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.

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。

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.

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.

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.

Assessment of Radiological Hazards of Sedimentary, Igneous and Sediments Natural Rocks

Gamma-ray spectroscopy based on a 100% efficiency hyper-pure germanium detector was used to evaluate the activity concentrations of 226Ra, 232Th, and 40K natural radionuclides in sedimentary, conglomerate, igneous and sedi-ments rock samples collected from four different locations in Eastern desert in Egypt. The obtained activity concentrations are used to evaluate the radi-ological hazards indices, absorbed dose rate, annual effective dose equivalent in air, radium equivalent, external and internal hazard index, radiation level index, annual gonadal dose equivalent, excess lifetime cancer risk and expo-sure rate. The results show that 1) the absorbed dose rate depends on the rock type, 2) the annual effective dose equivalent in air in 71% of sample below 20 mSvy-1 (permissible limit for workers), 3) the conglomerate rocks show low radioactivity level, 4) sedimentary rocks are rich in radium while igneous rocks are rich in thorium and the sediments rocks are rich in both radium and thorium.

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.

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.

Deformation,structure and potential hazard of a landslide based on InSAR in Banbar county,Xizang(Tibet)

The Tibetan Plateau is characterized by complex geological conditions and a relatively fragile ecological environment.In recent years,there has been continuous development and increased human activity in the Tibetan Plateau region,leading to a rising risk of landslides.The landslide in Banbar County,Xizang(Tibet),have been perturbed by ongoing disturbances from human engineering activities,making it susceptible to instability and displaying distinct features.In this study,small baseline subset synthetic aperture radar interferometry(SBAS-InSAR)technology is used to obtain the Line of Sight(LOS)deformation velocity field in the study area,and then the slope-orientation deformation field of the landslide is obtained according to the spatial geometric relationship between the satellite’s LOS direction and the landslide.Subsequently,the landslide thickness is inverted by applying the mass conservation criterion.The results show that the movement area of the landslide is about 6.57×10^(4)m^(2),and the landslide volume is about 1.45×10^(6)m^(3).The maximum estimated thickness and average thickness of the landslide are 39 m and 22 m,respectively.The thickness estimation results align with the findings from on-site investigation,indicating the applicability of this method to large-scale earth slides.The deformation rate of the landslide exhibits a notable correlation with temperature variations,with rainfall playing a supportive role in the deformation process and displaying a certain lag.Human activities exert the most substantial influence on the spatial heterogeneity of landslide deformation,leading to the direct impact of several prominent deformation areas due to human interventions.Simultaneously,utilizing the long short-term memory(LSTM)model to predict landslide displacement,and the forecast results demonstrate the effectiveness of the LSTM model in predicting landslides that are in a continuous development and movement phase.The landslide is still active,and based on the spatial heterogeneity of landslide deformation,new recommendations have been proposed for the future management of the landslide in order to mitigate potential hazards associated with landslide instability.

Enhancing Hazardous Chemical Management in Chinese University Laboratories:Strategies for Safety and Efficiency

This paper examines the management of hazardous chemicals in Chinese university laboratories,identifying key challenges and proposing improvements.It reviews current practices and safety measures,highlighting deficiencies such as inadequate safety systems and insufficient awareness among personnel.The study emphasizes the necessity of tailored safety management systems,the integration of digital tracking technologies like Radio Frequency Identification,and enhanced safety training for staff.The proposed recommendations aim to mitigate risks and enhance laboratory safety and efficiency.In conclusion,the paper asserts that a comprehensive approach,encompassing improved management systems,technological advancements,and educational initiatives,is essential for safer chemical handling in academic research environments.

Application of Hazard Vulnerability Analysis Based on Kaiser Model in Neonatal Breast Milk Management

Objective:To analyze the existing risks in breast milk management at the neonatal department and provide corresponding countermeasures.Methods:22 risk events were identified in 7 risk links in the process of bottle-feeding of breast milk.Hazard Vulnerability Analysis based on the Kaiser model was applied to investigate and evaluate the risk events.Results:High-risk events include breast milk quality inspection,hand hygiene during collection,disinfection of collectors,cold chain management,hand hygiene during the reception,breast milk closed-loop management,and post-collection disposal.Root cause analysis of high-risk events was conducted and breast milk management strategies outside the hospital and within the neonatal department were proposed.Conclusion:Hazard Vulnerability Analysis based on the Kaiser model can identify and assess neonatal breast milk management risks effectively,which helps improve the management of neonatal breast milk.It is conducive to the safe development and promotion of bottle feeding of breast milk for neonates,ensuring the quality of medical services and the safety of children.

Recent Advances of Deep Learning in Geological Hazard Forecasting

Geological hazard is an adverse geological condition that can cause loss of life and property.Accurate prediction and analysis of geological hazards is an important and challenging task.In the past decade,there has been a great expansion of geohazard detection data and advancement in data-driven simulation techniques.In particular,great efforts have been made in applying deep learning to predict geohazards.To understand the recent progress in this field,this paper provides an overview of the commonly used data sources and deep neural networks in the prediction of a variety of geological hazards.

Potential seismic landslide hazard and engineering effect in the Ya’an-Linzhi section of the Sichuan-Tibet transportation corridor, China

The Sichuan-Tibet transportation corridor is located at the eastern margin of the Qinghai-Tibet Plateau,where the complex topography and geological conditions,developed geo-hazards have severely restricted the planning and construction of major projects.For the long-term prevention and early control of regional seismic landslides,based on analyzing seismic landslide characteristics,the Newmark model was used to carry out the potential seismic landslide hazard assessment with a 50-year beyond probability 10%.The results show that the high seismic landslide hazard is mainly distributed along large active tectonic belts and deep-cut river canyons,and are significantly affected by the active tectonics.The low seismic landslide hazard is mainly distributed in the flat terrain such as the Quaternary basins,broad river valleys,and plateau planation planes.The major east-west linear projects mainly pass through five areas with high seismic landslide hazard:Luding-Kangding section,Yajiang-Xinlong(Yalong river)section,Batang-Baiyu(Jinsha river)section,Basu(Nujiang river)section,and Bomi-Linzhi(eastern Himalaya syntaxis)section.The seismic action of the Bomi-Linzhi section can also induce high-risk geo-hazard chains such as the high-level glacial lake breaks and glacial debris flows.The early prevention of seismic landslides should be strengthened in the areas with high seismic landslide hazard.

Evaluation of the submarine debris-flow hazard risks to planned subsea pipeline systems: a case study in the Qiongdongnan Basin, South China Sea

The ever-increasing deepwater oil and gas development in the Qiongdongnan Basin,South China Sea has initiated the need to evaluate submarine debris-flow hazard risks to seafloor infrastructures.This paper presents a case study on evaluating the debris-flow hazard risks to the planned pipeline systems in this region.We used a numerical model to perform simulations to support this quantitative evaluation.First,one relict failure interpreted across the development site was simulated.The back-analysis modeling was used to validate the applicability of the rheological parameters.Then,this model was applied to forecast the runout behaviors of future debris flows originating from the unstable upslope regions considered to be the most critical to the pipeline systems surrounding the Manifolds A and B.The model results showed that the potential debris-flow hazard risks rely on the location of structures and the selection of rheological parameters.For the Manifold B and connected pipeline systems,because of their remote distances away from unstable canyon flanks,the potential debris flows impose few risks.However,the pipeline systems around the Manifold A are exposed to significant hazard risks from future debris flows with selected rheological parameters.These results are beneficial for the design of a more resilient pipeline route in consideration of future debris-flow hazard risks.

The Salient Issues of Coastal Hazards and Disasters in Nigeria

The Nigerian coastline which stretches about 853 km has four distinct morphological zones namely, Barrier Lagoon, Mahin Mud coast, Niger Delta and Strand coast. Nigeria’s coastal zone is richly blessed with various natural resources like oil, gas, fish, sand etc., which are presently being exploited for economic development. Coastal populations have increased erratically from about 20% of the National population in 1993 to approximately 51,037,122 m (30% of the national population) in 2011. Development of coastal areas in Nigeria is accelerating and user conflicts are increasing. Both natural and anthropogenic activities in the coastal zone are leading to coastal hazards and eventual rapid degradation of the area. Significant coastal hazards include coastal erosion, storm surges, floods, land subsidence, pollution, especially oil spills and possibly seismicity, which could lead to earthquakes and tsunamis. These hazards are leading to disasters and effecting the socio-economic sustainability of the coastal area.

Occupational Health and Safety Hazards Experienced by Healthcare Workers at Two Hospitals in Suyani, Bono Region, Ghana

INTRODUCTION Occupational safety and health (OSH) is generally the anticipation, recognition, evaluation, and control of hazards arising in or from the workplace. The study sought to assess and evaluate occupational health and safety hazards experienced among health workers in the Bono region of Ghana. METHODOLOGY The study was descriptive cross-sectional quantitative study. Data was from two hundred (200) health workers and was analyzed using the binary logistic regression analysis. RESULTS The findings from the study show that risk factors associated with biological hazards were clinical staff [OR = 2.487 (1.146 - 5.397), p = 0.021], poor maintenance of hospital items [OR = 0.446 (0.240 - 0.831), p = 0.011], assault (verbal) abuse [OR = 2.581 (1.317 - 5.059), p = 0.006] and extreme pressure from work [OR = 2.975 (1.519 - 5.829), p = 0.001]. Non-biological hazards were associated with being single [OR = 0.499 (0.263 - 0.947), p = 0.034], being verbally assaulted [OR = 3.581 (1.865 - 6.876), p CONCLUSION Risk factors related with biological hazards include poor maintenance of hospital items and extreme pressure from work whereas non-biological hazards were associated with being single, being verbally assaulted. Clinical healthcare providers are more vulnerable to occupational health and safety hazards. The study recommends the provision of strategic policies to promote and protect the workers’ health based on the development of the epidemiological profile of health, needs to be readjusted and strengthened.

Application of logistic regression model for hazard assessment of landslides caused by the 2012 Yiliang Ms 5.7 earthquake in Yunnan Province,China

Accurate assessment of seismic landslides hazard is a prerequisite and foundation for postdisaster relief of earthquakes.An Ms 5.7 earthquake occurring on September 7,2012,in Yiliang County,Yunnan Province,China,triggered hundreds of landslides.To explore the characteristics of coseismic landslides caused by this moderate-strong earthquake and their significance in predicting seismic landslides regionally,this study uses an artificial visual interpretation method based on a planet image with 5-m resolution to obtain the information of the coseismic landslides and establishes a coseismic landslide database containing data on 232 landslides.Nine influencing factors of landslides were selected for this study:elevation,relative elevation,slope angle,aspect,slope position,distance to river system,distance to faults,strata,and peak ground acceleration.The real probability of coseismic landslide occurrence is calculated by combining the Bayesian probability and logistic regression model.Based on the coseismic landslides,the probabilities of landslide occurrence under different peak ground acceleration are predicted using a logistic regression model.Finally,the model established in this paper is used to calculate the landslide probability of the Ludian Ms 6.5 earthquake that occurred in August 2014,78.9 km away from the macro-epicenter of the Yiliang earthquake.The probability is verified by the real coseismic landslides of this earthquake,which confirms the reliability of the method presented in this paper.This study proves that the model established according to the seismic landslides triggered by one earthquake has a good effect on the seismic landslides hazard assessment of similar magnitude,and can provide a reference for seismic landslides prediction of moderate-strong earthquakes in this region.

Thinking on Effective Methods of Successful Prediction of Geological Hazards in Shaanxi, China

In the process of human survival and development, it is inevitable to transform the original state of the world, thus forming a contradiction between the earth and the earth. The violent form of this contradiction is geological disasters. Geological disasters pose a threat to human life and property, and cause damage caused by natural or human factors, often causing casualties. The destruction process of geological disasters is usually a gradual process, showing many pre-disaster symptoms, such as local landslides, surface cracks, building deformation, tree skew, and ground sound. Evacuation can be avoided in advance according to the disaster precursors, so as to avoid casualties and achieve successful prediction. By reviewing the general situation of geological disasters in Shaanxi Province and the casualties in 2020, the difficulties in the prevention and control of geological disasters are summarized. In view of these difficulties, an on-site investigation, visit and analysis of geological disaster points and successful forecast points in Shaanxi Province in 2020 were conducted. In addition, combined with actual cases and years of work experience, the successful prediction experience of geological disasters was discussed from 8 aspects. Finally, the “Regulations on the Reward for Successful Geological Disaster Forecasting in Shaanxi Province” was revised in order to improve the successful prediction ability of geological disasters in Shaanxi Province and even the whole country, provide reference for future prevention and control of geological disasters, and effectively protect the safety of people’s lives and property.

An Adaptive Approach for Hazard Regression Modeling

Regression models for survival time data involve estimation of the hazard rate as a function of predictor variables and associated slope parameters. An adaptive approach is formulated for such hazard regression modeling. The hazard rate is modeled using fractional polynomials, that is, linear combinations of products of power transforms of time together with other available predictors. These fractional polynomial models are restricted to generating positive-valued hazard rates and decreasing survival times. Exponentially distributed survival times are a special case. Parameters are estimated using maximum likelihood estimation allowing for right censored survival times. Models are evaluated and compared using likelihood cross-validation (LCV) scores. LCV scores and tolerance parameters are used to control an adaptive search through alternative fractional polynomial hazard rate models to identify effective models for the underlying survival time data. These methods are demonstrated using two different survival time data sets including survival times for lung cancer patients and for multiple myeloma patients. For the lung cancer data, the hazard rate depends distinctly on time. However, controlling for cell type provides a distinct improvement while the hazard rate depends only on cell type and no longer on time. Furthermore, Cox regression is unable to identify a cell type effect. For the multiple myeloma data, the hazard rate also depends distinctly on time. Moreover, consideration of hemoglobin at diagnosis provides a distinct improvement, the hazard rate still depends distinctly on time, and hemoglobin distinctly moderates the effect of time on the hazard rate. These results indicate that adaptive hazard rate modeling can provide unique insights into survival time data.