The proton exchange membrane fuel cell(PEMFC)and the hydrogen hybrid power system are studied by the fuzzy-PID(FPID)controlmethod and the fuzzy-PID controlmethod by Artificial Bee Colony algorithm(ABCFPID),respectivel...The proton exchange membrane fuel cell(PEMFC)and the hydrogen hybrid power system are studied by the fuzzy-PID(FPID)controlmethod and the fuzzy-PID controlmethod by Artificial Bee Colony algorithm(ABCFPID),respectively.The results reveal that compared with the FPID control method,the temperature overshoot of the PEMFC stack under the ABC-FPID control method is decreased by 0.6%.Moreover,the circulating water flow rate within the full operating envelope(about 3 min)is reduced by 19.46 L,which means the ABC-FPID control method is more effective in regulating the stack temperature.Then,the ABC-FPID control method is proposed to study the hydrogen hybrid power system,and the system output power matching,operating characteristic curve of the fuel cell,state of charge(SOC)of the lithium battery,system efficiency and hydrogen demand are obtained.The results indicate that the maximum system efficiency reaches 46.3%,the average system efficiency is 33.8%,and the average hydrogen demand is 0.192 kg/s.Overall,the ABC-FPID control method can efficiently ensure the stability of the fuel cell’s output power,and actively prompt the lithium battery to fulfill the function of“peak shaving and valley filling”under variable load power conditions.展开更多
Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosyst...Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosystem functions in China’s Loess Plateau have significantly improved.However,intensified human activities have also exacerbated the pressures on the region’s fragile ecological environment.This study investigates the spatiotemporal variations in the human activity intensity index(HAI)and net ecosystem benefits(NEB)from 2000 to 2020,using expert-based assessments and an enhanced cost-benefit evaluation framework.Results indicate that HAI increased by 16.7% and 16.6% at the grid and county levels,respectively.NEB exhibited pronounced spatial heterogeneity,with a total increase of USD 36.2 trillion at the grid scale.At the county level,the average NEB rose by 75%.The degree of trade-off was higher at the grid scale than at the county scale,while the synergistic areas initially expanded and then declined at both scales.Key areas for improvement and regions of lagging development were identified as priority zones for ecological management and spatial planning at both spatial resolutions.This study offers scientific insights and practical guidance for harmonizing ecological conservation with high-quality development in ecologically vulnerable regions.展开更多
Objective:To investigate the application effect of intelligent empowerment standardized airway management process in patients receiving mechanical ventilation.Methods:A retrospective analysis was conducted on the clin...Objective:To investigate the application effect of intelligent empowerment standardized airway management process in patients receiving mechanical ventilation.Methods:A retrospective analysis was conducted on the clinical data of 79 EICU inpatients who underwent tracheal intubation and mechanical ventilation treatment at our hospital from January 2023 to May 2025.The patients were divided into a control group(conventional airway management process,n=40)and a study group(intelligent empowerment standardized airway management process,n=39)based on the intervention protocols they received.Oral health scores,dental plaque index,oral odor,serum inflammatory markers[C-reactive protein(CRP),procalcitonin(PCT)],clinical pulmonary infection score(CPIS),as well as the incidence of ventilator-associated pneumonia(VAP),duration of mechanical ventilation,and length of stay in the EICU were assessed before and after treatment.Results:The baseline values of all indicators were consistent between the two groups before intervention(p>0.05).After corresponding interventions,both groups showed significant improvements in Beck oral health scores,dental plaque index,and oral odor,with more pronounced improvements observed in the study group(p<0.05).After the intervention,the research group showed a significant decrease in serum CRP and PCT levels,as well as CPIS scores(p<0.05).In contrast,the control group experienced an increase in these three indicators to a certain extent(p<0.05).Moreover,the incidence of ventilator-associated pneumonia(VAP),duration of mechanical ventilation,and length of stay in the EICU were all lower in the research group compared to the control group,while the nurse’s compliance rate with the protocol was higher in the research group(p<0.05).Conclusion:The standardized airway management protocol empowered by intelligent technology can significantly improve nursing compliance,benefit oral health status,reduce the risk of pulmonary infection and systemic inflammation levels,and promote rapid patient recovery,demonstrating considerable potential for widespread adoption.展开更多
Tooth developmental anomalies are a group of disorders caused by unfavorable factors affecting the tooth development process,resulting in abnormalities in tooth number,structure,and morphology.These anomalies typicall...Tooth developmental anomalies are a group of disorders caused by unfavorable factors affecting the tooth development process,resulting in abnormalities in tooth number,structure,and morphology.These anomalies typically manifest during childhood,impairing dental function,maxillofacial development,and facial aesthetics,while also potentially impacting overall physical and mental health.The complex etiology and diverse clinical phenotypes of these anomalies pose significant challenges for prevention,early diagnosis,and treatment.As they usually emerge early in life,long-term management and multidisciplinary collaboration in dental care are essential.However,there is currently a lack of systematic clinical guidelines for the diagnosis and treatment of these conditions,adding to the difficulties in clinical practice.In response to this need,this expert consensus summarizes the classifications,etiology,typical clinical manifestations,and diagnostic criteria of tooth developmental anomalies based on current clinical evidence.It also provides prevention strategies and stage-specific clinical management recommendations to guide clinicians in diagnosis and treatment,promoting early intervention and standardized care for these anomalies.展开更多
Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fund...Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fundamental trade-off between haze and transparency,coupled with impractical thicknesses(≥1 mm).Inspired by squid’s skin-peeling mechanism,this work develops a peroxyformic acid(HCOOOH)-enabled precision peeling strategy to isolate intact 10-μm-thick bamboo green(BG)frameworks—100×thinner than wood-based counterparts while achieving an unprecedented optical performance(88%haze with 80%transparency).This performance surpasses delignified biomass(transparency<40%at 1 mm)and matches engineered cellulose composites,yet requires no energy-intensive nanofibrillation.The preserved native cellulose I crystalline structure(64.76%crystallinity)and wax-coated uniaxial fibril alignment(Hermans factor:0.23)contribute to high mechanical strength(903 MPa modulus)and broadband light scattering.As a light-management layer in polycrystalline silicon solar cells,the BG framework boosts photoelectric conversion efficiency by 0.41%absolute(18.74%→19.15%),outperforming synthetic anti-reflective coatings.The work establishes a scalable,waste-to-wealth route for optical-grade cellulose materials in next-generation optoelectronics.展开更多
Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bot...Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bottleneck,severely affecting device stability and long-term operational performance.Herein,we present a multifunctional strategy by incorporating highly thermally conductive Ti_(3)C_(2)T_(X) MXene nanosheets into the perovskite layer to simultaneously enhance thermal management and optoelectronic properties.The Ti_(3)C_(2)T_(X) nanosheets,embedded at perovskite grain boundaries,construct efficient thermal conduction pathways,significantly improving the thermal conductivity and diffusivity of the film.This leads to a notable reduction in the device’s steady-state operating temperature from 42.96 to 39.97 under 100 mW cm^(−2) illumination,thereby alleviating heat-induced performance degradation.Beyond thermal regulation,Ti_(3)C_(2)T_(X),with high conductivity and negatively charged surface terminations,also serves as an effective defect passivation agent,reducing trap-assisted recombination,while simultaneously facilitating charge extraction and transport by optimizing interfacial energy alignment.As a result,the Ti_(3)C_(2)T_(X)-modified PSC achieve a champion PCE of 25.13%and exhibit outstanding thermal stability,retaining 80%of the initial PCE after 500 h of thermal aging at 85 and 30±5%relative humidity.(In contrast,control PSC retain only 58%after 200 h.)Moreover,under continuous maximum power point tracking in N2 atmosphere,Ti_(3)C_(2)T_(X)-modified PSC retained 70%of the initial PCE after 500 h,whereas the control PSC drop sharply to 20%.These findings highlight the synergistic role of Ti_(3)C_(2)T_(X) in thermal management and optoelectronic performance,paving the way for the development of high-efficiency and heat-resistant perovskite photovoltaics.展开更多
Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods...Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.展开更多
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
As an emerging thermal management strategy,dynamic radiative cooling(DRC)technology enables dynamic modulation of spectral radiation properties under varying environmental conditions through the directional design of ...As an emerging thermal management strategy,dynamic radiative cooling(DRC)technology enables dynamic modulation of spectral radiation properties under varying environmental conditions through the directional design of material spectral characteristics.However,a comprehensive review of the basic physical mechanisms of radiative heat transfer in DRC materials and various design principles involved in dynamic radiative thermal regulation is still lacking.This review systematically summarizes recent advances in this field,spanning from fundamental physical principles to intrinsic molecular and electronic mechanisms,and further to representative material systems and multi-band regulation strategies,highlighting the interdisciplinary research achievements and technological innovations.This work outlines the core mechanisms governing the regulation of different spectral bands during radiative heat transfer processes.Then,the main categories of DRC materials are systematically reviewed,including actively responsive structures,passively responsive structures,and multi-stimuli-responsive materials.Furthermore,the challenges faced by current DRC technology and future development trends are summarized and discussed,providing valuable reference and guidance for further research in this field.Although DRC technologies still face significant challenges in material stability,manufacturing processes,and system integration,the continuous advances in related areas and multifunctional materials are expected to broaden the application prospects of DRC in the future.展开更多
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
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
Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is es...Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is essential for fire management and designing land restoration programs in arid and semi-arid ecosystems.This study provided a new approach to evaluate the flammability of shrublands and woodlands using flammability indices(FIs)including time to ignition(TI),duration of combustion(DC),and flame height(FH)of plant species and their relative frequencies in the Dalfard Basin of southeastern Iran.The results showed that there was a significant difference in FIs between land covers.Shrublands had higher flammability potential compared with woodlands.Plant moisture content had a negative relationship with TI(P<0.010)and no significant relationship with DC and FH(P>0.050).Artemisia spp.,Astragalus gossypinus Fischer,Amygdalus scoparia Spach,and Cymbopogon jwarancusa(Jones)Schult.had the highest FI.Tree species such as Rhazya stricta Decne.,and Pistacia atlantica Desf.showed greater resistance to fire.Using principal component analysis,the relationship between species and FIs was examined,and TI of wet fuel was the most important FI in relation to species.Structural equation model showed that life form(P<0.001)was the most important flammability driver.Precipitation(P<0.010)and legume species(P<0.010)were significantly related to the flammability in arid land.This study emphasizes the importance of managing high-risk species and using resistant species in vegetation restoration and shows that combining species FIs with their abundance is an effective tool for assessing fire risk and fuel management at the plant community scale.展开更多
With the intensification of population aging in China,the problem of cognitive impairment in the elderly has become increasingly prominent,attracting widespread attention from all sectors of society.Geriatric cognitiv...With the intensification of population aging in China,the problem of cognitive impairment in the elderly has become increasingly prominent,attracting widespread attention from all sectors of society.Geriatric cognitive impairment is characterized by chronicity,which not only seriously threatens the health of the elderly and reduces their quality of life,but also imposes a heavy burden on families and society due to its long course.Attaching importance to and strengthening the chronic disease management of elderly cognitive impairment has profound significance for delaying disease progression,improving patients’quality of life,and reducing the burden of family care.Therefore,this paper first comprehensively understands elderly cognitive impairment by briefly elaborating on its definition and characteristics;on this basis,it focuses on exploring effective strategies for the chronic disease management of elderly cognitive impairment,hoping to provide new ideas and methods for the management of this condition and offer useful references for relevant clinical research and practice.展开更多
The environmental wind tunnel of high-speed railway trains serves as a crucial experimental facility for the research and development of high-speed railway technology.The refrigeration system within the wind tunnel is...The environmental wind tunnel of high-speed railway trains serves as a crucial experimental facility for the research and development of high-speed railway technology.The refrigeration system within the wind tunnel is an important subsystem.However,the design of the wind tunnel refrigeration system management program presents significant scientific challenges and limitations.Traditional management approaches in wind tunnel refrigeration systems suffer from prolonged decision-making times and reliance on experiential knowledge,necessitating the need for intelligent transformation.This paper aims to address these issues by exploring existing intelligent management methodologies and defining the concept of a wind tunnel intelligent laboratory along with its primary modules.Furthermore,we propose a water cooler failure prediction model based on the existing equipment model of the wind tunnel's refrigeration system.This model effectively predicts the Remaining Useful Life(RUL) of the water cooler in the case of fouling failure,contributing to enhanced efficiency,cost reduction,and safety improvements in laboratories.展开更多
Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods a...Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.展开更多
The China-Laos Railway(CLR),connecting two nations,has created a new paradigm for international cooperation on border management.On September 4,2025,China and Laos signed an intergovernmental agreement on"juxtapo...The China-Laos Railway(CLR),connecting two nations,has created a new paradigm for international cooperation on border management.On September 4,2025,China and Laos signed an intergovernmental agreement on"juxtaposed border control"arrangements for the CLR,the first such agreement between China and a neighboring country.展开更多
Lassa fever(LF)is an acute viral hemorrhagic illness caused by the Lassa virus(LASV),an enveloped,spherical virus belonging to the Arenaviridae family.LASV possess a single-stranded RNA genome of negative polarity and...Lassa fever(LF)is an acute viral hemorrhagic illness caused by the Lassa virus(LASV),an enveloped,spherical virus belonging to the Arenaviridae family.LASV possess a single-stranded RNA genome of negative polarity and exhibits high genetic diversity,corresponding to the geographical distribution of its seven principal distinct clades across West Africa[1].LASV was first isolated in 1969 from an American missionary nurse stationed in the rural town of Lassa,Borno State,Nigeria,following her return from a brief vacation in the United States[2].展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to ...The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to more than 30% of the world's population,predominantly in developing countries where per capita farmland and food supply are only 40% of those in developed nations(FAO 2018).Meeting the Zero Hunger target amid ongoing population growth in these regions requires a substantial increase in agricultural production while minimizing soil degradation and adverse ecological impacts.This challenge is shared by many countries across South Asia,Africa,and Central and South America.展开更多
Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu prov...Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu province,a national leader in both economic and agricultural development,as a case area to construct a multidimensional framework for assessing the recessive morphological characteristics of multifunctional cultivated land use.We examine temporal dynamics,spatial heterogeneity,and propose an integrated zoning strategy based on empirical analysis.The results reveal that:(1)The recessive morphology index shows a consistent upward trend,with structural breaks in 2007 and 2013,and a spatial shift from“higher in the east and lower in the west”to“higher in the south and lower in the north.”(2)Coordination among sub-dimensions of the index has steadily improved.(3)The index is expected to continue rising in the next decade,though at a slower pace.(4)To promote coordinated multidimensional land-use development,we recommend a policy framework that reinforces existing strengths,addresses weaknesses,and adapts zoning schemes to current spatial conditions.This research offers new insights into multifunctional cultivated land systems and underscores their role in enhancing human well-being,securing food supply,and supporting sustainable urban-rural integration.展开更多
基金supported by the Natural Science Foundation of Jiangsu Province(BK20231445)Aeronautical Science Foundation of China(20230028052001).
文摘The proton exchange membrane fuel cell(PEMFC)and the hydrogen hybrid power system are studied by the fuzzy-PID(FPID)controlmethod and the fuzzy-PID controlmethod by Artificial Bee Colony algorithm(ABCFPID),respectively.The results reveal that compared with the FPID control method,the temperature overshoot of the PEMFC stack under the ABC-FPID control method is decreased by 0.6%.Moreover,the circulating water flow rate within the full operating envelope(about 3 min)is reduced by 19.46 L,which means the ABC-FPID control method is more effective in regulating the stack temperature.Then,the ABC-FPID control method is proposed to study the hydrogen hybrid power system,and the system output power matching,operating characteristic curve of the fuel cell,state of charge(SOC)of the lithium battery,system efficiency and hydrogen demand are obtained.The results indicate that the maximum system efficiency reaches 46.3%,the average system efficiency is 33.8%,and the average hydrogen demand is 0.192 kg/s.Overall,the ABC-FPID control method can efficiently ensure the stability of the fuel cell’s output power,and actively prompt the lithium battery to fulfill the function of“peak shaving and valley filling”under variable load power conditions.
基金National Natural Science Foundation of China(Grant No.U2243225)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB40000000)+2 种基金the Natural Science Basic Research Program of Shaanxi(Grant No.Z2024-ZYFS-0065)the Funding of Top Young talents of Ten Thousand talents Plan in China(2021)the Fundamental Research Funds for the Central Universities(Grants No.2452023071 and 2023HHZX002).
文摘Understanding the complex interactions between human activities and ecosystem functions is a prerequisite for achieving sustainable development.Since the implementation of the“Grain for Green”Project in 1999,ecosystem functions in China’s Loess Plateau have significantly improved.However,intensified human activities have also exacerbated the pressures on the region’s fragile ecological environment.This study investigates the spatiotemporal variations in the human activity intensity index(HAI)and net ecosystem benefits(NEB)from 2000 to 2020,using expert-based assessments and an enhanced cost-benefit evaluation framework.Results indicate that HAI increased by 16.7% and 16.6% at the grid and county levels,respectively.NEB exhibited pronounced spatial heterogeneity,with a total increase of USD 36.2 trillion at the grid scale.At the county level,the average NEB rose by 75%.The degree of trade-off was higher at the grid scale than at the county scale,while the synergistic areas initially expanded and then declined at both scales.Key areas for improvement and regions of lagging development were identified as priority zones for ecological management and spatial planning at both spatial resolutions.This study offers scientific insights and practical guidance for harmonizing ecological conservation with high-quality development in ecologically vulnerable regions.
文摘Objective:To investigate the application effect of intelligent empowerment standardized airway management process in patients receiving mechanical ventilation.Methods:A retrospective analysis was conducted on the clinical data of 79 EICU inpatients who underwent tracheal intubation and mechanical ventilation treatment at our hospital from January 2023 to May 2025.The patients were divided into a control group(conventional airway management process,n=40)and a study group(intelligent empowerment standardized airway management process,n=39)based on the intervention protocols they received.Oral health scores,dental plaque index,oral odor,serum inflammatory markers[C-reactive protein(CRP),procalcitonin(PCT)],clinical pulmonary infection score(CPIS),as well as the incidence of ventilator-associated pneumonia(VAP),duration of mechanical ventilation,and length of stay in the EICU were assessed before and after treatment.Results:The baseline values of all indicators were consistent between the two groups before intervention(p>0.05).After corresponding interventions,both groups showed significant improvements in Beck oral health scores,dental plaque index,and oral odor,with more pronounced improvements observed in the study group(p<0.05).After the intervention,the research group showed a significant decrease in serum CRP and PCT levels,as well as CPIS scores(p<0.05).In contrast,the control group experienced an increase in these three indicators to a certain extent(p<0.05).Moreover,the incidence of ventilator-associated pneumonia(VAP),duration of mechanical ventilation,and length of stay in the EICU were all lower in the research group compared to the control group,while the nurse’s compliance rate with the protocol was higher in the research group(p<0.05).Conclusion:The standardized airway management protocol empowered by intelligent technology can significantly improve nursing compliance,benefit oral health status,reduce the risk of pulmonary infection and systemic inflammation levels,and promote rapid patient recovery,demonstrating considerable potential for widespread adoption.
基金supported by the grants No.82370912 from the National Natural Science Foundation of ChinaNo.2022020801010499 from the Bureau of Science and Technology of Wuhan,ChinaNo.2042023kf0231 from the Fundamental Research Funds for the Central Universities,China。
文摘Tooth developmental anomalies are a group of disorders caused by unfavorable factors affecting the tooth development process,resulting in abnormalities in tooth number,structure,and morphology.These anomalies typically manifest during childhood,impairing dental function,maxillofacial development,and facial aesthetics,while also potentially impacting overall physical and mental health.The complex etiology and diverse clinical phenotypes of these anomalies pose significant challenges for prevention,early diagnosis,and treatment.As they usually emerge early in life,long-term management and multidisciplinary collaboration in dental care are essential.However,there is currently a lack of systematic clinical guidelines for the diagnosis and treatment of these conditions,adding to the difficulties in clinical practice.In response to this need,this expert consensus summarizes the classifications,etiology,typical clinical manifestations,and diagnostic criteria of tooth developmental anomalies based on current clinical evidence.It also provides prevention strategies and stage-specific clinical management recommendations to guide clinicians in diagnosis and treatment,promoting early intervention and standardized care for these anomalies.
基金supported by National Natural Science Foundation of China(32494793).
文摘Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fundamental trade-off between haze and transparency,coupled with impractical thicknesses(≥1 mm).Inspired by squid’s skin-peeling mechanism,this work develops a peroxyformic acid(HCOOOH)-enabled precision peeling strategy to isolate intact 10-μm-thick bamboo green(BG)frameworks—100×thinner than wood-based counterparts while achieving an unprecedented optical performance(88%haze with 80%transparency).This performance surpasses delignified biomass(transparency<40%at 1 mm)and matches engineered cellulose composites,yet requires no energy-intensive nanofibrillation.The preserved native cellulose I crystalline structure(64.76%crystallinity)and wax-coated uniaxial fibril alignment(Hermans factor:0.23)contribute to high mechanical strength(903 MPa modulus)and broadband light scattering.As a light-management layer in polycrystalline silicon solar cells,the BG framework boosts photoelectric conversion efficiency by 0.41%absolute(18.74%→19.15%),outperforming synthetic anti-reflective coatings.The work establishes a scalable,waste-to-wealth route for optical-grade cellulose materials in next-generation optoelectronics.
基金the National Natural Science Foundation of China(Nos.62374029,22175029,62474033,and W2433038)the Young Elite Scientists Sponsorship Program by CAST(No.YESS20220550)+2 种基金the Sichuan Science and Technology Program(No.2024NSFSC0250)the Natural Science Foundation of Shenzhen Innovation Committee(JCYJ20210324135614040)the Fundamental Research Funds for the Central Universities of China(No.ZYGX2022J032).
文摘Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bottleneck,severely affecting device stability and long-term operational performance.Herein,we present a multifunctional strategy by incorporating highly thermally conductive Ti_(3)C_(2)T_(X) MXene nanosheets into the perovskite layer to simultaneously enhance thermal management and optoelectronic properties.The Ti_(3)C_(2)T_(X) nanosheets,embedded at perovskite grain boundaries,construct efficient thermal conduction pathways,significantly improving the thermal conductivity and diffusivity of the film.This leads to a notable reduction in the device’s steady-state operating temperature from 42.96 to 39.97 under 100 mW cm^(−2) illumination,thereby alleviating heat-induced performance degradation.Beyond thermal regulation,Ti_(3)C_(2)T_(X),with high conductivity and negatively charged surface terminations,also serves as an effective defect passivation agent,reducing trap-assisted recombination,while simultaneously facilitating charge extraction and transport by optimizing interfacial energy alignment.As a result,the Ti_(3)C_(2)T_(X)-modified PSC achieve a champion PCE of 25.13%and exhibit outstanding thermal stability,retaining 80%of the initial PCE after 500 h of thermal aging at 85 and 30±5%relative humidity.(In contrast,control PSC retain only 58%after 200 h.)Moreover,under continuous maximum power point tracking in N2 atmosphere,Ti_(3)C_(2)T_(X)-modified PSC retained 70%of the initial PCE after 500 h,whereas the control PSC drop sharply to 20%.These findings highlight the synergistic role of Ti_(3)C_(2)T_(X) in thermal management and optoelectronic performance,paving the way for the development of high-efficiency and heat-resistant perovskite photovoltaics.
基金supported by the project“Romanian Hub for Artificial Intelligence-HRIA”,Smart Growth,Digitization and Financial Instruments Program,2021–2027,MySMIS No.334906.
文摘Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.
基金supported by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
基金supported by the Taishan Scholars of Shandong Province(tsqn202408151)the National Natural Science Foundation of China(Grant Nos.52476067,52306078,and 52576053).
文摘As an emerging thermal management strategy,dynamic radiative cooling(DRC)technology enables dynamic modulation of spectral radiation properties under varying environmental conditions through the directional design of material spectral characteristics.However,a comprehensive review of the basic physical mechanisms of radiative heat transfer in DRC materials and various design principles involved in dynamic radiative thermal regulation is still lacking.This review systematically summarizes recent advances in this field,spanning from fundamental physical principles to intrinsic molecular and electronic mechanisms,and further to representative material systems and multi-band regulation strategies,highlighting the interdisciplinary research achievements and technological innovations.This work outlines the core mechanisms governing the regulation of different spectral bands during radiative heat transfer processes.Then,the main categories of DRC materials are systematically reviewed,including actively responsive structures,passively responsive structures,and multi-stimuli-responsive materials.Furthermore,the challenges faced by current DRC technology and future development trends are summarized and discussed,providing valuable reference and guidance for further research in this field.Although DRC technologies still face significant challenges in material stability,manufacturing processes,and system integration,the continuous advances in related areas and multifunctional materials are expected to broaden the application prospects of DRC in the future.
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.
基金supported by the National Natural Science Foundation of China(W2412135)the Youth Innovation Promotion Association of the Chinese Academy of Sciences.
文摘As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.
文摘Arid and semi-arid ecosystems are prone to extensive fires due to specific climatic conditions,sparse vegetation cover,and high density of fine fuels.Understanding the flammability characteristics of land covers is essential for fire management and designing land restoration programs in arid and semi-arid ecosystems.This study provided a new approach to evaluate the flammability of shrublands and woodlands using flammability indices(FIs)including time to ignition(TI),duration of combustion(DC),and flame height(FH)of plant species and their relative frequencies in the Dalfard Basin of southeastern Iran.The results showed that there was a significant difference in FIs between land covers.Shrublands had higher flammability potential compared with woodlands.Plant moisture content had a negative relationship with TI(P<0.010)and no significant relationship with DC and FH(P>0.050).Artemisia spp.,Astragalus gossypinus Fischer,Amygdalus scoparia Spach,and Cymbopogon jwarancusa(Jones)Schult.had the highest FI.Tree species such as Rhazya stricta Decne.,and Pistacia atlantica Desf.showed greater resistance to fire.Using principal component analysis,the relationship between species and FIs was examined,and TI of wet fuel was the most important FI in relation to species.Structural equation model showed that life form(P<0.001)was the most important flammability driver.Precipitation(P<0.010)and legume species(P<0.010)were significantly related to the flammability in arid land.This study emphasizes the importance of managing high-risk species and using resistant species in vegetation restoration and shows that combining species FIs with their abundance is an effective tool for assessing fire risk and fuel management at the plant community scale.
文摘With the intensification of population aging in China,the problem of cognitive impairment in the elderly has become increasingly prominent,attracting widespread attention from all sectors of society.Geriatric cognitive impairment is characterized by chronicity,which not only seriously threatens the health of the elderly and reduces their quality of life,but also imposes a heavy burden on families and society due to its long course.Attaching importance to and strengthening the chronic disease management of elderly cognitive impairment has profound significance for delaying disease progression,improving patients’quality of life,and reducing the burden of family care.Therefore,this paper first comprehensively understands elderly cognitive impairment by briefly elaborating on its definition and characteristics;on this basis,it focuses on exploring effective strategies for the chronic disease management of elderly cognitive impairment,hoping to provide new ideas and methods for the management of this condition and offer useful references for relevant clinical research and practice.
文摘The environmental wind tunnel of high-speed railway trains serves as a crucial experimental facility for the research and development of high-speed railway technology.The refrigeration system within the wind tunnel is an important subsystem.However,the design of the wind tunnel refrigeration system management program presents significant scientific challenges and limitations.Traditional management approaches in wind tunnel refrigeration systems suffer from prolonged decision-making times and reliance on experiential knowledge,necessitating the need for intelligent transformation.This paper aims to address these issues by exploring existing intelligent management methodologies and defining the concept of a wind tunnel intelligent laboratory along with its primary modules.Furthermore,we propose a water cooler failure prediction model based on the existing equipment model of the wind tunnel's refrigeration system.This model effectively predicts the Remaining Useful Life(RUL) of the water cooler in the case of fouling failure,contributing to enhanced efficiency,cost reduction,and safety improvements in laboratories.
文摘Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.
文摘The China-Laos Railway(CLR),connecting two nations,has created a new paradigm for international cooperation on border management.On September 4,2025,China and Laos signed an intergovernmental agreement on"juxtaposed border control"arrangements for the CLR,the first such agreement between China and a neighboring country.
文摘Lassa fever(LF)is an acute viral hemorrhagic illness caused by the Lassa virus(LASV),an enveloped,spherical virus belonging to the Arenaviridae family.LASV possess a single-stranded RNA genome of negative polarity and exhibits high genetic diversity,corresponding to the geographical distribution of its seven principal distinct clades across West Africa[1].LASV was first isolated in 1969 from an American missionary nurse stationed in the rural town of Lassa,Borno State,Nigeria,following her return from a brief vacation in the United States[2].
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
文摘The United Nations Sustainable Development Goal(SDG) 2 aims to achieve Zero Hunger by 2030.However,global hunger and food insecurity have continued to rise at an alarming rate(UN 2023).Subtropical regions are home to more than 30% of the world's population,predominantly in developing countries where per capita farmland and food supply are only 40% of those in developed nations(FAO 2018).Meeting the Zero Hunger target amid ongoing population growth in these regions requires a substantial increase in agricultural production while minimizing soil degradation and adverse ecological impacts.This challenge is shared by many countries across South Asia,Africa,and Central and South America.
基金National Natural Science Foundation of China,No.42101252。
文摘Rapid regional population shifts and spatial polarization have heightened pressure on cultivated land—a critical resource demanding urgent attention amid ongoing urban-rural transition.This study selects Jiangsu province,a national leader in both economic and agricultural development,as a case area to construct a multidimensional framework for assessing the recessive morphological characteristics of multifunctional cultivated land use.We examine temporal dynamics,spatial heterogeneity,and propose an integrated zoning strategy based on empirical analysis.The results reveal that:(1)The recessive morphology index shows a consistent upward trend,with structural breaks in 2007 and 2013,and a spatial shift from“higher in the east and lower in the west”to“higher in the south and lower in the north.”(2)Coordination among sub-dimensions of the index has steadily improved.(3)The index is expected to continue rising in the next decade,though at a slower pace.(4)To promote coordinated multidimensional land-use development,we recommend a policy framework that reinforces existing strengths,addresses weaknesses,and adapts zoning schemes to current spatial conditions.This research offers new insights into multifunctional cultivated land systems and underscores their role in enhancing human well-being,securing food supply,and supporting sustainable urban-rural integration.
