Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combinin...Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.展开更多
To deal with a polluted by-product of coal production,central China’s Shanxi Province has explored a governance path that addresses both the symptoms and root causes.
As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-govern...As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.展开更多
Nowadays,advances in communication technology and cloud computing have spawned a variety of smart mobile devices,which will generate a great amount of computing-intensive businesses,and require corresponding resources...Nowadays,advances in communication technology and cloud computing have spawned a variety of smart mobile devices,which will generate a great amount of computing-intensive businesses,and require corresponding resources of computation and communication.Multiaccess edge computing(MEC)can offload computing-intensive tasks to the nearby edge servers,which alleviates the pressure of devices.Ultra-dense network(UDN)can provide effective spectrum resources by deploying a large number of micro base stations.Furthermore,network slicing can support various applications in different communication scenarios.Therefore,this paper integrates the ultra-dense network slicing and the MEC technology,and introduces a hybrid computing offloading strategy in order to satisfy various quality of service(QoS)of edge devices.In order to dynamically allocate limited resources,the above problem is formulated as multiagent distributed deep reinforcement learning(DRL),which will achieve low overhead computation offloading strategy and real-time resource allocation decisions.In this context,federated learning is added to train DRL agents in a distributed manner,where each agent is dedicated to exploring actions composed of offloading decisions and allocating resources,so as to jointly optimize system delay and energy consumption.Simulation results show that the proposed learning algorithm has better performance compared with other strategies in literature.展开更多
With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service...With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service resources,uneven distribution,and prominent supply-demand contradictions have seriously affected service quality.Big data technology,with core advantages including data collection,analysis and mining,and accurate prediction,provides a new solution for the allocation of community elderly care service resources.This paper systematically studies the application value of big data technology in the allocation of community elderly care service resources from three aspects:resource allocation efficiency,service accuracy,and management intelligence.Combined with practical needs,it proposes optimal allocation strategies such as building a big data analysis platform and accurately grasping the elderly’s care needs,striving to provide operable path references for the construction of community elderly care service systems,promoting the early realization of the elderly care service goal of“adequate support and proper care for the elderly”,and boosting the high-quality development of China’s elderly care service industry.展开更多
Mineral resources in Asia continent and its mining industry play a significant role in the economic growth and industrialization of both Asia and the world.Asia continent boasts the most comprehensive kinds of mineral...Mineral resources in Asia continent and its mining industry play a significant role in the economic growth and industrialization of both Asia and the world.Asia continent boasts the most comprehensive kinds of minerals,with reserves of at least 38 of over 80 widely used minerals worldwide accounting for more than30%of the global total reserves.Asia continent experienced three main tectonic evolution and mineralization stages:The Precambrian,the Paleozoic,and the Mesozoic to Cenozoic.The abundant mineral resources in this continent can be divided into seven first-order metallogenic belts(metallogenic domains),18 second-order metallogenic belts(metallogenic provinces),61 third-order metallogenic belts(metallogenic zones),and nine main minerogenetic series.Asia continent exhibits the most significant metallogenic specialization among all continents.Specifically,granite belts of Asia continent manifest pronounced metallogenic specialization of tin,rare metals,and porphyry Cu-Au-Mo deposits.Its maficultramafic rock belts and ophiolite belts display notable metallogenic specialization of lateritic nickel deposits and magmatic type chromite deposits,while its Mesozoic to Cenozoic basalt belts show remarkable metallogenic specialization of lateritic bauxite deposits.Consequently,many giant metallogenic belts were formed,including the Southeast Asian tin belt,the Qinghai-Xizang Plateau rare metal metallogenic belt,the Tethyan porphyry Cu-Au-Mo metallogenic belt,the circum-Pacific porphyry Cu-Au-Mo metallogenic belt,the Southeast Asian lateritic bauxite metallogenic belt,the Deccan Plateau lateritic bauxite metallogenic belt in India,the Southeast Asian lateritic nickel metallogenic belt,and the Tethyan magmatic type chromite metallogenic belt—all of which are significant metallogenic belts in Asia continent.Future mineral exploration in Asia should focus primarily on the Precambrian mineralization of ancient cratons,the Paleozoic mineralization of the Central Asian-Mongolian orogenic belt,and the Mesozoic to Cenozoic mineralization of the Tethyan and circum-Pacific mobile belts.Asia's mining industry not only underpins its own economic growth but also propels global economic development and industrialization,contributing significantly to the world economy.Asia boasts the highest production value of minerals,the largest annual production of minerals,and the greatest trade value of mineral products among all the continents,having emerged as the trade center of global mineral products and the center of the mining industry economy.China is identified as one of the few countries that possess the most comprehensive kinds of minerals,and its mining industry has supported and driven the economic development and industrialization of Asia and even the world.Standing as the largest mineral producer worldwide,China ranked first in the production of 28 mineral commodities in the world in 2022.Besides,China exhibits the highest annual production value of minerals and the largest trade value of mineral products among all countries.Therefore,China's demand for global mineral products influences the global supply and demand patterns of minerals and the world economic situation.展开更多
Owing to the emergence of drug resistance and high morbidity,the need for novel antiviral drugs with novel targets is highly sought after.Marine-derived compounds mostly possess potent antiviral activity and serve as ...Owing to the emergence of drug resistance and high morbidity,the need for novel antiviral drugs with novel targets is highly sought after.Marine-derived compounds mostly possess potent antiviral activity and serve as a primary source for developing novel antiviral drugs,making the rapid discovery and evaluation of marine antiviral agents particularly crucial.Thus,future research should place greater emphasis on the identification of novel antiviral targets through the combination of artificial intelligence(AI)and structural pharmacology,as well as expanding the marine resource and target databases.展开更多
Based on new understandings of the whole petroleum system theory for coal measures,and utilizing data from coal-rock gas wells and other oil and gas wells in numerous pilot test areas for key parameter validation,this...Based on new understandings of the whole petroleum system theory for coal measures,and utilizing data from coal-rock gas wells and other oil and gas wells in numerous pilot test areas for key parameter validation,this study conducted a national resource assessment of coal-rock gas widely developed in marine-continental transitional and continental strata in major petroliferous basins like Ordos,Sichuan and Junggar in China.The main achievements and understandings were obtained as follows.(1)A resource evaluation methodology for coal-rock gas was established,incorporating varying geological/data conditions.(2)Key parameter thresholds for deep coal-rock gas resource evaluation were defined,including the upper limits of critical depth(1500,2000,2500 m),lower limit of reservoir thickness(1 m),and lower limits of gas content in medium-low rank and medium-high rank coals(2,10 m^(3)/t),depending on varying geological conditions across basins.(3)Methods for determining key parameters such as gas content,porosity,and technical recovery factor were developed using the basic data from coal-rock gas experiments/tests and logging.(4)Evaluation results indicate that the geological resources of coal-rock gas in the 14 major basins of onshore China amount to 55.11×10^(12) m^(3).Resources at depths of 1500-3000,3000-5000,5000-6000 m account for 50.29%,43.11%,6.60%of the total,respectively.Resource classification shows that Class Ⅰ,Ⅱ,and Ⅲ resources constitute 21.80%,32.76%,45.44%,with the Class Ⅰ and Ⅱ technically recoverable resources of approximately 13.23×10^(12) m^(3).(5)The Ordos Basin remains the most favorable province,while the Sichuan,Junggar and Tarim basins are the promising targets,for future exploration and development of coal-rock gas in the country.Other basins including Bohai Bay,Qaidam,Tuha,Songliao and Hailar are considered as prospective options.Coal-rock gas production is expected to reach 500×10^(8) m^(3) annually within the next 10-15 years,positioning it as a major contributor to the natural gas production growth of China and a crucial alternative resource for ensuring the national gas supply.展开更多
In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their explora...In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their exploration,extraction,and processing.His successor,Claudia Sheinbaum,reaffirmed this assertive resource governance policy in October 2024.As a direct consequence,the operations of the Chinese firm,Ganfeng Lithium in Mexico,experienced significant disruption.展开更多
State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The la...State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.展开更多
Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the id...Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and the analysis of the resource status transition, the resource allocation process and the necessity of resource reconstruction are presented, l^esource reconstruction algorithms are designed to determine the resource reconstruction types, and it is shown that they can achieve the goal of resource on-demand allocation through three methodologies： resource combination, resource split, and resource random adjustment. The effects that the resource users have on the resource reconstruction results, the deviation between resources and requirements, and the uniformity of resource distribution are studied by three experiments. The experiments show that resource reconstruction has a close relationship with resource requirements, but it is not the same with current distribution of resources. The algorithms can complete the resource adjustment with a lower cost and form the logic resources to match the demands of resource users easily.展开更多
In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this neces...In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this necessitates effective management of computation and wireless resources tailored to the requirements of various services.The heterogeneity of computation resources and interference among shared wireless resources pose significant coordination and management challenges.To solve these problems,this work provides an overview of multi-dimensional resource management in 6G SIG RAN,including computation and wireless resource.Firstly it provides with a review of current investigations on computation and wireless resource management and an analysis of existing deficiencies and challenges.Then focusing on the provided challenges,the work proposes an MEC-based computation resource management scheme and a mixed numerology-based wireless resource management scheme.Furthermore,it outlines promising future technologies,including joint model-driven and data-driven resource management technology,and blockchain-based resource management technology within the 6G SIG network.The work also highlights remaining challenges,such as reducing communication costs associated with unstable ground-to-satellite links and overcoming barriers posed by spectrum isolation.Overall,this comprehensive approach aims to pave the way for efficient and effective resource management in future 6G networks.展开更多
To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing...To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing resource management models lack openness,sharing ability and scalability,which make it difficult for many heterogeneous resources to co-exist in the same system. It is also difficult to resolve the conflicts between distributed self-management and centralized scheduling in the system. This paper analyzes the characteristics of resources in the distributed environment and proposes a new resource management architecture by considering the resource aggregation capacity of cloud computing. The architecture includes a universal resource scheduling optimization model which has been applied successfully in double-district multi-ship-scheduling multi-container-yard empty containers transporting of international shipping logistics. Applications in all these domains prove that this new resource management architecture is feasible and can achieve the expected effect.展开更多
Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating ...Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation potential.This paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous systems.The survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous infrastructures.This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes.Furthermore,proposes future directions,including AI-driven optimization techniques and hybrid orchestrationmodels.By addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing ecosystems.This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.展开更多
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
In the vast hinterland of the Qinghai-Xizang Plateau in western China,a profound green transformation is advancing quietly.On the vast Gobi Desert,arrays of solar panels resemble a shimmering silver sea.White wind tur...In the vast hinterland of the Qinghai-Xizang Plateau in western China,a profound green transformation is advancing quietly.On the vast Gobi Desert,arrays of solar panels resemble a shimmering silver sea.White wind turbines stand tall against the sky,with their blades swirling slowly in the wind.Golmud,a city in west China’s Qinghai Province formerly known for its abundant natural resources.展开更多
The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tas...The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.展开更多
State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The la...State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.展开更多
Achieving the dual carbon goal through energy transition has become a global consensus.The increasingly recognized of mineral resources is increasingly recognized due to their role in determining the pace of energy tr...Achieving the dual carbon goal through energy transition has become a global consensus.The increasingly recognized of mineral resources is increasingly recognized due to their role in determining the pace of energy transition.China has a leading capacity in the production and processing of certain minerals.However,because the major sources are abroad,China still faces certain disadvantages in acquiring upstream resources.In response to the complex international situation and high consumption demand。展开更多
Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the c...Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.展开更多
文摘Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.
文摘To deal with a polluted by-product of coal production,central China’s Shanxi Province has explored a governance path that addresses both the symptoms and root causes.
基金supported by the National Natural Science Foundation of China(W2412135)the Youth Innovation Promotion Association of the Chinese Academy of Sciences.
文摘As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.
文摘Nowadays,advances in communication technology and cloud computing have spawned a variety of smart mobile devices,which will generate a great amount of computing-intensive businesses,and require corresponding resources of computation and communication.Multiaccess edge computing(MEC)can offload computing-intensive tasks to the nearby edge servers,which alleviates the pressure of devices.Ultra-dense network(UDN)can provide effective spectrum resources by deploying a large number of micro base stations.Furthermore,network slicing can support various applications in different communication scenarios.Therefore,this paper integrates the ultra-dense network slicing and the MEC technology,and introduces a hybrid computing offloading strategy in order to satisfy various quality of service(QoS)of edge devices.In order to dynamically allocate limited resources,the above problem is formulated as multiagent distributed deep reinforcement learning(DRL),which will achieve low overhead computation offloading strategy and real-time resource allocation decisions.In this context,federated learning is added to train DRL agents in a distributed manner,where each agent is dedicated to exploring actions composed of offloading decisions and allocating resources,so as to jointly optimize system delay and energy consumption.Simulation results show that the proposed learning algorithm has better performance compared with other strategies in literature.
文摘With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service resources,uneven distribution,and prominent supply-demand contradictions have seriously affected service quality.Big data technology,with core advantages including data collection,analysis and mining,and accurate prediction,provides a new solution for the allocation of community elderly care service resources.This paper systematically studies the application value of big data technology in the allocation of community elderly care service resources from three aspects:resource allocation efficiency,service accuracy,and management intelligence.Combined with practical needs,it proposes optimal allocation strategies such as building a big data analysis platform and accurately grasping the elderly’s care needs,striving to provide operable path references for the construction of community elderly care service systems,promoting the early realization of the elderly care service goal of“adequate support and proper care for the elderly”,and boosting the high-quality development of China’s elderly care service industry.
基金funded by geological survey project of China Geological Survey(DD20211404)。
文摘Mineral resources in Asia continent and its mining industry play a significant role in the economic growth and industrialization of both Asia and the world.Asia continent boasts the most comprehensive kinds of minerals,with reserves of at least 38 of over 80 widely used minerals worldwide accounting for more than30%of the global total reserves.Asia continent experienced three main tectonic evolution and mineralization stages:The Precambrian,the Paleozoic,and the Mesozoic to Cenozoic.The abundant mineral resources in this continent can be divided into seven first-order metallogenic belts(metallogenic domains),18 second-order metallogenic belts(metallogenic provinces),61 third-order metallogenic belts(metallogenic zones),and nine main minerogenetic series.Asia continent exhibits the most significant metallogenic specialization among all continents.Specifically,granite belts of Asia continent manifest pronounced metallogenic specialization of tin,rare metals,and porphyry Cu-Au-Mo deposits.Its maficultramafic rock belts and ophiolite belts display notable metallogenic specialization of lateritic nickel deposits and magmatic type chromite deposits,while its Mesozoic to Cenozoic basalt belts show remarkable metallogenic specialization of lateritic bauxite deposits.Consequently,many giant metallogenic belts were formed,including the Southeast Asian tin belt,the Qinghai-Xizang Plateau rare metal metallogenic belt,the Tethyan porphyry Cu-Au-Mo metallogenic belt,the circum-Pacific porphyry Cu-Au-Mo metallogenic belt,the Southeast Asian lateritic bauxite metallogenic belt,the Deccan Plateau lateritic bauxite metallogenic belt in India,the Southeast Asian lateritic nickel metallogenic belt,and the Tethyan magmatic type chromite metallogenic belt—all of which are significant metallogenic belts in Asia continent.Future mineral exploration in Asia should focus primarily on the Precambrian mineralization of ancient cratons,the Paleozoic mineralization of the Central Asian-Mongolian orogenic belt,and the Mesozoic to Cenozoic mineralization of the Tethyan and circum-Pacific mobile belts.Asia's mining industry not only underpins its own economic growth but also propels global economic development and industrialization,contributing significantly to the world economy.Asia boasts the highest production value of minerals,the largest annual production of minerals,and the greatest trade value of mineral products among all the continents,having emerged as the trade center of global mineral products and the center of the mining industry economy.China is identified as one of the few countries that possess the most comprehensive kinds of minerals,and its mining industry has supported and driven the economic development and industrialization of Asia and even the world.Standing as the largest mineral producer worldwide,China ranked first in the production of 28 mineral commodities in the world in 2022.Besides,China exhibits the highest annual production value of minerals and the largest trade value of mineral products among all countries.Therefore,China's demand for global mineral products influences the global supply and demand patterns of minerals and the world economic situation.
文摘Owing to the emergence of drug resistance and high morbidity,the need for novel antiviral drugs with novel targets is highly sought after.Marine-derived compounds mostly possess potent antiviral activity and serve as a primary source for developing novel antiviral drugs,making the rapid discovery and evaluation of marine antiviral agents particularly crucial.Thus,future research should place greater emphasis on the identification of novel antiviral targets through the combination of artificial intelligence(AI)and structural pharmacology,as well as expanding the marine resource and target databases.
基金Supported by the National Science and Technology Major Project(2025ZD1404200)Research Project of PetroChina Company Limited(2024DJ23)Scientific Research and Technology Development Project of PetroChina Research Institute of Petroleum Exploration&Development(2024vzz).
文摘Based on new understandings of the whole petroleum system theory for coal measures,and utilizing data from coal-rock gas wells and other oil and gas wells in numerous pilot test areas for key parameter validation,this study conducted a national resource assessment of coal-rock gas widely developed in marine-continental transitional and continental strata in major petroliferous basins like Ordos,Sichuan and Junggar in China.The main achievements and understandings were obtained as follows.(1)A resource evaluation methodology for coal-rock gas was established,incorporating varying geological/data conditions.(2)Key parameter thresholds for deep coal-rock gas resource evaluation were defined,including the upper limits of critical depth(1500,2000,2500 m),lower limit of reservoir thickness(1 m),and lower limits of gas content in medium-low rank and medium-high rank coals(2,10 m^(3)/t),depending on varying geological conditions across basins.(3)Methods for determining key parameters such as gas content,porosity,and technical recovery factor were developed using the basic data from coal-rock gas experiments/tests and logging.(4)Evaluation results indicate that the geological resources of coal-rock gas in the 14 major basins of onshore China amount to 55.11×10^(12) m^(3).Resources at depths of 1500-3000,3000-5000,5000-6000 m account for 50.29%,43.11%,6.60%of the total,respectively.Resource classification shows that Class Ⅰ,Ⅱ,and Ⅲ resources constitute 21.80%,32.76%,45.44%,with the Class Ⅰ and Ⅱ technically recoverable resources of approximately 13.23×10^(12) m^(3).(5)The Ordos Basin remains the most favorable province,while the Sichuan,Junggar and Tarim basins are the promising targets,for future exploration and development of coal-rock gas in the country.Other basins including Bohai Bay,Qaidam,Tuha,Songliao and Hailar are considered as prospective options.Coal-rock gas production is expected to reach 500×10^(8) m^(3) annually within the next 10-15 years,positioning it as a major contributor to the natural gas production growth of China and a crucial alternative resource for ensuring the national gas supply.
文摘In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their exploration,extraction,and processing.His successor,Claudia Sheinbaum,reaffirmed this assertive resource governance policy in October 2024.As a direct consequence,the operations of the Chinese firm,Ganfeng Lithium in Mexico,experienced significant disruption.
文摘State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.
基金supported by National High Technology Research and Development Program of China (863 Program)(No. 2007AA010305)the Excellent Doctor Degree Dissertation Fund of Xi an University of Technology (No. 102-211007)
文摘Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and the analysis of the resource status transition, the resource allocation process and the necessity of resource reconstruction are presented, l^esource reconstruction algorithms are designed to determine the resource reconstruction types, and it is shown that they can achieve the goal of resource on-demand allocation through three methodologies： resource combination, resource split, and resource random adjustment. The effects that the resource users have on the resource reconstruction results, the deviation between resources and requirements, and the uniformity of resource distribution are studied by three experiments. The experiments show that resource reconstruction has a close relationship with resource requirements, but it is not the same with current distribution of resources. The algorithms can complete the resource adjustment with a lower cost and form the logic resources to match the demands of resource users easily.
基金supported by the National Key Research and Development Program of China(No.2021YFB2900504).
文摘In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this necessitates effective management of computation and wireless resources tailored to the requirements of various services.The heterogeneity of computation resources and interference among shared wireless resources pose significant coordination and management challenges.To solve these problems,this work provides an overview of multi-dimensional resource management in 6G SIG RAN,including computation and wireless resource.Firstly it provides with a review of current investigations on computation and wireless resource management and an analysis of existing deficiencies and challenges.Then focusing on the provided challenges,the work proposes an MEC-based computation resource management scheme and a mixed numerology-based wireless resource management scheme.Furthermore,it outlines promising future technologies,including joint model-driven and data-driven resource management technology,and blockchain-based resource management technology within the 6G SIG network.The work also highlights remaining challenges,such as reducing communication costs associated with unstable ground-to-satellite links and overcoming barriers posed by spectrum isolation.Overall,this comprehensive approach aims to pave the way for efficient and effective resource management in future 6G networks.
基金Support by the National Key Technology Research and Development Program of China(No.2012BAA13B01,2014BAF07B02)the National Natural Science Foundation of China(No.61273038)+1 种基金Natural Science Foundation of Shandong Province(No.ZR2015FM006)Science and Technology Major Project of the Ministry of Science and Technology of Shandong Province(No.2015ZDXX0201B02)
文摘To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing resource management models lack openness,sharing ability and scalability,which make it difficult for many heterogeneous resources to co-exist in the same system. It is also difficult to resolve the conflicts between distributed self-management and centralized scheduling in the system. This paper analyzes the characteristics of resources in the distributed environment and proposes a new resource management architecture by considering the resource aggregation capacity of cloud computing. The architecture includes a universal resource scheduling optimization model which has been applied successfully in double-district multi-ship-scheduling multi-container-yard empty containers transporting of international shipping logistics. Applications in all these domains prove that this new resource management architecture is feasible and can achieve the expected effect.
文摘Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation potential.This paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous systems.The survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous infrastructures.This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes.Furthermore,proposes future directions,including AI-driven optimization techniques and hybrid orchestrationmodels.By addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing ecosystems.This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.
基金funding of the Deanship of Graduate Studies and Scientific Research,Jazan University,Saudi Arabia,through Project Number:ISP-2024.
文摘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.
文摘In the vast hinterland of the Qinghai-Xizang Plateau in western China,a profound green transformation is advancing quietly.On the vast Gobi Desert,arrays of solar panels resemble a shimmering silver sea.White wind turbines stand tall against the sky,with their blades swirling slowly in the wind.Golmud,a city in west China’s Qinghai Province formerly known for its abundant natural resources.
文摘The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.
文摘State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.
基金the General Project of the National Natural Science Foundation of China,“Research on the Method of CO_(2)Technology Economic Evaluation Based on Net Energy and Carbon Input-Output”(72274212)。
文摘Achieving the dual carbon goal through energy transition has become a global consensus.The increasingly recognized of mineral resources is increasingly recognized due to their role in determining the pace of energy transition.China has a leading capacity in the production and processing of certain minerals.However,because the major sources are abroad,China still faces certain disadvantages in acquiring upstream resources.In response to the complex international situation and high consumption demand。
基金support provided by the Qingdao Science and Technology Benefits People Demonstration and Guidance Project(21-1-4-sf-4-nsh).
文摘Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.
