Heavy metal(HM)contamination severely impacts global agricultural production.HMs toxicity effectively damaged the physiological functions such as imbalanced redox homeostasis,altered antioxidant enzyme activity,damage...Heavy metal(HM)contamination severely impacts global agricultural production.HMs toxicity effectively damaged the physiological functions such as imbalanced redox homeostasis,altered antioxidant enzyme activity,damage root system architecture,hindered photosynthetic apparatus,cellular toxicity,restricted mineral accumulation,and changed the metabolite production.Using phytohormones may be a successful strategy for enhancing and stimulating plant tolerance to HMs toxicity without affecting the environment.Melatonin(MT),a novel plant growth regulator,and powerful antioxidant molecule,enhances plant resilience to HMs stress by enhancing seedling growth,protecting the photosynthetic system,increasing nutritional status,balanced redox homeostasis,and restricting HMs accumulation from root to shoot.In addition,MT enhances the activity of antioxidant enzymes and triggers the ascorbate-glutathione(AsA-GSH)cycle,which helps remove excessive ROS.MT improves RuBisCO activity to improve photosynthesis and reduce the breakdown of chlorophyll.To identify future research needs,it is crucial to understand the comprehensive and intricate regulatory mechanisms of exogenous and endogenous MT-mediated reduction of heavy metal toxicity in plants.Melatonin has several functions,and this review sheds light on those functions and the molecular processes by which it alleviates HMs toxicity.More research is needed to fully understand how melatonin affects plant tolerance to heavy metals stress.展开更多
Shandong Port Group(SPG),which was established in August 2019,regards standardization as the cornerstone of modern enterprise management,and vigorously implements the standardization innovation strategy.Its standardiz...Shandong Port Group(SPG),which was established in August 2019,regards standardization as the cornerstone of modern enterprise management,and vigorously implements the standardization innovation strategy.Its standardization work mainly focuses on the following four aspects.展开更多
The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefit...The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefits over conventional methods of removing contaminants.Despite the numerous benefits of this technique,it has certain limitations that can be addressed by incorporating nanoparticles to improve its effectiveness.This review paper aims to explore the impact of heavy metal pollution on plants and human health.It highlights the role and mechanism of nanoparticles in enhancing phytoremediation,their application in the detection of heavy metals,and the strategies for the safe disposal of phytoremediation biomass.Biosynthesized nanoparticles are eco-friendly and non-toxic,with applications in biomedical and environmental fields.Nanoparticles can be used in the form of nano biosensors like smartphone-operated wireless sensors made from Cinnamomum camphora,enabling efficient detection of heavy metal ions.According to the studies,nanoparticles remove 80%–97%of heavy metals by various methods like reduction,precipitation,adsorption,etc.The phytoremediation biomass disposal can be done by heat treatment,phytomining,and microbial treatment with some modifications to further enhance their results.Phytoremediation is an environmentally friendly technique but requires further research and integration with biomass energy production to overcome scalability challenges and ensure safe biomass disposal.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
As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a no...As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.展开更多
The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.H...The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.展开更多
While desalination is a key solution for global freshwater scarcity,its implementation faces environmental challenges due to concentrated brine byproducts mainly disposed of via coastal discharge systems.Solar interfa...While desalination is a key solution for global freshwater scarcity,its implementation faces environmental challenges due to concentrated brine byproducts mainly disposed of via coastal discharge systems.Solar interfacial evaporation offers sustainable management potential,yet inevitable salt nucleation at evaporation interfaces degrades photothermal conversion and operational stability via light scattering and pathway blockage.Inspired by the mangrove leaf,we propose a photothermal 3D polydopamine and polypyrrole polymerized spacer fabric(PPSF)-based upward hanging model evaporation configuration with a reverse water feeding mechanism.This design enables zero-liquiddischarge(ZLD)desalination through phase-separation crystallization.The interconnected porous architecture and the rough surface of the PPSF enable superior water transport,achieving excellent solar-absorbing efficiency of 97.8%.By adjusting the tilt angle(θ),the evaporator separates the evaporation and salt crystallization zones via controlled capillary-driven brine transport,minimizing heat dissipation from brine discharge.At an optimal tilt angle of 52°,the evaporator reaches an evaporation rate of 2.81 kg m^(−2) h^(−1) with minimal heat loss(0.366 W)under 1-sun illumination while treating a 7 wt%waste brine solution.Furthermore,it sustains an evaporation rate of 2.71 kg m^(−2) h^(−1) over 72 h while ensuring efficient salt recovery.These results highlight a scalable,energy-efficient approach for sustainable ZLD desalination.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
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
To address the deficiencies in comprehensive surface contamination prevention strategies within China's nitrate-affected regions,this research innovatively proposes the DITAPH model-a systematic framework integrat...To address the deficiencies in comprehensive surface contamination prevention strategies within China's nitrate-affected regions,this research innovatively proposes the DITAPH model-a systematic framework integrating groundwater nitrate vulnerability assessment and Nitrate Vulnerable Zones(NVZs)delineation through optimization of hydrogeological parameters.Based on detailed hydrogeological and hydrochemical investigations,the DITAPH model was applied in the plain areas of Quanzhou to evaluate its applicability.The model selected hydrogeological parameters(depth of groundwater,lithology of the vadose zone,topographic slope,aquifer water yield property),one climatic parameter(precipitation),and two anthropogenic parameters(land use type and population density)as assessment indicators.The results of the groundwater nitrate vulnerability assessment showed that the low,relatively low,relatively high,and high groundwater nitrate vulnerability zones in the study area accounted for 5.96%,35.44%,53.74%and 4.86%of the total area,respectively.Groundwater nitrate vulnerability was most strongly influenced by human activities,followed by groundwater depth and topographic slope.The high vulnerability zone is mainly affected by domestic and industrial wastewater,whereas the relatively high groundwater nitrate vulnerability zone is primarily influenced by agricultural activities.Validation of the DITAPH model revealed a significant positive correlation between the DITAPH index(DI)and nitrate concentration(ρ(NO3−)).The results of the NVZs delineated by the DITAPH model are reliable and can serve as a tool for water resource management planning,guiding the development of targeted measures in the NVZs to prevent groundwater contamination.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
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
The Arno River Basin(Central Italy)is affected by a considerable anthropogenic pressure due to the presence of large cities and widespread industrial and agricultural practices.In this work,26 water samples from the A...The Arno River Basin(Central Italy)is affected by a considerable anthropogenic pressure due to the presence of large cities and widespread industrial and agricultural practices.In this work,26 water samples from the Arno River and its main tributaries were analyzed to assess the water pollution status.The geochemical composition of the Arno River changes from the source(dominated by a Ca-HCO_(3) facies)to the mouth(where a Na-Cl(SO4)chemistry prevails)with an increasing quality deterioration,as suggested by the Chemical Water Quality Index,due to anthropogenic contributions and seawater intrusion before flowing into the Ligurian Sea.The Ombrone and Usciana tributaries introduce anthropogenic pollutants into the Arno River,whilst Elsa tributary supplies significant contents of geogenic sulfate.The concentrations of dissolved nitrate and nitrite(up to 63 and 9 mg/L,respectively)and the respective isotopic values of𝛿15N and𝛿18O were also determined to understand origin and fate of the N-species in the Arno River Basin surface waters.The combined application of𝛿15N-NO_(3) and𝛿18O-NO_(3) and N-source apportionment modelling allowed the identification of soil organic nitrogen and sewage and domestic wastes as primary sources for dissolved NO_(3)-.The𝛿15N-NO_(2) and𝛿18O-NO_(2) values suggest that the nitrification process affects the ARB waters,thus controlling the abundances and proportion of the N-species.Our work indicates that additional efforts are needed to improve management strategies to reduce the release of nitrogenated species to the surface waters of the Arno River Basin,since little progress has been made from the early 2000s.展开更多
BACKGROUND Humeral shaft fractures are common and vary by age,with high-energy trauma observed in younger adults and low-impact injuries in older adults.Radial nerve palsy is a frequent complication.Treatment ranges f...BACKGROUND Humeral shaft fractures are common and vary by age,with high-energy trauma observed in younger adults and low-impact injuries in older adults.Radial nerve palsy is a frequent complication.Treatment ranges from nonoperative methods to surgical interventions such as intramedullary K-wires,which promote faster rehabilitation and improved elbow mobility.AIM To evaluate the outcomes of managing humeral shaft fractures using closed reduction and internal fixation with flexible intramedullary K-wires.METHODS This was a retrospective cohort study analyzing the medical records of patients with humeral shaft fractures managed with flexible intramedullary K-wires at King Abdulaziz Medical City,using non-random sampling and descriptive analysis for outcome evaluation.RESULTS This study assessed the clinical outcomes of 20 patients treated for humeral shaft fractures with intramedullary K-wires.Patients were predominantly male(n=16,80%),had an average age of 39.2 years,and a mean body mass index of 29.5 kg/m^(2).The fractures most frequently occurred in the middle third of the humerus(n=14,70%),with oblique fractures being the most common type(n=7,35%).All surgeries used general anesthesia and a posterior approach,with no intraoperative complications reported.Postoperatively,all patients achieved clinical and radiological union(n=20,100%),and the majority(n=13,65%)reached an elbow range of motion from 0 to 150 degrees.CONCLUSION These results suggest that intramedullary K-wire fixation may be an effective option for treating humeral shaft fractures,with favorable outcomes in range of motion recovery,fracture union,and a low rate of intraoperative complications.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
Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to miti...Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to mitigate the freshwater,energy and food crises.However,the performance of solar-driven systems decreases significantly during operation due to uncontrollable weather.This study proposes an integrated water/electricity cogeneration-cultivation system with superior thermal management.The energy storage evaporator,consisting of energy storage microcapsules/hydrogel composites,is optimally designed for sustainable desalination,achieving an evaporation rate of around 1.91 kg m^(-2)h^(-1).In the dark,heat released from the phase-change layer supported an evaporation rate of around 0.54kg m^(-2)h^(-1).Reverse electrodialysis harnessed the salinity-gradient energy enhanced during desalination,enabling the long-running WEC system to achieve a power output of~0.3 W m^(-2),which was almost three times higher than that of conventional seawater/surface water mixing.Additionally,an integrated crop irrigation platform utilized system drainage for real-time,on-demand wheat cultivation without secondary contaminants,facilitating seamless WEF integration.This work presents a novel approach to all-day solar water production,electricity generation and crop irrigation,offering a solution and blueprint for the sustainable development of WEF.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
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
Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency devia...Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency deviations,voltage fluctuations,and poor reactive power coordination,posing serious challenges to grid stability.Conventional Interconnection FlowControllers(IFCs)primarily regulate active power flowand fail to effectively handle dynamic frequency variations or reactive power sharing in multi-microgrid networks.To overcome these limitations,this study proposes an enhanced Interconnection Flow Controller(e-IFC)that integrates frequency response balancing and an Interconnection Reactive Power Flow Controller(IRFC)within a unified adaptive control structure.The proposed e-IFC is implemented and analyzed in DIgSILENT PowerFactory to evaluate its performance under various grid disturbances,including frequency drops,load changes,and reactive power fluctuations.Simulation results reveal that the e-IFC achieves 27.4% higher active power sharing accuracy,19.6% lower reactive power deviation,and 18.2% improved frequency stability compared to the conventional IFC.The adaptive controller ensures seamless transitions between grid-connected and islanded modes and maintains stable operation even under communication delays and data noise.Overall,the proposed e-IFCsignificantly enhances active-reactive power coordination and dynamic stability in renewable-integrated multi-microgrid systems.Future research will focus on coupling the e-IFC with tertiary-level optimization frameworks and conducting hardware-in-the-loop validation to enable its application in large-scale smart microgrid environments.展开更多
文摘Heavy metal(HM)contamination severely impacts global agricultural production.HMs toxicity effectively damaged the physiological functions such as imbalanced redox homeostasis,altered antioxidant enzyme activity,damage root system architecture,hindered photosynthetic apparatus,cellular toxicity,restricted mineral accumulation,and changed the metabolite production.Using phytohormones may be a successful strategy for enhancing and stimulating plant tolerance to HMs toxicity without affecting the environment.Melatonin(MT),a novel plant growth regulator,and powerful antioxidant molecule,enhances plant resilience to HMs stress by enhancing seedling growth,protecting the photosynthetic system,increasing nutritional status,balanced redox homeostasis,and restricting HMs accumulation from root to shoot.In addition,MT enhances the activity of antioxidant enzymes and triggers the ascorbate-glutathione(AsA-GSH)cycle,which helps remove excessive ROS.MT improves RuBisCO activity to improve photosynthesis and reduce the breakdown of chlorophyll.To identify future research needs,it is crucial to understand the comprehensive and intricate regulatory mechanisms of exogenous and endogenous MT-mediated reduction of heavy metal toxicity in plants.Melatonin has several functions,and this review sheds light on those functions and the molecular processes by which it alleviates HMs toxicity.More research is needed to fully understand how melatonin affects plant tolerance to heavy metals stress.
文摘Shandong Port Group(SPG),which was established in August 2019,regards standardization as the cornerstone of modern enterprise management,and vigorously implements the standardization innovation strategy.Its standardization work mainly focuses on the following four aspects.
文摘The surge in environmental pollution in recent years driven by numerous pollutants has necessitated the search for efficient removal methods.Phytoremediation is an eco-friendly technique that provides multiple benefits over conventional methods of removing contaminants.Despite the numerous benefits of this technique,it has certain limitations that can be addressed by incorporating nanoparticles to improve its effectiveness.This review paper aims to explore the impact of heavy metal pollution on plants and human health.It highlights the role and mechanism of nanoparticles in enhancing phytoremediation,their application in the detection of heavy metals,and the strategies for the safe disposal of phytoremediation biomass.Biosynthesized nanoparticles are eco-friendly and non-toxic,with applications in biomedical and environmental fields.Nanoparticles can be used in the form of nano biosensors like smartphone-operated wireless sensors made from Cinnamomum camphora,enabling efficient detection of heavy metal ions.According to the studies,nanoparticles remove 80%–97%of heavy metals by various methods like reduction,precipitation,adsorption,etc.The phytoremediation biomass disposal can be done by heat treatment,phytomining,and microbial treatment with some modifications to further enhance their results.Phytoremediation is an environmentally friendly technique but requires further research and integration with biomass energy production to overcome scalability challenges and ensure safe biomass disposal.
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funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB BremenThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP2/367/46)+1 种基金This research is supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.
基金supported by the National Key Research and Development Program of China under Grant 2022YFB2901501in part by the Science and Technology Innovation leading Talents Subsidy Project of Central Plains under Grant 244200510038.
文摘The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.
基金supported by National Key Research and Development Program of China(2022YFB3804902,2022YFB3804900)the National Natural Science Foundation of China(52203226,52161145406,42376045)the Fundamental Research Funds for the Central Universities(2232024Y-01,2232025D-02).
文摘While desalination is a key solution for global freshwater scarcity,its implementation faces environmental challenges due to concentrated brine byproducts mainly disposed of via coastal discharge systems.Solar interfacial evaporation offers sustainable management potential,yet inevitable salt nucleation at evaporation interfaces degrades photothermal conversion and operational stability via light scattering and pathway blockage.Inspired by the mangrove leaf,we propose a photothermal 3D polydopamine and polypyrrole polymerized spacer fabric(PPSF)-based upward hanging model evaporation configuration with a reverse water feeding mechanism.This design enables zero-liquiddischarge(ZLD)desalination through phase-separation crystallization.The interconnected porous architecture and the rough surface of the PPSF enable superior water transport,achieving excellent solar-absorbing efficiency of 97.8%.By adjusting the tilt angle(θ),the evaporator separates the evaporation and salt crystallization zones via controlled capillary-driven brine transport,minimizing heat dissipation from brine discharge.At an optimal tilt angle of 52°,the evaporator reaches an evaporation rate of 2.81 kg m^(−2) h^(−1) with minimal heat loss(0.366 W)under 1-sun illumination while treating a 7 wt%waste brine solution.Furthermore,it sustains an evaporation rate of 2.71 kg m^(−2) h^(−1) over 72 h while ensuring efficient salt recovery.These results highlight a scalable,energy-efficient approach for sustainable ZLD desalination.
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 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.
基金supported by the National Key Research and Development Program of China(No.2022YFF1301301)the Natural Science Foundation of Xiamen Municipality(No.3502Z202472047)the Geological Survey Program of China Geological Survey(DD20190303).
文摘To address the deficiencies in comprehensive surface contamination prevention strategies within China's nitrate-affected regions,this research innovatively proposes the DITAPH model-a systematic framework integrating groundwater nitrate vulnerability assessment and Nitrate Vulnerable Zones(NVZs)delineation through optimization of hydrogeological parameters.Based on detailed hydrogeological and hydrochemical investigations,the DITAPH model was applied in the plain areas of Quanzhou to evaluate its applicability.The model selected hydrogeological parameters(depth of groundwater,lithology of the vadose zone,topographic slope,aquifer water yield property),one climatic parameter(precipitation),and two anthropogenic parameters(land use type and population density)as assessment indicators.The results of the groundwater nitrate vulnerability assessment showed that the low,relatively low,relatively high,and high groundwater nitrate vulnerability zones in the study area accounted for 5.96%,35.44%,53.74%and 4.86%of the total area,respectively.Groundwater nitrate vulnerability was most strongly influenced by human activities,followed by groundwater depth and topographic slope.The high vulnerability zone is mainly affected by domestic and industrial wastewater,whereas the relatively high groundwater nitrate vulnerability zone is primarily influenced by agricultural activities.Validation of the DITAPH model revealed a significant positive correlation between the DITAPH index(DI)and nitrate concentration(ρ(NO3−)).The results of the NVZs delineated by the DITAPH model are reliable and can serve as a tool for water resource management planning,guiding the development of targeted measures in the NVZs to prevent groundwater contamination.
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.
文摘The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.
文摘The Arno River Basin(Central Italy)is affected by a considerable anthropogenic pressure due to the presence of large cities and widespread industrial and agricultural practices.In this work,26 water samples from the Arno River and its main tributaries were analyzed to assess the water pollution status.The geochemical composition of the Arno River changes from the source(dominated by a Ca-HCO_(3) facies)to the mouth(where a Na-Cl(SO4)chemistry prevails)with an increasing quality deterioration,as suggested by the Chemical Water Quality Index,due to anthropogenic contributions and seawater intrusion before flowing into the Ligurian Sea.The Ombrone and Usciana tributaries introduce anthropogenic pollutants into the Arno River,whilst Elsa tributary supplies significant contents of geogenic sulfate.The concentrations of dissolved nitrate and nitrite(up to 63 and 9 mg/L,respectively)and the respective isotopic values of𝛿15N and𝛿18O were also determined to understand origin and fate of the N-species in the Arno River Basin surface waters.The combined application of𝛿15N-NO_(3) and𝛿18O-NO_(3) and N-source apportionment modelling allowed the identification of soil organic nitrogen and sewage and domestic wastes as primary sources for dissolved NO_(3)-.The𝛿15N-NO_(2) and𝛿18O-NO_(2) values suggest that the nitrification process affects the ARB waters,thus controlling the abundances and proportion of the N-species.Our work indicates that additional efforts are needed to improve management strategies to reduce the release of nitrogenated species to the surface waters of the Arno River Basin,since little progress has been made from the early 2000s.
基金approved by King Abdullah International Medical Research Center Ethics Committee(approval No.0000074524).
文摘BACKGROUND Humeral shaft fractures are common and vary by age,with high-energy trauma observed in younger adults and low-impact injuries in older adults.Radial nerve palsy is a frequent complication.Treatment ranges from nonoperative methods to surgical interventions such as intramedullary K-wires,which promote faster rehabilitation and improved elbow mobility.AIM To evaluate the outcomes of managing humeral shaft fractures using closed reduction and internal fixation with flexible intramedullary K-wires.METHODS This was a retrospective cohort study analyzing the medical records of patients with humeral shaft fractures managed with flexible intramedullary K-wires at King Abdulaziz Medical City,using non-random sampling and descriptive analysis for outcome evaluation.RESULTS This study assessed the clinical outcomes of 20 patients treated for humeral shaft fractures with intramedullary K-wires.Patients were predominantly male(n=16,80%),had an average age of 39.2 years,and a mean body mass index of 29.5 kg/m^(2).The fractures most frequently occurred in the middle third of the humerus(n=14,70%),with oblique fractures being the most common type(n=7,35%).All surgeries used general anesthesia and a posterior approach,with no intraoperative complications reported.Postoperatively,all patients achieved clinical and radiological union(n=20,100%),and the majority(n=13,65%)reached an elbow range of motion from 0 to 150 degrees.CONCLUSION These results suggest that intramedullary K-wire fixation may be an effective option for treating humeral shaft fractures,with favorable outcomes in range of motion recovery,fracture union,and a low rate of intraoperative complications.
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.
基金supported by the National Natural Science Foundation of China(No.52070057)China Postdoctoral Science Foundation(No.2023M730855)Heilongjiang Postdoctoral Fund(No.LBH-Z22183)for financial support。
文摘Sustainable water,energy and food(WEF)supplies are the bedrock upon which human society depends.Solar-driven interfacial evaporation,combined with electricity generation and cultivation,is a promising approach to mitigate the freshwater,energy and food crises.However,the performance of solar-driven systems decreases significantly during operation due to uncontrollable weather.This study proposes an integrated water/electricity cogeneration-cultivation system with superior thermal management.The energy storage evaporator,consisting of energy storage microcapsules/hydrogel composites,is optimally designed for sustainable desalination,achieving an evaporation rate of around 1.91 kg m^(-2)h^(-1).In the dark,heat released from the phase-change layer supported an evaporation rate of around 0.54kg m^(-2)h^(-1).Reverse electrodialysis harnessed the salinity-gradient energy enhanced during desalination,enabling the long-running WEC system to achieve a power output of~0.3 W m^(-2),which was almost three times higher than that of conventional seawater/surface water mixing.Additionally,an integrated crop irrigation platform utilized system drainage for real-time,on-demand wheat cultivation without secondary contaminants,facilitating seamless WEF integration.This work presents a novel approach to all-day solar water production,electricity generation and crop irrigation,offering a solution and blueprint for the sustainable development of WEF.
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.
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 Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia,for funding this research work through the project number“NBU-FFR-2025-3623-11”.
文摘Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization.However,the high penetration of intermittent renewable sources often causes frequency deviations,voltage fluctuations,and poor reactive power coordination,posing serious challenges to grid stability.Conventional Interconnection FlowControllers(IFCs)primarily regulate active power flowand fail to effectively handle dynamic frequency variations or reactive power sharing in multi-microgrid networks.To overcome these limitations,this study proposes an enhanced Interconnection Flow Controller(e-IFC)that integrates frequency response balancing and an Interconnection Reactive Power Flow Controller(IRFC)within a unified adaptive control structure.The proposed e-IFC is implemented and analyzed in DIgSILENT PowerFactory to evaluate its performance under various grid disturbances,including frequency drops,load changes,and reactive power fluctuations.Simulation results reveal that the e-IFC achieves 27.4% higher active power sharing accuracy,19.6% lower reactive power deviation,and 18.2% improved frequency stability compared to the conventional IFC.The adaptive controller ensures seamless transitions between grid-connected and islanded modes and maintains stable operation even under communication delays and data noise.Overall,the proposed e-IFCsignificantly enhances active-reactive power coordination and dynamic stability in renewable-integrated multi-microgrid systems.Future research will focus on coupling the e-IFC with tertiary-level optimization frameworks and conducting hardware-in-the-loop validation to enable its application in large-scale smart microgrid environments.
