Cumulative effects of excess high-normal alanine aminotransferase levels in relation to new-onset metabolic dysfunction-associated fatty liver disease in China

BACKGROUND Within the normal range,elevated alanine aminotransferase(ALT)levels are associated with an increased risk of metabolic dysfunction-associated fatty liver disease(MAFLD).AIM To investigate the associations between repeated high-normal ALT measurements and the risk of new-onset MAFLD prospectively.METHODS A cohort of 3553 participants followed for four consecutive health examinations over 4 years was selected.The incidence rate,cumulative times,and equally and unequally weighted cumulative effects of excess high-normal ALT levels(ehALT)were measured.Cox proportional hazards regression was used to analyse the association between the cumulative effects of ehALT and the risk of new-onset MAFLD.RESULTS A total of 83.13%of participants with MAFLD had normal ALT levels.The incidence rate of MAFLD showed a linear increasing trend in the cumulative ehALT group.Compared with those in the low-normal ALT group,the multivariate adjusted hazard ratios of the equally and unequally weighted cumulative effects of ehALT were 1.651[95%confidence interval(CI):1.199-2.273]and 1.535(95%CI:1.119-2.106)in the third quartile and 1.616(95%CI:1.162-2.246)and 1.580(95%CI:1.155-2.162)in the fourth quartile,respectively.CONCLUSION Most participants with MAFLD had normal ALT levels.Long-term high-normal ALT levels were associated with a cumulative increased risk of new-onset MAFLD.

Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling

Spring consecutive rainfall events(CREs) are key triggers of geological hazards in the Three Gorges Reservoir area(TGR), China. However, previous projections of CREs based on the direct outputs of global climate models(GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF(Weather Research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6(Model for Interdisciplinary Research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6,indicating larger uncertainties in the CREs projected by MIROC6.

Effect of safety valve types on the gas venting behavior and thermal runaway hazard severity of large-format prismatic lithium iron phosphate batteries

The safety valve is an important component to ensure the safe operation of lithium-ion batteries(LIBs).However,the effect of safety valve type on the thermal runaway(TR)and gas venting behavior of LIBs,as well as the TR hazard severity of LIBs,are not known.In this paper,the TR and gas venting behavior of three 100 A h lithium iron phosphate(LFP)batteries with different safety valves are investigated under overheating.Compared to previous studies,the main contribution of this work is in studying and evaluating the effect of gas venting behavior and TR hazard severity of LFP batteries with three safety valve types.Two significant results are obtained:(Ⅰ)the safety valve type dominates over gas venting pressure of battery during safety venting,the maximum gas venting pressure of LFP batteries with a round safety valve is 3320 Pa,which is one order of magnitude higher than other batteries with oval or cavity safety valve;(Ⅱ)the LFP battery with oval safety valve has the lowest TR hazard as shown by the TR hazard assessment model based on gray-fuzzy analytic hierarchy process.This study reveals the effect of safety valve type on TR and gas venting,providing a clear direction for the safety valve design.

Exploring deep learning for landslide mapping:A comprehensive review

A detailed and accurate inventory map of landslides is crucial for quantitative hazard assessment and land planning.Traditional methods relying on change detection and object-oriented approaches have been criticized for their dependence on expert knowledge and subjective factors.Recent advancements in highresolution satellite imagery,coupled with the rapid development of artificial intelligence,particularly datadriven deep learning algorithms(DL)such as convolutional neural networks(CNN),have provided rich feature indicators for landslide mapping,overcoming previous limitations.In this review paper,77representative DL-based landslide detection methods applied in various environments over the past seven years were examined.This study analyzed the structures of different DL networks,discussed five main application scenarios,and assessed both the advancements and limitations of DL in geological hazard analysis.The results indicated that the increasing number of articles per year reflects growing interest in landslide mapping by artificial intelligence,with U-Net-based structures gaining prominence due to their flexibility in feature extraction and generalization.Finally,we explored the hindrances of DL in landslide hazard research based on the above research content.Challenges such as black-box operations and sample dependence persist,warranting further theoretical research and future application of DL in landslide detection.

Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.

Predicting the friction angle of clays using a multi-layer perceptron neural network enhanced by yeo-johnson transformation and coral reefs optimization

The accurate prediction of the friction angle of clays is crucial for assessing slope stability in engineering applications.This study addresses the importance of estimating the friction angle and presents the development of four soft computing models:YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and YJCSA-MLPnet.First of all,the Yeo-Johnson(YJ)transformation technique was used to stabilize the variance of data and make it more suitable for parametric statistical models that assume normality and equal variances.This technique is expected to improve the accuracy of friction angle prediction models.The friction angle prediction models then utilized multi-layer perceptron neural networks(MLPnet)and metaheuristic optimization algorithms to further enhance performance,including flower pollination algorithm(FPA),coral reefs optimization(CRO),ant colony optimization continuous(ACOC),and cuckoo search algorithm(CSA).The prediction models without the YJ technique,i.e.FPA-MLPnet,CRO-MLPnet,ACOC-MLPnet,and CSA-MLPnet,were then compared to those with the YJ technique,i.e.YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and YJ-CSA-MLPnet.Among these,the YJ-CRO-MLPnet model demonstrated superior reliability,achieving an accuracy of up to 83%in predicting the friction angle of clay in practical engineering scenarios.This improvement is significant,as it represents an increase from 1.3%to approximately 20%compared to the models that did not utilize the YJ transformation technique.

Problem identification and revitalization strategies for the recovery and reconstruction of traditional villages in the Ms 6.8 Luding Earthquake

Post-disaster reconstruction is a topic of global concern,and traditional villages have special heritage attributes and need to face more requirements and obstacles in post-disaster reconstruction.This paper summarizes four concepts based on the research on post-disaster reconstruction both domestically and internationally,as well as the recovery and reconstruction of cultural heritage.Through a field survey of traditional villages in the Ms 6.8 Luding earthquake-stricken area,it is found that there are problems such as insufficient awareness of heritage value,misalignment of scientific reconstruction technology,and insufficient protection of reconstruction elements during the reconstruction process.Traditional villages face the risk of declining or even loss of heritage value.In order to effectively protect traditional villages and inherit the carrier of regional culture,four targeted reconstruction response strategies are proposed,i.e.,to"establish special planning for traditional village preservation","emphasize recovery of the authenticity of village heritage","ensure elements for village heritage recovery"and"promote the activation and utilization of village heritage",based on the problems discovered during the survey and the four concepts summarized in the research on post-disaster reconstruction of traditional villages.The research results hope to provide useful reference for ancient cultural areas affected by earthquakes on how to protect cultural heritage during the post-disaster reconstruction process.

Automated machine learning for rainfall-induced landslide hazard mapping in Luhe County of Guangdong Province,China

Landslide hazard mapping is essential for regional landslide hazard management.The main objective of this study is to construct a rainfall-induced landslide hazard map of Luhe County,China based on an automated machine learning framework(AutoGluon).A total of 2241 landslides were identified from satellite images before and after the rainfall event,and 10 impact factors including elevation,slope,aspect,normalized difference vegetation index(NDVI),topographic wetness index(TWI),lithology,land cover,distance to roads,distance to rivers,and rainfall were selected as indicators.The WeightedEnsemble model,which is an ensemble of 13 basic machine learning models weighted together,was used to output the landslide hazard assessment results.The results indicate that landslides mainly occurred in the central part of the study area,especially in Hetian and Shanghu.Totally 102.44 s were spent to train all the models,and the ensemble model WeightedEnsemble has an Area Under the Curve(AUC)value of92.36%in the test set.In addition,14.95%of the study area was determined to be at very high hazard,with a landslide density of 12.02 per square kilometer.This study serves as a significant reference for the prevention and mitigation of geological hazards and land use planning in Luhe County.

Myths about Earthquakes:Quo vadis?

We are living in a world of numbers and calculations with enormous amount of pretty fast user-friendly software ready for an automatic output that may lead to a discovery or,alternatively,mislead to a deceptive conclusion,erroneous claims and predictions.As a matter of fact,nowadays,Science can disclose Natural Hazards,assess Risks,and deliver the state-of-the-art Knowledge of looming disaster in advance catastrophes along with useful Recommendations on the level of risks for decision making regarding engineering design,insurance,and emergency management.

Analysis of debris flow control effect and hazard assessment in Xinqiao Gully,Wenchuan M_(s)8.0 earthquake area based on numerical simulation

Xinqiao Gully is located in the area of the 2008 Wenchuan M_(s)8.0 earthquake in Sichuan province,China.Based on the investigation of the 2023"6-26"Xinqiao Gully debris flow event,this study assessed the effectiveness of the debris flow control project and evaluated the debris flow hazards.Through field investigation and numerical simulation methods,the indicators of flow intensity reduction rate and storage capacity fullness were proposed to quantify the effectiveness of the engineering measures in the debris flow event.The simulation results show that the debris flow control project reduced the flow intensity by41.05%to 64.61%.The storage capacity of the dam decreases gradually from upstream to the mouth of the gully,thus effectively intercepting and controlling the debris flow.By evaluating the debris flow of different recurrence intervals,further measures are recommended for managing debris flow events.

How far have we come?Review of main public policies to reduce landslide impacts in Brazil

During the rainy season in Brazil,landslides can have catastrophic consequences,including loss of life,damage to urban infrastructure and significant economic impacts.Now,more than eight million people in Brazil live in disaster-prone areas.The objective of this article is to present a chronological review of the principal policies and programmes at the national,state,and municipal levels,with an emphasis on their key actions aimed at mitigating the impact of disasters related to natural hazards,particularly landslides.Our analysis was based on official records of public policies from the national,state,and municipal governments.The results show that several initiatives were initially developed at the local and regional level.However,it was not until the late 1980s that a comprehensive organisation of civil protection at the national level emerged as a response measure.It is possible to highlight three phases(understanding,coexistence,and prevention)of institutional action focused on risk management in the face of disasters.Despite the growing knowledge of risk scenarios,disasters continue to occur in Brazil on an annual basis,revealing several obstacles to reducing their impact,particularly given the social and economic disparities between Brazilian regions and the applicability of public policies that must overcome the limitations of each municipality.

Coupling effect on the thermal hazard assessment of hazardous chemical materials via calorimetric technologies and simulation approaches

The coupling effect of heat absorption and release exists in the thermal decomposition of a few chemical materials.However,the impact of the above coupling on thermal hazard assessment is not considered in the literature studies.In this work,nitroguanidine(NQ)and 1,3,5-trinitro-1,3,5-triazine(RDX)are selected as representative materials to explore the influence of the coupling effect on the thermal hazard assessment of chemical materials.The linear heating experiments of NQ and RDX are carried out by a microcalorimeter and synchronous thermal analyser.The thermal decomposition curves are decoupled by advanced thermokinetics software.The thermal decomposition and kinetic parameters before and after decoupling are calculated.The results of TG experiment show that both NQ and RDX began to lose mass during the endothermic stage.The endothermic melting and exothermic decomposition of NQ and RDX are coupled within this stage.The coupling effect has different degrees of influence on its initial decomposition temperature and safety parameters.Compared with the parameters in the coupling state,the initial decomposition temperature and adiabatic induction period after decoupling decrease.The self-accelerating decomposition temperature increases,and internal thermal runaway time decreases.In the thermal hazard assessment of chemical materials with coupling effects,the calculated parameters after decoupling should be taken as an important safety index。

An extended social force model on unidirectional flow considering psychological and behavioral impacts of hazard source

An accurate assessment of the evacuation efficiency in case of disasters is of vital importance to the safety design of buildings and street blocks.Hazard sources not only physically but psychologically affect the pedestrians,which may further alter their behavioral patterns.This effect is especially significant in narrow spaces,such as corridors and alleys.This study aims to integrate a non-spreading hazard source into the social force model following the results from a previous experiment and simulation,and to simulate unidirectional pedestrian flows over various crowd densities and clarity–intensity properties of the hazard source.The integration include a virtual repulsion force from the hazard source and a decay on the social force term.The simulations reveal(i)that the hazard source creates virtual bottlenecks that suppress the flow,(ii)that the inter-pedestrian push forms a stabilisation phase on the flow-density curve within medium-to-high densities,and(iii)that the pedestrians are prone to a less orderly and stable pattern of movement in low clarity–intensity scenarios,possibly with lateral collisions passing the hazard source.

The Lambert-G Family:Properties,Inference,and Applications

This study proposes a new flexible family of distributions called the Lambert-G family.The Lambert family is very flexible and exhibits desirable properties.Its three-parameter special sub-models provide all significantmonotonic and non-monotonic failure rates.A special sub-model of the Lambert family called the Lambert-Lomax(LL)distribution is investigated.General expressions for the LL statistical properties are established.Characterizations of the LL distribution are addressed mathematically based on its hazard function.The estimation of the LL parameters is discussed using six estimation methods.The performance of this estimation method is explored through simulation experiments.The usefulness and flexibility of the LL distribution are demonstrated empirically using two real-life data sets.The LL model better fits the exponentiated Lomax,inverse power Lomax,Lomax-Rayleigh,power Lomax,and Lomax distributions.

Enhancing landslide hazards survey and management to reduce the loss of human lives and properties

Landslides are pervasive geohazards that pose a serious threat to human lives,property,and crucial engineering constructions.Annually,landslides lead to tens of thousands of fatalities(see the paper of"List of typical catastrophic landslides from March 2004 to February 2024"in this issue,doi:10.31035/cg2024079)and cause economic damages amounting to billions of dollars around the world,as well as disrupting crucial infrastructures such as railways,highways。

Investigation of Maxima Assumptions in Modelling Tropical Cyclone- Induced Hazards in the South China Sea

The present study aims to examine the suitability of two commonly used assumptions that simplify modelling metoceanconditions for designing offshore wind turbines in the South China Sea (SCS). The first assumption assumes thatjoint N-year extreme wind and wave events can be independently estimated and subsequently combined. The secondone assumes peak wind and waves can be modelled as occurring simultaneously during a tropical cyclone (TC) event.To better understand the potential TC activity, a set of 10000 years synthetic TC events are generated. The wind fieldmodel and the Mike 21 spectral wave model are employed to model the TC-induced hazards. Subsequently, theeffect of the assumptions is evaluated by analyzing the peak structural response of both monopile and semisubmersibleoffshore wind turbines during TC events. The results demonstrate that the examined assumptions are generally accurate.By assessing the implications of these assumptions, valuable insights are obtained, which can inform andimprove the modelling of TC-induced hazards in the SCS region.

Integrated hazard assessment of rockfall incidents in the Cap Aokas Cliff Region

Rock fall accidents in mountainous cliff areas have significant consequences for human life and transportation.This study aimed to evaluate the rockfall hazard in the Cap Aokas cliff region located along the northeast coast of Algeria by identifying the key factors contributing to rockfall occurrence.We employed a combination of kinematic analysis,Matterocking method,and 3D trajectory simulations to determine zones that are susceptible to rockfall mobilization.By using a probabilistic and structural approach in conjunction with photogrammetry,we identified the controlling factors.The kinematic analysis revealed the presence of five discontinuity families,which indicated both plane and wedge failure modes.The 3D trajectory simulations demonstrated that the falling blocks followed the stream direction.We then validated the susceptibility maps generated from the analysis using aerial photos and historical rockfall events.The findings of this study enhance our understanding of rockfall phenomena and provide valuable insights for the development of effective strategies to mitigate rockfall hazards.

Co-seismic surface displacement of the June 21, 2022 M_(W)6 Khōst,Afghanistan earthquake from InSAR observations

A robust estimation of the earthquake location, seismic moment, and fault geometry is essential for objective seismic hazard assessment. Seismic events in a remote location, specifically in the absence of seismic and GNSS networks, can be investigated effectively using the In SAR-based technique. This study adopts the Differential Interferometric SAR(DIn SAR) technique to quantify the co-seismic surface displacement caused by the June 21, 2022, Khōst M_(W)6 earthquake that occurred along the western plate boundary between the Indian and Eurasian plate. The interferograms show that the maximum surface deformation occurred on the northwest and southwest of the fault line. From coherence, the Line of Sight(LOS) displacement, and the co-seismic surface displacement analysis, it has been observed that surface deformation was most pronounced in the southwest region of the fault line, and the surface has moved to the opposite direction along the fault line, which indicates a sinistral slightly oblique strike-slip movement. This In SAR-based observation appears consistent with the seismic waveforms derived from co-seismic surface displacements. Further, it has been argued that the slip deficit accumulated during the period of the last about 48 years along the frontal region of the northward extension of the Suleiman range and associated fault zone is qualitatively estimated at about 1.5 m, which is consistent with the seismic waveforms derived finite slip model.

Research on intelligent search-and-secure technology in accelerator hazardous areas based on machine vision

Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.However,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale accelerators.By leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and security.Given the criticality of personal safety for stranded individuals,search and security processes must be sufficiently reliable.To ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring range.The YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the cameras.Furthermore,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive unit.This strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall rate.Specifically,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,respectively.Although there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software design.Experimental tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.

Preparation of lithium-ion battery anode materials from graphitized spent carbon cathode derived from aluminum electrolysis

Graphitized spent carbon cathode(SCC)is a hazardous solid waste generated in the aluminum electrolysis process.In this study,a flotation-acid leaching process is proposed for the purification of graphitized SCC,and the use of the purified SCC as an anode material for lithium-ion batteries is explored.The flotation and acid leaching processes were separately optimized through one-way experiments.The maximum SCC carbon content(93wt%)was achieved at a 90%proportion of−200-mesh flotation particle size,a slurry concentration of 10wt%,a rotation speed of 1600 r/min,and an inflatable capacity of 0.2 m^(3)/h(referred to as FSCC).In the subsequent acid leaching process,the SCC carbon content reached 99.58wt%at a leaching concentration of 5 mol/L,a leaching time of 100 min,a leaching temperature of 85°C,and an HCl/FSCC volume ratio of 5:1.The purified graphitized SCC(referred to as FSCC-CL)was utilized as an anode material,and it exhibited an initial capacity of 348.2 mAh/g at 0.1 C and a reversible capacity of 347.8 mAh/g after 100 cycles.Moreover,compared with commercial graphite,FSCC-CL exhibited better reversibility and cycle stability.Thus,purified SCC is an important candidate for anode material,and the flotation-acid leaching purification method is suitable for the resourceful recycling of SCC.