpsychology and cybersecurity policy development in small and medium-sized enterprises (SMEs). Through a mixed-methods approach incorporating surveys of 523 employees across 78 SMEs, qualitative interviews, and case studies, the research examines how psychological factors influence cybersecurity behaviors and policy effectiveness. Key findings reveal significant correlations between psychological factors and security outcomes, including the relationship between self-efficacy and policy compliance (r = 0.42, p β = 0.37, p < 0.001). The study identifies critical challenges in risk perception, policy complexity, and organizational culture affecting SME cybersecurity implementation. Results demonstrate that successful cybersecurity initiatives require the integration of psychological principles with technical solutions. The research provides a framework for developing human-centric security policies that address both behavioral and technical aspects of cybersecurity in resource-constrained environments.
基金co-supported by the National Natural Science Foundation of China(No.62103432)the China Postdoctoral Science Foundation(No.284881)the Young Talent fund of University Association for Science and Technology in Shaanxi,China(No.20210108)。
文摘Exo-atmospheric vehicles are constrained by limited maneuverability,which leads to the contradiction between evasive maneuver and precision strike.To address the problem of Integrated Evasion and Impact(IEI)decision under multi-constraint conditions,a hierarchical intelligent decision-making method based on Deep Reinforcement Learning(DRL)was proposed.First,an intelligent decision-making framework of“DRL evasion decision”+“impact prediction guidance decision”was established:it takes the impact point deviation correction ability as the constraint and the maximum miss distance as the objective,and effectively solves the problem of poor decisionmaking effect caused by the large IEI decision space.Second,to solve the sparse reward problem faced by evasion decision-making,a hierarchical decision-making method consisting of maneuver timing decision and maneuver duration decision was proposed,and the corresponding Markov Decision Process(MDP)was designed.A detailed simulation experiment was designed to analyze the advantages and computational complexity of the proposed method.Simulation results show that the proposed model has good performance and low computational resource requirement.The minimum miss distance is 21.3 m under the condition of guaranteeing the impact point accuracy,and the single decision-making time is 4.086 ms on an STM32F407 single-chip microcomputer,which has engineering application value.
基金supported by the National Natural Science Foundation of China (No.62202137)the China Postdoctoral Science Foundation (No.2023M730599)the Zhejiang Provincial Natural Science Foundation of China (No.LMS25F020009)。
文摘Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.
文摘Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd.cn/browse/al/al2019/。
文摘Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd.cn/browse/al/al2019/。
文摘Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd.cn/browse/al/al2019/。
文摘Innovation and Development Policy,简称“IDP”,中文名:《创新与发展政策(英文)》,是由中国科学院主管,中国科学院科技战略咨询研究院、中国科学学与科技政策研究会共同主办,国内外发行(ISSN:2096-5141,CN:10-1513/D)的英文国际期刊。目前期刊每年出版两期。已发表论文在期刊网站可以自由获取,http://idp-journal.casisd. cn/browse/al/al2019/。
文摘Purpose:This study examines the impact of research policy changes on scientific retractions of publications authored by Romanian authors,focusing on national trends and the interplay between policy reforms and publishing practices.Design/methodology/approach:Using data from the Retraction Watch Database and Web of Science(WoS),188 unique retractions involving Romanian authors(2000-2022)were analyzed.The study compared retraction patterns before and after the 2016 reforms,which prioritized the publication of articles in WoS-indexed journals over non-WoS outputs.Findings:The analysis identified two key trends:(1)before the 2016 reforms,retractions predominantly involved non-WoS journals(99 non-WoS retractions to 38 WoS retractions),a trend that reversed post-reform(16 non-WoS to 35 WoS),and(2)while the total number of WoS-indexed retractions increased after the reforms,the retraction rates for WoS articles remained stable.Post-reform reliance on MDPI journals,which have low retraction rates,partially explains this stability.Excluding MDPI publications,retraction rates for articles and reviews increase by 14.91%,aligning with patterns seen elsewhere.Research limitations:The study focuses on retractions involving Romanian authors,limiting its generalizability.Furthermore,reliance on database records may not fully capture all retractions.Practical implications:These findings underscore the need for research policy reforms to consider a broader range of effects,and the need for nuanced interpretations of retraction data,which are influenced by a complex range of factors,including specific publisher practices.Originality/value:This research is the first to investigate the complex relationship between research policy reforms,publisher behavior,and retraction trends.
文摘Background:Globally,the use of community pharmacies and pharmacists in the delivery of vaccination services has been hampered by several factors,laws,and regulations that do not support pharmacists to participate in the delivery of vaccination services.With the advent of COVID-19 pandemic,many countries have included community pharmacists and pharmacies in vaccination services to improve coverage.This study described the delivery of vaccination services in community pharmacies using the COVID-19 experience and how their involvement impacted vaccination coverage in Nigeria.It also exposed how this experience can be used to support policy revisions to formally recognize pharmacists in immunization delivery.Methods:A descriptive cross-sectional study was conducted among 474 community pharmacists in two southwestern States in Nigeria,using a semi-structured questionnaire.It determines the number of community pharmacists who have been trained in the delivery of vaccination services,the types of vaccination services provided,and vaccines administered in their pharmacies.Data were analyzed with descriptive and inferential statistics and p-value at≤0.05.Results:Response rate was 86.7%.Less than half of the respondents(40.1%)had undergone vaccination training.Of the 129(31.4%)respondents that provide vaccination services,72(55.8%)administer vaccines in their pharmacies.Out of these 72 respondents;45(62.5%)were administering vaccines before their involvement in COVID-19 vaccine administration;57(79.2%)of the health personnel who administer vaccines were pharmacists;60(83.3%)of them administer vaccines on request;22(30.6%)administered COVID-19 vaccines only;and only 7(9.7%)of the respondents had administered over 500 doses of COVID-19 vaccines.Training in vaccination was associated with the vaccination services provided(p<0.05).Respondents suggested government support through legal framework and policy review,training and empowering pharmacists in vaccine administration,and recognition of community pharmacists as PHC providers.
