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
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
This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in So...This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.展开更多
BACKGROUND Sustained viral load(VL)suppression is an important indicator of successful treatment among people living with human immunodeficiency virus(HIV).AIM To assess trends of different VL outcomes before and afte...BACKGROUND Sustained viral load(VL)suppression is an important indicator of successful treatment among people living with human immunodeficiency virus(HIV).AIM To assess trends of different VL outcomes before and after adoption of the Treat All policy among people living with HIV in Rwanda.METHODS Between 2014 and 2017,VL suppression[VL suppression(VLS)<200 copies/mL]was measured among people living with HIV from 28 healthcare facilities in Rwanda.Participant VL was measured at 6 months,18 months,and 30 months.The unit of analysis was visit-pair,with subjects across four visit-pair categories:(1)Sustained VL suppression(VL<200 copies/mL at two consecutive visits);(2)Persistent viremia(VL≥200 copies/mL at two consecutive visits);(3)Viral rebound(VL<200 copies/mL at prior visit only);and(4)Newly suppressed(VL<200 copies/mL at subsequent visit only).Poisson regression models with generalized estimating equations were used to estimate adjusted incidence risk ratio(aIRR)and 95%confidence intervals(CIs)for factors associated with sustained VLS.To handle missing data,multiple imputations was performed.RESULTS A total of 634 participants contributed 973 visit-pairs(295 single pairs and 339 double pairs).The median age was 37 years(interquartile range:32-43 years).The incidence rates of sustained VLS,persistent viremia,viral rebound,and new suppression were 85.2%,4.3%,4.6%,and 5.7%,respectively.Young individuals aged 18-24 years had higher incidence of viral rebound compared to those 25 years or older(14.8%vs 4.3%;P=0.011).Of the visit-pairs that had sustained VLS during the first two visits(49.8%;n=485),56.7%exhibited sustained VLS throughout follow-up.Compared to having no education,having at least primary education was associated with an increased likelihood of sustained VLS(aIRR=1.09;95%CI:1.01-1.17).Those who presented with advanced HIV disease at baseline had a 12%reduced likelihood of sustained VLS(aIRR=0.88;95%CI:0.79-0.99).Achieving sustained VLS did not differ before or after adoption of the Treat All policy.When the analysis was repeated on imputed datasets,similar results were found.CONCLUSION Although most people living with HIV have sustained VLS in Rwanda,individuals without formal education,those presenting with advanced HIV,and younger individuals were lagging on multiple outcomes.Interventions tailored to these individuals would improve treatment outcomes to achieve epidemic control.展开更多
Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models pla...Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models plays a vital role in guiding planners toword sustainable long-term aquifer exploita-tion.This study simulated monthly water table variations in the Kashan Plain over a ten-year period from 2008 to 2019 across 125 stress periods using the GMS model.The model was calibrated for both steady-state and transient conditions for the 2008–2016 period and validated for the 2016–2019 period.Results indicated a 4.4 m decline in groundwater levels over the 10-year study period.Given the plain's location in a arid climatic zone with limited effective precipitation for aquifer recharge,the study focused on ground-water extraction management.A modified two-point hedging policy was employed as a solution to mitigate critical groundwater depletion,reducing the annual drawdown rate from 0.44 m to 0.31 m and conserving 255 million cubic meters(mcm)of water annually.Although this approach slightly decreased reliability(i.e.the number of months meeting full water demands),it effectively minimized the risk of severe droughts and irreparable damages.This policy offers managers a dynamical and intelligent tool for regulating groundwater extraction,balancing aquifer sustainability with agricultural and urban water requirements.展开更多
Under the background of resource shortage and global warming,it is of great significance to explore the status,influencing factors and carbon emission reduction effect of waste recycling in China after the implementat...Under the background of resource shortage and global warming,it is of great significance to explore the status,influencing factors and carbon emission reduction effect of waste recycling in China after the implementation of new waste classification policy for guiding waste classification and carbon emission accounting.In this research,the temporal and spatial changes and influencing factors of waste recycling were studied from subdistrict level,life-cycle carbon emission reduction was predicted and policy suggestions for waste recycling were proposed.The results showed that after the implementation of new waste classification policy,the amount of recycled waste and the proportion of low-value recycled waste increased by 420.93 t and 2.29%per month on average,respectively.The district center has the largest amount of recycled waste.Income was the main factors affecting waste recycling,and online shopping and takeout could become important sources of recyclable waste.Accounting cradle-to-grave life cycle carbon footprint,waste plastics takes up the most contribution,accounting for 39.11%,and nearly 391.68 Mt CO_(2eq) would be reduced by waste recycling in China by 2030.Therefore,in the process of waste classification,refining waste classification to increase the amount of low-value recyclables,and rationally deploying collection and transportation vehicles to ensure efficient waste recycling are of great significance to achieve the goal of“carbon peaking and carbon neutrality”.展开更多
This paper examines the transformation and development of the Xinhui Chenpi industry under the rural revitalization strategy in China.The study highlights the significant growth of the industry,with the annual product...This paper examines the transformation and development of the Xinhui Chenpi industry under the rural revitalization strategy in China.The study highlights the significant growth of the industry,with the annual production of chenpi reaching approximately 7,000 tons and the total output value surpassing 26 billion yuan in 2024.The paper proposes strategies to foster sustainable growth in industries facing challenges such as inefficient production processes,inconsistent product quality,and a lack of policy awareness among operators.These strategies include optimizing support policies,enhancing regulatory frameworks,and leveraging digital technologies for brand building and market expansion.The research contributes to understanding the development trajectory of the Xinhui Chenpi industry and provides insights for policymakers and industry practitioners.展开更多
This study aims to analyze waste mitigation policies implemented in South Tangerang City,Indonesia,which faces significant challenges in waste management.Despite various mitigation efforts,issues such as limited landf...This study aims to analyze waste mitigation policies implemented in South Tangerang City,Indonesia,which faces significant challenges in waste management.Despite various mitigation efforts,issues such as limited landfill capacity,low community participation in waste sorting,and inadequate treatment facilities continue to hinder effective waste management.Using a case study approach,the research assesses the effectiveness of existing policies and identifies key barriers.The findings show that poor waste management,characterized by a high volume of waste sent to landfills,leads to severe environmental pollution—including air,soil,and water contamination—and increases the risk of disasters such as landfill collapses.This negative impact is not only felt by the environment,but also has an impact on public health and regional budget efficiency.While initiatives such as the 3R(Reduce,Reuse,Recycle)program and organic waste treatment have been introduced,low community engagement and inadequate treatment facilities remain major obstacles.The study also compares successful waste management policies from developed countries such as Germany,Sweden,and South Korea,offering valuable insights for local policy adaptation.Based on these findings,the study recommends increasing government capacity,improving access to and the quality of Reduce,Reuse,Recycle(WPP3R)Waste Treatment sites,providing incentives,encouraging community involvement,and promoting collaboration between the public and private sectors to achieve more efficient and sustainable waste management.展开更多
Bolt assembly by robots is a vital and difficult task for replacing astronauts in extravehicular activities(EVA),but the trajectory efficiency still needs to be improved during the wrench insertion into hex hole of bo...Bolt assembly by robots is a vital and difficult task for replacing astronauts in extravehicular activities(EVA),but the trajectory efficiency still needs to be improved during the wrench insertion into hex hole of bolt.In this paper,a policy iteration method based on reinforcement learning(RL)is proposed,by which the problem of trajectory efficiency improvement is constructed as an issue of RL-based objective optimization.Firstly,the projection relation between raw data and state-action space is established,and then a policy iteration initialization method is designed based on the projection to provide the initialization policy for iteration.Policy iteration based on the protective policy is applied to continuously evaluating and optimizing the action-value function of all state-action pairs till the convergence is obtained.To verify the feasibility and effectiveness of the proposed method,a noncontact demonstration experiment with human supervision is performed.Experimental results show that the initialization policy and the generated policy can be obtained by the policy iteration method in a limited number of demonstrations.A comparison between the experiments with two different assembly tolerances shows that the convergent generated policy possesses higher trajectory efficiency than the conservative one.In addition,this method can ensure safety during the training process and improve utilization efficiency of demonstration data.展开更多
Based on SPOT-5 images, 1：1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features an...Based on SPOT-5 images, 1：1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features and factors influencing farmland marginalization. The results showed： （1） During 2002-2012, the rate of farmland marginalization was 16.18%, which was mainly found in the high areas of northern Qiyao mountains and the medium-altitude areas of southern Qiyao mountains. And this farmland marginalization will increase, associated with non-agriculturalization of rural labourers and aging of the remaining labourers. （2） Elevation, distance radius from villages and road connections had a great in- fluence on farmland marginalization. Farmland marginalization rates showed an increasing trend with the increase of elevation, and 60.88% of the total farmland marginalization area is found at an altitude greater than 1000 m above sea level. The marginalization trend also increases with slope and distance from the distribution network. （3） Farmland area per labourer and the average age of farm labourers were major factors driving farmland marginalization. Farmland transfer and small agricultural machinery sets affect farmland marginalization with respect to management and productivity efficiency. （4） Farmland with ＂comparative-disadvantage-dominated marginalization＂ accounted for 55.32% of the total farmland marginalization area, followed by ＂location-dominated marginalization＂ （33.80%）. （5） According to the specifics of each real situation, different policies are suggested to mitigate the margin- alization. A ＂continuous marginalization＂ policy will encourage the return of farmland to forest in ＂terrain-dominated marginalization＂. An ＂anti-marginalization＂ policy is suggested to create new rural accommodation and improve the rural road system to counteract ＂terrain-dominated marginalization＂. And another ＂anti-marginalization＂ policy is planned to improve management and micro-mechanization for ＂comparative-disadvantage-dominated marginalization＂. A new idea was developed to integrate high resolution remote sensing and statistical data with survey information to identify land marginalization and its driving forces in mountainous areas.展开更多
We discuss the solution of complex multistage decision problems using methods that are based on the idea of policy iteration(PI),i.e.,start from some base policy and generate an improved policy.Rollout is the simplest...We discuss the solution of complex multistage decision problems using methods that are based on the idea of policy iteration(PI),i.e.,start from some base policy and generate an improved policy.Rollout is the simplest method of this type,where just one improved policy is generated.We can view PI as repeated application of rollout,where the rollout policy at each iteration serves as the base policy for the next iteration.In contrast with PI,rollout has a robustness property:it can be applied on-line and is suitable for on-line replanning.Moreover,rollout can use as base policy one of the policies produced by PI,thereby improving on that policy.This is the type of scheme underlying the prominently successful Alpha Zero chess program.In this paper we focus on rollout and PI-like methods for problems where the control consists of multiple components each selected(conceptually)by a separate agent.This is the class of multiagent problems where the agents have a shared objective function,and a shared and perfect state information.Based on a problem reformulation that trades off control space complexity with state space complexity,we develop an approach,whereby at every stage,the agents sequentially(one-at-a-time)execute a local rollout algorithm that uses a base policy,together with some coordinating information from the other agents.The amount of total computation required at every stage grows linearly with the number of agents.By contrast,in the standard rollout algorithm,the amount of total computation grows exponentially with the number of agents.Despite the dramatic reduction in required computation,we show that our multiagent rollout algorithm has the fundamental cost improvement property of standard rollout:it guarantees an improved performance relative to the base policy.We also discuss autonomous multiagent rollout schemes that allow the agents to make decisions autonomously through the use of precomputed signaling information,which is sufficient to maintain the cost improvement property,without any on-line coordination of control selection between the agents.For discounted and other infinite horizon problems,we also consider exact and approximate PI algorithms involving a new type of one-agent-at-a-time policy improvement operation.For one of our PI algorithms,we prove convergence to an agentby-agent optimal policy,thus establishing a connection with the theory of teams.For another PI algorithm,which is executed over a more complex state space,we prove convergence to an optimal policy.Approximate forms of these algorithms are also given,based on the use of policy and value neural networks.These PI algorithms,in both their exact and their approximate form are strictly off-line methods,but they can be used to provide a base policy for use in an on-line multiagent rollout scheme.展开更多
Results of the Global Burden of Disease, Injury and Risk Factor Study 2010 （GBD 2010） were released on December 13, 2012 in London, a series of papers concerning the project have been published in the Lancet[1]. Res...Results of the Global Burden of Disease, Injury and Risk Factor Study 2010 （GBD 2010） were released on December 13, 2012 in London, a series of papers concerning the project have been published in the Lancet[1]. Research findings of the project have been reported in the United States, the United Kingdom, Indonesia, China[2] and Australia, and widely applied across the world. In addition, the GBD 2010 will see more countries report their project research findings and implement these findings in the near future. The GBD 2010 provides researchers, administrators and policymakers with new and critical sources for their research, teaching and policymaking.展开更多
With the vigorous promotion of energy conservation and implementation of clean energy strategies,China＇s natural gas industry has entered a rapid development phase,and natural gas is playing an increasingly important...With the vigorous promotion of energy conservation and implementation of clean energy strategies,China＇s natural gas industry has entered a rapid development phase,and natural gas is playing an increasingly important role in China＇s energy structure.This paper uses a Generalized Weng model to forecast Chinese regional natural gas production,where accuracy and reasonableness compared with other predictions are enhanced by taking remaining estimated recoverable resources as a criterion.The forecast shows that China＇s natural gas production will maintain a rapid growth with peak gas of 323 billion cubic meters a year coming in 2036;in 2020,natural gas production will surpass that of oil to become a more important source of energy.Natural gas will play an important role in optimizing China＇s energy consumption structure and will be a strategic replacement of oil.This will require that exploration and development of conventional natural gas is highly valued and its industrial development to be reasonably planned.As well,full use should be made of domestic and international markets.Initiative should also be taken in the exploration and development of unconventional and deepwater gas,which shall form a complement to the development of China＇s conventional natural gas industry.展开更多
The libration control problem of space tether system(STS)for post-capture of payload is studied.The process of payload capture will cause tether swing and deviation from the nominal position,resulting in the failure o...The libration control problem of space tether system(STS)for post-capture of payload is studied.The process of payload capture will cause tether swing and deviation from the nominal position,resulting in the failure of capture mission.Due to unknown inertial parameters after capturing the payload,an adaptive optimal control based on policy iteration is developed to stabilize the uncertain dynamic system in the post-capture phase.By introducing integral reinforcement learning(IRL)scheme,the algebraic Riccati equation(ARE)can be online solved without known dynamics.To avoid computational burden from iteration equations,the online implementation of policy iteration algorithm is provided by the least-squares solution method.Finally,the effectiveness of the algorithm is validated by numerical simulations.展开更多
The rapid increase in resource sharing across domains in the cloud comput- ing environment makes the task of managing inter-domain access control policy integration difficult for the security administrators. Al- thoug...The rapid increase in resource sharing across domains in the cloud comput- ing environment makes the task of managing inter-domain access control policy integration difficult for the security administrators. Al- though a number of policy integration and sec- urity analysis mechanisms have been devel- oped, few focus on enabling the average ad- ministrator by providing an intuitive cognitive sense about the integrated policies, which considerably undermines the usability factor. In this paper we propose a visualization flame- work for inter-domain access control policy integration, which integrates Role Based Ac- cess Control （RBAC） policies on the basis of role-mapping and then visualizes the inte- grated result. The role mapping algorithm in the framework considers the hybrid role hier- archy. It can not only satisfy the security con- straints of non-cyclic inheritance and separa- tion of duty but also make visualization easier. The framework uses role-permission trees and semantic substrates to visualize the integrated policies. Through the interactive policy query visualization, the average administrator can gain an intuitive understanding of the policy integration result.展开更多
Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iterati...Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iteration(DTTV)algorithm,is developed.The iterative control law is designed to update the iterative value function which approximates the index function of optimal performance.The admissibility of the iterative control law is analyzed.The results show that the iterative value function is non-increasingly convergent to the Bellman-equation optimal solution.To implement the algorithm,neural networks are employed and a new implementation structure is established,which avoids solving the generalized Bellman equation in each iteration.Finally,the optimal control laws for torsional pendulum and inverted pendulum systems are obtained by using the DTTV policy iteration algorithm,where the mass and pendulum bar length are permitted to be time-varying parameters.The effectiveness of the developed method is illustrated by numerical results and comparisons.展开更多
Integrating and sharing data from different data sources is one of the trends to make better use of data. However, data integration hampers data confidentiality where each data source has its own access control policy...Integrating and sharing data from different data sources is one of the trends to make better use of data. However, data integration hampers data confidentiality where each data source has its own access control policy. This paper includes a discussion on the issue about access control across multiple data sources when they arc combined together in the scenario of searching over these data. A method based on multilevel security for data integration is proposed. The proposed method allows the merging of policies and also tackles the issue of policy conflicts between different data sources.展开更多
Government interventions to manage and improve trade-offs in social and ecological systems are made through various policy instruments.The conditions of the social ecological system(SES)are a function of the cumulativ...Government interventions to manage and improve trade-offs in social and ecological systems are made through various policy instruments.The conditions of the social ecological system(SES)are a function of the cumulatively implemented policy instruments.Although both policy instruments and social ecological system frameworks have played important roles in theoretical developments in resource management,they have largely been considered in isolation from each other.By including policy instruments into the SES framework,the proposed conceptual model serves as a template to examine how governing takes place by deciphering:1)how the biophysical system has been understood in resource governance;2)how the social system has been set up in resource governance;and 3)how the trade-offbetween dynamic biophysical and social systems has been managed in the governance of SESs.This model can assist identifying any absent,overlapping or contradictory policy instruments in the governance of an SES.展开更多
Valadimir Putin assumed office as President of Russia on 7th May. It is a signfor Russia to enter into a new era. Attention is called to how Russia will imple-ment its foreign policy during Putin presidency, and what ...Valadimir Putin assumed office as President of Russia on 7th May. It is a signfor Russia to enter into a new era. Attention is called to how Russia will imple-ment its foreign policy during Putin presidency, and what is the prospect. I Mr. Putin has started readjusting Russian foreign policy early as Acting Presi-dent. According to the newest version of the "Concept of National Security" andthe "New Foreign Doctrine", it is obvious that Russia will carry on pragmatic for-展开更多
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.
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.
文摘This study examines the effects of rapid land use changes in India,with a specific focus on Sonipat District in Haryana—a region undergoing significant urban expansion.Over the past two decades,rural landscapes in Sonipat have undergone notable transformation,as open spaces and agricultural lands are increasingly converted into residential colonies,commercial hubs,and industrial zones.While such changes reflect economic development and urban growth,they also raise critical concerns about sustainability,especially in terms of food security,groundwater depletion,and environmental degradation.The study examines land use changes between 2000 and 2024 using remote sensing techniques and spatial analysis.It further incorporates secondary data and insights from community-level interactions to assess the socio-economic and ecological impacts of this transformation.The findings indicate rising land fragmentation,loss of agricultural livelihoods,pressure on civic infrastructure,and increasing pollution—factors that threaten long-term regional sustainability.The study underscores the urgent need to reconcile urban development with environmental and social sustainability.By offering a detailed case study of Sonipat,this research contributes to the broader discourse on India’s urbanisation pathways.It aims to provide policymakers,planners,and researchers with evidence-based recommendations to manage land transitions more responsibly,promoting urban growth models that ensure ecological integrity,equitable development,and long-term resilience.
文摘BACKGROUND Sustained viral load(VL)suppression is an important indicator of successful treatment among people living with human immunodeficiency virus(HIV).AIM To assess trends of different VL outcomes before and after adoption of the Treat All policy among people living with HIV in Rwanda.METHODS Between 2014 and 2017,VL suppression[VL suppression(VLS)<200 copies/mL]was measured among people living with HIV from 28 healthcare facilities in Rwanda.Participant VL was measured at 6 months,18 months,and 30 months.The unit of analysis was visit-pair,with subjects across four visit-pair categories:(1)Sustained VL suppression(VL<200 copies/mL at two consecutive visits);(2)Persistent viremia(VL≥200 copies/mL at two consecutive visits);(3)Viral rebound(VL<200 copies/mL at prior visit only);and(4)Newly suppressed(VL<200 copies/mL at subsequent visit only).Poisson regression models with generalized estimating equations were used to estimate adjusted incidence risk ratio(aIRR)and 95%confidence intervals(CIs)for factors associated with sustained VLS.To handle missing data,multiple imputations was performed.RESULTS A total of 634 participants contributed 973 visit-pairs(295 single pairs and 339 double pairs).The median age was 37 years(interquartile range:32-43 years).The incidence rates of sustained VLS,persistent viremia,viral rebound,and new suppression were 85.2%,4.3%,4.6%,and 5.7%,respectively.Young individuals aged 18-24 years had higher incidence of viral rebound compared to those 25 years or older(14.8%vs 4.3%;P=0.011).Of the visit-pairs that had sustained VLS during the first two visits(49.8%;n=485),56.7%exhibited sustained VLS throughout follow-up.Compared to having no education,having at least primary education was associated with an increased likelihood of sustained VLS(aIRR=1.09;95%CI:1.01-1.17).Those who presented with advanced HIV disease at baseline had a 12%reduced likelihood of sustained VLS(aIRR=0.88;95%CI:0.79-0.99).Achieving sustained VLS did not differ before or after adoption of the Treat All policy.When the analysis was repeated on imputed datasets,similar results were found.CONCLUSION Although most people living with HIV have sustained VLS in Rwanda,individuals without formal education,those presenting with advanced HIV,and younger individuals were lagging on multiple outcomes.Interventions tailored to these individuals would improve treatment outcomes to achieve epidemic control.
文摘Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models plays a vital role in guiding planners toword sustainable long-term aquifer exploita-tion.This study simulated monthly water table variations in the Kashan Plain over a ten-year period from 2008 to 2019 across 125 stress periods using the GMS model.The model was calibrated for both steady-state and transient conditions for the 2008–2016 period and validated for the 2016–2019 period.Results indicated a 4.4 m decline in groundwater levels over the 10-year study period.Given the plain's location in a arid climatic zone with limited effective precipitation for aquifer recharge,the study focused on ground-water extraction management.A modified two-point hedging policy was employed as a solution to mitigate critical groundwater depletion,reducing the annual drawdown rate from 0.44 m to 0.31 m and conserving 255 million cubic meters(mcm)of water annually.Although this approach slightly decreased reliability(i.e.the number of months meeting full water demands),it effectively minimized the risk of severe droughts and irreparable damages.This policy offers managers a dynamical and intelligent tool for regulating groundwater extraction,balancing aquifer sustainability with agricultural and urban water requirements.
基金supported by the Construction of Environmental Science and Engineering Discipline for the Goal of Carbon Peaking and Carbon Neutrality Funding comes from Beijing Forestry University(No.2022XKJS0207).
文摘Under the background of resource shortage and global warming,it is of great significance to explore the status,influencing factors and carbon emission reduction effect of waste recycling in China after the implementation of new waste classification policy for guiding waste classification and carbon emission accounting.In this research,the temporal and spatial changes and influencing factors of waste recycling were studied from subdistrict level,life-cycle carbon emission reduction was predicted and policy suggestions for waste recycling were proposed.The results showed that after the implementation of new waste classification policy,the amount of recycled waste and the proportion of low-value recycled waste increased by 420.93 t and 2.29%per month on average,respectively.The district center has the largest amount of recycled waste.Income was the main factors affecting waste recycling,and online shopping and takeout could become important sources of recyclable waste.Accounting cradle-to-grave life cycle carbon footprint,waste plastics takes up the most contribution,accounting for 39.11%,and nearly 391.68 Mt CO_(2eq) would be reduced by waste recycling in China by 2030.Therefore,in the process of waste classification,refining waste classification to increase the amount of low-value recyclables,and rationally deploying collection and transportation vehicles to ensure efficient waste recycling are of great significance to achieve the goal of“carbon peaking and carbon neutrality”.
基金Research on the Digital Transformation of the Xinhui Dried Tangerine Peel Industry under the Rural Revitalization Strategy(2023HSQX100)。
文摘This paper examines the transformation and development of the Xinhui Chenpi industry under the rural revitalization strategy in China.The study highlights the significant growth of the industry,with the annual production of chenpi reaching approximately 7,000 tons and the total output value surpassing 26 billion yuan in 2024.The paper proposes strategies to foster sustainable growth in industries facing challenges such as inefficient production processes,inconsistent product quality,and a lack of policy awareness among operators.These strategies include optimizing support policies,enhancing regulatory frameworks,and leveraging digital technologies for brand building and market expansion.The research contributes to understanding the development trajectory of the Xinhui Chenpi industry and provides insights for policymakers and industry practitioners.
文摘This study aims to analyze waste mitigation policies implemented in South Tangerang City,Indonesia,which faces significant challenges in waste management.Despite various mitigation efforts,issues such as limited landfill capacity,low community participation in waste sorting,and inadequate treatment facilities continue to hinder effective waste management.Using a case study approach,the research assesses the effectiveness of existing policies and identifies key barriers.The findings show that poor waste management,characterized by a high volume of waste sent to landfills,leads to severe environmental pollution—including air,soil,and water contamination—and increases the risk of disasters such as landfill collapses.This negative impact is not only felt by the environment,but also has an impact on public health and regional budget efficiency.While initiatives such as the 3R(Reduce,Reuse,Recycle)program and organic waste treatment have been introduced,low community engagement and inadequate treatment facilities remain major obstacles.The study also compares successful waste management policies from developed countries such as Germany,Sweden,and South Korea,offering valuable insights for local policy adaptation.Based on these findings,the study recommends increasing government capacity,improving access to and the quality of Reduce,Reuse,Recycle(WPP3R)Waste Treatment sites,providing incentives,encouraging community involvement,and promoting collaboration between the public and private sectors to achieve more efficient and sustainable waste management.
基金supported by the National Natural Science Foundation of China(No.91848202)the Special Foundation(Pre-Station)of China Postdoctoral Science(No.2021TQ0089)。
文摘Bolt assembly by robots is a vital and difficult task for replacing astronauts in extravehicular activities(EVA),but the trajectory efficiency still needs to be improved during the wrench insertion into hex hole of bolt.In this paper,a policy iteration method based on reinforcement learning(RL)is proposed,by which the problem of trajectory efficiency improvement is constructed as an issue of RL-based objective optimization.Firstly,the projection relation between raw data and state-action space is established,and then a policy iteration initialization method is designed based on the projection to provide the initialization policy for iteration.Policy iteration based on the protective policy is applied to continuously evaluating and optimizing the action-value function of all state-action pairs till the convergence is obtained.To verify the feasibility and effectiveness of the proposed method,a noncontact demonstration experiment with human supervision is performed.Experimental results show that the initialization policy and the generated policy can be obtained by the policy iteration method in a limited number of demonstrations.A comparison between the experiments with two different assembly tolerances shows that the convergent generated policy possesses higher trajectory efficiency than the conservative one.In addition,this method can ensure safety during the training process and improve utilization efficiency of demonstration data.
基金The NSFC-IIASA Major International Joint Research Project, No.41161140352 Natural Science Foundation of Chongqing, No.2010JJ0069 Science and Technology Great Special Project on Controlling and Fathering Water Pollution during the National 12th Five-year Plan, No.2012ZX07104-003
文摘Based on SPOT-5 images, 1：1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features and factors influencing farmland marginalization. The results showed： （1） During 2002-2012, the rate of farmland marginalization was 16.18%, which was mainly found in the high areas of northern Qiyao mountains and the medium-altitude areas of southern Qiyao mountains. And this farmland marginalization will increase, associated with non-agriculturalization of rural labourers and aging of the remaining labourers. （2） Elevation, distance radius from villages and road connections had a great in- fluence on farmland marginalization. Farmland marginalization rates showed an increasing trend with the increase of elevation, and 60.88% of the total farmland marginalization area is found at an altitude greater than 1000 m above sea level. The marginalization trend also increases with slope and distance from the distribution network. （3） Farmland area per labourer and the average age of farm labourers were major factors driving farmland marginalization. Farmland transfer and small agricultural machinery sets affect farmland marginalization with respect to management and productivity efficiency. （4） Farmland with ＂comparative-disadvantage-dominated marginalization＂ accounted for 55.32% of the total farmland marginalization area, followed by ＂location-dominated marginalization＂ （33.80%）. （5） According to the specifics of each real situation, different policies are suggested to mitigate the margin- alization. A ＂continuous marginalization＂ policy will encourage the return of farmland to forest in ＂terrain-dominated marginalization＂. An ＂anti-marginalization＂ policy is suggested to create new rural accommodation and improve the rural road system to counteract ＂terrain-dominated marginalization＂. And another ＂anti-marginalization＂ policy is planned to improve management and micro-mechanization for ＂comparative-disadvantage-dominated marginalization＂. A new idea was developed to integrate high resolution remote sensing and statistical data with survey information to identify land marginalization and its driving forces in mountainous areas.
文摘We discuss the solution of complex multistage decision problems using methods that are based on the idea of policy iteration(PI),i.e.,start from some base policy and generate an improved policy.Rollout is the simplest method of this type,where just one improved policy is generated.We can view PI as repeated application of rollout,where the rollout policy at each iteration serves as the base policy for the next iteration.In contrast with PI,rollout has a robustness property:it can be applied on-line and is suitable for on-line replanning.Moreover,rollout can use as base policy one of the policies produced by PI,thereby improving on that policy.This is the type of scheme underlying the prominently successful Alpha Zero chess program.In this paper we focus on rollout and PI-like methods for problems where the control consists of multiple components each selected(conceptually)by a separate agent.This is the class of multiagent problems where the agents have a shared objective function,and a shared and perfect state information.Based on a problem reformulation that trades off control space complexity with state space complexity,we develop an approach,whereby at every stage,the agents sequentially(one-at-a-time)execute a local rollout algorithm that uses a base policy,together with some coordinating information from the other agents.The amount of total computation required at every stage grows linearly with the number of agents.By contrast,in the standard rollout algorithm,the amount of total computation grows exponentially with the number of agents.Despite the dramatic reduction in required computation,we show that our multiagent rollout algorithm has the fundamental cost improvement property of standard rollout:it guarantees an improved performance relative to the base policy.We also discuss autonomous multiagent rollout schemes that allow the agents to make decisions autonomously through the use of precomputed signaling information,which is sufficient to maintain the cost improvement property,without any on-line coordination of control selection between the agents.For discounted and other infinite horizon problems,we also consider exact and approximate PI algorithms involving a new type of one-agent-at-a-time policy improvement operation.For one of our PI algorithms,we prove convergence to an agentby-agent optimal policy,thus establishing a connection with the theory of teams.For another PI algorithm,which is executed over a more complex state space,we prove convergence to an optimal policy.Approximate forms of these algorithms are also given,based on the use of policy and value neural networks.These PI algorithms,in both their exact and their approximate form are strictly off-line methods,but they can be used to provide a base policy for use in an on-line multiagent rollout scheme.
文摘Results of the Global Burden of Disease, Injury and Risk Factor Study 2010 （GBD 2010） were released on December 13, 2012 in London, a series of papers concerning the project have been published in the Lancet[1]. Research findings of the project have been reported in the United States, the United Kingdom, Indonesia, China[2] and Australia, and widely applied across the world. In addition, the GBD 2010 will see more countries report their project research findings and implement these findings in the near future. The GBD 2010 provides researchers, administrators and policymakers with new and critical sources for their research, teaching and policymaking.
基金the National Social Science Funds of China (13&ZD159)the National Natural Science Foundation of China (71303258, 71373285)+1 种基金MOE (Ministry of Education in China) Project of Humanities and Social Sciences (13YJC630148)Science Foundation of China University of Petroleum, Beijing (ZX20150130) for sponsoring this joint research
文摘With the vigorous promotion of energy conservation and implementation of clean energy strategies,China＇s natural gas industry has entered a rapid development phase,and natural gas is playing an increasingly important role in China＇s energy structure.This paper uses a Generalized Weng model to forecast Chinese regional natural gas production,where accuracy and reasonableness compared with other predictions are enhanced by taking remaining estimated recoverable resources as a criterion.The forecast shows that China＇s natural gas production will maintain a rapid growth with peak gas of 323 billion cubic meters a year coming in 2036;in 2020,natural gas production will surpass that of oil to become a more important source of energy.Natural gas will play an important role in optimizing China＇s energy consumption structure and will be a strategic replacement of oil.This will require that exploration and development of conventional natural gas is highly valued and its industrial development to be reasonably planned.As well,full use should be made of domestic and international markets.Initiative should also be taken in the exploration and development of unconventional and deepwater gas,which shall form a complement to the development of China＇s conventional natural gas industry.
基金supported by the National Natural Science Foundation of China(No.62111530051)the Fundamental Research Funds for the Central Universities(No.3102017JC06002)the Shaanxi Science and Technology Program,China(No.2017KW-ZD-04).
文摘The libration control problem of space tether system(STS)for post-capture of payload is studied.The process of payload capture will cause tether swing and deviation from the nominal position,resulting in the failure of capture mission.Due to unknown inertial parameters after capturing the payload,an adaptive optimal control based on policy iteration is developed to stabilize the uncertain dynamic system in the post-capture phase.By introducing integral reinforcement learning(IRL)scheme,the algebraic Riccati equation(ARE)can be online solved without known dynamics.To avoid computational burden from iteration equations,the online implementation of policy iteration algorithm is provided by the least-squares solution method.Finally,the effectiveness of the algorithm is validated by numerical simulations.
基金supported in part by National Key Basic Research Program of China (973 Program) under Grant No.2013CB329603National Natural Science Foundation of China under Grant No.60903191
文摘The rapid increase in resource sharing across domains in the cloud comput- ing environment makes the task of managing inter-domain access control policy integration difficult for the security administrators. Al- though a number of policy integration and sec- urity analysis mechanisms have been devel- oped, few focus on enabling the average ad- ministrator by providing an intuitive cognitive sense about the integrated policies, which considerably undermines the usability factor. In this paper we propose a visualization flame- work for inter-domain access control policy integration, which integrates Role Based Ac- cess Control （RBAC） policies on the basis of role-mapping and then visualizes the inte- grated result. The role mapping algorithm in the framework considers the hybrid role hier- archy. It can not only satisfy the security con- straints of non-cyclic inheritance and separa- tion of duty but also make visualization easier. The framework uses role-permission trees and semantic substrates to visualize the integrated policies. Through the interactive policy query visualization, the average administrator can gain an intuitive understanding of the policy integration result.
基金supported in part by Fundamental Research Funds for the Central Universities(2022JBZX024)in part by the National Natural Science Foundation of China(61872037,61273167)。
文摘Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iteration(DTTV)algorithm,is developed.The iterative control law is designed to update the iterative value function which approximates the index function of optimal performance.The admissibility of the iterative control law is analyzed.The results show that the iterative value function is non-increasingly convergent to the Bellman-equation optimal solution.To implement the algorithm,neural networks are employed and a new implementation structure is established,which avoids solving the generalized Bellman equation in each iteration.Finally,the optimal control laws for torsional pendulum and inverted pendulum systems are obtained by using the DTTV policy iteration algorithm,where the mass and pendulum bar length are permitted to be time-varying parameters.The effectiveness of the developed method is illustrated by numerical results and comparisons.
基金Supported by the China MOE-China Mobile Research Fund(MCM20121051,MCM20130651)China MOE Doctoral Research Fund(20134407120017)+2 种基金Natural Science Foundation of Guangdong Province(S2012030006242)Guangdong Industry Development Fund(S2014-007)Guangzhou Industry Cooperation Fund(2014Y2-00004,2014Y2-00006)
文摘Integrating and sharing data from different data sources is one of the trends to make better use of data. However, data integration hampers data confidentiality where each data source has its own access control policy. This paper includes a discussion on the issue about access control across multiple data sources when they arc combined together in the scenario of searching over these data. A method based on multilevel security for data integration is proposed. The proposed method allows the merging of policies and also tackles the issue of policy conflicts between different data sources.
基金This work was funded by the Commonwealth of Australia under the Australia Awards Scholarship and was partly supported through the Aus-tralian Research Council Future Fellowship Program(FT130100274).
文摘Government interventions to manage and improve trade-offs in social and ecological systems are made through various policy instruments.The conditions of the social ecological system(SES)are a function of the cumulatively implemented policy instruments.Although both policy instruments and social ecological system frameworks have played important roles in theoretical developments in resource management,they have largely been considered in isolation from each other.By including policy instruments into the SES framework,the proposed conceptual model serves as a template to examine how governing takes place by deciphering:1)how the biophysical system has been understood in resource governance;2)how the social system has been set up in resource governance;and 3)how the trade-offbetween dynamic biophysical and social systems has been managed in the governance of SESs.This model can assist identifying any absent,overlapping or contradictory policy instruments in the governance of an SES.
文摘Valadimir Putin assumed office as President of Russia on 7th May. It is a signfor Russia to enter into a new era. Attention is called to how Russia will imple-ment its foreign policy during Putin presidency, and what is the prospect. I Mr. Putin has started readjusting Russian foreign policy early as Acting Presi-dent. According to the newest version of the "Concept of National Security" andthe "New Foreign Doctrine", it is obvious that Russia will carry on pragmatic for-
