Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may r...Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.展开更多
Governance debates gained strong momentum in Africa in early December 2025 as the China-Kenya Readers Forum on Xi Jinping:The Governance of China convened in Nairobi on 1 December 2025,followed by a promotional event ...Governance debates gained strong momentum in Africa in early December 2025 as the China-Kenya Readers Forum on Xi Jinping:The Governance of China convened in Nairobi on 1 December 2025,followed by a promotional event for the English edition of the book’s fifth volume on 3 December 2025 in Johannesburg,South Africa.展开更多
Vehicle Edge Computing(VEC)and Cloud Computing(CC)significantly enhance the processing efficiency of delay-sensitive and computation-intensive applications by offloading compute-intensive tasks from resource-constrain...Vehicle Edge Computing(VEC)and Cloud Computing(CC)significantly enhance the processing efficiency of delay-sensitive and computation-intensive applications by offloading compute-intensive tasks from resource-constrained onboard devices to nearby Roadside Unit(RSU),thereby achieving lower delay and energy consumption.However,due to the limited storage capacity and energy budget of RSUs,it is challenging to meet the demands of the highly dynamic Internet of Vehicles(IoV)environment.Therefore,determining reasonable service caching and computation offloading strategies is crucial.To address this,this paper proposes a joint service caching scheme for cloud-edge collaborative IoV computation offloading.By modeling the dynamic optimization problem using Markov Decision Processes(MDP),the scheme jointly optimizes task delay,energy consumption,load balancing,and privacy entropy to achieve better quality of service.Additionally,a dynamic adaptive multi-objective deep reinforcement learning algorithm is proposed.Each Double Deep Q-Network(DDQN)agent obtains rewards for different objectives based on distinct reward functions and dynamically updates the objective weights by learning the value changes between objectives using Radial Basis Function Networks(RBFN),thereby efficiently approximating the Pareto-optimal decisions for multiple objectives.Extensive experiments demonstrate that the proposed algorithm can better coordinate the three-tier computing resources of cloud,edge,and vehicles.Compared to existing algorithms,the proposed method reduces task delay and energy consumption by 10.64%and 5.1%,respectively.展开更多
Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance.Multi-objective spatial collaborative optimization is a powerful method f...Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance.Multi-objective spatial collaborative optimization is a powerful method for achieving sustainable regional development.Previous studies on multi-objective spatial optimization do not involve spatial corrections to simulation results based on the natural endowment of space resources.This study proposes an Ecological Security-Food Security-Urban Sustainable Development(ES-FS-USD)spatial optimization framework.This framework combines the non-dominated sorting genetic algorithm II(NSGA-II)and patch-generating land use simulation(PLUS)model with an ecological protection importance evaluation,comprehensive agricultural productivity evaluation,and urban sustainable development potential assessment and optimizes the territorial space in the Yangtze River Delta(YRD)region in 2035.The proposed sustainable development(SD)scenario can effectively reduce the destruction of landscape patterns of various land-use types while considering both ecological and economic benefits.The simulation results were further revised by evaluating the land-use suitability of the YRD region.According to the revised spatial pattern for the YRD in 2035,the farmland area accounts for 43.59%of the total YRD,which is 5.35%less than that in 2010.Forest,grassland,and water area account for 40.46%of the total YRD—an increase of 1.42%compared with the case in 2010.Construction land accounts for 14.72%of the total YRD—an increase of 2.77%compared with the case in 2010.The ES-FS-USD spatial optimization framework ensures that spatial optimization outcomes are aligned with the natural endowments of land resources,thereby promoting the sustainable use of land resources,improving the ability of spatial management,and providing valuable insights for decision makers.展开更多
Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Genev...Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Geneva,Switzerland,on November 4,where the topic of cooperation on trade-related carbon standards aroused heated discussions.The Leaders'Summit of the 30th Conference of the Parties(COP)to the UN Framework Convention on Climate Change(UNFCCC)was held in Belém,Brazil,on November 7.At the meeting,the Open Coalition on Compliance Carbon Markets was officially launched with the initial membership of 11 economies including Brazil,China,and the EU.As the world's first transnational alliance on compliant carbon markets,the coalition aims to coordinate carbon pricing mechanisms,emission trading systems and related policies in various countries,and realize the interconnection of global compliance carbon market networks.展开更多
The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition...The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.展开更多
With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm impro...With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm improvement.To reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy,while simultaneously enhancing user satisfaction on the demand side,this paper introduces an improvedmultiobjective Grey Wolf Optimizer based on Cauchy variation.The proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of becoming trapped in local optima.At the same time,adoptingmultiple energy storage methods to improve the consumption rate of renewable energy.Subsequently,under different energy balance orders,themulti-objective particle swarmalgorithm,multi-objective grey wolf optimizer,and Cauchy’s variant of the improvedmulti-objective grey wolf optimizer are used for example simulation,solving the Pareto solution set of the model and comparing.The analysis of the results reveals that,compared to the original optimizer,the improved optimizer decreases the daily cost by approximately 100 yuan,and reduces the energy abandonment rate to zero.Meanwhile,it enhances user satisfaction and ensures the stable operation of the micro-grid.展开更多
This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balanc...This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balance.By integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization process.The effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective algorithms.Furthermore,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy trains.The research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.展开更多
There is a growing recognition of the critical role of security governance in advancing democratic transition in the post-conflict environment.Despite such a recognition,the security sector reform concept has overshad...There is a growing recognition of the critical role of security governance in advancing democratic transition in the post-conflict environment.Despite such a recognition,the security sector reform concept has overshadowed the importance of the overarching strategic role of security governance in transition to democracy,particularly in Africa.This paper assesses the status and challenges facing security governance and how they thwarted the efforts to furthering the democratic transition in South Sudan.The paper shows a deterioration in security,safety and security governance outcomes since the independence of South Sudan in 2011 with such a trend unlikely to be abated in the near future without strategic interventions.Some of the challenges facing security governance in South Sudan include the legacies of some historical events including the“Big Tent Policy”,absence of strategic leadership,lack of overarching policy framework,impractical and tenuous security arrangements in the 2018 peace agreement,persistent postponement of the first elections,and dysfunctional justice sector.The paper provides some strategic and operational recommendations to improve security governance and advance democratic transition in South Sudan.These recommendations include formulation of an inclusive and people-centered national security policy,rigorous judicial reform,and early political agreement on new political infrastructure if conditions for holding the first national elections are not met in 2026.展开更多
River ethics,a significant advancement inspired by Chinese President XI Jinping's ecological civilization thought,embodies the philosophical essence of river governance and represents a legacy of innovation by gen...River ethics,a significant advancement inspired by Chinese President XI Jinping's ecological civilization thought,embodies the philosophical essence of river governance and represents a legacy of innovation by generations of water resources professionals.Rooted in river ecology,it offers a framework for advancing modern water governance systems and capabilities.This paper examines eight dimensions of river ethics to provide actionable recommendations:enhancing knowledge systems on water,rivers,and lakes;addressing critical challenges in water governance to strengthen the foundational role of water authorities in ensuring water security,resource management,ecological sustainability and environmental protection;optimizing water project planning to mitigate ecological impacts;ensuring high standards in the lifecycle management of water projects;refining water diversion strategies for precise scheduling;utilizing ecosystem complexity for river and lake restoration;implementing tiered management of water-related disasters;and driving reforms to modernize water governance systems and mechanisms.展开更多
In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimizatio...In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.展开更多
Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for ...Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for stakeholders and the entire community.Aims This study aims to establish a multidisciplinary consensus of principles for ethical governance of clinical BCI research for mental disorders and offer practical ethical guidance to stakeholders involved.Methods A systematic literature review,symposium and roundtable discussions,and a pre-Delphi(round 0)survey were conducted to form the questionnaire for the three-round modified Delphi study.Two rounds of surveys,followed by a third round of independent interviews of 25 experts from BCI-related research domains,were involved.We conducted quantitative analysis of responses and agreements among experts to reveal the consensus and differences regarding the ethical governance of mental BCI research from a multidisciplinary perspective.Results The Delphi panel emphasised important concerns of ethical review practices and ethical principles within the BCI context,identified qualified and highly influential institutions and personnel in conducting and advancing clinical BCI research,and recognised prioritised aspects in the risk-benefit evaluation.Experts expressed diverse opinions on specific ethical concerns,including concerns about invasive technology,its impact on humanity and potential social consequences.Agreement was reached that the practices of ethical governance of clinical BCI for mental disorders should focus on patient voluntariness,autonomy,long-term effects and related assessments of BCI interventions,as well as privacy protection,transparent reporting and ensuring that the research is conducted in qualified institutions with strong data security.Conclusions Ethical governance of clinical research on BCI for mental disorders should include interdisciplinary experts to balance various needs and incorporate the expertise of different stakeholders to avoid serious ethical issues.It requires scientifically grounded approaches,continuous monitoring and interdisciplinary collaboration to ensure evidence-based policies,comprehensive risk assessments and transparency,thereby promoting responsible innovations and protecting patient rights and well-being.展开更多
Values of individuals and organizations involved in decision-making processes form the basis for prioritizing outcomes in water governance.The novelty of this study lies in applying values to a specific decision-makin...Values of individuals and organizations involved in decision-making processes form the basis for prioritizing outcomes in water governance.The novelty of this study lies in applying values to a specific decision-making context.It aims to assess the prioritized water governance outcomes and the underlying value systems shaping the actions of the primary water utility responsible for water governance in Delhi,the Delhi Jal Board(DJB).The paper will critically examine the policies and acts of the DJB that drive water governance in Delhi at present,utilizing a values-based framework in conjunction with secondary literature and expert interviews,to draw a picture of the values reflected.The study does not substantiate the notion of economic values dominating the water-related deci-sions;rather,recent policy guidelines indicate prioritization of equitable and fair distribution of water.Findings of this paper show that making the values explicit is largely disregarded in formulating water acts and policies,and values are never elucidated in the public domain,doing which can encourage water policies and practices that are socially,economically,and ecologically viable in the long run.It is expected that this paper will generate a discussion on water values being an integral part of water governance discourses.展开更多
THIS year marks the 80th anniversary of the victory in the Chinese People’s War of Resistance against Japanese Aggression and the World Anti-Fascist War.At this historical juncture,Chinese President Xi Jinping put fo...THIS year marks the 80th anniversary of the victory in the Chinese People’s War of Resistance against Japanese Aggression and the World Anti-Fascist War.At this historical juncture,Chinese President Xi Jinping put forward the Global Governance Initiative(GGI)at the“Shanghai Cooperation Organization Plus”meeting in September.Focusing on the question of our times,essentially“what kind of global governance system should be built and how can global governance be reformed and improved,”the GGI embodies China’s solution to addressing the deficit in global governance.展开更多
Multi-instance image generation remains a challenging task in the field of computer vision.While existing diffusionmodels demonstrate impressive fidelity in image generation,they often struggle with precisely controll...Multi-instance image generation remains a challenging task in the field of computer vision.While existing diffusionmodels demonstrate impressive fidelity in image generation,they often struggle with precisely controlling each object’s shape,pose,and size.Methods like layout-to-image and mask-to-image provide spatial guidance but frequently suffer from object shape distortion,overlaps,and poor consistency,particularly in complex scenes with multiple objects.To address these issues,we introduce PolyDiffusion,a contour-based diffusion framework that encodes each object’s contour as a boundary-coordinate sequence,decoupling object shapes and positions.This approach allows for better control over object geometry and spatial positioning,which is critical for achieving high-quality multiinstance generation.We formulate the training process as a multi-objective optimization problem,balancing three key objectives:a denoising diffusion loss to maintain overall image fidelity,a cross-attention contour alignment loss to ensure precise shape adherence,and a reward-guided denoising objective that minimizes the Fréchet distance to real images.In addition,the Object Space-Aware Attention module fuses contour tokens with visual features,while a prior-guided fusion mechanism utilizes inter-object spatial relationships and class semantics to enhance consistency across multiple objects.Experimental results on benchmark datasets such as COCO-Stuff and VOC-2012 demonstrate that PolyDiffusion significantly outperforms existing layout-to-image and mask-to-image methods,achieving notable improvements in both image quality and instance-level segmentation accuracy.The implementation of Poly Diffusion is available at https://github.com/YYYYYJS/PolyDiffusion(accessed on 06 August 2025).展开更多
On September 1,2025,President Xi Jinping put forward the Global Governance Initiative at the“Shanghai Cooperation Organization Plus”Meeting.He outlined the principles,methods,and pathways essential for reforming and...On September 1,2025,President Xi Jinping put forward the Global Governance Initiative at the“Shanghai Cooperation Organization Plus”Meeting.He outlined the principles,methods,and pathways essential for reforming and improving global governance,calling on all parties to work together to strengthen it.展开更多
In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave pow...In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.展开更多
The rapid development of information technology in the digital era has led the development and reform in the field of education.Both the transformation and high-quality development of open universities have put forwar...The rapid development of information technology in the digital era has led the development and reform in the field of education.Both the transformation and high-quality development of open universities have put forward higher requirements for open education governance.Focusing on the important field of open education governance,this study,from the perspective of university governance,deeply explores the practical dilemmas faced by open education governance,such as unclear development positioning,difficulties in transformation and development,inadequate learning support services,insufficient depth of teaching reform,and weak professional development of teachers.In the lifelong learning education ecology of universal education,open education governance should focus on“useful and easy learning”,focus on industry-education integration,take serving society as its purpose,and promote the transformation and development of open education.Under the concept of collaboration and co-governance,a multi-subject collaborative governance mechanism should be built,and governance thinking should be actively implemented in open education and teaching affairs to accelerate the modernization of open education governance.This aims to realize the sustainable development of open education governance and provide strong theoretical support and practical guidance for building a more fair,high-quality,and flexible open education governance system.展开更多
At the“Shanghai Cooperation Organization Plus”Meeting in Tianjin on September 1,Chinese President Xi Jinping announced the Global Governance Initiative(GGI)-the fourth landmark global initiative proposed in a row si...At the“Shanghai Cooperation Organization Plus”Meeting in Tianjin on September 1,Chinese President Xi Jinping announced the Global Governance Initiative(GGI)-the fourth landmark global initiative proposed in a row since 2021.The initiation of the GGI can be seen as both China’s policy response to the current international landscape and to the objective deficiencies in the existing global governance system,as well as a logical and further step in the development of China’s diplomatic theories and practices in global governance.展开更多
文摘Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.
文摘Governance debates gained strong momentum in Africa in early December 2025 as the China-Kenya Readers Forum on Xi Jinping:The Governance of China convened in Nairobi on 1 December 2025,followed by a promotional event for the English edition of the book’s fifth volume on 3 December 2025 in Johannesburg,South Africa.
基金supported by Key Science and Technology Program of Henan Province,China(Grant Nos.242102210147,242102210027)Fujian Province Young and Middle aged Teacher Education Research Project(Science and Technology Category)(No.JZ240101)(Corresponding author:Dong Yuan).
文摘Vehicle Edge Computing(VEC)and Cloud Computing(CC)significantly enhance the processing efficiency of delay-sensitive and computation-intensive applications by offloading compute-intensive tasks from resource-constrained onboard devices to nearby Roadside Unit(RSU),thereby achieving lower delay and energy consumption.However,due to the limited storage capacity and energy budget of RSUs,it is challenging to meet the demands of the highly dynamic Internet of Vehicles(IoV)environment.Therefore,determining reasonable service caching and computation offloading strategies is crucial.To address this,this paper proposes a joint service caching scheme for cloud-edge collaborative IoV computation offloading.By modeling the dynamic optimization problem using Markov Decision Processes(MDP),the scheme jointly optimizes task delay,energy consumption,load balancing,and privacy entropy to achieve better quality of service.Additionally,a dynamic adaptive multi-objective deep reinforcement learning algorithm is proposed.Each Double Deep Q-Network(DDQN)agent obtains rewards for different objectives based on distinct reward functions and dynamically updates the objective weights by learning the value changes between objectives using Radial Basis Function Networks(RBFN),thereby efficiently approximating the Pareto-optimal decisions for multiple objectives.Extensive experiments demonstrate that the proposed algorithm can better coordinate the three-tier computing resources of cloud,edge,and vehicles.Compared to existing algorithms,the proposed method reduces task delay and energy consumption by 10.64%and 5.1%,respectively.
基金National Natural Science Foundation of China,No.42301470,No.52270185,No.42171389Capacity Building Program of Local Colleges and Universities in Shanghai,No.21010503300。
文摘Rapid urbanization in China has led to spatial antagonism between urban development and farmland protection and ecological security maintenance.Multi-objective spatial collaborative optimization is a powerful method for achieving sustainable regional development.Previous studies on multi-objective spatial optimization do not involve spatial corrections to simulation results based on the natural endowment of space resources.This study proposes an Ecological Security-Food Security-Urban Sustainable Development(ES-FS-USD)spatial optimization framework.This framework combines the non-dominated sorting genetic algorithm II(NSGA-II)and patch-generating land use simulation(PLUS)model with an ecological protection importance evaluation,comprehensive agricultural productivity evaluation,and urban sustainable development potential assessment and optimizes the territorial space in the Yangtze River Delta(YRD)region in 2035.The proposed sustainable development(SD)scenario can effectively reduce the destruction of landscape patterns of various land-use types while considering both ecological and economic benefits.The simulation results were further revised by evaluating the land-use suitability of the YRD region.According to the revised spatial pattern for the YRD in 2035,the farmland area accounts for 43.59%of the total YRD,which is 5.35%less than that in 2010.Forest,grassland,and water area account for 40.46%of the total YRD—an increase of 1.42%compared with the case in 2010.Construction land accounts for 14.72%of the total YRD—an increase of 2.77%compared with the case in 2010.The ES-FS-USD spatial optimization framework ensures that spatial optimization outcomes are aligned with the natural endowments of land resources,thereby promoting the sustainable use of land resources,improving the ability of spatial management,and providing valuable insights for decision makers.
文摘Two international conferences in November 2025 jointly outlined a profound transformation of climate governance.The Committee on Trade and Environment(CTE)of the World Trade Organization(WTO)held a conference in Geneva,Switzerland,on November 4,where the topic of cooperation on trade-related carbon standards aroused heated discussions.The Leaders'Summit of the 30th Conference of the Parties(COP)to the UN Framework Convention on Climate Change(UNFCCC)was held in Belém,Brazil,on November 7.At the meeting,the Open Coalition on Compliance Carbon Markets was officially launched with the initial membership of 11 economies including Brazil,China,and the EU.As the world's first transnational alliance on compliant carbon markets,the coalition aims to coordinate carbon pricing mechanisms,emission trading systems and related policies in various countries,and realize the interconnection of global compliance carbon market networks.
基金supported by National Natural Science Foundations of China(nos.12271326,62102304,61806120,61502290,61672334,61673251)China Postdoctoral Science Foundation(no.2015M582606)+2 种基金Industrial Research Project of Science and Technology in Shaanxi Province(nos.2015GY016,2017JQ6063)Fundamental Research Fund for the Central Universities(no.GK202003071)Natural Science Basic Research Plan in Shaanxi Province of China(no.2022JM-354).
文摘The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.
基金supported by the Open Fund of Guangxi Key Laboratory of Building New Energy and Energy Conservation(Project Number:Guike Energy 17-J-21-3).
文摘With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm improvement.To reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy,while simultaneously enhancing user satisfaction on the demand side,this paper introduces an improvedmultiobjective Grey Wolf Optimizer based on Cauchy variation.The proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of becoming trapped in local optima.At the same time,adoptingmultiple energy storage methods to improve the consumption rate of renewable energy.Subsequently,under different energy balance orders,themulti-objective particle swarmalgorithm,multi-objective grey wolf optimizer,and Cauchy’s variant of the improvedmulti-objective grey wolf optimizer are used for example simulation,solving the Pareto solution set of the model and comparing.The analysis of the results reveals that,compared to the original optimizer,the improved optimizer decreases the daily cost by approximately 100 yuan,and reduces the energy abandonment rate to zero.Meanwhile,it enhances user satisfaction and ensures the stable operation of the micro-grid.
基金supported by the National Natural Science Foundation of China(Project No.5217232152102391)+2 种基金Sichuan Province Science and Technology Innovation Talent Project(2024JDRC0020)China Shenhua Energy Company Limited Technology Project(GJNY-22-7/2300-K1220053)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-132).
文摘This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balance.By integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization process.The effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective algorithms.Furthermore,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy trains.The research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.
文摘There is a growing recognition of the critical role of security governance in advancing democratic transition in the post-conflict environment.Despite such a recognition,the security sector reform concept has overshadowed the importance of the overarching strategic role of security governance in transition to democracy,particularly in Africa.This paper assesses the status and challenges facing security governance and how they thwarted the efforts to furthering the democratic transition in South Sudan.The paper shows a deterioration in security,safety and security governance outcomes since the independence of South Sudan in 2011 with such a trend unlikely to be abated in the near future without strategic interventions.Some of the challenges facing security governance in South Sudan include the legacies of some historical events including the“Big Tent Policy”,absence of strategic leadership,lack of overarching policy framework,impractical and tenuous security arrangements in the 2018 peace agreement,persistent postponement of the first elections,and dysfunctional justice sector.The paper provides some strategic and operational recommendations to improve security governance and advance democratic transition in South Sudan.These recommendations include formulation of an inclusive and people-centered national security policy,rigorous judicial reform,and early political agreement on new political infrastructure if conditions for holding the first national elections are not met in 2026.
基金Three Gorges Follow-up Work Fund,Grant/Award Number:WE0161A042024National Key Research Program of China,Grant/Award Number:2024YFC3210900。
文摘River ethics,a significant advancement inspired by Chinese President XI Jinping's ecological civilization thought,embodies the philosophical essence of river governance and represents a legacy of innovation by generations of water resources professionals.Rooted in river ecology,it offers a framework for advancing modern water governance systems and capabilities.This paper examines eight dimensions of river ethics to provide actionable recommendations:enhancing knowledge systems on water,rivers,and lakes;addressing critical challenges in water governance to strengthen the foundational role of water authorities in ensuring water security,resource management,ecological sustainability and environmental protection;optimizing water project planning to mitigate ecological impacts;ensuring high standards in the lifecycle management of water projects;refining water diversion strategies for precise scheduling;utilizing ecosystem complexity for river and lake restoration;implementing tiered management of water-related disasters;and driving reforms to modernize water governance systems and mechanisms.
基金sponsored by R&D Program of Beijing Municipal Education Commission(KM202410009013).
文摘In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.
基金funded by the Shanghai Philosophy and Social Science Planning Project (2021BZX008)the National Social Science Foundation of China (23BZX110)the National Office for Philosophy and Social Science (20&ZD045).
文摘Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for stakeholders and the entire community.Aims This study aims to establish a multidisciplinary consensus of principles for ethical governance of clinical BCI research for mental disorders and offer practical ethical guidance to stakeholders involved.Methods A systematic literature review,symposium and roundtable discussions,and a pre-Delphi(round 0)survey were conducted to form the questionnaire for the three-round modified Delphi study.Two rounds of surveys,followed by a third round of independent interviews of 25 experts from BCI-related research domains,were involved.We conducted quantitative analysis of responses and agreements among experts to reveal the consensus and differences regarding the ethical governance of mental BCI research from a multidisciplinary perspective.Results The Delphi panel emphasised important concerns of ethical review practices and ethical principles within the BCI context,identified qualified and highly influential institutions and personnel in conducting and advancing clinical BCI research,and recognised prioritised aspects in the risk-benefit evaluation.Experts expressed diverse opinions on specific ethical concerns,including concerns about invasive technology,its impact on humanity and potential social consequences.Agreement was reached that the practices of ethical governance of clinical BCI for mental disorders should focus on patient voluntariness,autonomy,long-term effects and related assessments of BCI interventions,as well as privacy protection,transparent reporting and ensuring that the research is conducted in qualified institutions with strong data security.Conclusions Ethical governance of clinical research on BCI for mental disorders should include interdisciplinary experts to balance various needs and incorporate the expertise of different stakeholders to avoid serious ethical issues.It requires scientifically grounded approaches,continuous monitoring and interdisciplinary collaboration to ensure evidence-based policies,comprehensive risk assessments and transparency,thereby promoting responsible innovations and protecting patient rights and well-being.
基金Water Security and Sustainable Development Hub funded by the UK Research and Innovation's Global Challenges Research Fund(GCRF),Grant/Award Number:ES/S008179/1。
文摘Values of individuals and organizations involved in decision-making processes form the basis for prioritizing outcomes in water governance.The novelty of this study lies in applying values to a specific decision-making context.It aims to assess the prioritized water governance outcomes and the underlying value systems shaping the actions of the primary water utility responsible for water governance in Delhi,the Delhi Jal Board(DJB).The paper will critically examine the policies and acts of the DJB that drive water governance in Delhi at present,utilizing a values-based framework in conjunction with secondary literature and expert interviews,to draw a picture of the values reflected.The study does not substantiate the notion of economic values dominating the water-related deci-sions;rather,recent policy guidelines indicate prioritization of equitable and fair distribution of water.Findings of this paper show that making the values explicit is largely disregarded in formulating water acts and policies,and values are never elucidated in the public domain,doing which can encourage water policies and practices that are socially,economically,and ecologically viable in the long run.It is expected that this paper will generate a discussion on water values being an integral part of water governance discourses.
文摘THIS year marks the 80th anniversary of the victory in the Chinese People’s War of Resistance against Japanese Aggression and the World Anti-Fascist War.At this historical juncture,Chinese President Xi Jinping put forward the Global Governance Initiative(GGI)at the“Shanghai Cooperation Organization Plus”meeting in September.Focusing on the question of our times,essentially“what kind of global governance system should be built and how can global governance be reformed and improved,”the GGI embodies China’s solution to addressing the deficit in global governance.
基金supported in part by the Scientific Research Fund of National Natural Science Foundation of China(Grant No.62372168)the Hunan Provincial Natural Science Foundation of China(Grant No.2023JJ30266)+2 种基金the Research Project on teaching reform in Hunan province(No.HNJG-2022-0791)the Hunan University of Science and Technology(No.2022-44-8)the National Social Science Funds of China(19BZX044).
文摘Multi-instance image generation remains a challenging task in the field of computer vision.While existing diffusionmodels demonstrate impressive fidelity in image generation,they often struggle with precisely controlling each object’s shape,pose,and size.Methods like layout-to-image and mask-to-image provide spatial guidance but frequently suffer from object shape distortion,overlaps,and poor consistency,particularly in complex scenes with multiple objects.To address these issues,we introduce PolyDiffusion,a contour-based diffusion framework that encodes each object’s contour as a boundary-coordinate sequence,decoupling object shapes and positions.This approach allows for better control over object geometry and spatial positioning,which is critical for achieving high-quality multiinstance generation.We formulate the training process as a multi-objective optimization problem,balancing three key objectives:a denoising diffusion loss to maintain overall image fidelity,a cross-attention contour alignment loss to ensure precise shape adherence,and a reward-guided denoising objective that minimizes the Fréchet distance to real images.In addition,the Object Space-Aware Attention module fuses contour tokens with visual features,while a prior-guided fusion mechanism utilizes inter-object spatial relationships and class semantics to enhance consistency across multiple objects.Experimental results on benchmark datasets such as COCO-Stuff and VOC-2012 demonstrate that PolyDiffusion significantly outperforms existing layout-to-image and mask-to-image methods,achieving notable improvements in both image quality and instance-level segmentation accuracy.The implementation of Poly Diffusion is available at https://github.com/YYYYYJS/PolyDiffusion(accessed on 06 August 2025).
文摘On September 1,2025,President Xi Jinping put forward the Global Governance Initiative at the“Shanghai Cooperation Organization Plus”Meeting.He outlined the principles,methods,and pathways essential for reforming and improving global governance,calling on all parties to work together to strengthen it.
文摘In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.
基金2022 Education and Teaching Research and Reform Project of Guangdong Open University System,“Practical Dilemmas and Practical Paths of Educational Governance in Open Education in the Post-Pandemic Era”(Project No.:2022TXJG35)。
文摘The rapid development of information technology in the digital era has led the development and reform in the field of education.Both the transformation and high-quality development of open universities have put forward higher requirements for open education governance.Focusing on the important field of open education governance,this study,from the perspective of university governance,deeply explores the practical dilemmas faced by open education governance,such as unclear development positioning,difficulties in transformation and development,inadequate learning support services,insufficient depth of teaching reform,and weak professional development of teachers.In the lifelong learning education ecology of universal education,open education governance should focus on“useful and easy learning”,focus on industry-education integration,take serving society as its purpose,and promote the transformation and development of open education.Under the concept of collaboration and co-governance,a multi-subject collaborative governance mechanism should be built,and governance thinking should be actively implemented in open education and teaching affairs to accelerate the modernization of open education governance.This aims to realize the sustainable development of open education governance and provide strong theoretical support and practical guidance for building a more fair,high-quality,and flexible open education governance system.
文摘At the“Shanghai Cooperation Organization Plus”Meeting in Tianjin on September 1,Chinese President Xi Jinping announced the Global Governance Initiative(GGI)-the fourth landmark global initiative proposed in a row since 2021.The initiation of the GGI can be seen as both China’s policy response to the current international landscape and to the objective deficiencies in the existing global governance system,as well as a logical and further step in the development of China’s diplomatic theories and practices in global governance.
