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
The research findings on the ground motion and liquefaction potential analyses during the 2018 Great Indonesia Earthquake(M_(w)7.5)are significant and crucial.The earthquake triggered soil-structure damage due to liqu...The research findings on the ground motion and liquefaction potential analyses during the 2018 Great Indonesia Earthquake(M_(w)7.5)are significant and crucial.The earthquake triggered soil-structure damage due to liquefaction.This study,which thoroughly investigated four sites at Palu,was conducted by performing a comprehensive ground motion parameter analysis.The ground motion characteristics were presented and justified,particularly for the most impacted direction.Ground motion predictions were analysed to define the spectral accelerations,and matching spectral accelerations were conducted to produce ground motions for each site.Non-linear seismic ground response analysis based on the hyperbolic model of pressure pressure-dependent was performed to investigate cyclic soil behaviour.The results revealed that ground motion is crucial in significant soil damage,and the earthquake energy could trigger deep liquefaction.As the most significant ground motion,the vertical ground motion is essential in determining deep liquefaction.The discussion on the impact of liquefaction based on the results of the numerical analysis is presented.Significant ground motion with a longer duration could have a substantial impact on deep liquefaction in the study area.These findings depict how the 2018 Indonesia Earthquake(M_(w)7.5)triggered a mega-liquefaction in Palu City.The results could enhance the understanding of the importance of seismic hazard assessment.It is recommended that site investigation and soil improvement should be planned to counteract liquefaction damage before construction.This study also suggests conducting seismic hazard assessments for city development to minimise the potential disaster impact in the study area.展开更多
Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphi...Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphite.This study utilizes the porous“defect advantage”of a cathode carbon block matrix to prepare silicon-doped and asphalt-coated detoxified and purified waste graphitization cathode carbon blocks for use as high-performance silicon/carbon composite anode materials.The results show that the uniformly silicondoped silicon/carbon composite material features a unique amorphous carbon-encapsulated“locked silicon”structure,which effectively addresses issues such as cathode volume expansion,excessive growth of the solid electrolyte interphase(SEI)film,and poor electrical contact between active materials.Consequently,electrochemical performance is enhanced.After assembly in a half-cell,the PSCC/10%Si@C(purified waste graphitization cathode carbon/10%Si@C)material exhibits optimal electrochemical stability,with an initial charging specific capacity of 514.5 mAh/g at 0.1 C(1 C=170 mA/g)and a capacity retention rate of 95.1%after 100 cycles.At a charge rate of 2.0 C,a specific capacity of 216.9 mAh/g is achieved.This technology provides a new pathway for the economical and high-value utilization of waste cathode carbon blocks and the development of low-cost,high-performance anode materials.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
0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,...0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,87.45°E,with a depth of~10 km.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
Climate change and rising temperatures are accelerating the rate of deglaciation in the Hindu Kush Karakoram Himalaya(HKH)ranges,leading to the formation of new glacial lakes and the expansion of existing ones.These l...Climate change and rising temperatures are accelerating the rate of deglaciation in the Hindu Kush Karakoram Himalaya(HKH)ranges,leading to the formation of new glacial lakes and the expansion of existing ones.These lakes are often vulnerable to failure,posing a significant threat to downstream communities and infrastructure.Therefore,a comprehensive assessment of Glacier-Lake Outburst Flood(GLOF)hazards and risk assessment is crucial to evaluate flood runout characteristics and identify settlements and infrastructure that are exposed and vulnerable to floods,aiding in the development and implementation of risk reduction strategies.This study aims to simulate a GLOF event induced by the Shisper glacier lake in northern Pakistan,using the HEC-RAS,and to assess its impact on settlements,infrastructure,and agricultural land.For the hydrometeorological analysis of the GLOF event,topographic data from unmanned aerial vehicles(UAVs),stream profiles,discharge data,Manning's roughness coefficient(n),and land use/land cover(LULC)were analyzed using HEC-RAS and geographic information system(GIS).During the GLOF event on May 7,2022,a maximum water depth of 6.3 m and a maximum velocity of 9.5 m/s were recorded.Based on the runout characteristics of this event,vulnerability and risk assessments have been calculated.The physical,social,and environmental vulnerabilities of the at-risk elements were evaluated using the analytical hierarchy process(AHP)and integrated with the hazard data to develop a risk map.The study identified the areas,infrastructure and settlements susceptible to GLOF hazard to support the development and implementation of targeted and evidence-based mitigation and adaptation strategies.展开更多
Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The s...Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.展开更多
With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in...With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in university laboratories has faced numerous challenges,and traditional teaching methods have been insufficiently effective,with high-risk scenarios difficult to realistically recreate.Especially in special scenarios involving hazardous chemicals,conventional training methods struggle to enable learners to achieve deep understanding and behavioral formation.This study systematically integrates immersive technology theory with safety education needs,providing a replicable technical solution for safety education in high-risk environments.Its modular design approach has reference value for expansion into other professional fields,offering practical evidence for innovation in safety education models in the digital age.展开更多
Retrogressive landslides in sensitive clays pose significant risks to nearby infrastructure,as natural toe erosion or localized disturbances can trigger progressive block failures.While prior studies have largely reli...Retrogressive landslides in sensitive clays pose significant risks to nearby infrastructure,as natural toe erosion or localized disturbances can trigger progressive block failures.While prior studies have largely relied on two-dimensional(2D)large-deformation analyses,such models overlook key three-dimensional(3D)failure mechanisms and variability effects.This study develops a 3D probabilistic framework by integrating the Coupled Eulerian–Lagrangian(CEL)method with random field theory to simulate retrogressive landslides in spatially variable clay.Using Monte Carlo simulations,we compare 2D and 3D random large-deformation models to evaluate failure modes,runout distances,sliding velocities,and influence zones.The 3D analyses captured more complex failure modes—such as lateral retrogression and asynchronous block mobilization across slope width.Additionally,the 3D analyses predict longer mean runout distances(13.76 vs.11.92 m),wider mean influence distance(11.35 vs.8.73 m),and higher mean sliding velocities(4.66 vs.3.94 m/s)than their 2D counterparts.Moreover,3D models exhibit lower coefficients of variation(e.g.,0.10 for runout distance)due to spatial averaging across slope width.Probabilistic hazard assessment shows that 2D models significantly underpredict near-field failure probabilities(e.g.,48.8%vs.89.9%at 12 m from the slope toe).These findings highlight the limitations of 2D analyses and the importance of multi-directional spatial variability for robust geohazard assessments.The proposed 3D framework enables more realistic prediction of landslide mobility and supports the design of safer,risk-informed infrastructure.展开更多
Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researchin...Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researching geohazard,from regional to individual scale.The methodology includes the establishment of geological chain inventories,discrimination of geohazard chain modes,analyses of dynamics and dam breaches,and risk assessments.The following results were obtained:(1)In the downstream of Yarlung Zangbo River,175 sites were identified as high-risk for river blockage disasters,indicating the development of watershed geohazards.Five geohazard chain modes were summarized by incorporating geomorphological characteristics,historical events,landslide zoning,and materials.The risk areas of typical hazard were identified and assessed using InSAR data.(2)Glacier-related watershed geohazard chains are significantly different from traditional landslides.A detailed inversion analysis was conducted on the massive rock-ice avalanche in the Sedongpu gully in 2021.This particular event lasted roughly 300 seconds,with a maximum flow velocity of 77.2 m/s and a maximum flow height of 93 meters.By scrutinizing the dynamic processes and mechanical characteristics,mobility stages and phase transitions can be divided into four stages.(3)Watershed geohazard chains tend to block rivers.The peak breach discharge of the Yigong Landslide reached 12.4×10^(4) m^(3)/s,which is 36 times the volume of the seasonal flood discharge in the Yigong River.Megafloods caused by landslide dam breaches have significantly shaped the geomorphology.This study offers insights into disaster patterns and the multistaged movement characteristics of glacier-related watershed geohazard chains,providing a comprehensive method for investigations and assessments in glacial regions.展开更多
Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric lea...Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.展开更多
A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiag...A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiagu.The objective is to address two key unresolved issues:the evolution of detached glacier materials into debris flows or debris floods and the amplification of the impact range and threats.A comprehensive framework is developed that considers the impacts of near-field and far-field hazards.Numerical modeling,remote sensing,and field investigations were integrated to understand the interactions,transformations,and amplifications of hazards in the glacier hazard chain.The results indicate that extensive,nearly saturated sediments on the glacier valley floor,when entrained,amplify the magnitude of the mass flow.The topography plays a crucial role.When the valley outlet is perpendicular to the river course,topographic obstacles cause immediate halting,resulting in the formation of high barrier dams.Conversely,when the glacier valley aligns nearly parallel to the river course,the mass flow can travel a much longer distance upon entering the river,causing an enlarged affected area.The barrier dams can breach rapidly,causing breaching floods that amplify the downstream impact from several kilometers to hundreds of kilometers.Our analysis reveals that the overall impacts remain spatially limited.Specifically,downstream areas along the Yarlung Zangbo-Brahmaputra River are unlikely to face greater threats from the upstream floods than local monsoon floods.Our findings provide the foundation for the management of glacier hazard chains.展开更多
The three-dimensional(3D)geometry of a fault is a critical control on earthquake nucleation,dynamic rupture,stress triggering,and related seismic hazards.Therefore,a 3D model of an active fault can significantly impro...The three-dimensional(3D)geometry of a fault is a critical control on earthquake nucleation,dynamic rupture,stress triggering,and related seismic hazards.Therefore,a 3D model of an active fault can significantly improve our understanding of seismogenesis and our ability to evaluate seismic hazards.Utilising the SKUA GoCAD software,we constructed detailed seismic fault models for the 2021 M_(S)6.4 Yangbi earthquake in Yunnan,China,using two sets of relocated earthquake catalogs and focal mechanism solutions following a convenient 3D fault modeling workflow.Our analysis revealed a NW-striking main fault with a high-angle SW dip,accompanied by two branch faults.Interpretation of one dataset revealed a single NNW-striking branch fault SW of the main fault,whereas the other dataset indicated four steep NNE-striking segments with a left-echelon pattern.Additionally,a third ENE-striking short fault was identified NE of the main fault.In combination with the spatial distribution of pre-existing faults,our 3D fault models indicate that the Yangbi earthquake reactivated pre-existing NW-and NE-striking fault directions rather than the surface-exposed Weixi-Qiaohou-Weishan Fault zone.The occurrence of the Yangbi earthquake demonstrates that the reactivation of pre-existing faults away from active fault zones,through either cascade or conjugate rupture modes,can cause unexpected moderate-large earthquakes and severe disasters,necessitating attention in regions like southeast Xizang,which have complex fault systems.展开更多
The evacuation of people under threat is an effective disaster prevention and mitigation measure in response to flash floods and geological hazards,and it is also an essential element of pre-disaster planning.However,...The evacuation of people under threat is an effective disaster prevention and mitigation measure in response to flash floods and geological hazards,and it is also an essential element of pre-disaster planning.However,the effect of the interactions between perception factors on residents'willingness to evacuate is an urgent problem to be solved.Therefore,this paper introduces risk,stakeholder,and protective action perceptions from the protective action decision model as the main explanatory variables.These three core perceptions are subdivided into affective risk perception,cognitive risk perception,government perception,other-stakeholder perception,resourcerelated attributes,and hazard-related attributes.A questionnaire survey was conducted from June to July 2023 among residents of mountainous communities in nine villages in three towns in Sichuan Province,China.359 cross-sectional data were analyzed using structural equation modeling to explore the effects of six perception factors on evacuation intentions.The results of the study showed that:(1)affective risk perception,government perception,other-stakeholder perception,and hazard-related attributes all directly and positively influence residents'intentions to evacuate;(2)cognitive risk perception is mediated by stakeholder and protective action perceptions,which indirectly and positively affect residents'intentions to evacuate.Based on the hypothesized paths,strategies to improve residents'willingness to evacuate are discussed from the perspective of three core perceptions:strengthening disaster risk education,improving residents'cohesion,and building government credibility.The results of this study can provide theoretical support and practical suggestions for emergency management departments to formulate emergency evacuation strategies,which can aid decision-makers in better understanding residents'intentions to evacuate,optimizing evacuation information dissemination pathways,and strengthening disaster risk management capabilities.展开更多
Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives ...Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.展开更多
A new report from Jeanologia highlights theurgent need for the denim industry to adopt saferalternatives to harmful chemicals.The study alsostresses reducing excessive water use in garmentfinishing.The report,compiled...A new report from Jeanologia highlights theurgent need for the denim industry to adopt saferalternatives to harmful chemicals.The study alsostresses reducing excessive water use in garmentfinishing.The report,compiled in 2024,analyzed datafrom more than ll5,000 dentm finishing processes.lt found that 24%of denim finishing processes stilluse hazardous chemicals,posing risks to both theenvironment and the health of workers.展开更多
Nowadays,high-stable and ultrasensitive heavy metal detection is of utmost importance in water quality monitoring.Nanoparticle-enhanced laser-induced breakdown spectroscopy(NELIBS)shows high potential in hazardous met...Nowadays,high-stable and ultrasensitive heavy metal detection is of utmost importance in water quality monitoring.Nanoparticle-enhanced laser-induced breakdown spectroscopy(NELIBS)shows high potential in hazardous metal detection,however,encounters unstable and weak signals due to nonuniform distribution of analytes.Herein,we developed an interface self-assembly(ISA)method to create a uniformly distributed gold nanolayer at a liquid-liquid interface for positive heavy metal ions capture and NELIBS analysis.The electrostatically selfassembled Au nanoparticles(NPs)-analytes membrane was prepared at the oil-water interface by injecting ethanol into the mixture of cyclohexane and Au NPs-analytes water solution.Then,the interface self-assembled Au NPs-analytes membrane was transformed onto a laser-processed superhydrophilic Si slide for detection.Three heavy metals(cadmium(Cd),barium(Ba),and chromium(Cr))were analyzed to evaluate the stability and sensitivity of the ISA method for NELIBS.The results(Cd:RSD=3.6%,LoD=0.654 mg/L;Ba:RSD=3.4%,LoD=0.236 mg/L;Cr:RSD=7.7%,LoD=1.367 mg/L)demonstrated signal enhancement and high-stable and ultrasensitive detection.The actual sample detection(Cd:RE=7.71%,Ba:RE=6.78%)illustrated great reliability.The ISA method,creating a uniform distribution of NP-analytes at the interface,has promising prospects in NELIBS.展开更多
The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. ...The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. This study applies a robust Probabilistic Seismic Hazard Analysis (PSHA) framework to compute Maximum Considered Earthquake (MCE) and Risk-Targeted Maximum Considered Earthquake (MCER) values for major cities, including Jazan, Abha, and Najran. Utilizing local seismotectonic models, ground motion prediction equations (GMPEs), and soil classifications, the study generates precise ground motion parameters critical for infrastructure planning and safety. Results indicate significant seismic hazard variability, with Jazan showing high seismic risks with an MCER SA (0.2 s) of 0.45 g, compared to Najran’s lower risks at 0.23 g. Structural design guidelines, informed by MCE and MCER calculations, prioritize the integration of site-specific seismic data, enhanced ductility requirements, and advanced analytical methods to ensure resilient and sustainable infrastructure. The study underscores the necessity of localized seismic assessments and modern engineering practices to effectively mitigate seismic risks in this geologically complex region.展开更多
Snow avalanches present a significant threat to infrastructure,affecting buildings,roads,railways,and power lines,and frequently leading to massive economic losses in livelihoods and production.With the increase in re...Snow avalanches present a significant threat to infrastructure,affecting buildings,roads,railways,and power lines,and frequently leading to massive economic losses in livelihoods and production.With the increase in regional temperatures and the occurrence of extreme snowfall events,the frequency and intensity of avalanches have escalated,resulting in more severe incidents and higher casualty rates.As natural archives of environmental changes,tree rings offer valuable proxies for avalanche hazard assessments in regions where direct observation data is scarce,particularly in high-altitude regions.The dendrogeomorphology has been gradually being applied in avalanche hazard evaluation,however,it remains limited in China.To address this gap,this study systematically investigates the principles and methodologies for reconstructing avalanche histories and evaluates their applications in avalanche hazard assessments through a literature review and field observations.It provides a comprehensive overview of recent advancements in key areas,including the impact of avalanches on forest ecosystems,the reconstruction of avalanches,and the analysis of avalanche events(i.e.,the spatiotemporal distribution,the historical recurrence intervals,magnitudes,and triggering conditions of avalanches).Considering the current limitations in avalanche hazard assessments and the urgent need for such research in China,we outline key priorities and future directions,including refining reconstruction methodologies,developing a comprehensive tree-ring-based avalanche database for high-altitude regions,and establishing an advanced hazard assessment framework based on dendrochronological evidence.展开更多
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The World Class Professor(WCP)Program of the Directorate of Resources,Directorate General of Higher Education,Ministry of Education and Culture in 2023 supports this studythe JAPAN-ASEAN Science and Technology Innovation Platform(JASTIP-WP4)+3 种基金the University of Bengkulu's International Collaboration Research Fund(2183/UN30.15/LT/2019)for partial fundingthe C2F Fund for Postdoctoral Fellowship from Chulalongkorn Universitythe Thailand Science Research and Innovation Fund Chulalongkorn University(DISF68210001)the National Research Council of Thailand(N42A670572)。
文摘The research findings on the ground motion and liquefaction potential analyses during the 2018 Great Indonesia Earthquake(M_(w)7.5)are significant and crucial.The earthquake triggered soil-structure damage due to liquefaction.This study,which thoroughly investigated four sites at Palu,was conducted by performing a comprehensive ground motion parameter analysis.The ground motion characteristics were presented and justified,particularly for the most impacted direction.Ground motion predictions were analysed to define the spectral accelerations,and matching spectral accelerations were conducted to produce ground motions for each site.Non-linear seismic ground response analysis based on the hyperbolic model of pressure pressure-dependent was performed to investigate cyclic soil behaviour.The results revealed that ground motion is crucial in significant soil damage,and the earthquake energy could trigger deep liquefaction.As the most significant ground motion,the vertical ground motion is essential in determining deep liquefaction.The discussion on the impact of liquefaction based on the results of the numerical analysis is presented.Significant ground motion with a longer duration could have a substantial impact on deep liquefaction in the study area.These findings depict how the 2018 Indonesia Earthquake(M_(w)7.5)triggered a mega-liquefaction in Palu City.The results could enhance the understanding of the importance of seismic hazard assessment.It is recommended that site investigation and soil improvement should be planned to counteract liquefaction damage before construction.This study also suggests conducting seismic hazard assessments for city development to minimise the potential disaster impact in the study area.
基金supported by the National Natural Science Foundation of China(No.52274346).
文摘Waste graphitization cathode carbon blocks are a type of hazardous solid waste generated during the aluminum electrolysis process,and their proper disposal is a key step in the resource utilization of discarded graphite.This study utilizes the porous“defect advantage”of a cathode carbon block matrix to prepare silicon-doped and asphalt-coated detoxified and purified waste graphitization cathode carbon blocks for use as high-performance silicon/carbon composite anode materials.The results show that the uniformly silicondoped silicon/carbon composite material features a unique amorphous carbon-encapsulated“locked silicon”structure,which effectively addresses issues such as cathode volume expansion,excessive growth of the solid electrolyte interphase(SEI)film,and poor electrical contact between active materials.Consequently,electrochemical performance is enhanced.After assembly in a half-cell,the PSCC/10%Si@C(purified waste graphitization cathode carbon/10%Si@C)material exhibits optimal electrochemical stability,with an initial charging specific capacity of 514.5 mAh/g at 0.1 C(1 C=170 mA/g)and a capacity retention rate of 95.1%after 100 cycles.At a charge rate of 2.0 C,a specific capacity of 216.9 mAh/g is achieved.This technology provides a new pathway for the economical and high-value utilization of waste cathode carbon blocks and the development of low-cost,high-performance anode materials.
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funded by the National Key R&D Program of China(No.2020YFC150071)partly supported by the Shaanxi Province Geoscience Big Data and Geohazard Prevention Innovation Team(2022)and the Research Funds for the Interdisciplinary Projects,CHU(No.300104240914)。
文摘0 INTRODUCTION.According to the China Earthquake Networks Center,an M6.8 earthquake struck Dingri County,Xizang Autonomous Region,China,on 7 January 2025 at 9:05 a.m.local time.The epicenter is located at 28.5°N,87.45°E,with a depth of~10 km.
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.
基金the Higher Education Commission of Pakistan for supporting the study through the CRG-CPEC-130 project。
文摘Climate change and rising temperatures are accelerating the rate of deglaciation in the Hindu Kush Karakoram Himalaya(HKH)ranges,leading to the formation of new glacial lakes and the expansion of existing ones.These lakes are often vulnerable to failure,posing a significant threat to downstream communities and infrastructure.Therefore,a comprehensive assessment of Glacier-Lake Outburst Flood(GLOF)hazards and risk assessment is crucial to evaluate flood runout characteristics and identify settlements and infrastructure that are exposed and vulnerable to floods,aiding in the development and implementation of risk reduction strategies.This study aims to simulate a GLOF event induced by the Shisper glacier lake in northern Pakistan,using the HEC-RAS,and to assess its impact on settlements,infrastructure,and agricultural land.For the hydrometeorological analysis of the GLOF event,topographic data from unmanned aerial vehicles(UAVs),stream profiles,discharge data,Manning's roughness coefficient(n),and land use/land cover(LULC)were analyzed using HEC-RAS and geographic information system(GIS).During the GLOF event on May 7,2022,a maximum water depth of 6.3 m and a maximum velocity of 9.5 m/s were recorded.Based on the runout characteristics of this event,vulnerability and risk assessments have been calculated.The physical,social,and environmental vulnerabilities of the at-risk elements were evaluated using the analytical hierarchy process(AHP)and integrated with the hazard data to develop a risk map.The study identified the areas,infrastructure and settlements susceptible to GLOF hazard to support the development and implementation of targeted and evidence-based mitigation and adaptation strategies.
基金supported by the Key Research and Development Program of the Ministry of Science and Technology of China(grant number:2016YF0900605)the Key Research and Development Program of Hebei Province(grant number:192777129D)+1 种基金the Joint Fund for Iron and Steel of the Natural Science Foundation of Hebei Province(grant number:H2016209058)the National Natural Science Foundation for Regional Joint Fund of China(grant number:U22A20364)。
文摘Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.
文摘With the rapid development of virtual reality(VR)and augmented reality(AR)technologies,their application potential in the field of education has become increasingly significant.For a long time,fire safety education in university laboratories has faced numerous challenges,and traditional teaching methods have been insufficiently effective,with high-risk scenarios difficult to realistically recreate.Especially in special scenarios involving hazardous chemicals,conventional training methods struggle to enable learners to achieve deep understanding and behavioral formation.This study systematically integrates immersive technology theory with safety education needs,providing a replicable technical solution for safety education in high-risk environments.Its modular design approach has reference value for expansion into other professional fields,offering practical evidence for innovation in safety education models in the digital age.
基金supported by the National Key Research and Development Program of China(No.2024YFC2815400)the European Commission(Nos.HORIZON MSCA-2024-PF-01 and 101200637)+2 种基金the Opening Fund of the State Key Laboratory of Water Resources Engineering and Management at Wuhan University(No.2024SGG07)the Shandong Provincial Natural Science Foundation(No.ZR2025MS647)the Sand Hazards and Opportunities for Resilience,Energy,and Sustainability(SHORES)Center,funded by Tamkeen under the NYUAD Research Institute Award CG013.
文摘Retrogressive landslides in sensitive clays pose significant risks to nearby infrastructure,as natural toe erosion or localized disturbances can trigger progressive block failures.While prior studies have largely relied on two-dimensional(2D)large-deformation analyses,such models overlook key three-dimensional(3D)failure mechanisms and variability effects.This study develops a 3D probabilistic framework by integrating the Coupled Eulerian–Lagrangian(CEL)method with random field theory to simulate retrogressive landslides in spatially variable clay.Using Monte Carlo simulations,we compare 2D and 3D random large-deformation models to evaluate failure modes,runout distances,sliding velocities,and influence zones.The 3D analyses captured more complex failure modes—such as lateral retrogression and asynchronous block mobilization across slope width.Additionally,the 3D analyses predict longer mean runout distances(13.76 vs.11.92 m),wider mean influence distance(11.35 vs.8.73 m),and higher mean sliding velocities(4.66 vs.3.94 m/s)than their 2D counterparts.Moreover,3D models exhibit lower coefficients of variation(e.g.,0.10 for runout distance)due to spatial averaging across slope width.Probabilistic hazard assessment shows that 2D models significantly underpredict near-field failure probabilities(e.g.,48.8%vs.89.9%at 12 m from the slope toe).These findings highlight the limitations of 2D analyses and the importance of multi-directional spatial variability for robust geohazard assessments.The proposed 3D framework enables more realistic prediction of landslide mobility and supports the design of safer,risk-informed infrastructure.
基金supported by the National Natural Science Foundation of China(Nos.U2244227,U2244226,42177172)the National Key R&D Program of China(No.2022YFC3004301)China Geological Survey Project(No.DD20230538)。
文摘Frequent glacier-related watershed geohazard chains are causing severe damage to life and infrastructure,reported consistently from the Eastern Himalayan Syntaxis.This paper presents a systematic method for researching geohazard,from regional to individual scale.The methodology includes the establishment of geological chain inventories,discrimination of geohazard chain modes,analyses of dynamics and dam breaches,and risk assessments.The following results were obtained:(1)In the downstream of Yarlung Zangbo River,175 sites were identified as high-risk for river blockage disasters,indicating the development of watershed geohazards.Five geohazard chain modes were summarized by incorporating geomorphological characteristics,historical events,landslide zoning,and materials.The risk areas of typical hazard were identified and assessed using InSAR data.(2)Glacier-related watershed geohazard chains are significantly different from traditional landslides.A detailed inversion analysis was conducted on the massive rock-ice avalanche in the Sedongpu gully in 2021.This particular event lasted roughly 300 seconds,with a maximum flow velocity of 77.2 m/s and a maximum flow height of 93 meters.By scrutinizing the dynamic processes and mechanical characteristics,mobility stages and phase transitions can be divided into four stages.(3)Watershed geohazard chains tend to block rivers.The peak breach discharge of the Yigong Landslide reached 12.4×10^(4) m^(3)/s,which is 36 times the volume of the seasonal flood discharge in the Yigong River.Megafloods caused by landslide dam breaches have significantly shaped the geomorphology.This study offers insights into disaster patterns and the multistaged movement characteristics of glacier-related watershed geohazard chains,providing a comprehensive method for investigations and assessments in glacial regions.
基金financially supported by the National Natural Science Foundation of China(No.52125201)Beijing Natural Science Foundation(No.Z240025)and the Beijing Municipal Science and Technology(No.Z221100002722015).
文摘Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.
基金support from the National Natural Science Foundation of China(U20A20112,42061160480,42377196,and 52479095)the NSFC/RGC Joint Research Scheme(42061160480 and N_HKUST620/20)+1 种基金the Research Grants Council of the Hong Kong SAR Government(16203720,T22-606/23-R,and JRFS25266S09)the Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone(HZQB-KCZYB-2020083)。
文摘A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiagu.The objective is to address two key unresolved issues:the evolution of detached glacier materials into debris flows or debris floods and the amplification of the impact range and threats.A comprehensive framework is developed that considers the impacts of near-field and far-field hazards.Numerical modeling,remote sensing,and field investigations were integrated to understand the interactions,transformations,and amplifications of hazards in the glacier hazard chain.The results indicate that extensive,nearly saturated sediments on the glacier valley floor,when entrained,amplify the magnitude of the mass flow.The topography plays a crucial role.When the valley outlet is perpendicular to the river course,topographic obstacles cause immediate halting,resulting in the formation of high barrier dams.Conversely,when the glacier valley aligns nearly parallel to the river course,the mass flow can travel a much longer distance upon entering the river,causing an enlarged affected area.The barrier dams can breach rapidly,causing breaching floods that amplify the downstream impact from several kilometers to hundreds of kilometers.Our analysis reveals that the overall impacts remain spatially limited.Specifically,downstream areas along the Yarlung Zangbo-Brahmaputra River are unlikely to face greater threats from the upstream floods than local monsoon floods.Our findings provide the foundation for the management of glacier hazard chains.
基金financial support from the National Key R&D Program of China (No. 2021YFC3000600)National Natural Science Foundation of China (No. 41872206)National Nonprofit Fundamental Research Grant of China, Institute of Geology, China, Earthquake Administration (No. IGCEA2010)
文摘The three-dimensional(3D)geometry of a fault is a critical control on earthquake nucleation,dynamic rupture,stress triggering,and related seismic hazards.Therefore,a 3D model of an active fault can significantly improve our understanding of seismogenesis and our ability to evaluate seismic hazards.Utilising the SKUA GoCAD software,we constructed detailed seismic fault models for the 2021 M_(S)6.4 Yangbi earthquake in Yunnan,China,using two sets of relocated earthquake catalogs and focal mechanism solutions following a convenient 3D fault modeling workflow.Our analysis revealed a NW-striking main fault with a high-angle SW dip,accompanied by two branch faults.Interpretation of one dataset revealed a single NNW-striking branch fault SW of the main fault,whereas the other dataset indicated four steep NNE-striking segments with a left-echelon pattern.Additionally,a third ENE-striking short fault was identified NE of the main fault.In combination with the spatial distribution of pre-existing faults,our 3D fault models indicate that the Yangbi earthquake reactivated pre-existing NW-and NE-striking fault directions rather than the surface-exposed Weixi-Qiaohou-Weishan Fault zone.The occurrence of the Yangbi earthquake demonstrates that the reactivation of pre-existing faults away from active fault zones,through either cascade or conjugate rupture modes,can cause unexpected moderate-large earthquakes and severe disasters,necessitating attention in regions like southeast Xizang,which have complex fault systems.
基金supported by the National Natural Science Foundation of China(U20A20111)the National key R&D Program(2022YFC3080100)。
文摘The evacuation of people under threat is an effective disaster prevention and mitigation measure in response to flash floods and geological hazards,and it is also an essential element of pre-disaster planning.However,the effect of the interactions between perception factors on residents'willingness to evacuate is an urgent problem to be solved.Therefore,this paper introduces risk,stakeholder,and protective action perceptions from the protective action decision model as the main explanatory variables.These three core perceptions are subdivided into affective risk perception,cognitive risk perception,government perception,other-stakeholder perception,resourcerelated attributes,and hazard-related attributes.A questionnaire survey was conducted from June to July 2023 among residents of mountainous communities in nine villages in three towns in Sichuan Province,China.359 cross-sectional data were analyzed using structural equation modeling to explore the effects of six perception factors on evacuation intentions.The results of the study showed that:(1)affective risk perception,government perception,other-stakeholder perception,and hazard-related attributes all directly and positively influence residents'intentions to evacuate;(2)cognitive risk perception is mediated by stakeholder and protective action perceptions,which indirectly and positively affect residents'intentions to evacuate.Based on the hypothesized paths,strategies to improve residents'willingness to evacuate are discussed from the perspective of three core perceptions:strengthening disaster risk education,improving residents'cohesion,and building government credibility.The results of this study can provide theoretical support and practical suggestions for emergency management departments to formulate emergency evacuation strategies,which can aid decision-makers in better understanding residents'intentions to evacuate,optimizing evacuation information dissemination pathways,and strengthening disaster risk management capabilities.
基金supported by the National Natural Science Foundation of China,Nos.82071426,81873784Clinical Cohort Construction Program of Peking University Third Hospital,No.BYSYDL2019002(all to DF)。
文摘Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.
文摘A new report from Jeanologia highlights theurgent need for the denim industry to adopt saferalternatives to harmful chemicals.The study alsostresses reducing excessive water use in garmentfinishing.The report,compiled in 2024,analyzed datafrom more than ll5,000 dentm finishing processes.lt found that 24%of denim finishing processes stilluse hazardous chemicals,posing risks to both theenvironment and the health of workers.
基金supported by the National Natural Science Foundation of China(No.62075069 and 52303092)the Water Conservancy Technology project of Hunan Province,China(XSKJ2021000-32)+1 种基金the City University of Hong Kong(#7005507)the Open Project of Yunnan Precious Metals Laboratory Co.,Ltd(grant number YPML-2023050278).
文摘Nowadays,high-stable and ultrasensitive heavy metal detection is of utmost importance in water quality monitoring.Nanoparticle-enhanced laser-induced breakdown spectroscopy(NELIBS)shows high potential in hazardous metal detection,however,encounters unstable and weak signals due to nonuniform distribution of analytes.Herein,we developed an interface self-assembly(ISA)method to create a uniformly distributed gold nanolayer at a liquid-liquid interface for positive heavy metal ions capture and NELIBS analysis.The electrostatically selfassembled Au nanoparticles(NPs)-analytes membrane was prepared at the oil-water interface by injecting ethanol into the mixture of cyclohexane and Au NPs-analytes water solution.Then,the interface self-assembled Au NPs-analytes membrane was transformed onto a laser-processed superhydrophilic Si slide for detection.Three heavy metals(cadmium(Cd),barium(Ba),and chromium(Cr))were analyzed to evaluate the stability and sensitivity of the ISA method for NELIBS.The results(Cd:RSD=3.6%,LoD=0.654 mg/L;Ba:RSD=3.4%,LoD=0.236 mg/L;Cr:RSD=7.7%,LoD=1.367 mg/L)demonstrated signal enhancement and high-stable and ultrasensitive detection.The actual sample detection(Cd:RE=7.71%,Ba:RE=6.78%)illustrated great reliability.The ISA method,creating a uniform distribution of NP-analytes at the interface,has promising prospects in NELIBS.
文摘The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. This study applies a robust Probabilistic Seismic Hazard Analysis (PSHA) framework to compute Maximum Considered Earthquake (MCE) and Risk-Targeted Maximum Considered Earthquake (MCER) values for major cities, including Jazan, Abha, and Najran. Utilizing local seismotectonic models, ground motion prediction equations (GMPEs), and soil classifications, the study generates precise ground motion parameters critical for infrastructure planning and safety. Results indicate significant seismic hazard variability, with Jazan showing high seismic risks with an MCER SA (0.2 s) of 0.45 g, compared to Najran’s lower risks at 0.23 g. Structural design guidelines, informed by MCE and MCER calculations, prioritize the integration of site-specific seismic data, enhanced ductility requirements, and advanced analytical methods to ensure resilient and sustainable infrastructure. The study underscores the necessity of localized seismic assessments and modern engineering practices to effectively mitigate seismic risks in this geologically complex region.
基金supported by National Natural Science Foundation of China(NO.42371085)the Tibet Science and Technology Program(XZ202201ZY0011G)the Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK0906).
文摘Snow avalanches present a significant threat to infrastructure,affecting buildings,roads,railways,and power lines,and frequently leading to massive economic losses in livelihoods and production.With the increase in regional temperatures and the occurrence of extreme snowfall events,the frequency and intensity of avalanches have escalated,resulting in more severe incidents and higher casualty rates.As natural archives of environmental changes,tree rings offer valuable proxies for avalanche hazard assessments in regions where direct observation data is scarce,particularly in high-altitude regions.The dendrogeomorphology has been gradually being applied in avalanche hazard evaluation,however,it remains limited in China.To address this gap,this study systematically investigates the principles and methodologies for reconstructing avalanche histories and evaluates their applications in avalanche hazard assessments through a literature review and field observations.It provides a comprehensive overview of recent advancements in key areas,including the impact of avalanches on forest ecosystems,the reconstruction of avalanches,and the analysis of avalanche events(i.e.,the spatiotemporal distribution,the historical recurrence intervals,magnitudes,and triggering conditions of avalanches).Considering the current limitations in avalanche hazard assessments and the urgent need for such research in China,we outline key priorities and future directions,including refining reconstruction methodologies,developing a comprehensive tree-ring-based avalanche database for high-altitude regions,and establishing an advanced hazard assessment framework based on dendrochronological evidence.
