If one considers the number of language learners that are worldwide,the number of classroom-based language assessments(CBLAs)that are given each year,and the number of decisions that are made on the basis of these,it ...If one considers the number of language learners that are worldwide,the number of classroom-based language assessments(CBLAs)that are given each year,and the number of decisions that are made on the basis of these,it is obvious that in terms of sheer numbers,more students are affected by CBLAs per year than by those based on large-scale language assessments.Because of this,it is essential that classroom teachers have the knowledge,skills,and tools to enable them to develop and use CBLAs that they can justify to stakeholders,e.g.,students,parents,and school authorities.In this paper we describe the approach to CBLAs that we have developed.First,we discuss the role of assessment in teaching and learning,the kinds of decisions that classroom teachers need to make,and the different modes of CBLAs.We then describe the process of using CBLAs to help teachers make decisions that will have beneficial consequences.Next,we discuss fairness and accountability in assessment and the process of assessment justification,including an assessment use argument.Finally,we discuss the process of developing CBLAs,using an example of a classroom-based language assessment to illustrate this.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
This study compares the environmental sustainability of five alternatives for the remediation of marine sediments of one of the most polluted coastal sites in Europe(Bagnoli-Coroglio bay,Mediterranean Sea),using the L...This study compares the environmental sustainability of five alternatives for the remediation of marine sediments of one of the most polluted coastal sites in Europe(Bagnoli-Coroglio bay,Mediterranean Sea),using the Life Cycle Assessment(LCA)methodology.The treatments are either in-situ or exsitu,the latter requiring an initial dredging to transport the contaminated sediments to the management site.More in detail,four ex-situ remediation technologies based on landfilling,bioremediation,electrokinetic technique and soil washing were identified.These technologies are compared to an in-situ strategy currently under validation for enhancing bioremediation of the polluted sediments of the Bagnoli-Coroglio site.Our results indicate that the disposal in landfilling site is the worst option in most categories(e.g.,650 kg CO_(2) eq./t of treated sediment,considering the nearest landfilling site),followed by the bioremediation,mainly due to the high energy demand.Electrokinetic remediation,soil washing,and innovative in-situ technology represent the most sustainable options.In particular,the new in-situ technology appears to be the least impacting in all categories(e.g.,54 kg CO_(2) eq./t of treated sediment),although it is expected to require longer treatment time(estimated up to 12 months based on its potential efficiency).It can reduce the impact on climate change more than 12 times compared to the disposal and 7 times compared to bioremediation in addition to the possibility to avoid/reduce the dredging operations and the consequent dispersion of pollutants.The results open relevant perspectives towards more eco-sustainable and costly effective actions for the reclamation of contaminated marine sediments.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
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
Background:Artificial intelligence(AI)is transforming healthcare,demanding reevaluation of medical education.China's“New Medical Education”initiative urgently requires a standardized AI literacy framework for me...Background:Artificial intelligence(AI)is transforming healthcare,demanding reevaluation of medical education.China's“New Medical Education”initiative urgently requires a standardized AI literacy framework for medical students to address fragmented standards,rapid technological evolution,and insufficient localized ethical norms.Objective:To establish a Chinese expert consensus defining core AI competencies and a multi-modal assessment framework for medical students.Methods:A multidisciplinary(including medical education,clinical medicine,medical AI,public health,and medical ethics)expert group(n=32)developed an initial competency list based on the“Knowledge-Skills-Attitude”Medical Competency Model.Two Delphi rounds(100%response rate;consensus threshold:mean≥4.0,CV≤0.25)refined the framework.Core competencies were prioritized via Analytic Hierarchy Process(AHP).The final consensus document was established after multiple expert group meetings.Results:The consensus defines AI literacy for medical students as a comprehensive attribute for integrating AI into profes-sional knowledge,clinical practice,research,and health management.It comprises a 21-item Competencies of AI Proficiency(CAIP)list across knowledge(eight indicators),skills(seven indicators),and attitude(six indicators)dimensions.Key com-petencies prioritized include understanding AI's role in multidisciplinary knowledge integration(CAIP3),identifying AI output biases(CAIP4),understanding health data governance(CAIP2),maintaining physician-led AI-assisted diagnosis(CAIP16),and identifying AI diagnostic biases(CAIP12).A multi-modal assessment framework is recommended,including paper-based/computerized tests for knowledge,situational judgment tests(SJTs)for attitudes,and objective structured clinical examinations(OSCEs)with a specific“AI Clinical Decision Conflict Scoring Scale”for skills.A multi-stage dynamic assessment system(“Pre-enrollment-Pre-clinical-Post-clinical”)is proposed for longitudinal tracking.Educational integration pathways emphasize embedding AI literacy modularly from early undergraduate years,constructing an integrated curriculum covering fundamental principles,advanced large model applications(e.g.,prompt engineering,agent development),and ethical considerations,supported by a"digital twin hospital platform."Conclusion:This consensus provides authoritative,China-specific guidance for defining and assessing medical students'AI literacy,adhering to national policies and regulations.It offers a core action framework for optimizing AI integration into medical education,fostering future healthcare professionals proficient in both AI technology and medical humanism,with a commitment to dynamic updating to adapt to evolving AI advancements.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
Despite the widespread presence and frequent detection of polycyclic aromatic hydrocarbons(PAHs)in various aspects of life,there is limited research on their exposure levels in pregnant women and cumulative exposure f...Despite the widespread presence and frequent detection of polycyclic aromatic hydrocarbons(PAHs)in various aspects of life,there is limited research on their exposure levels in pregnant women and cumulative exposure from the living environment.This study included 1311 women in late pregnancy from the Zunyi birth cohort and measured the urinary concentrations of 10 hydroxylated PAH metabolites(OH-PAHs).Risk assessment was conducted based on the estimated daily intake to calculate the hazard quotient and hazard index(HI).A linear regression model was used to analyze the relationship between creatinine-adjusted OH-PAHs concentrations and living environment and lifestyle factors,while principal component analysis was applied to trace the sources of PAHs exposure.1-OHPYR was detected in all participants’urine,with naphthalene metabolites having the highest concentrations among creatinine-adjusted PAHs.OH-PAHs concentrations were associated with housing type,room number,cooking frequency,household size,exercise frequency,fuel type,distance from main road,and drinking water source.Pregnant women using traditional fuels and living in bungalows had higher health risks than those using clean energy and living in buildings.Those living within 100 m of a main road had higher HI than those farther away.Coal combustion was identified as the primary source of PAHs exposure.The study emphasizes the importance of reducing PAHs exposure,especially for pregnant women living in polluted environments.It recommends public health interventions such as improving indoor ventilation and providing clean energy to reduce related health risks.展开更多
With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Tradition...With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Traditional path planning algorithms typically combine Dubins curves with local optimization to minimize trajectory length under 3D spatial constraints.However,these methods often overlook the correlation between pilot control quality and UAV flight dynamics,limiting their adaptability in complex scenarios.In this paper,we propose an intelligent flight evaluation model specifically designed to enhancemulti-waypoint trajectory optimization algorithms.Our model leverages a decision tree to integrate attitude parameters and trajectory matching metrics,establishing a quantitative link between pilot control quality and UAV flight states.Experimental results demonstrate that the proposed model not only accurately assesses pilot performance across diverse skill levels but also improves the optimality of generated trajectories.When integrated with our path planning algorithm,it efficiently produces optimal trajectories while strictly adhering to UAV flight constraints.This integrated framework highlights significant potential for real-time UAV training,performance assessment,and adaptive mission planning applications.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
Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—esp...Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.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
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
INTRODUCTION On March 28,2025,at 06:20:52 UTC,a shallow,magnitude M_(w)7.7 earthquake struck Myanmar(Burma)with an epicenter near the major city of Mandalay.This event,the strongest seismic activity recorded in Myanma...INTRODUCTION On March 28,2025,at 06:20:52 UTC,a shallow,magnitude M_(w)7.7 earthquake struck Myanmar(Burma)with an epicenter near the major city of Mandalay.This event,the strongest seismic activity recorded in Myanmar since 1950,generated intense shaking across much of the country,extended into regions of Thailand,and was felt in China's Yunnan and Guangxi provinces.展开更多
Erratum to:Journal of Earth Science https://doi.org/10.1007/s12583-025-0187-4 The original version of this article unfortunately contained one mistake.The presentation in Page2384 was incorrect.The corrected one is gi...Erratum to:Journal of Earth Science https://doi.org/10.1007/s12583-025-0187-4 The original version of this article unfortunately contained one mistake.The presentation in Page2384 was incorrect.The corrected one is given below.The NTL loss ratio(Figure 4a)was calculated as the variation between pre-earthquake(March 27)and post-earthquake(March 28)radiance values in cloud-free areas.展开更多
Insulin resistance(IR)is widely recognized as a key contributor to metabolic disorders,and various surrogate indices have been developed to estimate IR in clinical and research settings.The hyperinsulinemic-euglycemic...Insulin resistance(IR)is widely recognized as a key contributor to metabolic disorders,and various surrogate indices have been developed to estimate IR in clinical and research settings.The hyperinsulinemic-euglycemic clamp is considered the gold standard method for assessing insulin resistance due to its precision;however,its complexity limits its widespread clinical application.Consequently,surrogate indices derived from fasting and post-load glucose and insulin levels have been developed to estimate IR,facilitating early detection and risk stratification in metabolic disorders.This mini-review discusses the clinical utility,strengths,and limitations of key IR indices,including the homeostasis model assessment of IR,quantitative insulin sensitivity check index,Matsuda index,and triglyceride-glucose index.Overall,the evidence presented to date suggests that these indices provide valuable estimates of IR in various popula-tions.Yet,their applicability varies depending on ethnic background,disease status,and clinical setting.Integrating these indices into routine clinical practice and research could improve metabolic risk assessment and guide preventive interventions.Further investigations are necessary to refine their accuracy and determine optimal cut-off values for various populations.展开更多
Background Non-invasive computed tomography angiography(CTA)-based fractional flow reserve(CT-FFR)could become a gatekeeper to invasive coronary angiography.Deep learning(DL)-based CT-FFR has shown promise when compar...Background Non-invasive computed tomography angiography(CTA)-based fractional flow reserve(CT-FFR)could become a gatekeeper to invasive coronary angiography.Deep learning(DL)-based CT-FFR has shown promise when compared to invasive FFR.To evaluate the performance of a DL-based CT-FFR technique,DeepVessel FFR(DVFFR).Methods This retrospective study was designed for iScheMia Assessment based on a Retrospective,single-center Trial of CTFFR(SMART).Patients suspected of stable coronary artery disease(CAD)and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1,2016 to December 30,2018.FFR obtained during invasive coronary angiography was used as the reference standard.DVFFR was calculated blindly using a DL-based CTFFR approach that utilized the complete tree structure of the coronary arteries.Results Three hundred and thirty nine patients(60.5±10.0 years and 209 men)and 414 vessels with direct invasive FFR were included in the analysis.At per-vessel level,sensitivity,specificity,accuracy,positive predictive value(PPV)and negative predictive value(NPV)of DVFFR were 94.7%,88.6%,90.8%,82.7%,and 96.7%,respectively.The area under the receiver operating characteristics curve(AUC)was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference(P<0.0001).At patient level,sensitivity,specificity,accuracy,PPV and NPV of DVFFR were 93.8%,88.0%,90.3%,83.0%,and 95.8%,respectively.The computation for DVFFR was fast with the average time of 22.5±1.9 s.Conclusions The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone.Coronary artery disease(CAD)is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia.Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.展开更多
This paper deeply analyzes the characteristics of core courses of the traffic engineering specialty and the problems existing in traditional assessment methods,and proposes a series of reform measures for the assessme...This paper deeply analyzes the characteristics of core courses of the traffic engineering specialty and the problems existing in traditional assessment methods,and proposes a series of reform measures for the assessment methods of core courses of the traffic engineering specialty.By introducing diversified assessment methods,focusing on process assessment,and strengthening the assessment of practical abilities,the aim is to improve students’learning enthusiasm and initiative,and cultivate students’innovation ability and practical ability to meet the needs of traffic engineering professionals in the new era.展开更多
This study examines the empirical feasibility of quantitatively integrating environmental value information into Strategic Environmental Assessment(SEA).An analytical framework was established to incorporate environme...This study examines the empirical feasibility of quantitatively integrating environmental value information into Strategic Environmental Assessment(SEA).An analytical framework was established to incorporate environmental cost estimates into the SEA process by utilizing ecosystem service unit values provided by the Environmental Valuation Information System(EVIS),a national platform developed to support the evaluation of policies and projects.The framework was applied to a case study involving a multipurpose rural water development project in South Korea.Ecosystem service losses resulting from the project were quantified using biophysical indicators,such as vegetation biomass,forest area,and hydrological functions,and subsequently monetized through the application of the market price method,replacement cost method,and contingent valuation method.The total annual environmental cost was estimated to be approximately KRW 56.18 billion,with the majority attributable to losses in forest conservation and climate regulation services.These findings demonstrate that quantified environmental data can serve as a robust basis for alternative comparison and site evaluation within SEA.The study provides empirical evidence supporting the advancement of SEA from a predominantly procedural tool focused on environmental protection to a more comprehensive sustainability assessment framework that integrates environmental,economic,and social considerations.Furthermore,the results suggest that EVIS-based quantitative information holds potential for broader application in other national evaluation systems,such as preliminary feasibility studies and regulatory impact assessments.展开更多
文摘If one considers the number of language learners that are worldwide,the number of classroom-based language assessments(CBLAs)that are given each year,and the number of decisions that are made on the basis of these,it is obvious that in terms of sheer numbers,more students are affected by CBLAs per year than by those based on large-scale language assessments.Because of this,it is essential that classroom teachers have the knowledge,skills,and tools to enable them to develop and use CBLAs that they can justify to stakeholders,e.g.,students,parents,and school authorities.In this paper we describe the approach to CBLAs that we have developed.First,we discuss the role of assessment in teaching and learning,the kinds of decisions that classroom teachers need to make,and the different modes of CBLAs.We then describe the process of using CBLAs to help teachers make decisions that will have beneficial consequences.Next,we discuss fairness and accountability in assessment and the process of assessment justification,including an assessment use argument.Finally,we discuss the process of developing CBLAs,using an example of a classroom-based language assessment to illustrate this.
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support in the literature analysis.This study has been carried out in the framework of the project funded by EU entitled“Bioremediation of contaminated sediments in coastal areas of exindustrial sites-LIFE SEDREMED”(No.LIFE20 ENV/IT/000572).
文摘This study compares the environmental sustainability of five alternatives for the remediation of marine sediments of one of the most polluted coastal sites in Europe(Bagnoli-Coroglio bay,Mediterranean Sea),using the Life Cycle Assessment(LCA)methodology.The treatments are either in-situ or exsitu,the latter requiring an initial dredging to transport the contaminated sediments to the management site.More in detail,four ex-situ remediation technologies based on landfilling,bioremediation,electrokinetic technique and soil washing were identified.These technologies are compared to an in-situ strategy currently under validation for enhancing bioremediation of the polluted sediments of the Bagnoli-Coroglio site.Our results indicate that the disposal in landfilling site is the worst option in most categories(e.g.,650 kg CO_(2) eq./t of treated sediment,considering the nearest landfilling site),followed by the bioremediation,mainly due to the high energy demand.Electrokinetic remediation,soil washing,and innovative in-situ technology represent the most sustainable options.In particular,the new in-situ technology appears to be the least impacting in all categories(e.g.,54 kg CO_(2) eq./t of treated sediment),although it is expected to require longer treatment time(estimated up to 12 months based on its potential efficiency).It can reduce the impact on climate change more than 12 times compared to the disposal and 7 times compared to bioremediation in addition to the possibility to avoid/reduce the dredging operations and the consequent dispersion of pollutants.The results open relevant perspectives towards more eco-sustainable and costly effective actions for the reclamation of contaminated marine sediments.
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Science and Technology Innovation 2030 Major Project,Grant/Award Number:2023ZD0508506。
文摘Background:Artificial intelligence(AI)is transforming healthcare,demanding reevaluation of medical education.China's“New Medical Education”initiative urgently requires a standardized AI literacy framework for medical students to address fragmented standards,rapid technological evolution,and insufficient localized ethical norms.Objective:To establish a Chinese expert consensus defining core AI competencies and a multi-modal assessment framework for medical students.Methods:A multidisciplinary(including medical education,clinical medicine,medical AI,public health,and medical ethics)expert group(n=32)developed an initial competency list based on the“Knowledge-Skills-Attitude”Medical Competency Model.Two Delphi rounds(100%response rate;consensus threshold:mean≥4.0,CV≤0.25)refined the framework.Core competencies were prioritized via Analytic Hierarchy Process(AHP).The final consensus document was established after multiple expert group meetings.Results:The consensus defines AI literacy for medical students as a comprehensive attribute for integrating AI into profes-sional knowledge,clinical practice,research,and health management.It comprises a 21-item Competencies of AI Proficiency(CAIP)list across knowledge(eight indicators),skills(seven indicators),and attitude(six indicators)dimensions.Key com-petencies prioritized include understanding AI's role in multidisciplinary knowledge integration(CAIP3),identifying AI output biases(CAIP4),understanding health data governance(CAIP2),maintaining physician-led AI-assisted diagnosis(CAIP16),and identifying AI diagnostic biases(CAIP12).A multi-modal assessment framework is recommended,including paper-based/computerized tests for knowledge,situational judgment tests(SJTs)for attitudes,and objective structured clinical examinations(OSCEs)with a specific“AI Clinical Decision Conflict Scoring Scale”for skills.A multi-stage dynamic assessment system(“Pre-enrollment-Pre-clinical-Post-clinical”)is proposed for longitudinal tracking.Educational integration pathways emphasize embedding AI literacy modularly from early undergraduate years,constructing an integrated curriculum covering fundamental principles,advanced large model applications(e.g.,prompt engineering,agent development),and ethical considerations,supported by a"digital twin hospital platform."Conclusion:This consensus provides authoritative,China-specific guidance for defining and assessing medical students'AI literacy,adhering to national policies and regulations.It offers a core action framework for optimizing AI integration into medical education,fostering future healthcare professionals proficient in both AI technology and medical humanism,with a commitment to dynamic updating to adapt to evolving AI advancements.
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.
基金supported by the National Key R&D Program of China(Nos.2018YFC1004300 and 2018YFC1004302)the Science&Technology Program of Guizhou Province(Nos.QKHHBZ[2020]3002,QKHPTRC-GCC[2022]039-1 and QKHPTRCCXTD[2022]014)the Scientific Research Program of Guizhou Provincial Department of Education(No.QJJ[2023]019).
文摘Despite the widespread presence and frequent detection of polycyclic aromatic hydrocarbons(PAHs)in various aspects of life,there is limited research on their exposure levels in pregnant women and cumulative exposure from the living environment.This study included 1311 women in late pregnancy from the Zunyi birth cohort and measured the urinary concentrations of 10 hydroxylated PAH metabolites(OH-PAHs).Risk assessment was conducted based on the estimated daily intake to calculate the hazard quotient and hazard index(HI).A linear regression model was used to analyze the relationship between creatinine-adjusted OH-PAHs concentrations and living environment and lifestyle factors,while principal component analysis was applied to trace the sources of PAHs exposure.1-OHPYR was detected in all participants’urine,with naphthalene metabolites having the highest concentrations among creatinine-adjusted PAHs.OH-PAHs concentrations were associated with housing type,room number,cooking frequency,household size,exercise frequency,fuel type,distance from main road,and drinking water source.Pregnant women using traditional fuels and living in bungalows had higher health risks than those using clean energy and living in buildings.Those living within 100 m of a main road had higher HI than those farther away.Coal combustion was identified as the primary source of PAHs exposure.The study emphasizes the importance of reducing PAHs exposure,especially for pregnant women living in polluted environments.It recommends public health interventions such as improving indoor ventilation and providing clean energy to reduce related health risks.
基金funded in part by the Fundamental Research Funds for the Central Universities under Grant NS2023052in part by the Natural Science Foundation of Jiangsu Province of China under Grants No.BK20231439 and No.BK20222012.
文摘With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Traditional path planning algorithms typically combine Dubins curves with local optimization to minimize trajectory length under 3D spatial constraints.However,these methods often overlook the correlation between pilot control quality and UAV flight dynamics,limiting their adaptability in complex scenarios.In this paper,we propose an intelligent flight evaluation model specifically designed to enhancemulti-waypoint trajectory optimization algorithms.Our model leverages a decision tree to integrate attitude parameters and trajectory matching metrics,establishing a quantitative link between pilot control quality and UAV flight states.Experimental results demonstrate that the proposed model not only accurately assesses pilot performance across diverse skill levels but also improves the optimality of generated trajectories.When integrated with our path planning algorithm,it efficiently produces optimal trajectories while strictly adhering to UAV flight constraints.This integrated framework highlights significant potential for real-time UAV training,performance assessment,and adaptive mission planning applications.
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funded by the National Natural Science Foundation of China(NSFC)under Grant Number 72071209.
文摘Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.
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.
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 the National Key R&D Program of the Republic of China(Nos.2023YFC3007303,2017YFB0504104)the Science and Technology Projects of Gansu Provincial(No.24JRRA1188)。
文摘INTRODUCTION On March 28,2025,at 06:20:52 UTC,a shallow,magnitude M_(w)7.7 earthquake struck Myanmar(Burma)with an epicenter near the major city of Mandalay.This event,the strongest seismic activity recorded in Myanmar since 1950,generated intense shaking across much of the country,extended into regions of Thailand,and was felt in China's Yunnan and Guangxi provinces.
文摘Erratum to:Journal of Earth Science https://doi.org/10.1007/s12583-025-0187-4 The original version of this article unfortunately contained one mistake.The presentation in Page2384 was incorrect.The corrected one is given below.The NTL loss ratio(Figure 4a)was calculated as the variation between pre-earthquake(March 27)and post-earthquake(March 28)radiance values in cloud-free areas.
文摘Insulin resistance(IR)is widely recognized as a key contributor to metabolic disorders,and various surrogate indices have been developed to estimate IR in clinical and research settings.The hyperinsulinemic-euglycemic clamp is considered the gold standard method for assessing insulin resistance due to its precision;however,its complexity limits its widespread clinical application.Consequently,surrogate indices derived from fasting and post-load glucose and insulin levels have been developed to estimate IR,facilitating early detection and risk stratification in metabolic disorders.This mini-review discusses the clinical utility,strengths,and limitations of key IR indices,including the homeostasis model assessment of IR,quantitative insulin sensitivity check index,Matsuda index,and triglyceride-glucose index.Overall,the evidence presented to date suggests that these indices provide valuable estimates of IR in various popula-tions.Yet,their applicability varies depending on ethnic background,disease status,and clinical setting.Integrating these indices into routine clinical practice and research could improve metabolic risk assessment and guide preventive interventions.Further investigations are necessary to refine their accuracy and determine optimal cut-off values for various populations.
文摘Background Non-invasive computed tomography angiography(CTA)-based fractional flow reserve(CT-FFR)could become a gatekeeper to invasive coronary angiography.Deep learning(DL)-based CT-FFR has shown promise when compared to invasive FFR.To evaluate the performance of a DL-based CT-FFR technique,DeepVessel FFR(DVFFR).Methods This retrospective study was designed for iScheMia Assessment based on a Retrospective,single-center Trial of CTFFR(SMART).Patients suspected of stable coronary artery disease(CAD)and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1,2016 to December 30,2018.FFR obtained during invasive coronary angiography was used as the reference standard.DVFFR was calculated blindly using a DL-based CTFFR approach that utilized the complete tree structure of the coronary arteries.Results Three hundred and thirty nine patients(60.5±10.0 years and 209 men)and 414 vessels with direct invasive FFR were included in the analysis.At per-vessel level,sensitivity,specificity,accuracy,positive predictive value(PPV)and negative predictive value(NPV)of DVFFR were 94.7%,88.6%,90.8%,82.7%,and 96.7%,respectively.The area under the receiver operating characteristics curve(AUC)was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference(P<0.0001).At patient level,sensitivity,specificity,accuracy,PPV and NPV of DVFFR were 93.8%,88.0%,90.3%,83.0%,and 95.8%,respectively.The computation for DVFFR was fast with the average time of 22.5±1.9 s.Conclusions The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone.Coronary artery disease(CAD)is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia.Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.
基金Key Project of Educational Science of China Association for Transportation Education and Research(Class B)(JT2024ZD077)。
文摘This paper deeply analyzes the characteristics of core courses of the traffic engineering specialty and the problems existing in traditional assessment methods,and proposes a series of reform measures for the assessment methods of core courses of the traffic engineering specialty.By introducing diversified assessment methods,focusing on process assessment,and strengthening the assessment of practical abilities,the aim is to improve students’learning enthusiasm and initiative,and cultivate students’innovation ability and practical ability to meet the needs of traffic engineering professionals in the new era.
基金funded by Korea Environmental Industry&Technology Institute(KEITI)through“Development of Aquatic Ecosystem Service Evaluation Indicators and Valuation Technology”of the Korea Ministry of Environment(MOE)(RS-2025-02214985).
文摘This study examines the empirical feasibility of quantitatively integrating environmental value information into Strategic Environmental Assessment(SEA).An analytical framework was established to incorporate environmental cost estimates into the SEA process by utilizing ecosystem service unit values provided by the Environmental Valuation Information System(EVIS),a national platform developed to support the evaluation of policies and projects.The framework was applied to a case study involving a multipurpose rural water development project in South Korea.Ecosystem service losses resulting from the project were quantified using biophysical indicators,such as vegetation biomass,forest area,and hydrological functions,and subsequently monetized through the application of the market price method,replacement cost method,and contingent valuation method.The total annual environmental cost was estimated to be approximately KRW 56.18 billion,with the majority attributable to losses in forest conservation and climate regulation services.These findings demonstrate that quantified environmental data can serve as a robust basis for alternative comparison and site evaluation within SEA.The study provides empirical evidence supporting the advancement of SEA from a predominantly procedural tool focused on environmental protection to a more comprehensive sustainability assessment framework that integrates environmental,economic,and social considerations.Furthermore,the results suggest that EVIS-based quantitative information holds potential for broader application in other national evaluation systems,such as preliminary feasibility studies and regulatory impact assessments.
