Since language is a tool for communication,proficiency in English communication is a fundamental necessity for talent in the 21st century.However,surveys reveal that most college students at private colleges possess i...Since language is a tool for communication,proficiency in English communication is a fundamental necessity for talent in the 21st century.However,surveys reveal that most college students at private colleges possess inadequate oral English skills,and what some have learned is“mute English.”Therefore,developing their English-speaking skills is another challenge faced by students attending private schools.Online diagnostic assessment methods are growing globally with the use of technology.UDig diagnostic assessment system is one of the online English diagnostic assessment platforms currently being widely used in China.Therefore,the present work is conducted to investigate and conduct an oral English learning-oriented assessment model in college English using the online diagnostic assessment.With the research result,it is hoped that the study could provide useful information for improving UDig system and make a better use of it in college oral English learning and teaching.展开更多
Excessive levels of Fluoride(F−)and Cadmium(Cd)in drinking groundwater may pose health risks.This study assessed the health risks associated with F−and Cd contamination in rural drinking groundwater sources in Wutai C...Excessive levels of Fluoride(F−)and Cadmium(Cd)in drinking groundwater may pose health risks.This study assessed the health risks associated with F−and Cd contamination in rural drinking groundwater sources in Wutai County,Shanxi Province,China,to support population health protection,water resource management,and environmental decision-making.Groundwater samples were collected and analyzed,and a Human Health Risk Model(HHRA)was applied to evaluate groundwater quality.The results showed that both contents of F−and Cd in groundwater exceeded the Class III limits of China's national groundwater quality standard(GB/T 14848—2024).Fluoride levels met the Class V threshold,with enrichment area mainly located in the east part of the study area.Cadmium levels reached Class IV,with elevated concentrations primarily observed in the western and northwestern regions.Correlation analysis revealed that F−showed weak or no correlation with other measured substances,indicating independent sources.Health risk assessment results indicated that F−poses potential health risks to rural residents,while cadmium,due to its relatively low concentrations,does not currently present a significant health risk.Among different demographic groups,the health risk levels of F−exposure followed the order:Infants>children>adult females>adult males.The findings highlight that fluoride is the primary contributor to health risks associated with groundwater consumption in the study area.Strengthened monitoring and prevention of F−contamination are urgently needed.This research provides a scientific basis for the prevention and control of fluoride pollution in groundwater and offers practical guidance for safeguarding drinking water safety in rural China.展开更多
Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly deve...Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly develops and deployment increases,these impacts are becoming increasingly evident.A comprehensive understanding of these impacts is crucial for sustainable development.Based on the harmonization of previous detailed life cycle assessment(LCA)studies,this study develops a simplified LCA model that estimates the life cycle environmental impacts of wind turbines based on their nominal power.Using this simplified LCA model,we assess the global warming potential(GWP),acidification potential(AP),and cumulative energy demand(CED)of wind power at the regional scale for 2022 and under three future scenarios(high-power wind turbine promotion,reduced wind curtailment,and a comprehensive development scenario).The results indicate that in 2022,the life cycle GWP,AP,and CED of wind power in western China were 10.76 g CO_(2) eq/kWh,0.177 g SO_(2) eq/kWh,and 17.6 kJ/kWh,respectively.Scenario simulations suggest that reducing wind curtailment is the most effective approach for reducing emissions in Inner Mongolia,Gansu,Qinghai,Ningxia,and Xinjiang,producing average decreases of 8.64%in GWP,8.39%in AP,and 9.26%in CED.In contrast,for Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Xizang,and Shaanxi,the promotion of high-power wind turbines provides greater environmental benefits than reducing curtailment,producing average decreases of 3.45%,3.09%,and 4.29%in GWP,AP,and CED,respectively.These findings help clarify the environmental impact of wind power across its life cycle at the regional scale and provide theoretical references for the direction of future wind power development and the formulation of related policies.展开更多
Plants constitute nearly 80%of the planet’s total biomass(Bar-On et al.,2018);however,this vital group is experiencing severe threats,and recent evaluations indicate that approximately 45%of the world's described...Plants constitute nearly 80%of the planet’s total biomass(Bar-On et al.,2018);however,this vital group is experiencing severe threats,and recent evaluations indicate that approximately 45%of the world's described plant species are at risk of extinction(Bachman et al.,2024).The number of plant extinctions has increased by 60%in the last 100 years(Di Marco et al.,2017).Over the past 250 years,571 plant species have gone extinct—more than twice the combined total of extinct birds,mammals,and amphibians(217 species)(Briggs,2019).展开更多
Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general contr...Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general control zones—are established based on the ecological red line,the lower-limit line for environmental quality,and the resource use line.Human activities are regulated through a permit system.Integrated and multifactorial protection of soil,plant,hydrological,and atmospheric elements is promoted at the regional level.A follow-up assessment contributes to the improvement of policy implementation and effectiveness.This study demonstrates the achievements of the TLOP policy in Sichuan Province.Results show that(1)276 protection zones have been established under the ecological red line,covering key ecosystems and protected areas to ensure environmental security.Under the lower-limit line,1,626 functional(priority,key,and general control)zones have been designated to regulate air,water,and soil quality,enhancing environmental capacity and pollution control.(2)Through the integration and merging of the three lines,1,128 integrated management zones have been established,including 375,625,and 128 priority protection,critical control,and general control zones,respectively.Each zone has its own list of environmental permits to regulate human activities according to different environmental protection and natural resource development regimes.(3)The design of the follow-up assessment index system was informed by regional primary functions and industrial structure.The index system for provinces and cities is structured around three primary indicators—implementation updating,application,and guarantees—and 15 secondary indicators.The system for critical control zones is structured around environmental access,management,and effectiveness and 14 secondary indicators.A stringent environmental zoning system has been established through the TLOP policy,thereby safeguarding environmental security,promoting harmonious existence between humans and nature,and supporting the vision of Beautiful China.展开更多
Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although la...Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although land cover information has long been recognized as an essential component for monitoring SDGs,a standardized scientific framework for identifying and prioritizing land cover related essential variables does not exist.Therefore,we propose a novel expert-and data-driven framework for identifying,refining,and selecting a priority list of Essential Land cover-related Variables for SDGs(ELcV4SDGs).This framework integrates methods including expert knowledge-based analysis,clustering of variables with similar attributes,and quantified index calculation to establish the priority list.Applying the framework to 15 specific SDG indicators,we found that the ELcV4SDGs priority list comprises three main categories,type and structure,pattern and intensity,and process and evolution of land cover,which are further divided into 19 subcategories and ultimately encompass 50 general variables.The ELcV4SDGs will support detailed spatial monitoring and enhance their scientific applications for SDG monitoring and assessment,thereby guiding future SDG priority actions and informing decision-making to advance the 2030 SDGs agenda at local,national,and global levels.展开更多
Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogen...Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.展开更多
Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article ha...Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.展开更多
This study developed a modeling methodology for statistical optimization-based geologic hazard susceptibility assessment,aiming to enhance the comprehensive performance and classification accuracy of the assessment mo...This study developed a modeling methodology for statistical optimization-based geologic hazard susceptibility assessment,aiming to enhance the comprehensive performance and classification accuracy of the assessment models.First,the cumulative probability method revealed that a low probability(15%)of geologic hazards between any two geologic hazard points occurred outside a buffer zone with a radius of 2297 m(i.e.,the distance threshold).The training dataset was established,consisting of negative samples(non-hazard points)randomly generated based on the distance threshold,positive samples(i.e.,historical hazards),and 13 conditioning factors.Then,models were built using five machine learning algorithms,namely random forest(RF),gradient boosting decision tree(GBDT),naive Bayes(NB),logistic regression(LR),and support vector machine(SVM).The comprehensive performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and overall accuracy(OA)as indicators,revealing that RF exhibited the best performance,with OA and AUC values of 2.7127 and 0.981,respectively.Furthermore,the machine learning models constructed by considering the distance threshold outperformed those built using the unoptimized dataset.The characteristic factors were ranked using the mutual information method,with their scores decreasing in the order of rainfall(0.1616),altitude(0.06),normalized difference vegetation index(NDVI;0.04),and distance from roads(0.03).Finally,the geologic hazard susceptibility classification was assessed using the natural breaks method combined with a clustering algorithm.The results indicate that the clustering algorithm exhibited higher classification accuracy than the natural breaks method.The findings of this study demonstrate that the proposed model optimization scheme can provide a scientific basis for the prevention and control of geologic hazards.展开更多
For mission-oriented unmanned aerial vehicle(UAV)swarms,mission capability assessment provides an important reference in the design and development process,and is a precondition for mission success.For this multi-crit...For mission-oriented unmanned aerial vehicle(UAV)swarms,mission capability assessment provides an important reference in the design and development process,and is a precondition for mission success.For this multi-criteria decisionmaking(MCDM)problem,the current literature lacks a way to unambiguously present criteria and the popular fuzzy analytic network process(ANP)approaches neglect the hesitancy of subjective judgments.To fill these research gaps,an MCDM method based on unified architecture framework(UAF)and interval-valued spherical fuzzy ANP(IVSF-ANP)is proposed in this paper.Firstly,selected viewpoints in UAF are extended to construct criteria models with standardized representation.Secondly,interval-valued spherical fuzzy sets are introduced to ANP to weight interdependent criteria,handling fuzziness and hesitancy in pairwise comparisons.A method of adjusting weights of experts based on their decision similarities is also included in this process to reduce ambiguity brought by multiple experts.Next,performance characteristics are non-linearly transformed regarding to expectations to get final results.This proposition is applied to assess the mission capability of UAV swarms to search and strike surface vessels.Comparative analysis shows that the proposed method is valid and reasonable.展开更多
Controlling heavy metal pollution in agricultural soil has been a significant challenge.These heavy metals seriously threaten the surrounding ecological environment and human health.The effective assessment and remedi...Controlling heavy metal pollution in agricultural soil has been a significant challenge.These heavy metals seriously threaten the surrounding ecological environment and human health.The effective assessment and remediation of heavy metals in agricultural soils are crucial.These two aspects support each other,forming a close and complete decisionmaking chain.Therefore,this review systematically summarizes the distribution characteristics of soil heavy metal pollution,the correlation between soil and crop heavy metal contents,the presence pattern and migration and transformation mode of heavy metals in the soil-crop system.The advantages and disadvantages of the risk evaluation tools and models of heavy metal pollution in farmland are further outlined,which provides important guidance for an in-depth understanding of the characteristics of heavymetal pollution in farmland soils and the assessment of the environmental risk.Soil remediation strategies involve multiple physical,chemical,biological and even combined technologies,and this paper compares the potential and effect of the above current remediation technologies in heavy metal polluted farmland soils.Finally,the main problems and possible research directions of future heavy metal risk assessment and remediation technologies in agricultural soils are prospected.This review provides new ideas for effective assessment and selection of remediation technologies based on the characterization of soil heavy metals.展开更多
Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy densit...Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy density and electrochemical performance to enable it comparable to Li-ion batteries,without considering thermal hazard of Na-ion batteries and comparison with Li-ion batteries.To address this issue,our work comprehensively compares commercial prismatic lithium iron phosphate(LFP) battery,lithium nickel cobalt manganese oxide(NCM523) battery and Na-ion battery of the same size from thermal hazard perspective using Accelerating Rate Calorimeter.The thermal hazard of the three cells is then qualitatively assessed from thermal stability,early warning and thermal runaway severity perspectives by integrating eight characteristic parameters.The Na-ion cell displays comparable thermal stability with LFP while LFP exhibits the lowest thermal runaway hazard and severity.However,the Na-ion cell displays the lowest safety venting temperature and the longest time interval between safety venting and thermal runaway,allowing the generated gas to be released as early as possible and detected in a timely manner,providing sufficient time for early warning.Finally,a database of thermal runaway characteristic temperature for Li-ion and Na-ion cells is collected and processed to delineate four thermal hazard levels for quantitative assessment.Overall,LFP cells exhibit the lowest thermal hazard,followed by the Na-ion cells and NCM523 cells.This work clarifies the thermal hazard discrepancy between the Na-ion cell and prevalent Li-ion cells,providing crucial guidance for development and application of Na-ion cell.展开更多
Phthalate esters(PAEs),recognized as endocrine disruptors,are released into the environment during usage,thereby exerting adverse ecological effects.This study investigates the occurrence,sources,and risk assessment o...Phthalate esters(PAEs),recognized as endocrine disruptors,are released into the environment during usage,thereby exerting adverse ecological effects.This study investigates the occurrence,sources,and risk assessment of PAEs in surface water obtained from 36 sampling points within the Yellow River and Yangtze River basins.The total concentration of PAEs in the Yellow River spans from124.5 to 836.5 ng/L,with Dimethyl phthalate(DMP)(75.4±102.7 ng/L)and Diisobutyl phthalate(DiBP)(263.4±103.1 ng/L)emerging as the predominant types.Concentrations exhibit a pattern of upstream(512.9±202.1 ng/L)>midstream(344.5±135.3 ng/L)>downstream(177.8±46.7 ng/L).In the Yangtze River,the total concentration ranges from 81.9 to 441.6 ng/L,with DMP(46.1±23.4 ng/L),Diethyl phthalate(DEP)(93.3±45.2 ng/L),and DiBP(174.2±67.6 ng/L)as the primary components.Concentration levels follow a midstream(324.8±107.3 ng/L)>upstream(200.8±51.8 ng/L)>downstream(165.8±71.6 ng/L)pattern.Attention should be directed towards the moderate ecological risks of DiBP in the upstream of HH,and both the upstream and midstream of CJ need consideration for the moderate ecological risks associated with Di-n-octyl phthalate(DNOP).Conversely,in other regions,the associated risk with PAEs is either low or negligible.The main source of PAEs in Yellow River is attributed to the release of construction land,while in the Yangtze River Basin,it stems from the accumulation of pollutants in lakes and forests discharged into the river.These findings are instrumental for pinpointing sources of PAEs pollution and formulating control strategies in the Yellow and Yangtze Rivers,providing valuable insights for global PAEs research in other major rivers.展开更多
Understanding the levels,causes,and sources of fluoride in groundwater is critical for public health,effective water resource management,and sustainable utilization.This study employs multivariate statistical methods,...Understanding the levels,causes,and sources of fluoride in groundwater is critical for public health,effective water resource management,and sustainable utilization.This study employs multivariate statistical methods,hazard quotient assessment,and geochemical analyses,such as mineral saturation index,ionic activities,and Gibbs diagrams,to investigate the hydrochemical characteristics,causes,and noncarcinogenic risks of fluoride in Red bed groundwater and geothermal water in the Guang'an area and neighboring regions.Approximately 9%of the Red bed groundwater samples contain fluoride concentrations exceeding 1 mg·L^(-1).The predominant water types identified are Cl-Na and HCO_(3)-Na,primarily influenced by evapotranspiration.Low-fluoride groundwater and high-fluoride geothermal water exhibit distinct hydrochemical types HCO_(3)-Ca and SO_(4)-Ca,respectively,which are mainly related to the weathering of carbonate,sulfate,and fluorite-containing rocks.Correlation analysis reveals that fluoride content in Red bed groundwater is positively associated with Na^(+),Cl^(-),SO_(4)^(2-),and TDS(r^(2)=0.45-0.64,p<0.01),while in geothermal water,it correlates strongly with pH,K^(+),Ca^(2+),and Mg^(2+)(r^(2)=0.52-0.80,p<0.05).Mineral saturation indices and ionic activities indicate that ion exchange processes and the dissolution of minerals such as carbonatite and fluorite are important sources of fluoride in groundwater.The enrichment of fluorine in the Red bed groundwater is linked to evaporation,cation exchange and dissolution of fluorite,caused by the lithologic characteristics of the red bed in this area.However,it exhibits minimal correlation with the geothermal water in the adjacent area.The noncarcinogenic health risk assessment indicates that 7%(n=5)of Red bed groundwater points exceed the fluoride safety limit for adults,while 12%(n=8)exceed the limit for children.These findings underscore the importance of avoiding highly fluoridated red bed groundwater as a direct drinking source and enhancing groundwater monitoring to mitigate health risks associated with elevated fluoride levels.展开更多
Earthquakes pose significant perils to the built environment in urban areas.To avert the calamitous aftermath of earthquakes,it is imperative to construct seismic resilient cities.Due to the intricacy of the concept o...Earthquakes pose significant perils to the built environment in urban areas.To avert the calamitous aftermath of earthquakes,it is imperative to construct seismic resilient cities.Due to the intricacy of the concept of urban seismic resilience(USR),its assessment is a large-scale system engineering issue.The assessment of USR should be based on the notion of urban seismic capacity(USC)assessment,which includes casualties,economic loss,and recovery time as criteria.Functionality loss is also included in the assessment of USR in addition to these criteria.The assessment indicator system comprising five dimensions(building and lifeline infrastructure,environment,society,economy,and institution)and 20 indicators has been devised to quantify USR.The analytical hierarchy process(AHP)is utilized to compute the weights of the criteria,dimensions,and indicators in the urban seismic resilience assessment(USRA)indicator system.When the necessary data for a city are obtainable,the seismic resilience of that city can be assessed using this framework.To illustrate the proposed methodology,a moderate-sized city in China was selected as a case study.The assessment results indicate a high level of USR,suggesting that the city possesses strong capabilities to withstand and recover from potential future earthquakes.展开更多
Background There is scarce data about comparisons between geriatric assessment tools in patients with aortic stenosis(AS).We aimed to describe the geriatric profile of patients with AS undergoing transcatheter aortic ...Background There is scarce data about comparisons between geriatric assessment tools in patients with aortic stenosis(AS).We aimed to describe the geriatric profile of patients with AS undergoing transcatheter aortic valve implantation(TAVI)and to analyze the ability of different tools for predicting clinical outcomes in this context.Methods This was a single center retrospective registry including patients with AS undergoing TAVI and surviving to hospital discharge.The primary endpoint was all-cause mortality or need for urgent readmission one year after TAVI.Results A total of 377 patients were included(mean age of 80.4 years).Most patients were independent or mildly dependent,with an optimal cognitive status.The proportion of frailty ranged from 17.6%to 49.8%.A total of 20 patients(5.3%)died and 110/377 patients(29.2%)died or were readmitted during follow up.Overall,most components of the geriatric assessment showed an association with clinical outcomes.Disability for instrumental activities showed a significant association with mortality and a strong association with the rate of mortality or readmission.The association between frailty and clinical outcomes was higher for short physical performance battery(SPPB),essential frailty toolset(EFT)and the frailty index based on comprehensive geriatric assessment(IF-VIG)and lower for Fried criteria and FRAIL scale.Conclusions AS patients from this series presented a good physical performance,optimal cognitive status and a reasonably low prevalence of frailty.The best predictive ability was observed for disability for instrumental activities and frailty as measured by the EFT,SPPB and the IF-VIG.展开更多
To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforce...To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforcement learning with rule-based decision-making methods.A risk assessment model for lane-change maneuvers considering uncertain predictions of surrounding vehicles is established as a safety filter to improve learning efficiency while correcting dangerous actions for safety enhancement.On this basis,a Risk-fused DDQN is constructed utilizing the model-based risk assessment and supervision mechanism.The proposed reinforcement learning algorithm sets up a separate experience buffer for dangerous trials and punishes such actions,which is shown to improve the sampling efficiency and training outcomes.Compared with conventional DDQN methods,the proposed algorithm improves the convergence value of cumulated reward by 7.6%and 2.2%in the two constructed scenarios in the simulation study and reduces the number of training episodes by 52.2%and 66.8%respectively.The success rate of lane change is improved by 57.3%while the time headway is increased at least by 16.5%in real vehicle tests,which confirms the higher training efficiency,scenario adaptability,and security of the proposed Risk-fused DDQN.展开更多
The traditional transient stability assessment(TSA)model for power systems has three disadvantages:capturing critical information during faults is difficult,aperiodic and oscillatory unstable conditions are not distin...The traditional transient stability assessment(TSA)model for power systems has three disadvantages:capturing critical information during faults is difficult,aperiodic and oscillatory unstable conditions are not distinguished,and poor generalizability is exhibited by systems with high renewable energy penetration.To address these issues,a novel ResGRU architecture for TSA is proposed in this study.First,a residual neural network(ResNet)is used for deep feature extraction of transient information.Second,a bidirectional gated recurrent unit combined with a multi-attention mechanism(BiGRU-Attention)is used to establish temporal feature dependencies.Their combination constitutes a TSA framework based on the ResGRU architecture.This method predicts three transient conditions:oscillatory instability,aperiodic instability,and stability.The model was trained offline using stochastic gradient descent with a thermal restart(SGDR)optimization algorithm in the offline training phase.This significantly improves the generalizability of the model.Finally,simulation tests on IEEE 145-bus and 39-bus systems confirmed that the proposed method has higher adaptability,accuracy,scalability,and rapidity than the conventional TSA approach.The proposed model also has superior robustness for PMU incomplete configurations,PMU noisy data,and packet loss.展开更多
Due to their high mechanical compliance and excellent biocompatibility,conductive hydrogels exhibit significant potential for applications in flexible electronics.However,as the demand for high sensitivity,superior me...Due to their high mechanical compliance and excellent biocompatibility,conductive hydrogels exhibit significant potential for applications in flexible electronics.However,as the demand for high sensitivity,superior mechanical properties,and strong adhesion performance continues to grow,many conventional fabrication methods remain complex and costly.Herein,we propose a simple and efficient strategy to construct an entangled network hydrogel through a liquid-metal-induced cross-linking reaction,hydrogel demonstrates outstanding properties,including exceptional stretchability(1643%),high tensile strength(366.54 kPa),toughness(350.2 kJ m^(−3)),and relatively low mechanical hysteresis.The hydrogel exhibits long-term stable reusable adhesion(104 kPa),enabling conformal and stable adhesion to human skin.This capability allows it to effectively capture high-quality epidermal electrophysiological signals with high signal-to-noise ratio(25.2 dB)and low impedance(310 ohms).Furthermore,by integrating advanced machine learning algorithms,achieving an attention classification accuracy of 91.38%,which will significantly impact fields like education,healthcare,and artificial intelligence.展开更多
Hurricanes are one of the most destructive natural disasters that can cause catastrophic losses to both communities and infrastructure.Assessment of hurricane risk furnishes a spatial depiction of the interplay among ...Hurricanes are one of the most destructive natural disasters that can cause catastrophic losses to both communities and infrastructure.Assessment of hurricane risk furnishes a spatial depiction of the interplay among hazard,vulnerability,exposure,and mitigation capacity,crucial for understanding and managing the risks hurricanes pose to communities.These assessments aid in gauging the efficacy of existing hurricane mitigation strategies and gauging their resilience across diverse climate change scenarios.A systematic review was conducted,encompassing 94 articles,to scrutinize the structure,data inputs,assumptions,methodologies,perils modelled,and key predictors of hurricane risk.This review identified key research gaps essential for enhancing future risk assessments.The complex interaction between hurricane perils may be disastrous and underestimated in the majority of risk assessments which focus on a single peril,commonly storm surge and flood,resulting in inadequacies in disaster resilience planning.Most risk assessments were based on hurricane frequency rather than hurricane damage,which is more insightful for policymakers.Furthermore,considering secondary indirect impacts stemming from hurricanes,including real estate market and business interruption,could enrich economic impact assessments.Hurricane mitigation measures were the most under-utilised category of predictors leveraged in only 5%of studies.The top six predictive factors for hurricane risk were land use,slope,precipitation,elevation,population density,and soil texture/drainage.Another notable research gap identified was the potential of machine learning techniques in risk assessments,offering advantages over traditional MCDM and numerical models due to their ability to capture complex nonlinear relationships and adaptability to different study regions.Existing machine learning based risk assessments leverage random forest models(42%of studies)followed by neural network models(19%of studies),with further research required to investigate diverse machine learning algorithms such as ensemble models.A further research gap is model validation,in particular assessing transferability to a new study region.Additionally,harnessing simulated data and refining projections related to demographic and built environment dynamics can bolster the sophistication of climate change scenario assessments.By addressing these research gaps,hurricane risk assessments can furnish invaluable insights for national policymakers,facilitating the development of robust hurricane mitigation strategies and the construction of hurricane-resilient communities.To the authors’knowledge,this represents the first literature review specifically dedicated to quantitative hurricane risk assessments,encompassing a comparison of Multi-criteria Decision Making(MCDM),numerical models,and machine learning models.Ultimately,advancements in hurricane risk assessments and modelling stand poised to mitigate potential losses to communities and infrastructure both in the immediate and long-term future.展开更多
文摘Since language is a tool for communication,proficiency in English communication is a fundamental necessity for talent in the 21st century.However,surveys reveal that most college students at private colleges possess inadequate oral English skills,and what some have learned is“mute English.”Therefore,developing their English-speaking skills is another challenge faced by students attending private schools.Online diagnostic assessment methods are growing globally with the use of technology.UDig diagnostic assessment system is one of the online English diagnostic assessment platforms currently being widely used in China.Therefore,the present work is conducted to investigate and conduct an oral English learning-oriented assessment model in college English using the online diagnostic assessment.With the research result,it is hoped that the study could provide useful information for improving UDig system and make a better use of it in college oral English learning and teaching.
基金supported by the Northeast Geological Science and Technology Innovation Center of China Geological Survey(Grant NO.QCJJ2022-43)the Natural Resources Comprehensive Survey Project(Grant Nos.DD20230470,DD20230508)the National Groundwater Monitoring Network Operation and Maintenance Program(Grant No.DD20251300109).
文摘Excessive levels of Fluoride(F−)and Cadmium(Cd)in drinking groundwater may pose health risks.This study assessed the health risks associated with F−and Cd contamination in rural drinking groundwater sources in Wutai County,Shanxi Province,China,to support population health protection,water resource management,and environmental decision-making.Groundwater samples were collected and analyzed,and a Human Health Risk Model(HHRA)was applied to evaluate groundwater quality.The results showed that both contents of F−and Cd in groundwater exceeded the Class III limits of China's national groundwater quality standard(GB/T 14848—2024).Fluoride levels met the Class V threshold,with enrichment area mainly located in the east part of the study area.Cadmium levels reached Class IV,with elevated concentrations primarily observed in the western and northwestern regions.Correlation analysis revealed that F−showed weak or no correlation with other measured substances,indicating independent sources.Health risk assessment results indicated that F−poses potential health risks to rural residents,while cadmium,due to its relatively low concentrations,does not currently present a significant health risk.Among different demographic groups,the health risk levels of F−exposure followed the order:Infants>children>adult females>adult males.The findings highlight that fluoride is the primary contributor to health risks associated with groundwater consumption in the study area.Strengthened monitoring and prevention of F−contamination are urgently needed.This research provides a scientific basis for the prevention and control of fluoride pollution in groundwater and offers practical guidance for safeguarding drinking water safety in rural China.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF1303405).
文摘Compared with traditional energy sources,wind power has a lower environmental impact.However,emissions are still generated across the life cycle of wind turbines,from production to recycling.As wind power rapidly develops and deployment increases,these impacts are becoming increasingly evident.A comprehensive understanding of these impacts is crucial for sustainable development.Based on the harmonization of previous detailed life cycle assessment(LCA)studies,this study develops a simplified LCA model that estimates the life cycle environmental impacts of wind turbines based on their nominal power.Using this simplified LCA model,we assess the global warming potential(GWP),acidification potential(AP),and cumulative energy demand(CED)of wind power at the regional scale for 2022 and under three future scenarios(high-power wind turbine promotion,reduced wind curtailment,and a comprehensive development scenario).The results indicate that in 2022,the life cycle GWP,AP,and CED of wind power in western China were 10.76 g CO_(2) eq/kWh,0.177 g SO_(2) eq/kWh,and 17.6 kJ/kWh,respectively.Scenario simulations suggest that reducing wind curtailment is the most effective approach for reducing emissions in Inner Mongolia,Gansu,Qinghai,Ningxia,and Xinjiang,producing average decreases of 8.64%in GWP,8.39%in AP,and 9.26%in CED.In contrast,for Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Xizang,and Shaanxi,the promotion of high-power wind turbines provides greater environmental benefits than reducing curtailment,producing average decreases of 3.45%,3.09%,and 4.29%in GWP,AP,and CED,respectively.These findings help clarify the environmental impact of wind power across its life cycle at the regional scale and provide theoretical references for the direction of future wind power development and the formulation of related policies.
基金support of the ORG.one project of Oxford Nanopore Technologies(ONT),the Rufford Grants(45249-1)the Idea Wild Grants(Project ID-KJOSINDI0125-00)the Mohamed Bin Zyed Species Conservation(MBZ)(GEF Grant no-240535253)Funds in our efforts to conserve threatened trees in the Western Ghats Biodiversity Hotspot Forest regions.
文摘Plants constitute nearly 80%of the planet’s total biomass(Bar-On et al.,2018);however,this vital group is experiencing severe threats,and recent evaluations indicate that approximately 45%of the world's described plant species are at risk of extinction(Bachman et al.,2024).The number of plant extinctions has increased by 60%in the last 100 years(Di Marco et al.,2017).Over the past 250 years,571 plant species have gone extinct—more than twice the combined total of extinct birds,mammals,and amphibians(217 species)(Briggs,2019).
基金supported by the National Natural Science Foundation of China(grant numbers 42171085)and the National Key R&D Program of China(Grant No.2024YFF1307801,2024YFF1307804).
文摘Integrated environmental management is important for sustainable development.Under China’s“Three Lines One Permit”(TLOP)policy,three types of management zones—priority protection,critical control,and general control zones—are established based on the ecological red line,the lower-limit line for environmental quality,and the resource use line.Human activities are regulated through a permit system.Integrated and multifactorial protection of soil,plant,hydrological,and atmospheric elements is promoted at the regional level.A follow-up assessment contributes to the improvement of policy implementation and effectiveness.This study demonstrates the achievements of the TLOP policy in Sichuan Province.Results show that(1)276 protection zones have been established under the ecological red line,covering key ecosystems and protected areas to ensure environmental security.Under the lower-limit line,1,626 functional(priority,key,and general control)zones have been designated to regulate air,water,and soil quality,enhancing environmental capacity and pollution control.(2)Through the integration and merging of the three lines,1,128 integrated management zones have been established,including 375,625,and 128 priority protection,critical control,and general control zones,respectively.Each zone has its own list of environmental permits to regulate human activities according to different environmental protection and natural resource development regimes.(3)The design of the follow-up assessment index system was informed by regional primary functions and industrial structure.The index system for provinces and cities is structured around three primary indicators—implementation updating,application,and guarantees—and 15 secondary indicators.The system for critical control zones is structured around environmental access,management,and effectiveness and 14 secondary indicators.A stringent environmental zoning system has been established through the TLOP policy,thereby safeguarding environmental security,promoting harmonious existence between humans and nature,and supporting the vision of Beautiful China.
基金supported by the Key Program of National Natural Science Foundation of China(Grant No.41930650)Young Scientists Fund of the National Natural Science Foundation of China(Grant No.42301310).
文摘Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although land cover information has long been recognized as an essential component for monitoring SDGs,a standardized scientific framework for identifying and prioritizing land cover related essential variables does not exist.Therefore,we propose a novel expert-and data-driven framework for identifying,refining,and selecting a priority list of Essential Land cover-related Variables for SDGs(ELcV4SDGs).This framework integrates methods including expert knowledge-based analysis,clustering of variables with similar attributes,and quantified index calculation to establish the priority list.Applying the framework to 15 specific SDG indicators,we found that the ELcV4SDGs priority list comprises three main categories,type and structure,pattern and intensity,and process and evolution of land cover,which are further divided into 19 subcategories and ultimately encompass 50 general variables.The ELcV4SDGs will support detailed spatial monitoring and enhance their scientific applications for SDG monitoring and assessment,thereby guiding future SDG priority actions and informing decision-making to advance the 2030 SDGs agenda at local,national,and global levels.
基金supported by the National Natural Science Foundation of China (Nos.42422705,42207175,42177117 and 42577170)the Ningbo Youth Leading Talent Project (No.2024QL051)+1 种基金the Chinese Academy of Engineering Science and Technology Strategy Consulting Project (No.2025-XZ-57)the Central Government Funding Program for Guiding Local Science and Technology Development (No.2025ZY01028)。
文摘Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.
文摘Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.
基金supported by a project entitled Loess Plateau Region-Watershed-Slope Geological Hazard Multi-Scale Collaborative Intelligent Early Warning System of the National Key R&D Program of China(2022YFC3003404)a project of the Shaanxi Youth Science and Technology Star(2021KJXX-87)public welfare geological survey projects of Shaanxi Institute of Geologic Survey(20180301,201918,202103,and 202413)。
文摘This study developed a modeling methodology for statistical optimization-based geologic hazard susceptibility assessment,aiming to enhance the comprehensive performance and classification accuracy of the assessment models.First,the cumulative probability method revealed that a low probability(15%)of geologic hazards between any two geologic hazard points occurred outside a buffer zone with a radius of 2297 m(i.e.,the distance threshold).The training dataset was established,consisting of negative samples(non-hazard points)randomly generated based on the distance threshold,positive samples(i.e.,historical hazards),and 13 conditioning factors.Then,models were built using five machine learning algorithms,namely random forest(RF),gradient boosting decision tree(GBDT),naive Bayes(NB),logistic regression(LR),and support vector machine(SVM).The comprehensive performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and overall accuracy(OA)as indicators,revealing that RF exhibited the best performance,with OA and AUC values of 2.7127 and 0.981,respectively.Furthermore,the machine learning models constructed by considering the distance threshold outperformed those built using the unoptimized dataset.The characteristic factors were ranked using the mutual information method,with their scores decreasing in the order of rainfall(0.1616),altitude(0.06),normalized difference vegetation index(NDVI;0.04),and distance from roads(0.03).Finally,the geologic hazard susceptibility classification was assessed using the natural breaks method combined with a clustering algorithm.The results indicate that the clustering algorithm exhibited higher classification accuracy than the natural breaks method.The findings of this study demonstrate that the proposed model optimization scheme can provide a scientific basis for the prevention and control of geologic hazards.
基金supported by the National Natural Science Foundation of China(62073267,61903305)the Fundamental Research Funds for the Central Universities(HXGJXM202214)。
文摘For mission-oriented unmanned aerial vehicle(UAV)swarms,mission capability assessment provides an important reference in the design and development process,and is a precondition for mission success.For this multi-criteria decisionmaking(MCDM)problem,the current literature lacks a way to unambiguously present criteria and the popular fuzzy analytic network process(ANP)approaches neglect the hesitancy of subjective judgments.To fill these research gaps,an MCDM method based on unified architecture framework(UAF)and interval-valued spherical fuzzy ANP(IVSF-ANP)is proposed in this paper.Firstly,selected viewpoints in UAF are extended to construct criteria models with standardized representation.Secondly,interval-valued spherical fuzzy sets are introduced to ANP to weight interdependent criteria,handling fuzziness and hesitancy in pairwise comparisons.A method of adjusting weights of experts based on their decision similarities is also included in this process to reduce ambiguity brought by multiple experts.Next,performance characteristics are non-linearly transformed regarding to expectations to get final results.This proposition is applied to assess the mission capability of UAV swarms to search and strike surface vessels.Comparative analysis shows that the proposed method is valid and reasonable.
基金supported by the National Natural Science Foundation of China(Nos.52100184,and U22A20617).
文摘Controlling heavy metal pollution in agricultural soil has been a significant challenge.These heavy metals seriously threaten the surrounding ecological environment and human health.The effective assessment and remediation of heavy metals in agricultural soils are crucial.These two aspects support each other,forming a close and complete decisionmaking chain.Therefore,this review systematically summarizes the distribution characteristics of soil heavy metal pollution,the correlation between soil and crop heavy metal contents,the presence pattern and migration and transformation mode of heavy metals in the soil-crop system.The advantages and disadvantages of the risk evaluation tools and models of heavy metal pollution in farmland are further outlined,which provides important guidance for an in-depth understanding of the characteristics of heavymetal pollution in farmland soils and the assessment of the environmental risk.Soil remediation strategies involve multiple physical,chemical,biological and even combined technologies,and this paper compares the potential and effect of the above current remediation technologies in heavy metal polluted farmland soils.Finally,the main problems and possible research directions of future heavy metal risk assessment and remediation technologies in agricultural soils are prospected.This review provides new ideas for effective assessment and selection of remediation technologies based on the characterization of soil heavy metals.
基金supported by the National Key R&D Program of China(No.2022YFE0207400)supported by the Xiaomi Young Talents Programsupported by the Youth Innovation Promotion Association CAS(No.Y201768)。
文摘Na-ion batteries are considered a promising next-generation battery alternative to Li-ion batteries,due to the abundant Na resources and low cost.Most efforts focus on developing new materials to enhance energy density and electrochemical performance to enable it comparable to Li-ion batteries,without considering thermal hazard of Na-ion batteries and comparison with Li-ion batteries.To address this issue,our work comprehensively compares commercial prismatic lithium iron phosphate(LFP) battery,lithium nickel cobalt manganese oxide(NCM523) battery and Na-ion battery of the same size from thermal hazard perspective using Accelerating Rate Calorimeter.The thermal hazard of the three cells is then qualitatively assessed from thermal stability,early warning and thermal runaway severity perspectives by integrating eight characteristic parameters.The Na-ion cell displays comparable thermal stability with LFP while LFP exhibits the lowest thermal runaway hazard and severity.However,the Na-ion cell displays the lowest safety venting temperature and the longest time interval between safety venting and thermal runaway,allowing the generated gas to be released as early as possible and detected in a timely manner,providing sufficient time for early warning.Finally,a database of thermal runaway characteristic temperature for Li-ion and Na-ion cells is collected and processed to delineate four thermal hazard levels for quantitative assessment.Overall,LFP cells exhibit the lowest thermal hazard,followed by the Na-ion cells and NCM523 cells.This work clarifies the thermal hazard discrepancy between the Na-ion cell and prevalent Li-ion cells,providing crucial guidance for development and application of Na-ion cell.
基金supported by the Ministry of Science and Technology of China(Nos.2021YFC3200904 and 2022YFC3203705)the National Natural Science Foundation of China(Nos.52270012 and 52070184).
文摘Phthalate esters(PAEs),recognized as endocrine disruptors,are released into the environment during usage,thereby exerting adverse ecological effects.This study investigates the occurrence,sources,and risk assessment of PAEs in surface water obtained from 36 sampling points within the Yellow River and Yangtze River basins.The total concentration of PAEs in the Yellow River spans from124.5 to 836.5 ng/L,with Dimethyl phthalate(DMP)(75.4±102.7 ng/L)and Diisobutyl phthalate(DiBP)(263.4±103.1 ng/L)emerging as the predominant types.Concentrations exhibit a pattern of upstream(512.9±202.1 ng/L)>midstream(344.5±135.3 ng/L)>downstream(177.8±46.7 ng/L).In the Yangtze River,the total concentration ranges from 81.9 to 441.6 ng/L,with DMP(46.1±23.4 ng/L),Diethyl phthalate(DEP)(93.3±45.2 ng/L),and DiBP(174.2±67.6 ng/L)as the primary components.Concentration levels follow a midstream(324.8±107.3 ng/L)>upstream(200.8±51.8 ng/L)>downstream(165.8±71.6 ng/L)pattern.Attention should be directed towards the moderate ecological risks of DiBP in the upstream of HH,and both the upstream and midstream of CJ need consideration for the moderate ecological risks associated with Di-n-octyl phthalate(DNOP).Conversely,in other regions,the associated risk with PAEs is either low or negligible.The main source of PAEs in Yellow River is attributed to the release of construction land,while in the Yangtze River Basin,it stems from the accumulation of pollutants in lakes and forests discharged into the river.These findings are instrumental for pinpointing sources of PAEs pollution and formulating control strategies in the Yellow and Yangtze Rivers,providing valuable insights for global PAEs research in other major rivers.
基金supported by the China Geological Survey Project(Nos.DD20220864 and DD20243077).
文摘Understanding the levels,causes,and sources of fluoride in groundwater is critical for public health,effective water resource management,and sustainable utilization.This study employs multivariate statistical methods,hazard quotient assessment,and geochemical analyses,such as mineral saturation index,ionic activities,and Gibbs diagrams,to investigate the hydrochemical characteristics,causes,and noncarcinogenic risks of fluoride in Red bed groundwater and geothermal water in the Guang'an area and neighboring regions.Approximately 9%of the Red bed groundwater samples contain fluoride concentrations exceeding 1 mg·L^(-1).The predominant water types identified are Cl-Na and HCO_(3)-Na,primarily influenced by evapotranspiration.Low-fluoride groundwater and high-fluoride geothermal water exhibit distinct hydrochemical types HCO_(3)-Ca and SO_(4)-Ca,respectively,which are mainly related to the weathering of carbonate,sulfate,and fluorite-containing rocks.Correlation analysis reveals that fluoride content in Red bed groundwater is positively associated with Na^(+),Cl^(-),SO_(4)^(2-),and TDS(r^(2)=0.45-0.64,p<0.01),while in geothermal water,it correlates strongly with pH,K^(+),Ca^(2+),and Mg^(2+)(r^(2)=0.52-0.80,p<0.05).Mineral saturation indices and ionic activities indicate that ion exchange processes and the dissolution of minerals such as carbonatite and fluorite are important sources of fluoride in groundwater.The enrichment of fluorine in the Red bed groundwater is linked to evaporation,cation exchange and dissolution of fluorite,caused by the lithologic characteristics of the red bed in this area.However,it exhibits minimal correlation with the geothermal water in the adjacent area.The noncarcinogenic health risk assessment indicates that 7%(n=5)of Red bed groundwater points exceed the fluoride safety limit for adults,while 12%(n=8)exceed the limit for children.These findings underscore the importance of avoiding highly fluoridated red bed groundwater as a direct drinking source and enhancing groundwater monitoring to mitigate health risks associated with elevated fluoride levels.
基金supported by the National Key R&D Program of China(No.2023YFC3805100)the National Natural Science Foundation of China(Nos.52222811 and 52494963)。
文摘Earthquakes pose significant perils to the built environment in urban areas.To avert the calamitous aftermath of earthquakes,it is imperative to construct seismic resilient cities.Due to the intricacy of the concept of urban seismic resilience(USR),its assessment is a large-scale system engineering issue.The assessment of USR should be based on the notion of urban seismic capacity(USC)assessment,which includes casualties,economic loss,and recovery time as criteria.Functionality loss is also included in the assessment of USR in addition to these criteria.The assessment indicator system comprising five dimensions(building and lifeline infrastructure,environment,society,economy,and institution)and 20 indicators has been devised to quantify USR.The analytical hierarchy process(AHP)is utilized to compute the weights of the criteria,dimensions,and indicators in the urban seismic resilience assessment(USRA)indicator system.When the necessary data for a city are obtainable,the seismic resilience of that city can be assessed using this framework.To illustrate the proposed methodology,a moderate-sized city in China was selected as a case study.The assessment results indicate a high level of USR,suggesting that the city possesses strong capabilities to withstand and recover from potential future earthquakes.
文摘Background There is scarce data about comparisons between geriatric assessment tools in patients with aortic stenosis(AS).We aimed to describe the geriatric profile of patients with AS undergoing transcatheter aortic valve implantation(TAVI)and to analyze the ability of different tools for predicting clinical outcomes in this context.Methods This was a single center retrospective registry including patients with AS undergoing TAVI and surviving to hospital discharge.The primary endpoint was all-cause mortality or need for urgent readmission one year after TAVI.Results A total of 377 patients were included(mean age of 80.4 years).Most patients were independent or mildly dependent,with an optimal cognitive status.The proportion of frailty ranged from 17.6%to 49.8%.A total of 20 patients(5.3%)died and 110/377 patients(29.2%)died or were readmitted during follow up.Overall,most components of the geriatric assessment showed an association with clinical outcomes.Disability for instrumental activities showed a significant association with mortality and a strong association with the rate of mortality or readmission.The association between frailty and clinical outcomes was higher for short physical performance battery(SPPB),essential frailty toolset(EFT)and the frailty index based on comprehensive geriatric assessment(IF-VIG)and lower for Fried criteria and FRAIL scale.Conclusions AS patients from this series presented a good physical performance,optimal cognitive status and a reasonably low prevalence of frailty.The best predictive ability was observed for disability for instrumental activities and frailty as measured by the EFT,SPPB and the IF-VIG.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFE0117100)National Science Foundation of China(Grant No.52102468,52325212)Fundamental Research Funds for the Central Universities。
文摘To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforcement learning with rule-based decision-making methods.A risk assessment model for lane-change maneuvers considering uncertain predictions of surrounding vehicles is established as a safety filter to improve learning efficiency while correcting dangerous actions for safety enhancement.On this basis,a Risk-fused DDQN is constructed utilizing the model-based risk assessment and supervision mechanism.The proposed reinforcement learning algorithm sets up a separate experience buffer for dangerous trials and punishes such actions,which is shown to improve the sampling efficiency and training outcomes.Compared with conventional DDQN methods,the proposed algorithm improves the convergence value of cumulated reward by 7.6%and 2.2%in the two constructed scenarios in the simulation study and reduces the number of training episodes by 52.2%and 66.8%respectively.The success rate of lane change is improved by 57.3%while the time headway is increased at least by 16.5%in real vehicle tests,which confirms the higher training efficiency,scenario adaptability,and security of the proposed Risk-fused DDQN.
基金financially supported by State Key Laboratory of HVDC No.SKLHVDC-2023-KF-03.
文摘The traditional transient stability assessment(TSA)model for power systems has three disadvantages:capturing critical information during faults is difficult,aperiodic and oscillatory unstable conditions are not distinguished,and poor generalizability is exhibited by systems with high renewable energy penetration.To address these issues,a novel ResGRU architecture for TSA is proposed in this study.First,a residual neural network(ResNet)is used for deep feature extraction of transient information.Second,a bidirectional gated recurrent unit combined with a multi-attention mechanism(BiGRU-Attention)is used to establish temporal feature dependencies.Their combination constitutes a TSA framework based on the ResGRU architecture.This method predicts three transient conditions:oscillatory instability,aperiodic instability,and stability.The model was trained offline using stochastic gradient descent with a thermal restart(SGDR)optimization algorithm in the offline training phase.This significantly improves the generalizability of the model.Finally,simulation tests on IEEE 145-bus and 39-bus systems confirmed that the proposed method has higher adaptability,accuracy,scalability,and rapidity than the conventional TSA approach.The proposed model also has superior robustness for PMU incomplete configurations,PMU noisy data,and packet loss.
基金supported by the National Key Research&Development Program of China(grant no.2022YFC3500503)the National Natural Science Foundation of China(grant nos.62227807,12374171,12004034,62402041)+2 种基金the Beijing Institute of Technology Research Fund Program for Young Scholars,Chinathe Fundamental Research Funds for the Central Universities(grant nos.2024CX06060)Beijing Youth Talent Lifting Project.
文摘Due to their high mechanical compliance and excellent biocompatibility,conductive hydrogels exhibit significant potential for applications in flexible electronics.However,as the demand for high sensitivity,superior mechanical properties,and strong adhesion performance continues to grow,many conventional fabrication methods remain complex and costly.Herein,we propose a simple and efficient strategy to construct an entangled network hydrogel through a liquid-metal-induced cross-linking reaction,hydrogel demonstrates outstanding properties,including exceptional stretchability(1643%),high tensile strength(366.54 kPa),toughness(350.2 kJ m^(−3)),and relatively low mechanical hysteresis.The hydrogel exhibits long-term stable reusable adhesion(104 kPa),enabling conformal and stable adhesion to human skin.This capability allows it to effectively capture high-quality epidermal electrophysiological signals with high signal-to-noise ratio(25.2 dB)and low impedance(310 ohms).Furthermore,by integrating advanced machine learning algorithms,achieving an attention classification accuracy of 91.38%,which will significantly impact fields like education,healthcare,and artificial intelligence.
基金supported by the Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS),University of Technology Sydney(UTS),Australia and was supported by the Research Training Program(RTP)of the Australian Government.
文摘Hurricanes are one of the most destructive natural disasters that can cause catastrophic losses to both communities and infrastructure.Assessment of hurricane risk furnishes a spatial depiction of the interplay among hazard,vulnerability,exposure,and mitigation capacity,crucial for understanding and managing the risks hurricanes pose to communities.These assessments aid in gauging the efficacy of existing hurricane mitigation strategies and gauging their resilience across diverse climate change scenarios.A systematic review was conducted,encompassing 94 articles,to scrutinize the structure,data inputs,assumptions,methodologies,perils modelled,and key predictors of hurricane risk.This review identified key research gaps essential for enhancing future risk assessments.The complex interaction between hurricane perils may be disastrous and underestimated in the majority of risk assessments which focus on a single peril,commonly storm surge and flood,resulting in inadequacies in disaster resilience planning.Most risk assessments were based on hurricane frequency rather than hurricane damage,which is more insightful for policymakers.Furthermore,considering secondary indirect impacts stemming from hurricanes,including real estate market and business interruption,could enrich economic impact assessments.Hurricane mitigation measures were the most under-utilised category of predictors leveraged in only 5%of studies.The top six predictive factors for hurricane risk were land use,slope,precipitation,elevation,population density,and soil texture/drainage.Another notable research gap identified was the potential of machine learning techniques in risk assessments,offering advantages over traditional MCDM and numerical models due to their ability to capture complex nonlinear relationships and adaptability to different study regions.Existing machine learning based risk assessments leverage random forest models(42%of studies)followed by neural network models(19%of studies),with further research required to investigate diverse machine learning algorithms such as ensemble models.A further research gap is model validation,in particular assessing transferability to a new study region.Additionally,harnessing simulated data and refining projections related to demographic and built environment dynamics can bolster the sophistication of climate change scenario assessments.By addressing these research gaps,hurricane risk assessments can furnish invaluable insights for national policymakers,facilitating the development of robust hurricane mitigation strategies and the construction of hurricane-resilient communities.To the authors’knowledge,this represents the first literature review specifically dedicated to quantitative hurricane risk assessments,encompassing a comparison of Multi-criteria Decision Making(MCDM),numerical models,and machine learning models.Ultimately,advancements in hurricane risk assessments and modelling stand poised to mitigate potential losses to communities and infrastructure both in the immediate and long-term future.
