The process of ＂re-resourcing of converter slag＂ was put forward based on the analysis of the existing steel slag treatment process.The converter slag obtained from Jinan steel plant was studied.After grinding,the s...The process of ＂re-resourcing of converter slag＂ was put forward based on the analysis of the existing steel slag treatment process.The converter slag obtained from Jinan steel plant was studied.After grinding,the slag contained 3.3% of iron particles,54.84% of magnetic part（wTFe=20%）,and 41.84% of non-magnetic part,which could be used for making cement directly.At a temperature below 1000 ℃,the non-magnetic Fe2O3 in the slag could be efficiently reduced to magnetic iron by pure H2 and CO.The slag after precise reduction had high degree of dispersion and did not get sintered,which provided an optimum condition for the separation of iron and impurities.To separate the slag and enrich the iron after reduction,the laboratory-scale device of magnetic separation was designed and made.The process of slag re-resourcing,which included magnetic sorting,precise reduction,magnetic separation,and removal of free calcium oxide（f-CaO）,was proposed to obtain iron-rich magnetic materials and cement adulterant materials.Through this process,33 kg iron particles,150 kg iron-rich material and 700 kg cement could be obtained in each ton slag.Besides,this process to recycle converter slag had a lower energy and material consumption and no pollutant emission.展开更多
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
The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind powe...The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind power continues to expand,the disposal of waste wind turbine blades(WWTB)has emerged as a significant challenge.These blades are predominantly composed of epoxy resin(EP)polymers,carbon fibers(CFs),and glass fibers(GFs).Improper disposal not only exacerbates environmental concerns but also leads to the loss of valuable resources,particularly carbon-based materials.Pyrolysis technology,a versatile and environmentally sustainable method for resource recovery,has garnered considerable attention in the context of WWTB disposal.This work presents a comprehensive review of the pyrolytic recycling of WWTB,focusing on the principles and classifications of pyrolysis technology,key factors influencing the pyrolysis process,as well as the pyrolysis methods,equipment,products,and their applications.Through an in-depth analysis of the current research on the pyrolytic recycling of WWTB,this review identifies critical unresolved issues in the field and provides a forward-looking perspective on emerging research trends.展开更多
Recently,the Internet of Things(IoT)technology has been utilized in a wide range of services and applications which significantly transforms digital ecosystems through seamless interconnectivity between various smart ...Recently,the Internet of Things(IoT)technology has been utilized in a wide range of services and applications which significantly transforms digital ecosystems through seamless interconnectivity between various smart devices.Furthermore,the IoT plays a key role in multiple domains,including industrial automation,smart homes,and intelligent transportation systems.However,an increasing number of connected devices presents significant challenges related to efficient resource allocation and system responsiveness.To address these issue,this research proposes a Modified Walrus Optimization Algorithm(MWaOA)for effective resource management in smart IoT systems.In the proposed MWaOA,a crowding process is incorporated to maintain diversity and avoid premature convergence thereby enhancing the global search capability.During resource allocation,the MWaOA prevents early convergence,which aids in achieving a better balance between the exploration and exploitation phases during optimization.Empirical evaluations show that the MWaOA reduces energy consumption by approximately 4% to 34%and minimizes the response time by 6% to 33% across different service arrival rates.Compared to traditional optimization algorithms,MWaOA reduces energy consumption by 5% to 30%and minimizes the response time by 4% to 28% across different simulation epochs.The proposed MWaOA provides adaptive and robust resource allocation,thereby minimizing transmission cost while considering network constraints and real-time performance parameters.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
In 2025,the global rare earth exploration and development sector achieved breakthroughs across multiple fronts.Projects advanced intensively across the Americas,Oceania,Africa,and Europe,with significant growth in res...In 2025,the global rare earth exploration and development sector achieved breakthroughs across multiple fronts.Projects advanced intensively across the Americas,Oceania,Africa,and Europe,with significant growth in resources,continuous emergence of new deposits,and strong impetus injected into the industry by technological innovation and policy support.The global rare earth resource supply pattern was further optimized (Table 1).1.Fruitful results in resource growth and new deposit discoveriesBrazil emerged as a core region for resource growth.The Colossus rare earth deposit saw a 150%increase in resources and announced its first reserve estimate.The Caldeira rare earth deposit’s resource estimate grew by 50%.The combined ore resources in the Caladão rare earth deposit’s Zones A and B reached 5.72×10~8 tonnes,with a total rare earth oxide(TREO) grade of 0.1506%,concurrently hosting 2.29×10~4tonnes of gallium metal resources.展开更多
The increasing penetration of inverter-based resources(IBRs)and renewable energy resources poses significant challenges to the stability and controllability of modern power systems.Dynamic virtual power plants(DVPPs)h...The increasing penetration of inverter-based resources(IBRs)and renewable energy resources poses significant challenges to the stability and controllability of modern power systems.Dynamic virtual power plants(DVPPs)have emerged as a transformative solution for aggregating and controlling heterogeneously distributed energy resources(DERs)flexibly and dynamically.This paper presents a comprehensive review of DVPPs,covering their conceptual evolution—from microgrids to virtual power plants(VPPs)and fast-acting VPPs—culminating in the dynamic DVPP paradigm.This review explores key architectural frameworks,including grid-forming and grid-following roles,as well as AC/DC interfacing strategies.Emphasis is placed on secondary frequency and voltage control mechanisms,dynamic-based and market-based disaggregation,and control methodologies tailored to DERs.展开更多
The energy transition inspired by carbon neutrality targets and the increasing threat of extreme events raise multi-objective development requirements for power systems.This paper proposes a multi-objective resource a...The energy transition inspired by carbon neutrality targets and the increasing threat of extreme events raise multi-objective development requirements for power systems.This paper proposes a multi-objective resource allocation model to determine the type,number and location of flexible resources to increase the values of resilience,carbon reduction and renewable energy consumption.To evaluate the values of resilience,a restoration model for transmission systems is established that considers the coordination of fossil-fuel generators,energy storage systems(ESSs)and renewable energy generators in building restoration paths.The collaborative power-carbon-tradable green certificate(TGC)market model is then applied to evaluate the resource values in terms of carbon reduction and renewable energy consumption.Finally,the model is formulated as a mixed-integer linear programming(MILP)with a nonconvex feasible domain,and the normalized normal constraint(NNC)method is applied to obtain approximate Pareto frontiers for decision makers.Case studies validate the effectiveness of the proposed model in improving multi-factor values and analyze the impact of resource regulation capacity on values of restoration and carbon reduction.展开更多
Reconciling biodiversity conservation with economic advancement represents a defining challenge of the Anthropocene epoch.Although ecotourism is widely promoted as a strategy capable of delivering both environmental a...Reconciling biodiversity conservation with economic advancement represents a defining challenge of the Anthropocene epoch.Although ecotourism is widely promoted as a strategy capable of delivering both environmental and developmental benefits,empirical evidence regarding its ecological and socioeconomic impacts remains limited.This study critically examined the Hide-in-Bird Pond(HIBP)model,a rapidly expanding,community-based avitourism framework in China that integrates targeted wildlife provisioning with concealed infrastructure for bird observation,simultaneously establishing a novel income source for economically marginalized rural regions through ecotourism.Semi-structured online interviews were conducted with 98 HIBP operators,and thematic analysis was applied to evaluate current developmental patterns,spatial distribution,and conservation outcomes.A total of 251 HIBP sites were identified across China,predominantly located in biodiversity-rich but economically marginalized regions.These sites collectively supported 524 bird species—36%of China's avifauna—including 148 species classified as nationally protected or threatened(38%of nationally listed bird taxa).These findings suggest that HIBP can serve as an integrative socio-ecological platform that aligns conservation objectives with sustainable rural development.However,the absence of standardized governance frameworks and ecological safeguards poses significant risks to biodiversity an d long-term sustainability.Implementation of science-based adaptive management systems,incorporating systematic biodiversity monitoring,inclusive stakeholder coordination,and certified sustainable tourism protocols,is critical to ensure ecological integrity and sectoral resilience.These findings offer novel insights into aligning conservation objectives with economic development across regions characterized by high biodiversity and persistent economic disadvantage.展开更多
Coal serves not only as a crucial energy resource but also as a significant reservoir of critical metal elements,including Lithium(Li),Gallium(Ga),Germanium(Ge),and rare earth elements(REE).This paper provides a syste...Coal serves not only as a crucial energy resource but also as a significant reservoir of critical metal elements,including Lithium(Li),Gallium(Ga),Germanium(Ge),and rare earth elements(REE).This paper provides a systematic review of the enrichment characteristics,occurrence modes,and comprehensive utilization potential of these critical metals in coal.Globally,the distribution of these metal resources exhibits significant regional heterogeneity.While the concentration in most coals falls below industrial cut-off grades,anomalous enrichment in specific coal basins results in Li,Ga,Ge,and REE concentrations far exceeding global averages,highlighting their considerable potential as unconventional metal deposits.The occurrence modes of these metals are diverse:Li is primarily hosted in mineral phases;Ga exists in inorganic,organic,and complex forms;Ge shows a strong association with organic matter;and REE are mainly present in adsorbed/isomorphic forms within clay minerals,while also displaying organic affinity.Direct extraction of metals from raw coal is often cost-prohibitive;effective recovery is therefore more feasible when integrated with coal processing.Metals are further enriched in solid wastes such as coal gangue,fly ash,and bottom ash,from which recovery is more economically and technically viable.Current comprehensive utilization primarily employs integrated mineral processing-hydrometallurgy approaches.Future research should focus on elucidating the precise occurrence forms of metals in coal and solid wastes,optimizing pre-treatment methods,and selecting effective activators and leachants.Advancing the synergistic extraction and green recovery of multiple associated resources from coal and its by-products is essential for achieving high-value,comprehensive utilization of coal-based resources.展开更多
China-Zimbabwe collaboration is creating new opportunities for innovation and development of youth Zimbabwe’s development has long faced obstacles linked to Western economic sanctions,measures that many view as unjus...China-Zimbabwe collaboration is creating new opportunities for innovation and development of youth Zimbabwe’s development has long faced obstacles linked to Western economic sanctions,measures that many view as unjust or unlawful.Yet,despite these constraints,Zimbabwe remains a nation rich in natural resources and endowed with a highly educated population,with its youth standing out as a particularly dynamic force.展开更多
Metaheuristic algorithms,renowned for strong global search capabilities,are effective tools for solving complex optimization problems and show substantial potential in e-Health applications.This review provides a syst...Metaheuristic algorithms,renowned for strong global search capabilities,are effective tools for solving complex optimization problems and show substantial potential in e-Health applications.This review provides a systematic overview of recent advancements in metaheuristic algorithms and highlights their applications in e-Health.We selected representative algorithms published between 2019 and 2024,and quantified their influence using an entropy-weighted method based on journal impact factors and citation counts.CThe Harris Hawks Optimizer(HHO)demonstrated the highest early citation impact.The study also examined applications in disease prediction models,clinical decision support,and intelligent health monitoring.Notably,the Chaotic Salp Swarm Algorithm(CSSA)achieved 99.69% accuracy in detecting Novel Coronavirus Pneumonia.Future research should progress in three directions:improving theoretical reliability and performance predictability in medical contexts;designing more adaptive and deployable mechanisms for real-world systems;and integrating ethical,privacy,and technological considerations to enable precision medicine,digital twins,and intelligent medical devices.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
This study investigates the potential of starch extracted from underutilized agro-industrial resources as non-food-competing raw materials for the development of flexible bioplastics for food packaging applications.St...This study investigates the potential of starch extracted from underutilized agro-industrial resources as non-food-competing raw materials for the development of flexible bioplastics for food packaging applications.Starch was extracted from three biomass sources:rubber cassava(Manihot glaziovii),banana stem,and banana peel from Ambonese banana(Musa acuminata L.).Rubber cassava starch(SRC)exhibited the highest starch yield(50.68±0.28%),significantly surpassing banana stem(SBS,14.20±0.25%)and banana peel(SBP,3.07±0.15%).The amylose contents of SRC,SBS,and SBP were 28.18%,52.80%,and 56.57%,respectively,while their amylopectin contents were 71.83%,47.20%,and 43.43%.FTIR spectra confirmed the absence of cyanogenic groups in SRC,indicating its safety for packaging applications.XRD analysis revealed that PSRC films were predominantly amorphous,while PSBS and PSBP showed higher crystallinity.The enhancement of mechanical properties,specifically PSBS,showed the highest tensile strength at 16.04±0.56 MPa,whereas PSRC demonstrated the highest elongation at break at 23.57±0.40%,which could be attributed to the inherent characteristics of the starch sources.Additionally,PSRC film exhibited the highest transparency at 60.2%,the greatest water solubility at 34.92%,and the lowest water contact angle at 41.58○,confirming its more hydrophilic nature compared to other films.This work highlights the potential of low-cost,sustainable,and non-food agro-industrial starch sources as promising candidates for the development of flexible,eco-friendly bioplastics.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.
1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic inf...1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic information sciences, remote sensing and cartography. Manuscripts come from different parts of the world.展开更多
Space exploration and manufacturing are of critical importance for scientific advancement,technological innovation,national security,and the acquisition of extraterrestrial resources.In view of this,chemical and biolo...Space exploration and manufacturing are of critical importance for scientific advancement,technological innovation,national security,and the acquisition of extraterrestrial resources.In view of this,chemical and biological nano-/micro-/meso-scale manufacturing provide complementary approaches to overcome key space exploration challenges by enabling the in-situ production of essential life-support materials,propellants,and other resources.This review examines the origin and historical evolution of space manufacturing and the latest advances across different environments—from orbital space stations and the lunar surface to Mars and asteroids.It is structured to present the current state of research,outline key manufacturing strategies and technologies,assess the technical and environmental challenges,and discuss emerging trends and future directions.Besides,the potential applications of emerging technologies such as synthetic biology and artificial intelligence in overcoming the limitations of microgravity,limited resources,and extreme conditions are discussed.Ultimately,this integrative review could serve to guide future development,from advancing space science and disruptive manufacturing to enabling interdisciplinary and application-level innovations.展开更多
The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous c...The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous computing networks.Finding an optimal computational resource for task offloading and then executing efficiently is a critical issue to achieve a trade-off between energy consumption and transmission delay.In this network,the task processed at fog nodes reduces transmission delay.Still,it increases energy consumption,while routing tasks to the cloud server saves energy at the cost of higher communication delay.Moreover,the order in which offloaded tasks are executed affects the system’s efficiency.For instance,executing lower-priority tasks before higher-priority jobs can disturb the reliability and stability of the system.Therefore,an efficient strategy of optimal computation offloading and task scheduling is required for operational efficacy.In this paper,we introduced a multi-objective and enhanced version of Cheeta Optimizer(CO),namely(MoECO),to jointly optimize the computation offloading and task scheduling in cloud-fog networks to minimize two competing objectives,i.e.,energy consumption and communication delay.MoECO first assigns tasks to the optimal computational nodes and then the allocated tasks are scheduled for processing based on the task priority.The mathematical modelling of CO needs improvement in computation time and convergence speed.Therefore,MoECO is proposed to increase the search capability of agents by controlling the search strategy based on a leader’s location.The adaptive step length operator is adjusted to diversify the solution and thus improves the exploration phase,i.e.,global search strategy.Consequently,this prevents the algorithm from getting trapped in the local optimal solution.Moreover,the interaction factor during the exploitation phase is also adjusted based on the location of the prey instead of the adjacent Cheetah.This increases the exploitation capability of agents,i.e.,local search capability.Furthermore,MoECO employs a multi-objective Pareto-optimal front to simultaneously minimize designated objectives.Comprehensive simulations in MATLAB demonstrate that the proposed algorithm obtains multiple solutions via a Pareto-optimal front and achieves an efficient trade-off between optimization objectives compared to baseline methods.展开更多
In scenarios where ground-based cloud computing infrastructure is unavailable,unmanned aerial vehicles(UAVs)act as mobile edge computing(MEC)servers to provide on-demand computation services for ground terminals.To ad...In scenarios where ground-based cloud computing infrastructure is unavailable,unmanned aerial vehicles(UAVs)act as mobile edge computing(MEC)servers to provide on-demand computation services for ground terminals.To address the challenge of jointly optimizing task scheduling and UAV trajectory under limited resources and high mobility of UAVs,this paper presents PER-MATD3,a multi-agent deep reinforcement learning algorithm with prioritized experience replay(PER)into the Centralized Training with Decentralized Execution(CTDE)framework.Specifically,PER-MATD3 enables each agent to learn a decentralized policy using only local observations during execution,while leveraging a shared replay buffer with prioritized sampling and centralized critic during training to accelerate convergence and improve sample efficiency.Simulation results show that PER-MATD3 reduces average task latency by up to 23%,improves energy efficiency by 21%,and enhances service coverage compared to state-of-the-art baselines,demonstrating its effectiveness and practicality in scenarios without terrestrial networks.展开更多
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
基金Item Sponsored by National Science and Technology Support Program of China(2006BAE03A10)
文摘The process of ＂re-resourcing of converter slag＂ was put forward based on the analysis of the existing steel slag treatment process.The converter slag obtained from Jinan steel plant was studied.After grinding,the slag contained 3.3% of iron particles,54.84% of magnetic part（wTFe=20%）,and 41.84% of non-magnetic part,which could be used for making cement directly.At a temperature below 1000 ℃,the non-magnetic Fe2O3 in the slag could be efficiently reduced to magnetic iron by pure H2 and CO.The slag after precise reduction had high degree of dispersion and did not get sintered,which provided an optimum condition for the separation of iron and impurities.To separate the slag and enrich the iron after reduction,the laboratory-scale device of magnetic separation was designed and made.The process of slag re-resourcing,which included magnetic sorting,precise reduction,magnetic separation,and removal of free calcium oxide（f-CaO）,was proposed to obtain iron-rich magnetic materials and cement adulterant materials.Through this process,33 kg iron particles,150 kg iron-rich material and 700 kg cement could be obtained in each ton slag.Besides,this process to recycle converter slag had a lower energy and material consumption and no pollutant emission.
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.
基金Supported by the National Natural Science Foundation of China(22468035,22468036,22368038,22308048)the Natural Science Foundation of Inner Mongolia(2024QN02018,2025MS02030)+2 种基金First-class Discipline Research Special Project of Inner Mongolia(YLXKZX-NGD-045)Inner Mongolia Autonomous Region Postgraduate Research Innovation Project(KC2024047B)Research Foundation for Introducing High-level Talents in Inner Mongolia Autonomous Region。
文摘The global energy landscape is undergoing a profound transformation,with wind energy,especially wind power,gaining increasing prominence due to its clean,renewable nature.However,as the installed capacity of wind power continues to expand,the disposal of waste wind turbine blades(WWTB)has emerged as a significant challenge.These blades are predominantly composed of epoxy resin(EP)polymers,carbon fibers(CFs),and glass fibers(GFs).Improper disposal not only exacerbates environmental concerns but also leads to the loss of valuable resources,particularly carbon-based materials.Pyrolysis technology,a versatile and environmentally sustainable method for resource recovery,has garnered considerable attention in the context of WWTB disposal.This work presents a comprehensive review of the pyrolytic recycling of WWTB,focusing on the principles and classifications of pyrolysis technology,key factors influencing the pyrolysis process,as well as the pyrolysis methods,equipment,products,and their applications.Through an in-depth analysis of the current research on the pyrolytic recycling of WWTB,this review identifies critical unresolved issues in the field and provides a forward-looking perspective on emerging research trends.
文摘Recently,the Internet of Things(IoT)technology has been utilized in a wide range of services and applications which significantly transforms digital ecosystems through seamless interconnectivity between various smart devices.Furthermore,the IoT plays a key role in multiple domains,including industrial automation,smart homes,and intelligent transportation systems.However,an increasing number of connected devices presents significant challenges related to efficient resource allocation and system responsiveness.To address these issue,this research proposes a Modified Walrus Optimization Algorithm(MWaOA)for effective resource management in smart IoT systems.In the proposed MWaOA,a crowding process is incorporated to maintain diversity and avoid premature convergence thereby enhancing the global search capability.During resource allocation,the MWaOA prevents early convergence,which aids in achieving a better balance between the exploration and exploitation phases during optimization.Empirical evaluations show that the MWaOA reduces energy consumption by approximately 4% to 34%and minimizes the response time by 6% to 33% across different service arrival rates.Compared to traditional optimization algorithms,MWaOA reduces energy consumption by 5% to 30%and minimizes the response time by 4% to 28% across different simulation epochs.The proposed MWaOA provides adaptive and robust resource allocation,thereby minimizing transmission cost while considering network constraints and real-time performance parameters.
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In 2025,the global rare earth exploration and development sector achieved breakthroughs across multiple fronts.Projects advanced intensively across the Americas,Oceania,Africa,and Europe,with significant growth in resources,continuous emergence of new deposits,and strong impetus injected into the industry by technological innovation and policy support.The global rare earth resource supply pattern was further optimized (Table 1).1.Fruitful results in resource growth and new deposit discoveriesBrazil emerged as a core region for resource growth.The Colossus rare earth deposit saw a 150%increase in resources and announced its first reserve estimate.The Caldeira rare earth deposit’s resource estimate grew by 50%.The combined ore resources in the Caladão rare earth deposit’s Zones A and B reached 5.72×10~8 tonnes,with a total rare earth oxide(TREO) grade of 0.1506%,concurrently hosting 2.29×10~4tonnes of gallium metal resources.
文摘The increasing penetration of inverter-based resources(IBRs)and renewable energy resources poses significant challenges to the stability and controllability of modern power systems.Dynamic virtual power plants(DVPPs)have emerged as a transformative solution for aggregating and controlling heterogeneously distributed energy resources(DERs)flexibly and dynamically.This paper presents a comprehensive review of DVPPs,covering their conceptual evolution—from microgrids to virtual power plants(VPPs)and fast-acting VPPs—culminating in the dynamic DVPP paradigm.This review explores key architectural frameworks,including grid-forming and grid-following roles,as well as AC/DC interfacing strategies.Emphasis is placed on secondary frequency and voltage control mechanisms,dynamic-based and market-based disaggregation,and control methodologies tailored to DERs.
基金supported by the Science and Technology Project of the State Grid Corporation of China“Research on Comprehensive Value Evaluation Method of Flexible Adjusting Resources under Carbon-electricity-certificate Market Coupling Environment”(No.5108-202455038A-1-1-ZN).
文摘The energy transition inspired by carbon neutrality targets and the increasing threat of extreme events raise multi-objective development requirements for power systems.This paper proposes a multi-objective resource allocation model to determine the type,number and location of flexible resources to increase the values of resilience,carbon reduction and renewable energy consumption.To evaluate the values of resilience,a restoration model for transmission systems is established that considers the coordination of fossil-fuel generators,energy storage systems(ESSs)and renewable energy generators in building restoration paths.The collaborative power-carbon-tradable green certificate(TGC)market model is then applied to evaluate the resource values in terms of carbon reduction and renewable energy consumption.Finally,the model is formulated as a mixed-integer linear programming(MILP)with a nonconvex feasible domain,and the normalized normal constraint(NNC)method is applied to obtain approximate Pareto frontiers for decision makers.Case studies validate the effectiveness of the proposed model in improving multi-factor values and analyze the impact of resource regulation capacity on values of restoration and carbon reduction.
基金supported by the Gaoligong Mountain Ecological Function Enhancement and Sustainable Development Technology Research(202303AC1000120303)Gaoligong Mountain Ecological Function Enhancement and Invasive Plant Species Prevention and Control Technology Project(2022YFF130240304)National Key R&D Program of China(2022YFC2602500)。
文摘Reconciling biodiversity conservation with economic advancement represents a defining challenge of the Anthropocene epoch.Although ecotourism is widely promoted as a strategy capable of delivering both environmental and developmental benefits,empirical evidence regarding its ecological and socioeconomic impacts remains limited.This study critically examined the Hide-in-Bird Pond(HIBP)model,a rapidly expanding,community-based avitourism framework in China that integrates targeted wildlife provisioning with concealed infrastructure for bird observation,simultaneously establishing a novel income source for economically marginalized rural regions through ecotourism.Semi-structured online interviews were conducted with 98 HIBP operators,and thematic analysis was applied to evaluate current developmental patterns,spatial distribution,and conservation outcomes.A total of 251 HIBP sites were identified across China,predominantly located in biodiversity-rich but economically marginalized regions.These sites collectively supported 524 bird species—36%of China's avifauna—including 148 species classified as nationally protected or threatened(38%of nationally listed bird taxa).These findings suggest that HIBP can serve as an integrative socio-ecological platform that aligns conservation objectives with sustainable rural development.However,the absence of standardized governance frameworks and ecological safeguards poses significant risks to biodiversity an d long-term sustainability.Implementation of science-based adaptive management systems,incorporating systematic biodiversity monitoring,inclusive stakeholder coordination,and certified sustainable tourism protocols,is critical to ensure ecological integrity and sectoral resilience.These findings offer novel insights into aligning conservation objectives with economic development across regions characterized by high biodiversity and persistent economic disadvantage.
基金supported by the Key Support Project of Regional Innovation and Development Joint Fund of the National Natural Science Foundation of China(No.U24A2095).
文摘Coal serves not only as a crucial energy resource but also as a significant reservoir of critical metal elements,including Lithium(Li),Gallium(Ga),Germanium(Ge),and rare earth elements(REE).This paper provides a systematic review of the enrichment characteristics,occurrence modes,and comprehensive utilization potential of these critical metals in coal.Globally,the distribution of these metal resources exhibits significant regional heterogeneity.While the concentration in most coals falls below industrial cut-off grades,anomalous enrichment in specific coal basins results in Li,Ga,Ge,and REE concentrations far exceeding global averages,highlighting their considerable potential as unconventional metal deposits.The occurrence modes of these metals are diverse:Li is primarily hosted in mineral phases;Ga exists in inorganic,organic,and complex forms;Ge shows a strong association with organic matter;and REE are mainly present in adsorbed/isomorphic forms within clay minerals,while also displaying organic affinity.Direct extraction of metals from raw coal is often cost-prohibitive;effective recovery is therefore more feasible when integrated with coal processing.Metals are further enriched in solid wastes such as coal gangue,fly ash,and bottom ash,from which recovery is more economically and technically viable.Current comprehensive utilization primarily employs integrated mineral processing-hydrometallurgy approaches.Future research should focus on elucidating the precise occurrence forms of metals in coal and solid wastes,optimizing pre-treatment methods,and selecting effective activators and leachants.Advancing the synergistic extraction and green recovery of multiple associated resources from coal and its by-products is essential for achieving high-value,comprehensive utilization of coal-based resources.
文摘China-Zimbabwe collaboration is creating new opportunities for innovation and development of youth Zimbabwe’s development has long faced obstacles linked to Western economic sanctions,measures that many view as unjust or unlawful.Yet,despite these constraints,Zimbabwe remains a nation rich in natural resources and endowed with a highly educated population,with its youth standing out as a particularly dynamic force.
基金Supported by National Natural Science Foundation of China(Grant No.62506054)Natural Science Foundation of Chongqing,China(Grant Nos.CSTB2022NSCQ-MSX1571,CSTB2024NSCQ-MSX1118)+2 种基金the Science and Technology Research Program of Chongqing Municipal Education Commission(Grant Nos.KJQN202400841,KJZD-M202500804)The National Natural Science Foundation of China(Grant No.61976030)Chongqing Technology and Business University High-level Talent Research Initiation Project(Grant No.2256004).
文摘Metaheuristic algorithms,renowned for strong global search capabilities,are effective tools for solving complex optimization problems and show substantial potential in e-Health applications.This review provides a systematic overview of recent advancements in metaheuristic algorithms and highlights their applications in e-Health.We selected representative algorithms published between 2019 and 2024,and quantified their influence using an entropy-weighted method based on journal impact factors and citation counts.CThe Harris Hawks Optimizer(HHO)demonstrated the highest early citation impact.The study also examined applications in disease prediction models,clinical decision support,and intelligent health monitoring.Notably,the Chaotic Salp Swarm Algorithm(CSSA)achieved 99.69% accuracy in detecting Novel Coronavirus Pneumonia.Future research should progress in three directions:improving theoretical reliability and performance predictability in medical contexts;designing more adaptive and deployable mechanisms for real-world systems;and integrating ethical,privacy,and technological considerations to enable precision medicine,digital twins,and intelligent medical devices.
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supported by the RIIM BRIN and LPDP Grants,grant number B-2880/II.7.5/KS.00/4/2025 dan B-7930/III.6/TK.01.03/4/2025 under the scheme BRIN-KONEKSI Joint Call for Proposalsthe theme“Indonesia's Bioeconomy:Maximising Sustainable Marine Biodiversity Utilisation 2024”No 6/II.7/HK/2025.
文摘This study investigates the potential of starch extracted from underutilized agro-industrial resources as non-food-competing raw materials for the development of flexible bioplastics for food packaging applications.Starch was extracted from three biomass sources:rubber cassava(Manihot glaziovii),banana stem,and banana peel from Ambonese banana(Musa acuminata L.).Rubber cassava starch(SRC)exhibited the highest starch yield(50.68±0.28%),significantly surpassing banana stem(SBS,14.20±0.25%)and banana peel(SBP,3.07±0.15%).The amylose contents of SRC,SBS,and SBP were 28.18%,52.80%,and 56.57%,respectively,while their amylopectin contents were 71.83%,47.20%,and 43.43%.FTIR spectra confirmed the absence of cyanogenic groups in SRC,indicating its safety for packaging applications.XRD analysis revealed that PSRC films were predominantly amorphous,while PSBS and PSBP showed higher crystallinity.The enhancement of mechanical properties,specifically PSBS,showed the highest tensile strength at 16.04±0.56 MPa,whereas PSRC demonstrated the highest elongation at break at 23.57±0.40%,which could be attributed to the inherent characteristics of the starch sources.Additionally,PSRC film exhibited the highest transparency at 60.2%,the greatest water solubility at 34.92%,and the lowest water contact angle at 41.58○,confirming its more hydrophilic nature compared to other films.This work highlights the potential of low-cost,sustainable,and non-food agro-industrial starch sources as promising candidates for the development of flexible,eco-friendly bioplastics.
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1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic information sciences, remote sensing and cartography. Manuscripts come from different parts of the world.
基金supported by National Natural Science Foundation of China(22278241)a grant from the Institute Guo Qiang,Tsinghua University(2021GQG1016).
文摘Space exploration and manufacturing are of critical importance for scientific advancement,technological innovation,national security,and the acquisition of extraterrestrial resources.In view of this,chemical and biological nano-/micro-/meso-scale manufacturing provide complementary approaches to overcome key space exploration challenges by enabling the in-situ production of essential life-support materials,propellants,and other resources.This review examines the origin and historical evolution of space manufacturing and the latest advances across different environments—from orbital space stations and the lunar surface to Mars and asteroids.It is structured to present the current state of research,outline key manufacturing strategies and technologies,assess the technical and environmental challenges,and discuss emerging trends and future directions.Besides,the potential applications of emerging technologies such as synthetic biology and artificial intelligence in overcoming the limitations of microgravity,limited resources,and extreme conditions are discussed.Ultimately,this integrative review could serve to guide future development,from advancing space science and disruptive manufacturing to enabling interdisciplinary and application-level innovations.
基金appreciation to the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R384)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The cloud-fog computing paradigm has emerged as a novel hybrid computing model that integrates computational resources at both fog nodes and cloud servers to address the challenges posed by dynamic and heterogeneous computing networks.Finding an optimal computational resource for task offloading and then executing efficiently is a critical issue to achieve a trade-off between energy consumption and transmission delay.In this network,the task processed at fog nodes reduces transmission delay.Still,it increases energy consumption,while routing tasks to the cloud server saves energy at the cost of higher communication delay.Moreover,the order in which offloaded tasks are executed affects the system’s efficiency.For instance,executing lower-priority tasks before higher-priority jobs can disturb the reliability and stability of the system.Therefore,an efficient strategy of optimal computation offloading and task scheduling is required for operational efficacy.In this paper,we introduced a multi-objective and enhanced version of Cheeta Optimizer(CO),namely(MoECO),to jointly optimize the computation offloading and task scheduling in cloud-fog networks to minimize two competing objectives,i.e.,energy consumption and communication delay.MoECO first assigns tasks to the optimal computational nodes and then the allocated tasks are scheduled for processing based on the task priority.The mathematical modelling of CO needs improvement in computation time and convergence speed.Therefore,MoECO is proposed to increase the search capability of agents by controlling the search strategy based on a leader’s location.The adaptive step length operator is adjusted to diversify the solution and thus improves the exploration phase,i.e.,global search strategy.Consequently,this prevents the algorithm from getting trapped in the local optimal solution.Moreover,the interaction factor during the exploitation phase is also adjusted based on the location of the prey instead of the adjacent Cheetah.This increases the exploitation capability of agents,i.e.,local search capability.Furthermore,MoECO employs a multi-objective Pareto-optimal front to simultaneously minimize designated objectives.Comprehensive simulations in MATLAB demonstrate that the proposed algorithm obtains multiple solutions via a Pareto-optimal front and achieves an efficient trade-off between optimization objectives compared to baseline methods.
基金supported by the National Natural Science Foundation of China under Grant No.61701100.
文摘In scenarios where ground-based cloud computing infrastructure is unavailable,unmanned aerial vehicles(UAVs)act as mobile edge computing(MEC)servers to provide on-demand computation services for ground terminals.To address the challenge of jointly optimizing task scheduling and UAV trajectory under limited resources and high mobility of UAVs,this paper presents PER-MATD3,a multi-agent deep reinforcement learning algorithm with prioritized experience replay(PER)into the Centralized Training with Decentralized Execution(CTDE)framework.Specifically,PER-MATD3 enables each agent to learn a decentralized policy using only local observations during execution,while leveraging a shared replay buffer with prioritized sampling and centralized critic during training to accelerate convergence and improve sample efficiency.Simulation results show that PER-MATD3 reduces average task latency by up to 23%,improves energy efficiency by 21%,and enhances service coverage compared to state-of-the-art baselines,demonstrating its effectiveness and practicality in scenarios without terrestrial networks.
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.
