To optimize the overall layout of water resource allocation in the Beijing-Tianjin-Hebei region,the adaptabil‐ity of the water resource system to the regional social-ecological systems has to be enhanced.Based on the...To optimize the overall layout of water resource allocation in the Beijing-Tianjin-Hebei region,the adaptabil‐ity of the water resource system to the regional social-ecological systems has to be enhanced.Based on the driver-pressure-state-impact-response(DPSIR)framework,this study constructs an evaluation index system to analyze the adaptability mechanisms of Beijing-Tianjin-Hebei’s water resource system according to the three major constituent social-ecological systems(i.e.,economic,social,and ecological systems).Moreover,it adopts the technique of order preference similarity to the ideal solution(TOPSIS)to comprehensively evaluate the adaptability of Beijing-Tianjin-Hebei’s water resource system based on three constituent social-ecological systems(i.e.,economic,social,and ecological systems)and identifies the spatiotemporal differentiation char‐acteristics of the region.Our results showed that,①from 2000 to 2020,the adaptability of Beijing-Tianjin Hebei’s water resource system,as a whole,significantly improved.In terms of stages,from 2000 to 2007,the adaptability of the water resource social system was significantly higher than that of economic and ecological systems in the region.From 2008 to 2015,by accelerating the transformation and upgrading of industrial structures,improving the efficiency of economic water utilization,and strengthening the governance of the water ecosystem,the adaptability of water resource economic and ecological systems rapidly improved;how‐ever,that of the water resource ecological system was still the lowest.Additionally,the adaptability of the wa‐ter resource economic system exceeded that of the social system.From 2016 to 2020,the gap in adaptability of the water resource system to all three major constituent systems gradually narrowed.By 2020,the three sys‐tems entered a relatively balanced development stage,with the adaptability of the entire water resource system and the three major constituent systems maintaining a high level.②The economic system was significantly af‐fected by per capita GDP,per capita water resources,and the efficiency of economic water utilization.Addition‐ally,the social system was significantly affected by water consumption per unit of irrigation area.Meanwhile,the ecological system was significantly influenced by precipitation,water pollution discharge performance indi‐cators,and the structure optimization indicators of water supply.According to the evaluation results,we pro‐pose countermeasures and provide recommendations to optimize the overall layout of water resource alloca‐tion and promote the coordinated management of water resources in the Beijing-Tianjin-Hebei region.展开更多
Water resources of inland river basins of arid Northwest China will be profoundly affected by future accelerated glacier melt. Based on scenarios of climate warming, accelerated glacier melt and socioeconomic developm...Water resources of inland river basins of arid Northwest China will be profoundly affected by future accelerated glacier melt. Based on scenarios of climate warming, accelerated glacier melt and socioeconomic development in the future, vulnerability of the Yarkent River Basin water resources for 2010-2030 is evaluated quantitatively using the indicator of water deficiency ratio. Results show that the quantity of the basin＇s water resources will continuously increase over the next 20 years, mainly due to the effect of climate warming and accelerated glacier melt. But, in the next 10 years, the basin will have a deficient water status, and the water resource system will be quite vulnerable. This is due to an increased water demand from rapidly increasing socioeco- nomic development and a lack of low water-use efficiency in the near future. After about 2020, water supply will outstrip demand, greatly relieving the basin＇s water deficient due to increased water resources and the advancement of water-saving technology. Contrast to the hypothetical situation of unchanged glacier melt, climate wanning and resulting accelerated glacier melt may play a role in relieving the supply-demand strain to some extent.展开更多
In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its as...In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.展开更多
Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and ...Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.展开更多
In this paper,unmanned aerial vehicle(UAV)is adopted to serve as aerial base station(ABS)and mobile edge computing(MEC)platform for wire-less communication systems.When Internet of Things devices(IoTDs)cannot cope wit...In this paper,unmanned aerial vehicle(UAV)is adopted to serve as aerial base station(ABS)and mobile edge computing(MEC)platform for wire-less communication systems.When Internet of Things devices(IoTDs)cannot cope with computation-intensive and/or time-sensitive tasks,part of tasks is offloaded to the UAV side,and UAV process them with its own computing resources and caching resources.Thus,the burden of IoTDs gets relieved under the satisfaction of the quality of service(QoS)require-ments.However,owing to the limited resources of UAV,the cost of whole system,i.e.,that is defined as the weighted sum of energy consumption and time de-lay with caching,should be further optimized while the objective function and the constraints are non-convex.Therefore,we first jointly optimize commu-nication resources B,computing resources F and of-floading rates X with alternating iteration and convex optimization method,and then determine the value of caching decision Y with branch-and-bound(BB)al-gorithm.Numerical results show that UAV assisting partial task offloading with content caching is supe-rior to local computing and full offloading mechanism without caching,and meanwhile the cost of whole sys-tem gets further optimized with our proposed scheme.展开更多
Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,th...Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.展开更多
As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational ...As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational capability of the vehicle which reduces task processing latency and power con-sumption effectively and meets the quality of service requirements of vehicle users.However,there are still some problems in the MEC-assisted IoV system such as poor connectivity and high cost.Unmanned aerial vehicles(UAVs)equipped with MEC servers have become a promising approach for providing com-munication and computing services to mobile vehi-cles.Hence,in this article,an optimal framework for the UAV-assisted MEC system for IoV to minimize the average system cost is presented.Through joint consideration of computational offloading decisions and computational resource allocation,the optimiza-tion problem of our proposed architecture is presented to reduce system energy consumption and delay.For purpose of tackling this issue,the original non-convex issue is converted into a convex issue and the alternat-ing direction method of multipliers-based distributed optimal scheme is developed.The simulation results illustrate that the presented scheme can enhance the system performance dramatically with regard to other schemes,and the convergence of the proposed scheme is also significant.展开更多
Natural gas hydrate(NGH),as a widely recognized clean energy,has shown a significant resource potential.However,due to the lack of a unified evaluation methodology and the difficult determination of key parameters,the...Natural gas hydrate(NGH),as a widely recognized clean energy,has shown a significant resource potential.However,due to the lack of a unified evaluation methodology and the difficult determination of key parameters,the evaluation results of global NGH resource are greatly different.This paper establishes a quantitative relationship between NGH resource potential and conventional oil and gas resource and a NGH resource evaluation model based on the whole petroleum system(WPS)and through the analysis of dynamic field controlling hydrocarbon accumulation.The global NGH initially in-place and recoverable resources are inverted through the Monte Carlo simulation,and verified by using the volume analogy method based on drilling results and the trend analysis method of previous evaluation results.The proposed evaluation model considers two genetic mechanisms of natural gas(biological degradation and thermal degradation),surface volume conversion factor difference between conventional natural gas and NGH,and the impacts of differences in favorable distribution area and thickness and in other aspects on the results of NGH resource evaluation.The study shows that the global NGH initially in-place and recoverable resources are 99×10^(12) m^(3) and 30×10^(12) m3,with averages of 214×10^(12) m^(3) and 68×10^(12) m^(3),respectively,less than 5% of the total conventional oil and gas resources,and they can be used as a supplement for the future energy of the world.The proposed NGH resource evaluation model creates a new option of evaluation method and technology,and generates reliable data of NGH resource according to the reliability comprehensive analysis and test,providing a parameter basis for subsequent NGH exploration and development.展开更多
Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological inn...Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological innovation social responsibility(CISR)is analyzed.Based on this,this paper constructs a system dynamics model to analyze the changes in resource deployment system affected by CISR.The simulation model is developed using Venism personal learning edition(PLE).The results show that CISR,acted as a new factor affecting the resource deployment system,has a positive effect on resource deployment system performance.Moreover,when CISR exceeds the threshold value,the resource deployment system performance increases significantly faster,reflecting that the resource deployment system becomes more efficient.The results show that the method proposed in this paper is feasible and efficient.This research provides theoretical and practical implications for resource deployment system research.展开更多
Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic...Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.展开更多
Pressure-preserved coring technologies are critical for deep-earth resource exploration but are constrained by the inability to achieve multidirectional coring,restricting exploration range while escalating costs and ...Pressure-preserved coring technologies are critical for deep-earth resource exploration but are constrained by the inability to achieve multidirectional coring,restricting exploration range while escalating costs and environmental impacts.We developed a multidirectional pressure-preserved coring system based on magnetic control for deep-earth environments up to 5000 m.The system integrates a magnetically controlled method and key pressure-preserved components to ensure precise self-triggering and self-sealing.It is supported by geometric control equations for optimizing structural stability.Their structure was verified and optimized through theoretical and numerical calculations to meet design objectives.To clarify the self-triggering mechanism in complex environments,a dynamic interference model was established,verifying stability during multidirectional coring.The prototype was fabricated,and functional tests confirmed that it met its design objectives.In a 300-meter-deep test inclined well,10 coring operations were completed with a 100%pressure-preserved success rate,confirming the accuracy of the dynamic interference model analysis.Field trials in a 1970-meter-deep inclined petroleum well,representative of complex environments,demonstrated an in-situ pressure preservation efficiency of 92.18%at 22 MPa.This system innovatively expands the application scope of pressure-preserved coring,providing technical support for efficient and sustainable deep resources exploration and mining.展开更多
Aimed at the doubly near-far problems in a large range suffered by the remote user group and in a small range existing in both nearby and remote user groups during energy harvesting and computation offloading,a resour...Aimed at the doubly near-far problems in a large range suffered by the remote user group and in a small range existing in both nearby and remote user groups during energy harvesting and computation offloading,a resource allocation method for unmanned aerial vehicle(UAV)-assisted and user cooperation non-linear energy harvesting mobile edge computing(MEC)system is proposed.The UAV equipped with an MEC server is introduced to provide energy and computing services for the remote user group to alleviate the doubly near-far problem in a large range suffered by the remote user group.The doubly near-far problem in a small range existing in both nearby and remote user groups is mitigated by user cooperation.The specific user cooperation strategy is that the user near the base station or the UAV is used as a relay to transfer the computing task of the user far from the base station or the UAV to the MEC server for computing.By jointly optimizing users’offloading time,users’transmitting power,and the hovering position of the UAV,the resource allocation problem is modeled as a nonlinear programming problem with the objective of maximizing computation efficiency.The suboptimal solution is obtained by adopting the differential evolution algorithm.Simulation results show that,compared with the resource allocation method based on genetic algorithm and the without user cooperation method,the proposed method has higher computation efficiency.展开更多
This paper focuses on the issue of nurses’job burnout and conducts an in-depth analysis of its contributing factors from multiple dimensions,including organizational management,job characteristics,and individual attr...This paper focuses on the issue of nurses’job burnout and conducts an in-depth analysis of its contributing factors from multiple dimensions,including organizational management,job characteristics,and individual attributes.These factors include shortages in nursing human resources,lack of management support,excessive workload,and differences in coping strategies.Based on this analysis,targeted human resource management strategies are proposed,covering aspects such as optimizing human resource allocation,leadership development and organizational support,humanized management practices,and competency development with supporting systems.The aim is to alleviate nurses’job burnout,improve the quality of nursing work and nurses’professional well-being,and provide theoretical reference and practical guidance for human resource management in the nursing industry.展开更多
Dear Editor,This letter presents a joint probabilistic scheduling and resource allocation method(PSRA) for 5G-based wireless networked control systems(WNCSs). As a control-aware optimization method, PSRA minimizes the...Dear Editor,This letter presents a joint probabilistic scheduling and resource allocation method(PSRA) for 5G-based wireless networked control systems(WNCSs). As a control-aware optimization method, PSRA minimizes the linear quadratic Gaussian(LQG) control cost of WNCSs by optimizing the activation probability of subsystems, the number of uplink repetitions, and the durations of uplink and downlink phases. Simulation results show that PSRA achieves smaller LQG control costs than existing works.展开更多
The Polar Regions host one of the harshest and most unique ecosystems on Earth,harboring a diverse array of micro-and macro-organisms.These inhabitants showcase remarkable taxonomic and genetic originality,presenting ...The Polar Regions host one of the harshest and most unique ecosystems on Earth,harboring a diverse array of micro-and macro-organisms.These inhabitants showcase remarkable taxonomic and genetic originality,presenting unparalleled opportunities for bioprospecting,alongside demonstrating extraordinary adaptation mechanisms for survival.Furthermore,polar organisms play crucial roles in facilitating organic matter decomposition,carbon fixation and sequestration,and biogeochemical cycling.Moreover,these organisms serve as pivotal indicators of global climate shifts.Therefore,exploring the polar organisms and ecosystem holds profound and significant implications for gaining deeper insights into scientific frontiers such as global biodiversity,elementary cycling,climate change,resource utilization,and the awe of life in extreme environments.展开更多
Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 3...Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers,selected according to PRISMA guidelines,to evaluate the performance of Hybrid Artificial Neural Networks(HANNs)in ET estimation.The findings demonstrate that HANNs,particularly those combining Multilayer Perceptrons(MLPs),Recurrent Neural Networks(RNNs),and Convolutional Neural Networks(CNNs),are highly effective in capturing the complex nonlinear relationships and tem-poral dependencies characteristic of hydrological processes.These hybrid models,often integrated with optimization algorithms and fuzzy logic frameworks,significantly improve the predictive accuracy and generalization capabilities of ET estimation.The growing adoption of advanced evaluation metrics,such as Kling-Gupta Efficiency(KGE)and Taylor Diagrams,highlights the increasing demand for more robust performance assessments beyond traditional methods.Despite the promising results,challenges remain,particularly regarding model interpretability,computational efficiency,and data scarcity.Future research should prioritize the integration of interpretability techniques,such as attention mechanisms,Local Interpretable Model-Agnostic Explanations(LIME),and feature importance analysis,to enhance model transparency and foster stakeholder trust.Additionally,improving HANN models’scalability and computational efficiency is crucial,especially for large-scale,real-world applications.Approaches such as transfer learning,parallel processing,and hyperparameter optimization will be essential in overcoming these challenges.This study underscores the transformative potential of HANN models for precise ET estimation,particularly in water-scarce and climate-vulnerable regions.By integrating CNNs for automatic feature extraction and leveraging hybrid architectures,HANNs offer considerable advantages for optimizing water management,particularly agriculture.Addressing challenges related to interpretability and scalability will be vital to ensuring the widespread deployment and operational success of HANNs in global water resource management.展开更多
As part of my master’s programme in resource use and environmental science at China Agricultural University,I had the privilege of joining a study trip to the Shiyang River Basin and its surrounding areas from 17 to ...As part of my master’s programme in resource use and environmental science at China Agricultural University,I had the privilege of joining a study trip to the Shiyang River Basin and its surrounding areas from 17 to 21 July 2025.This trip to Gansu Province was organised under the China-Africa Joint Centre for Agricultural Demonstration and Training in Arid Regions programme,an initiative aligned with President Xi Jinping’s call for deeper China-Africa cooperation.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.
The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This rev...The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.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
基金This paper was supported by the Humanities and Social Science Foundation of Ministry of Education“Research on the optimal adapt‐ability of basin initial water rights and industrial structures under the rigid constraints of water resource”[Grant number:21YJCZH176]Beijing Municipal Natural Science Foundation of China“Research on Bi-directional optimal adaptability of water resource and indus‐trial structures under the coordinated development of the Beijing Tianjin-Hebei region”[Grant number:9202005].
文摘To optimize the overall layout of water resource allocation in the Beijing-Tianjin-Hebei region,the adaptabil‐ity of the water resource system to the regional social-ecological systems has to be enhanced.Based on the driver-pressure-state-impact-response(DPSIR)framework,this study constructs an evaluation index system to analyze the adaptability mechanisms of Beijing-Tianjin-Hebei’s water resource system according to the three major constituent social-ecological systems(i.e.,economic,social,and ecological systems).Moreover,it adopts the technique of order preference similarity to the ideal solution(TOPSIS)to comprehensively evaluate the adaptability of Beijing-Tianjin-Hebei’s water resource system based on three constituent social-ecological systems(i.e.,economic,social,and ecological systems)and identifies the spatiotemporal differentiation char‐acteristics of the region.Our results showed that,①from 2000 to 2020,the adaptability of Beijing-Tianjin Hebei’s water resource system,as a whole,significantly improved.In terms of stages,from 2000 to 2007,the adaptability of the water resource social system was significantly higher than that of economic and ecological systems in the region.From 2008 to 2015,by accelerating the transformation and upgrading of industrial structures,improving the efficiency of economic water utilization,and strengthening the governance of the water ecosystem,the adaptability of water resource economic and ecological systems rapidly improved;how‐ever,that of the water resource ecological system was still the lowest.Additionally,the adaptability of the wa‐ter resource economic system exceeded that of the social system.From 2016 to 2020,the gap in adaptability of the water resource system to all three major constituent systems gradually narrowed.By 2020,the three sys‐tems entered a relatively balanced development stage,with the adaptability of the entire water resource system and the three major constituent systems maintaining a high level.②The economic system was significantly af‐fected by per capita GDP,per capita water resources,and the efficiency of economic water utilization.Addition‐ally,the social system was significantly affected by water consumption per unit of irrigation area.Meanwhile,the ecological system was significantly influenced by precipitation,water pollution discharge performance indi‐cators,and the structure optimization indicators of water supply.According to the evaluation results,we pro‐pose countermeasures and provide recommendations to optimize the overall layout of water resource alloca‐tion and promote the coordinated management of water resources in the Beijing-Tianjin-Hebei region.
基金supported by the Western Project Program of the Chinese Academy of Sciences(Nos.KZCX-XB2-04-04,KZCX2-XB2-09-6)
文摘Water resources of inland river basins of arid Northwest China will be profoundly affected by future accelerated glacier melt. Based on scenarios of climate warming, accelerated glacier melt and socioeconomic development in the future, vulnerability of the Yarkent River Basin water resources for 2010-2030 is evaluated quantitatively using the indicator of water deficiency ratio. Results show that the quantity of the basin＇s water resources will continuously increase over the next 20 years, mainly due to the effect of climate warming and accelerated glacier melt. But, in the next 10 years, the basin will have a deficient water status, and the water resource system will be quite vulnerable. This is due to an increased water demand from rapidly increasing socioeco- nomic development and a lack of low water-use efficiency in the near future. After about 2020, water supply will outstrip demand, greatly relieving the basin＇s water deficient due to increased water resources and the advancement of water-saving technology. Contrast to the hypothetical situation of unchanged glacier melt, climate wanning and resulting accelerated glacier melt may play a role in relieving the supply-demand strain to some extent.
基金supported by Beijing Natural Science Fund–Haidian Original Innovation Joint Fund(L232040 and L232045).
文摘In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.
基金supported by the Deanship of Scientific Research and Graduate Studies at King Khalid University under research grant number(R.G.P.2/93/45).
文摘Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.
基金supported by National Natural Science Foundation of China(No.61821001)Science and Technology Key Project of Guangdong Province,China(2019B010157001).
文摘In this paper,unmanned aerial vehicle(UAV)is adopted to serve as aerial base station(ABS)and mobile edge computing(MEC)platform for wire-less communication systems.When Internet of Things devices(IoTDs)cannot cope with computation-intensive and/or time-sensitive tasks,part of tasks is offloaded to the UAV side,and UAV process them with its own computing resources and caching resources.Thus,the burden of IoTDs gets relieved under the satisfaction of the quality of service(QoS)require-ments.However,owing to the limited resources of UAV,the cost of whole system,i.e.,that is defined as the weighted sum of energy consumption and time de-lay with caching,should be further optimized while the objective function and the constraints are non-convex.Therefore,we first jointly optimize commu-nication resources B,computing resources F and of-floading rates X with alternating iteration and convex optimization method,and then determine the value of caching decision Y with branch-and-bound(BB)al-gorithm.Numerical results show that UAV assisting partial task offloading with content caching is supe-rior to local computing and full offloading mechanism without caching,and meanwhile the cost of whole sys-tem gets further optimized with our proposed scheme.
基金supported by the Science and Technology Project of the State Grid Corporation of China(5400-202255158A-1-1-ZN).
文摘Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.
基金in part by the National Natural Science Foundation of China(NSFC)under Grant 62371012in part by the Beijing Natural Science Foundation under Grant 4252001.
文摘As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational capability of the vehicle which reduces task processing latency and power con-sumption effectively and meets the quality of service requirements of vehicle users.However,there are still some problems in the MEC-assisted IoV system such as poor connectivity and high cost.Unmanned aerial vehicles(UAVs)equipped with MEC servers have become a promising approach for providing com-munication and computing services to mobile vehi-cles.Hence,in this article,an optimal framework for the UAV-assisted MEC system for IoV to minimize the average system cost is presented.Through joint consideration of computational offloading decisions and computational resource allocation,the optimiza-tion problem of our proposed architecture is presented to reduce system energy consumption and delay.For purpose of tackling this issue,the original non-convex issue is converted into a convex issue and the alternat-ing direction method of multipliers-based distributed optimal scheme is developed.The simulation results illustrate that the presented scheme can enhance the system performance dramatically with regard to other schemes,and the convergence of the proposed scheme is also significant.
基金Supported by the Major Consultation Project of the Chinese Academy of Sciences(2019-ZW11-Z-035)Technology Development Project of PetroChina Research Institute of Petroleum Exploration&Development(2021DJ0101)。
文摘Natural gas hydrate(NGH),as a widely recognized clean energy,has shown a significant resource potential.However,due to the lack of a unified evaluation methodology and the difficult determination of key parameters,the evaluation results of global NGH resource are greatly different.This paper establishes a quantitative relationship between NGH resource potential and conventional oil and gas resource and a NGH resource evaluation model based on the whole petroleum system(WPS)and through the analysis of dynamic field controlling hydrocarbon accumulation.The global NGH initially in-place and recoverable resources are inverted through the Monte Carlo simulation,and verified by using the volume analogy method based on drilling results and the trend analysis method of previous evaluation results.The proposed evaluation model considers two genetic mechanisms of natural gas(biological degradation and thermal degradation),surface volume conversion factor difference between conventional natural gas and NGH,and the impacts of differences in favorable distribution area and thickness and in other aspects on the results of NGH resource evaluation.The study shows that the global NGH initially in-place and recoverable resources are 99×10^(12) m^(3) and 30×10^(12) m3,with averages of 214×10^(12) m^(3) and 68×10^(12) m^(3),respectively,less than 5% of the total conventional oil and gas resources,and they can be used as a supplement for the future energy of the world.The proposed NGH resource evaluation model creates a new option of evaluation method and technology,and generates reliable data of NGH resource according to the reliability comprehensive analysis and test,providing a parameter basis for subsequent NGH exploration and development.
基金supported by the National Natural Science Foundation of China(72072047)the Fundamental Research Funds for the Central Universities(HIT.HSS.ESD202310)+3 种基金the Research Project on Graduates’Education and Teaching Reform of HIT(23MS011)the research Project on Higher Education of Heilongjiang Higher Education Association(23GJYBC011)the Natural Science Foundation of Shandong Province(ZR2023QG010)the Shandong Philosophy and Social Science Research Project(22CSDJ03).
文摘Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological innovation social responsibility(CISR)is analyzed.Based on this,this paper constructs a system dynamics model to analyze the changes in resource deployment system affected by CISR.The simulation model is developed using Venism personal learning edition(PLE).The results show that CISR,acted as a new factor affecting the resource deployment system,has a positive effect on resource deployment system performance.Moreover,when CISR exceeds the threshold value,the resource deployment system performance increases significantly faster,reflecting that the resource deployment system becomes more efficient.The results show that the method proposed in this paper is feasible and efficient.This research provides theoretical and practical implications for resource deployment system research.
文摘Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.
基金supported by the National Key Research and Development Program of China(No.2023YFF0615401)Joint Funds of the National Natural Science Foundation of China(No.U24A2087)+1 种基金Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(No.SKLGME022009)the National Natural Science Foundation of China(No.42477191)。
文摘Pressure-preserved coring technologies are critical for deep-earth resource exploration but are constrained by the inability to achieve multidirectional coring,restricting exploration range while escalating costs and environmental impacts.We developed a multidirectional pressure-preserved coring system based on magnetic control for deep-earth environments up to 5000 m.The system integrates a magnetically controlled method and key pressure-preserved components to ensure precise self-triggering and self-sealing.It is supported by geometric control equations for optimizing structural stability.Their structure was verified and optimized through theoretical and numerical calculations to meet design objectives.To clarify the self-triggering mechanism in complex environments,a dynamic interference model was established,verifying stability during multidirectional coring.The prototype was fabricated,and functional tests confirmed that it met its design objectives.In a 300-meter-deep test inclined well,10 coring operations were completed with a 100%pressure-preserved success rate,confirming the accuracy of the dynamic interference model analysis.Field trials in a 1970-meter-deep inclined petroleum well,representative of complex environments,demonstrated an in-situ pressure preservation efficiency of 92.18%at 22 MPa.This system innovatively expands the application scope of pressure-preserved coring,providing technical support for efficient and sustainable deep resources exploration and mining.
基金the National Natural Science Foundation of China(No.61871133)the Natural Science Foundation of Fujian Province(No.2021J01587)。
文摘Aimed at the doubly near-far problems in a large range suffered by the remote user group and in a small range existing in both nearby and remote user groups during energy harvesting and computation offloading,a resource allocation method for unmanned aerial vehicle(UAV)-assisted and user cooperation non-linear energy harvesting mobile edge computing(MEC)system is proposed.The UAV equipped with an MEC server is introduced to provide energy and computing services for the remote user group to alleviate the doubly near-far problem in a large range suffered by the remote user group.The doubly near-far problem in a small range existing in both nearby and remote user groups is mitigated by user cooperation.The specific user cooperation strategy is that the user near the base station or the UAV is used as a relay to transfer the computing task of the user far from the base station or the UAV to the MEC server for computing.By jointly optimizing users’offloading time,users’transmitting power,and the hovering position of the UAV,the resource allocation problem is modeled as a nonlinear programming problem with the objective of maximizing computation efficiency.The suboptimal solution is obtained by adopting the differential evolution algorithm.Simulation results show that,compared with the resource allocation method based on genetic algorithm and the without user cooperation method,the proposed method has higher computation efficiency.
基金Zhejiang Provincial Medical and Health Science and Technology Projects(Project No:2024KY1339)。
文摘This paper focuses on the issue of nurses’job burnout and conducts an in-depth analysis of its contributing factors from multiple dimensions,including organizational management,job characteristics,and individual attributes.These factors include shortages in nursing human resources,lack of management support,excessive workload,and differences in coping strategies.Based on this analysis,targeted human resource management strategies are proposed,covering aspects such as optimizing human resource allocation,leadership development and organizational support,humanized management practices,and competency development with supporting systems.The aim is to alleviate nurses’job burnout,improve the quality of nursing work and nurses’professional well-being,and provide theoretical reference and practical guidance for human resource management in the nursing industry.
基金supported by the Liaoning Revitalization Talents Program(XLYC2203148)
文摘Dear Editor,This letter presents a joint probabilistic scheduling and resource allocation method(PSRA) for 5G-based wireless networked control systems(WNCSs). As a control-aware optimization method, PSRA minimizes the linear quadratic Gaussian(LQG) control cost of WNCSs by optimizing the activation probability of subsystems, the number of uplink repetitions, and the durations of uplink and downlink phases. Simulation results show that PSRA achieves smaller LQG control costs than existing works.
文摘The Polar Regions host one of the harshest and most unique ecosystems on Earth,harboring a diverse array of micro-and macro-organisms.These inhabitants showcase remarkable taxonomic and genetic originality,presenting unparalleled opportunities for bioprospecting,alongside demonstrating extraordinary adaptation mechanisms for survival.Furthermore,polar organisms play crucial roles in facilitating organic matter decomposition,carbon fixation and sequestration,and biogeochemical cycling.Moreover,these organisms serve as pivotal indicators of global climate shifts.Therefore,exploring the polar organisms and ecosystem holds profound and significant implications for gaining deeper insights into scientific frontiers such as global biodiversity,elementary cycling,climate change,resource utilization,and the awe of life in extreme environments.
文摘Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers,selected according to PRISMA guidelines,to evaluate the performance of Hybrid Artificial Neural Networks(HANNs)in ET estimation.The findings demonstrate that HANNs,particularly those combining Multilayer Perceptrons(MLPs),Recurrent Neural Networks(RNNs),and Convolutional Neural Networks(CNNs),are highly effective in capturing the complex nonlinear relationships and tem-poral dependencies characteristic of hydrological processes.These hybrid models,often integrated with optimization algorithms and fuzzy logic frameworks,significantly improve the predictive accuracy and generalization capabilities of ET estimation.The growing adoption of advanced evaluation metrics,such as Kling-Gupta Efficiency(KGE)and Taylor Diagrams,highlights the increasing demand for more robust performance assessments beyond traditional methods.Despite the promising results,challenges remain,particularly regarding model interpretability,computational efficiency,and data scarcity.Future research should prioritize the integration of interpretability techniques,such as attention mechanisms,Local Interpretable Model-Agnostic Explanations(LIME),and feature importance analysis,to enhance model transparency and foster stakeholder trust.Additionally,improving HANN models’scalability and computational efficiency is crucial,especially for large-scale,real-world applications.Approaches such as transfer learning,parallel processing,and hyperparameter optimization will be essential in overcoming these challenges.This study underscores the transformative potential of HANN models for precise ET estimation,particularly in water-scarce and climate-vulnerable regions.By integrating CNNs for automatic feature extraction and leveraging hybrid architectures,HANNs offer considerable advantages for optimizing water management,particularly agriculture.Addressing challenges related to interpretability and scalability will be vital to ensuring the widespread deployment and operational success of HANNs in global water resource management.
文摘As part of my master’s programme in resource use and environmental science at China Agricultural University,I had the privilege of joining a study trip to the Shiyang River Basin and its surrounding areas from 17 to 21 July 2025.This trip to Gansu Province was organised under the China-Africa Joint Centre for Agricultural Demonstration and Training in Arid Regions programme,an initiative aligned with President Xi Jinping’s call for deeper China-Africa cooperation.
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.
文摘The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.
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.
