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Key Mechanisms on Resource Optimization Allocation in Minority Game Based on Reinforcement Learning 认领 引用
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作者 Changyan Di Tianyi Wang +1 位作者 Qingguo Zhou Jinqiang Wang 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2025年第2期721-731,共11页
The emergence of coordinated and consistent macro behavior among self-interested individuals competing for limited resources represents a central inquiry in comprehending market mechanisms and collective behavior.Trad... The emergence of coordinated and consistent macro behavior among self-interested individuals competing for limited resources represents a central inquiry in comprehending market mechanisms and collective behavior.Traditional economics tackles this challenge through a mathematical and theoretical lens,assuming individuals are entirely rational and markets tend to stabilize through the price mechanism.Our paper addresses this issue from an econophysics standpoint,employing reinforcement learning to construct a multi-agent system modeled on minority games.Our study has undertaken a comparative analysis from both collective and individual perspectives,affirming the pivotal roles of reward feedback and individual memory in addressing the aforementioned challenge.Reward feedback serves as the guiding force for the evolution of collective behavior,propelling it towards an overall increase in rewards.Individuals,drawing insights from their own rewards through accumulated learning,gain information about the collective state and adjust their behavior accordingly.Furthermore,we apply information theory to present a formalized equation for the evolution of collective behavior.Our research supplements existing conclusions regarding the mechanisms of a free market and,at a micro level,unveils the dynamic evolution of individual behavior in synchronization with the collective. 展开更多
关键词 minority game optimization of resource allocation multi-agent system reinforcement learning
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ANNDRA-IoT:A Deep Learning Approach for Optimal Resource Allocation in Internet of Things Environments 认领 引用
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作者 Abdullah M.Alqahtani Kamran Ahmad Awan +1 位作者 Abdulaziz Almaleh Osama Aletri 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第3期3155-3179,共25页
Efficient resource management within Internet of Things(IoT)environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities.This study introduces a neural network-ba... Efficient resource management within Internet of Things(IoT)environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities.This study introduces a neural network-based model that uses Long-Short-Term Memory(LSTM)to optimize resource allocation under dynam-ically changing conditions.Designed to monitor the workload on individual IoT nodes,the model incorporates long-term data dependencies,enabling adaptive resource distribution in real time.The training process utilizes Min-Max normalization and grid search for hyperparameter tuning,ensuring high resource utilization and consistent performance.The simulation results demonstrate the effectiveness of the proposed method,outperforming the state-of-the-art approaches,including Dynamic and Efficient Enhanced Load-Balancing(DEELB),Optimized Scheduling and Collaborative Active Resource-management(OSCAR),Convolutional Neural Network with Monarch Butterfly Optimization(CNN-MBO),and Autonomic Workload Prediction and Resource Allocation for Fog(AWPR-FOG).For example,in scenarios with low system utilization,the model achieved a resource utilization efficiency of 95%while maintaining a latency of just 15 ms,significantly exceeding the performance of comparative methods. 展开更多
关键词 Internet of things resource optimization deep learning optimal resource allocation neural network efficiency
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Cross-layer resource allocation based on equivalent bandwidth in OFDMA systems 认领 引用
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作者 Su Pan Cheng Li +1 位作者 Sheng Zhang Danwei Chen 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2016年第4期754-762,共9页
A quality of service（QoS） guaranteed cross-layer resource allocation algorithm with physical layer, medium access control（MAC） layer and call admission control（CAC） considered simultaneously is proposed for the ... A quality of service（QoS） guaranteed cross-layer resource allocation algorithm with physical layer, medium access control（MAC） layer and call admission control（CAC） considered simultaneously is proposed for the full IP orthogonal frequency division multiple access（OFDMA） communication system, which can ensure the quality of multimedia services in full IP networks.The algorithm converts the physical layer resources such as subcarriers, transmission power, and the QoS metrics into equivalent bandwidth which can be distributed by the base station in all three layers. By this means, the QoS requirements in terms of bit error rate（BER）, transmission delay and dropping probability can be guaranteed by the cross-layer optimal equivalent bandwidth allocation. The numerical results show that the proposed algorithm has higher spectrum efficiency compared to the existing systems. 展开更多
关键词 resource allocation equivalent bandwidth crosslayer optimization orthogonal frequency division multiple access（OFDMA）
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Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties 认领 引用 被引量：11
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作者 Sajad Najafi Ravadanegh Mohammad Reza Jannati Oskuee Masoumeh Karimi 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第8期1837-1849,共13页
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a... This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration. 展开更多
关键词 optimal reconfiguration renewable energy resources sitting and sizing capacitor allocation electric distribution system uncertainty modeling scenario based-stochastic programming multi-objective genetic algorithm
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The Cloud Manufacturing Resource Scheduling Optimization Method Based on Game Theory 认领 引用 被引量：2
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作者 Xiaoxuan Yang Zhou Fang 《Journal on Artificial Intelligence》 2022年第4期229-243,共15页
In order to optimize resource integration and optimal scheduling problems in the cloud manufacturing environment,this paper proposes to use load balancing,service cost and service quality as optimization goals for res... In order to optimize resource integration and optimal scheduling problems in the cloud manufacturing environment,this paper proposes to use load balancing,service cost and service quality as optimization goals for resource scheduling,however,resource providers have resource utilization requirements for cloud manufacturing platforms.In the process of resource optimization scheduling,the interests of all parties have conflicts of interest,which makes it impossible to obtain better optimization results for resource scheduling.Therefore,amultithreaded auto-negotiation method based on the Stackelberg game is proposed to resolve conflicts of interest in the process of resource scheduling.The cloud manufacturing platform first calculates the expected value reduction plan for each round of global optimization,using the negotiation algorithm based on the Stackelberg game,the cloud manufacturing platformnegotiates andmediateswith the participants’agents,to maximize self-interest by constantly changing one’s own plan,iteratively find multiple sets of locally optimized negotiation plans and return to the cloud manufacturing platform.Through multiple rounds of negotiation and calculation,we finally get a target expected value reduction plan that takes into account the benefits of the resource provider and the overall benefits of the completion of the manufacturing task.Finally,through experimental simulation and comparative analysis,the validity and rationality of the model are verified. 展开更多
关键词 Cloud manufacturing resource scheduling optimal allocation of resources conflict of interest stackelberg game
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Cascading Failure Dynamics and Edge-Intelligent Defense in Space-Air-Ground Integrated Networks for Internet of Things 认领 引用
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作者 Peiying Zhang Yihong Yu +3 位作者 Lizhuang Tan Shuqing He Jian Wang Ameer El-Sayed 《Computers, Materials & Continua》 SCIE EI 2026年第8期865-880,共16页
As a core information infrastructure in the 6G era,the Space-Air-Ground Integrated Network(SAGIN)integrates space-based,air-based,and ground-based network resources to achieve seamless communication across all domains... As a core information infrastructure in the 6G era,the Space-Air-Ground Integrated Network(SAGIN)integrates space-based,air-based,and ground-based network resources to achieve seamless communication across all domains.However,its characteristics such as heterogeneous node coupling and dynamic topology changes make it prone to cascading failures,severely threatening critical business continuity in Internet of Things(IoT)applications spanning smart cities,healthcare,transportation,and industrial automation.This paper conducts systematic research addressing challenges including modeling difficulties in SAGIN cascading failure propagation,insufficient coordination of defense strategies,and poor resource adaptability.First,a multi-factor coupled dynamic model of cascading failure propagation is established to quantify the synergistic effects of node heterogeneity,link dynamics,and load redistribution.Second,a closed-loop collaborative defense system integrating“early warning-isolation-self-healing”is designed.The system incorporates a lightweight greedy-based self-healing algorithm and uses multi-criteria decision-making(Analytic Hierarchy Process)for resource optimization.These approaches ensure real-time performance and energy efficiency on resource-constrained edge nodes.Third,a joint simulation platform combining NS-3 and MATLAB is built to validate the model and strategies across diverse IoT application scenarios.Experimental results show that the proposed propagation model maintains prediction error within 10%,the defense strategies increase failure recovery rates to 85%–90%,reduce communication interruption duration by over 60%,and lower resource overhead by 20%–25%,providing theoretical support and technical guarantees for stable SAGIN operation in security and resiliency-critical environments. 展开更多
关键词 Space-Air-Ground Integrated Network cascading failure defense strategy edge intelligence Internet of Things resource allocation and optimization real-time and energy efficiency security and resiliency network reliability
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Analysis of Research Trends and Output Effectiveness in the Medical Field Based on the National Natural Science Foundation of China 认领 引用
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作者 Jin Hu Hui Huang +1 位作者 Xinjie Bao Hua Bai 《Health Care Science》 CSCD 2026年第3期231-239,共9页
Background:This study aims to analyze the trends in research focus and output effectiveness in the medical field supported by the National Natural Science Foundation of China(NSFC)over the past 15 years,providing a ba... Background:This study aims to analyze the trends in research focus and output effectiveness in the medical field supported by the National Natural Science Foundation of China(NSFC)over the past 15 years,providing a basis for the optimal allocation of scientific research resources.Methods:Based on the NSFC Big Data Knowledge Management Service Database,a retrospective approach was adopted to retrieve data on completed projects and output achievements from 2009 to 2023.Indicators,including compound annual growth rate(CAGR)and output-to-project ratio,were used to evaluate the growth of project completion and research productivity across 35 secondary medical categories.Results:Over the 15-year period,a total of 439,637 NSFC projects were completed,with the Division of Medical Science ranking first in both scale(23%)and growth rate(CAGR 11%).The 35 secondary categories(H01–H35)under the Division of Medical Science showed differentiated development characteristics,namely“a few growing rapidly,most growing steadily,and a small number lagging behind”:six directions including biomedical engineering had a CAGR of≥15%;oncology and traditional chinese medicine contributed large output volumes but showed low output-to-project ratios,whereas neuroscience,imaging medicine,and biomedical engineering achieved high efficiency.Key Programs achieved the highest output-to-project ratios,followed by the General Program and then the Young Scientists Fund.Conclusions:The completion and output of NSFC-funded medical projects reflect national strategic orientations and disciplinary development laws,but imbalance remains between project scale and output efficiency across subfields.It is suggested to establish a dynamic evaluation mechanism,promote the“basic research-application-transformation”collaborative model,support small-scale yet high-efficiency fields,and conduct long-term tracking of output achievements.These measures are expected to optimize the allocation of NSFC funding resources. 展开更多
关键词 compound annual growth rate medical field National Natural Science Foundation of China optimal allocation of resources output-to-project ratio
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Analysis of the benefits of applying intelligent construction technologies in building construction 认领 引用
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作者 OUYANG Binsheng 《外文科技期刊数据库（文摘版）工程技术》 2026年第5期133-137,共5页
With the accelerating urbanization process and continuous advancements in the construction industry, traditional construction methods have become inadequate for meeting high-quality and low-energy consumption requirem... With the accelerating urbanization process and continuous advancements in the construction industry, traditional construction methods have become inadequate for meeting high-quality and low-energy consumption requirements. Intelligent construction technology represents a groundbreaking approach that leverages digitalization, information systems, and automation to deliver comprehensive innovations in construction practices. This article first examines key challenges in construction, then elaborates on the development context and core concepts of intelligent construction technology, while exploring its specific impacts on streamlining workflows, optimizing resource allocation, and ensuring project quality. The study conducts an in-depth analysis of how this technology reduces project timelines, lowers costs, and enhances safety management, demonstrating its capability to enable real-time communication and flexible adjustments of engineering data, thereby significantly transforming construction management methodologies. It further highlights the technology's remarkable contributions to improving green construction standards and reducing carbon emissions at construction sites. Research findings indicate that intelligent construction not only substantially boosts production efficiency and overall project quality but also establishes a solid technological foundation for sustainable development. The paper comprehensively discusses three key dimensions—team collaboration, technological integration, and information processing—clearly illustrating its pivotal role in accelerating construction speeds, optimizing project structures, and ensuring safety protocols. In conclusion, this study provides a crucial theoretical foundation and practical guidance for the improvement and innovative development of construction methods, demonstrating significant potential for widespread application and offering a clear direction for the future advancement of the entire industry. 展开更多
关键词 Intelligent construction technology Construction engineering Construction process reengineering Resource allocation optimization Green construction
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Distributed Chunk-Based Optimization for MultiCarrier Ultra-Dense Networks 认领 引用 被引量：2
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作者 GUO Shaozhen XING Chengwen +2 位作者 FEI Zesong ZHOU Gui YAN Xinge 《China Communications》 SCIE CSCD 2016年第1期80-90,共11页
In this paper,a distributed chunkbased optimization algorithm is proposed for the resource allocation in broadband ultra-dense small cell networks.Based on the proposed algorithm,the power and subcarrier allocation pr... In this paper,a distributed chunkbased optimization algorithm is proposed for the resource allocation in broadband ultra-dense small cell networks.Based on the proposed algorithm,the power and subcarrier allocation problems are jointly optimized.In order to make the resource allocation suitable for large scale networks,the optimization problem is decomposed first based on an effective decomposition algorithm named optimal condition decomposition(OCD) algorithm.Furthermore,aiming at reducing implementation complexity,the subcarriers are divided into chunks and are allocated chunk by chunk.The simulation results show that the proposed algorithm achieves more superior performance than uniform power allocation scheme and Lagrange relaxation method,and then the proposed algorithm can strike a balance between the complexity and performance of the multi-carrier Ultra-Dense Networks. 展开更多
关键词 ultra-dense small cell networks optimization chunk power allocation subcarrier allocation distributed resource allocation
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Non-Convex Optimization of Resource Allocation in Fog Computing Using Successive Approximation 认领 引用 被引量：1
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作者 LI Shiyong LIU Huan +1 位作者 LI Wenzhe SUN Wei 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2024年第2期805-840,共36页
Fog computing can deliver low delay and advanced IT services to end users with substantially reduced energy consumption.Nevertheless,with soaring demands for resource service and the limited capability of fog nodes,ho... Fog computing can deliver low delay and advanced IT services to end users with substantially reduced energy consumption.Nevertheless,with soaring demands for resource service and the limited capability of fog nodes,how to allocate and manage fog computing resources properly and stably has become the bottleneck.Therefore,the paper investigates the utility optimization-based resource allocation problem between fog nodes and end users in fog computing.The authors first introduce four types of utility functions due to the diverse tasks executed by end users and build the resource allocation model aiming at utility maximization.Then,for only the elastic tasks,the convex optimization method is applied to obtain the optimal results;for the elastic and inelastic tasks,with the assistance of Jensen’s inequality,the primal non-convex model is approximated to a sequence of equivalent convex optimization problems using successive approximation method.Moreover,a two-layer algorithm is proposed that globally converges to an optimal solution of the original problem.Finally,numerical simulation results demonstrate its superior performance and effectiveness.Comparing with other works,the authors emphasize the analysis for non-convex optimization problems and the diversity of tasks in fog computing resource allocation. 展开更多
关键词 Fog computing non-convex optimization optimal resource allocation successive approximation method utility function
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A New Integrated Epidemic-Logistics Model for Optimal Resources Allocation with a Dynamic Varying of Inventory and an Implementing of Social Interventions During a Viral Epidemic 认领 引用
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作者 BAO Sulifu HU Zhi-Hua 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2025年第6期2577-2608,共32页
This research addresses existing shortcomings in epidemic-logistics studies by emphasizing the integration of multiple models to determine optimal strategies for medical resource allocation during public health emerge... This research addresses existing shortcomings in epidemic-logistics studies by emphasizing the integration of multiple models to determine optimal strategies for medical resource allocation during public health emergencies,such as the COVID-19 outbreak.The authors develop a multi-model integrated epidemic-logistics model that seamlessly merges three specific sub-models:Optimal allocation,epidemic dynamics,and production-inventory.This model dynamically tracks the real-time varying in resource inventory levels at supply nodes and the storage capacities at transit hubs within a logistics network.Unique to the proposed research is the embedding of both the production-inventory mechanism and the impact of a social intervention(Traditional Chinese medicine as the background)within a logistics framework of resource allocation.Moreover,the authors also introduce an adaptive demand function that possesses learning ability and a probabilistic understanding,crucial for gauging real-time resource demands in affected regions.The proposed innovation extends to designing a recursive and linearizable structure,transforming the intricate multi-model system into solvable sub-models,while also offering a standardized method for creating demand functions.The numerical simulations and sensitivity analysis demonstrate the efficiency and robustness of the proposed model.The proposed framework not only enhances theoretical understandings of epidemic resource management but also provides policymakers with actionable strategies for future pandemics. 展开更多
关键词 Demand function dynamics integrated epidemic-logistics optimal resource allocation production-inventory
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Optimal resource allocation with spatiotemporal transmission discovery for efective disease control 认领 引用 被引量：10
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作者 Jinfu Ren Mutong Liu +1 位作者 Yang Liu Jiming Liu 《Infectious Diseases of Poverty》 SCIE CAS 2022年第2期102-103,共2页
Background:The new waves of COVID-19 outbreaks caused by the SARS-CoV-2 Omicron variant are developing rapidly and getting out of control around the world,especially in highly populated regions.The healthcare capacity... Background:The new waves of COVID-19 outbreaks caused by the SARS-CoV-2 Omicron variant are developing rapidly and getting out of control around the world,especially in highly populated regions.The healthcare capacity(especially the testing resources,vaccination coverage,and hospital capacity)is becoming extremely insufcient as the demand will far exceed the supply.To address this time-critical issue,we need to answer a key question:How can we efectively infer the daily transmission risks in diferent districts using machine learning methods and thus lay out the corresponding resource prioritization strategies,so as to alleviate the impact of the Omicron outbreaks?Methods:We propose a computational method for future risk mapping and optimal resource allocation based on the quantitative characterization of spatiotemporal transmission patterns of the Omicron variant.We collect the publicly available data from the ofcial website of the Hong Kong Special Administrative Region(HKSAR)Government and the study period in this paper is from December 27,2021 to July 17,2022(including a period for future prediction).First,we construct the spatiotemporal transmission intensity matrices across diferent districts based on infection case records.With the constructed cross-district transmission matrices,we forecast the future risks of various locations daily by means of the Gaussian process.Finally,we develop a transmission-guided resource prioritization strategy that enables efective control of Omicron outbreaks under limited capacity.Results:We conduct a comprehensive investigation of risk mapping and resource allocation in Hong Kong,China.The maps of the district-level transmission risks clearly demonstrate the irregular and spatiotemporal varying patterns of the risks,making it difcult for the public health authority to foresee the outbreaks and plan the responses accordingly.With the guidance of the inferred transmission risks,the developed prioritization strategy enables the optimal testing resource allocation for integrative case management(including case detection,quarantine,and further treatment),i.e.,with the 300,000 testing capacity per day;it could reduce the infection peak by 87.1% compared with the population-based allocation strategy(case number reduces from 20,860 to 2689)and by 24.2% compared with the case-based strategy(case number reduces from 3547 to 2689),signifcantly alleviating the burden of the healthcare system.Conclusions:Computationally characterizing spatiotemporal transmission patterns allows for the efective risk mapping and resource prioritization;such adaptive strategies are of critical importance in achieving timely outbreak control under insufcient capacity.The proposed method can help guide public-health responses not only to the Omicron outbreaks but also to the potential future outbreaks caused by other new variants.Moreover,the investigation conducted in Hong Kong,China provides useful suggestions on how to achieve efective disease control with insufcient capacity in other highly populated countries and regions. 展开更多
关键词 COVID-19 Omicron outbreak Densely populated regions Spatiotemporal transmission risk Optimal resource allocation Integrative case management Efective disease control
Retrospect and reflection on the construction of large-scale technology platform of the State Key Laboratory of Natural and Biomimetic Drugs in 2018–2020 认领 引用 被引量：2
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作者 Shuxiang Song 《Journal of Chinese Pharmaceutical Sciences》 CAS CSCD 2019年第12期878-884,共7页
The State Key Laboratory of Natural and Biomimetic Drugs was approved for a funding of nearly 100 million yuan specifically aimed at the purchase and maintenance of equipment and instruments from 2018 to 2020,which is... The State Key Laboratory of Natural and Biomimetic Drugs was approved for a funding of nearly 100 million yuan specifically aimed at the purchase and maintenance of equipment and instruments from 2018 to 2020,which is a record high.The Laboratory focuses on two major directions of scientific research,the"basic scientific problems of drug resistance of complex components of natural products"and the"key biomimetic scientific problems of endogenous substances therapeutic functions".The selection of scientific instruments and equipment,trial production,upgrading,as well as high level of technical and management personnel allocation and other aspects are critical to meet the development needs of the Key Laboratory and to maintain the advantages and leading role in these two major directions of scientific research. 展开更多
关键词 Instrument platform construction Optimization of resource allocation Scientific research service
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The relationship between controllability, optimal testing resource allocation, and incubation-latent period mismatch as revealed by COVID-19 认领 引用 被引量：1
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作者 Jeffery Demers William F.Fagan +1 位作者 Sriya Potluri Justin M.Calabrese 《Infectious Disease Modelling》 CSCD 2023年第2期514-538,共25页
The severe shortfall in testing supplies during the initial COVID-19 outbreak and ensuing struggle to manage the pandemic have affirmed the critical importance of optimal supplyconstrained resource allocation strategi... The severe shortfall in testing supplies during the initial COVID-19 outbreak and ensuing struggle to manage the pandemic have affirmed the critical importance of optimal supplyconstrained resource allocation strategies for controlling novel disease epidemics.To address the challenge of constrained resource optimization for managing diseases with complications like pre-and asymptomatic transmission,we develop an integro partial differential equation compartmental disease model which incorporates realistic latent,incubation,and infectious period distributions along with limited testing supplies for identifying and quarantining infected individuals.Our model overcomes the limitations of typical ordinary differential equation compartmental models by decoupling symptom status from model compartments to allow a more realistic representation of symptom onset and presymptomatic transmission.To analyze the influence of these realistic features on disease controllability,we find optimal strategies for reducing total infection sizes that allocate limited testing resources between‘clinical’testing,which targets symptomatic individuals,and‘non-clinical’testing,which targets non-symptomatic individuals.We apply our model not only to the original,delta,and omicron COVID-19 variants,but also to generically parameterized disease systems with varying mismatches between latent and incubation period distributions,which permit varying degrees of presymptomatic transmission or symptom onset before infectiousness.We find that factors that decrease controllability generally call for reduced levels of non-clinical testing in optimal strategies,while the relationship between incubation-latent mismatch,controllability,and optimal strategies is complicated.In particular,though greater degrees of presymptomatic transmission reduce disease controllability,they may increase or decrease the role of nonclinical testing in optimal strategies depending on other disease factors like transmissibility and latent period length.Importantly,our model allows a spectrum of diseases to be compared within a consistent framework such that lessons learned from COVID-19 can be transferred to resource constrained scenarios in future emerging epidemics and analyzed for optimality. 展开更多
关键词 Testing quarantine control Optimal resource allocation Presymptomatic transmission Latent period Incubation period Age of infection
Distributed Algorithm for Robust Resource Allocation with Polyhedral Uncertain Allocation Parameters 认领 引用 被引量：6
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作者 ZENG Xianlin YI Peng HONG Yiguang 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2018年第1期103-119,共17页
This paper studies a distributed robust resource allocation problem with nonsmooth objective functions under polyhedral uncertain allocation parameters. In the considered distributed robust resource allocation problem... This paper studies a distributed robust resource allocation problem with nonsmooth objective functions under polyhedral uncertain allocation parameters. In the considered distributed robust resource allocation problem, the（nonsmooth） objective function is a sum of local convex objective functions assigned to agents in a multi-agent network. Each agent has a private feasible set and decides a local variable, and all the local variables are coupled with a global affine inequality constraint,which is subject to polyhedral uncertain parameters. With the duality theory of convex optimization,the authors derive a robust counterpart of the robust resource allocation problem. Based on the robust counterpart, the authors propose a novel distributed continuous-time algorithm, in which each agent only knows its local objective function, local uncertainty parameter, local constraint set, and its neighbors＇ information. Using the stability theory of differential inclusions, the authors show that the algorithm is able to find the optimal solution under some mild conditions. Finally, the authors give an example to illustrate the efficacy of the proposed algorithm. 展开更多
关键词 Distributed optimization resource allocation robust optimization polyhedral uncertain parameters nonsmooth optimization
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Enhancing Attention Network Spatiotemporal Dynamics for Motor Rehabilitation in Parkinson's Disease 认领 引用
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作者 Guangying Pei Mengxuan Hu +10 位作者 Jian Ouyang Zhaohui Jin Kexin Wang Detao Meng Yixuan Wang Keke Chen Li Wang Li-Zhi Cao Shintaro Funahashi Tianyi Yan Boyan Fang 《Cyborg and Bionic Systems》 SCIE EI CAS CSCD 2025年第1期479-492,共14页
Optimizing resource allocation for Parkinson's disease(PD)motor rehabilitation necessitates identifying biomarkers of responsiveness and dynamic neuroplasticity signatures underlying efficacy.A cohort study of 52 ... Optimizing resource allocation for Parkinson's disease(PD)motor rehabilitation necessitates identifying biomarkers of responsiveness and dynamic neuroplasticity signatures underlying efficacy.A cohort study of 52 early-stage PD patients undergoing 2-week multidisciplinary intensive rehabilitation therapy(MIRT)was conducted,which stratified participants into responders and nonresponders.A multimodal analysis of resting-state electroencephalography(EEG)microstates and functional magnetic resonance imaging(fMRI)coactivation patterns was performed to characterize MIRT-induced spatiotemporal network reorganization.Responders demonstrated clinically meaningful improvement in motor symptoms,exceeding the minimal clinically important difference threshold of 3.25 on the Unified PD Rating Scale part III,alongside significant reductions in bradykinesia and a significant enhancement in quality-of-life scores at the 3-month followup.Resting-state EEG in responders showed a significant attenuation in microstate C and a significant enhancement in microstate D occurrences,along with significantly increased transitions from microstate A/B to D,which significantly correlated with motor function,especially in bradykinesia gains.Concurrently,fMRI analyses identified a prolonged dwell time of the dorsal attention network coactivation/ventral attention network deactivation pattern,which was significantly inversely associated with microstate C occurrence and significantly linked to motor improvement.The identified brain spatiotemporal neural markers were validated using machine learning models to assess the efficacy of MIRT in motor rehabilitation for PD patients,achieving an average accuracy rate of 86%.These findings suggest that MIRT may facilitate a shift in neural networks from sensory processing to higher-order cognitive control,with the dynamic reallocation of attentional resources.This preliminary study validates the necessity of integrating cognitive-motor strategies for the motor rehabilitation of PD and identifies novel neural markers for assessing treatment efficacy. 展开更多
关键词 cohort study identifying biomarkers multimodal analysis optimizing resource allocation spatiotemporal dynamics Parkinsons disease intensive rehabilitation motor rehabilitation
Pain,agitation,and delirium practices in Chinese intensive care units:A national multicenter survey study 认领 引用
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作者 Xiaofeng Ou Lijie Wang +14 位作者 Jie Yang Pan Tao Cunzhen Wang Minying Chen Xuan Song Zhiyong Liu Zhenguo Zeng Man Huang Xiaogan Jiang Shusheng Li Erzhen Chen Lixia Liu Xuelian Liao Yan Kang the Analgesia and Sedation Quality Control Subspecialty Group,National Center for Medical Quality Control in Critical Care Medicine 《Chinese Medical Journal》 SCIE CAS CSCD 2025年第22期3031-3033,共3页
To the Editor:The standardized management of pain–agitation–delirium(PAD)represents a fundamental component of clinical practice in intensive care units(ICUs).[1]Evidence-based analgesia and sedation strategies not ... To the Editor:The standardized management of pain–agitation–delirium(PAD)represents a fundamental component of clinical practice in intensive care units(ICUs).[1]Evidence-based analgesia and sedation strategies not only alleviate patients’physiological discomfort and psychological distress,but also significantly reduce mechanical ventilation duration,improve long-term prognosis,and optimize healthcare resource allocation.[1,2]Equally crucial is delirium management,as evidenced by studies demonstrating that delirium duration independently predicts mortality risk,hospital stay length,healthcare expenditures,and acquired dementia incidence. 展开更多
关键词 agitation standardized management pain mechanical ventilation intensive care evidence based analgesia optimize healthcare resource allocation equally delirium
Update on the global,regional,and national burden of pancreatic cancer:Insights from the Global Burden of Disease 2021 Study 认领 引用
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作者 Huijuan Cheng Guodong Sun +1 位作者 Hao Chen Yumin Li 《Chinese Medical Journal》 SCIE CAS CSCD 2025年第21期2850-2852,共3页
To the Editor:Pancreatic cancer(PC)is one of the most lethal malignancies,with a five-year survival rate below 10%.Despite advancements in treatment,PC is still associated with poor survival outcomes,contributing to a... To the Editor:Pancreatic cancer(PC)is one of the most lethal malignancies,with a five-year survival rate below 10%.Despite advancements in treatment,PC is still associated with poor survival outcomes,contributing to a significant global disease burden.[1]In the context of global aging,a comprehensive report on the burden of PC is crucial to optimize healthcare resource allocation and formulate effective prevention strategies. 展开更多
关键词 formulate effective prevention strategies five year survival rate survival outcomes national burden optimize healthcare resource allocation regional burden global burden pancreatic cancer
MICRO-LEVEL FEATURES OF CHINA'S HIGH-QUALITY ECONOMIC DEVELOPMENT 认领 引用
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作者 Shu Jianjun 《Social Sciences in China》 2025年第3期96-98,共3页
Financialization must guard against excessively deviating from the real economy,and the development of the platform economy should also forestall the tendency towards excessive financialization.Both need to be organic... Financialization must guard against excessively deviating from the real economy,and the development of the platform economy should also forestall the tendency towards excessive financialization.Both need to be organically integrated with the macroeconomy to jointly support the healthy development of the national economy.In this process,differentiated policies play a critical role in stabilizing price transmission channels and optimizing resource allocation. 展开更多
关键词 micro level financialization development platform economy optimizing resource allocation high quality economic development real economy platform economy stabilizing price transmission channels
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