Dynamic Voting Classifier for Risk Identification in Supply Chain 4.0

Supply chain 4.0 refers to the fourth industrial revolution’s supply chain management systems,which integrate the supply chain’s manufacturing operations,information technology,and telecommunication processes.Although supply chain 4.0 aims to improve supply chains’production systems and profitability,it is subject to different operational and disruptive risks.Operational risks are a big challenge in the cycle of supply chain 4.0 for controlling the demand and supply operations to produce and deliver products across IT systems.This paper proposes a voting classifier to identify the operational risks in the supply chain 4.0 based on a Sine Cosine Dynamic Group(SCDG)algorithm.Exploration and exploitation mechanisms of the basic Sine Cosine Algorithm(CSA)are adjusted and controlled by two groups of agents that can be changed dynamically during the iterations.External and internal features were collected and analyzed from different data sources of service level agreements and transaction data from various KSA firms to validate the proposed algorithm’s efficiency.A balanced accuracy of 0.989 and a Mean Square Error(MSE)of 0.0476 were achieved compared with other optimization-based classifier techniques.A one-way analysis of variance(ANOVA)and Wilcoxon rank-sum tests were performed to show the superiority of the proposed SCDG algorithm.Thus,the experimental results indicate the effectiveness of the proposed SCDG algorithm-based voting classifier.

Review of Empirical Studies on Climate Risk—Effects and Activism

This review focuses on major contemporary empirical studies that examine both the physical and regulatory sides of climate risk. These studies explore how climate risk affects firms’ operating performance and leverage, stock and bond valuation, cost of capital, and managerial behavior. We also discuss how the effect of climate risk on real estate markets depends on individuals’ beliefs about climate change. Furthermore, we summarize papers on climate risk activism and how firms can employ financial devices and technology to mitigate their climate risk. Finally, we make some recommendations for further research areas.

Association between autoimmune gastritis and gastric polyps:Clinical characteristics and risk factors

BACKGROUND The relationship between autoimmune gastritis(AIG)and gastric polyps(GPs)is not well understood.AIM To explore the clinical characteristics and risk factors of AIG with GPs in patients.METHODS This double center retrospective study included 530 patients diagnosed with AIG from July 2019 to July 2023.We collected clinical,biochemical,serological,and demographic data were of each patient.Logistic regression analyses,both multivariate and univariate,were conducted to pinpoint independent risk factors for GPs in patients with AIG patients.Receiver operating characteristic curves were utilized to establish the optimal cutoff values,sensitivity,and specificity of these risk factors for predicting GPs in patients with AIG.RESULTS Patients with GPs had a higher median age than those without GPs[61(52.25-69)years vs 58(47-66)years,P=0.006].The gastrin-17 levels were significantly elevated in patients with GPs compared with those without GPs[91.9(34.2-138.9)pmol/mL vs 60.9(12.6-98.4)pmol/mL,P<0.001].Additionally,the positive rate of parietal cell antibody(PCA)antibody was higher in these patients than in those without GPs(88.6%vs 73.6%,P<0.001).Multivariate and univariate analyses revealed that PCA positivity[odds ratio(OR)=2.003,P=0.017],pepsinogen II(OR=1.053,P=0.015),and enterochromaffin like cells hyperplasia(OR=3.116,P<0.001)were significant risk factors for GPs,while pepsinogen I was identified as a protective factor.CONCLUSION PCA positivity and enterochromaffin like cells hyperplasia are significant risk factor for the development of GPs in patients with AIG.Elevated gastrin-17 levels may also play a role in this process.These findings suggest potential targets for further research and therapeutic intervention in managing GPs in patients with AIG.

Prediabetes and atrial fibrillation risk stratification,phenotyping,and possible reversal to normoglycemia

Patients admitted with prediabetes and atrial fibrillation are at high risk for major adverse cardiac or cerebrovascular events independent of confounding variables.The shared pathophysiology between these three serious but common diseases and their association with atherosclerotic cardiovascular risk factors establish a vicious circle culminating in high atherogenicity.Because of that,it is of paramount importance to perform risk stratification of patients with prediabetes to define phenotypes that benefit from various interventions.Furthermore,stress hyperglycemia assessment of hospitalized patients and consensus on the definition of prediabetes is vital.The roles lifestyle and metformin play in prediabetes are well established.However,the role of glucagon-like peptide agonists and metabolic surgery is less clear.Prediabetes is considered an intermediate between normoglycemia and diabetes along the blood glucose continuum.One billion people are expected to suffer from prediabetes by the year 2045.Therefore,realworld randomized controlled trials to assess major adverse cardiac or cerebrovascular event risk reduction and reversal/prevention of type 2 diabetes among patients are needed to determine the proper interventions.

Burden of mental disorders and risk factors in the Western Pacific region from 1990 to 2021

BACKGROUND The burden of mental disorders(MD)in the Western Pacific Region(WPR)re-mains a critical public health concern,with substantial variations across demogra-phics and countries.AIM To analyze the burden of MD in the WPR from 1990 to 2021,along with associated risk factors,to reveal changing trends and emerging challenges.METHODS We used data from the Global Burden of Disease 2021,analyzing prevalence,incidence,and disability-adjusted life years(DALYs)of MD from 1990 to 2021.Statistical methods included age-standardisation and uncertainty analysis to address variations in population structure and data completeness.RESULTS Between 1990 and 2021,the prevalence of MD rose from 174.40 million cases[95%uncertainty interval(UI):160.17-189.84]to 234.90 million cases(95%UI:219.04-252.50),with corresponding DALYs increasing from 22.8 million(95%UI:17.22-28.79)to 32.07 million(95%UI:24.50-40.68).During this period,the burden of MD shifted towards older age groups.Depressive and anxiety disorders were predominant,with females showing higher DALYs for depressive and anxiety disorders,and males more affected by conduct disorders,attention-deficit hyperactivity disorder,and autism spectrum disorders.Australia,New Zealand,and Malaysia reported the highest burdens,whereas Vietnam,China,and Brunei Darussalam reported the lowest.Additionally,childhood sexual abuse and bullying,and intimate partner violence emerged as significant risk factors.CONCLUSION This study highlights the significant burden of MD in the WPR,with variations by age,gender,and nation.The coronavirus disease 2019 pandemic has exacerbated the situation,emphasizing the need for a coordinated response.

Arsenic and fluoride co-enrichment of groundwater in the loess areas and associated human health risks:A case study of Dali County in the Guanzhong Basin

This study aims to reveal the occurrence and origin of typical groundwater with high arsenic and fluoride concentrations in the loess area of the Guanzhong Basin—a Neogene faulted basin.Key findings are as follows:(1)Groundwater samples with high arsenic and fluoride concentrations collected from the loess area and the terraces of the Weihe River accounted for 26%and 30%,respectively,of the total samples,with primary hydrochemical type identified as HCO_(3)-Na.The karst and sand areas exhibit relatively high groundwater quality,serving as preferred sources for water supply.It is recommended that local governments fully harness groundwater in these areas;(2)groundwater with high arsenic and fluoride concentrations in the loess area and the alluvial plain of rivers in Dali County is primarily distributed within the Guanzhong Basin,which represents the drainage zone of groundwater;(3)arsenic and fluoride in groundwater originate principally from natural and anthropogenic sources;(4)the human health risk assessments reveal that long-term intake of groundwater with high arsenic and fluoride concentrations pose cancer or non-cancer risks,which are more serious to kids compared to adults.This study provides a theoretical basis for the prevention and treatment of groundwater with high arsenic and fluoride concentrations in loess areas.

Rolling Decision Model of Thermal Power Retrofit and Generation Expansion Planning Considering Carbon Emissions and Power Balance Risk

With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.

Planetary health risks in urban agriculture

Urban agriculture is gaining recognition for its potential contributions to environmental resilience and climate change adaptation,providing advantages such as urban greening,reduced heat island effects,and decreased air pollution.Moreover,it indirectly supports communities during weather events and natural disasters,ensuring food security and fostering community cohesion.However,concerns about planetary health risks persist in highly urbanized and climate-affected areas.Employing electronic databases such as Web of Science and PubMed and adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines,we identified 55 relevant papers to comprehend the planetary health risks associated with urban agriculture,The literature review identified five distinct health risks related to urban agriculture:(1)trace metal risks in urban farms;(2)health risks associated with wastewater irrigation;(3)zoonotic risks;(4)other health risks;and(5)social and economic risks.The study highlights that urban agriculture,while emphasizing environmental benefits,particularly raises concerns about trace metal bioaccumulation in soil and vegetables,posing health risks for populations.Other well studied risks included wastewater irrigation and backyard livestock farming.The main limitations in the available literature were in studying infectious diseases and antibiotic resistance associated with urban agriculture.

Contamination assessment,source apportionment and associated health risks of PTEs in agricultural soil under five land-use patterns in Sanya,China

To understand the levels of potentially toxic elements(PTEs)contamination in soils and their effects on human health from different agricultural land use in Sanya,China.128 soil samples(64 topsoil samples and corresponding subsoil samples)were collected from the five representative land-use patterns.Inductively coupled plasma mass spectrometry(ICP-MS),Atomic fluorescence spectrometry(AFS),and Inductively coupled plasma optical emission spectrometry(ICP-OES)were used to determine the content of PTEs(As,Cd,Hg,Cu,Cr,Ni,Pb,Zn,Co,Mo,Sb,and V).Correlation analysis and factor analysis were used to determine the source of PTEs.Geo-accumulation index(I_(geo)),hazard quotient(HQ),and total carcinogenic risk index(TR)were used to measure the PTEs contamination and its relative health impacts.Results showed that the average values of 12 PTEs in topsoil were higher than the Hainan soil geochemical baseline,showing different degrees of PTEs accumulation effect.The concentration of PTEs in the topsoil was lower than those in the subsoil except for Cd and Hg.The I_(geo)revealed that the major accumulated element in soils was As followed by Mo.Source apportionment suggested that parent materials and agricultural practices were the dominant factors for PTEs accumulation in the topsoil.Noncarcinogenic risks of soil samples from five land-use patterns presented a trend of paddy field>dry field>woodland>orchard>garden plot.However,the HQ values of 12 PTEs were less than the recommended limit of HQ=1,representing that there are no non-carcinogenic risks of PTEs for children and adults in the study area.The TR values are within 6.95×10^(-6)-1.38×10^(-5),which corresponds to the low level.Therefore the PTEs in the agricultural soil of the study area show little influence on the health status of the local population.

Wind risk and mitigation calculator framework for determining the wind annualized risk for single- and multi-family homes to support resilient community decision-making

Communicating risks and mitigation benefits associated with natural hazards such as wind to the general public is challenging given the location-dependency of parameters and the complexity of the problem.Web tools play a crucial role in educating residents,decision-makers,and stakeholders regarding potential wind hazard losses to,for example,residential buildings.However,a notable gap exists on the practical incorporation of mitigation actions within these tools.This gap hampers the collective awareness and understanding among stakeholders,communities,and citizens regarding the tangible advantages of mitigation strategies in reducing wind-related risks.Furthermore,there exists a need to elucidate the functionality and objectives of these tools in a more accessible manner.This study aims to present and outline the wind risk and mitigation calculator tool(WRMCT)within the Hazardaware platform,which is an address-based risk assessment tool.This tool,developed for 196 counties in the Gulf of Mexico coastal area,facilitates users’education of potential risks and benefits associated with mitigation strategies.WRMCT enables users to access location-specific wind risk and interactively suggests potential mitigation actions along with economic savings to support informed decisions and residential risk reduction.WRMCT intends to enhance users’ability to make informed decisions,take proactive measures in mitigating wind hazards,and contribute to the development of resilient,residential communities.

基于voting集成的智能电能表故障多分类方法

为提升智能电能表故障准确分类能力,助力维护人员迅速排除故障,提出基于投票法voting集成的智能电能表故障多分类方法。针对实际智能电能表故障数据进行编码预处理,基于皮尔逊系数法筛选智能电能表故障分类关键影响因素,结合合成少数类过采样技术(synthetic minority oversampling technique, SMOTE)算法解决数据类别不平衡问题,由此建立模型所需数据集,再通过投票法进行模型融合,结合粒子群PSO(particle swarm optimization)确定各基模型的权重,据此构建基于极限梯度提升树(extreme gradient boosting trees, XGBT)、K近邻(k-nearest neighbor, KNN)和朴素贝叶斯(naive bayes, NB)模型的智能电能表故障多分类方法。实测实验结果表明:所提出方法能有效实现智能电能表的故障快速准确分类,与现有方法相比,在智能电能表的故障分类精确率、召回率及F1-Score均有明显提升。

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

Effectiveness of colorectal cancer screening integrating non-genetic and genetic risk: a prospective study based on UK Biobank data

Objective: Few studies have evaluated the benefits of colorectal cancer(CRC) screening integrating both non-genetic and genetic risk factors. Here, we aimed to integrate an existing non-genetic risk model(QCancer-10) and a 139-variant polygenic risk score to evaluate the effectiveness of screening on CRC incidence and mortality.Methods: We applied the integrated model to calculate 10-year CRC risk for 430,908 participants in the UK Biobank, and divided the participants into low-, intermediate-, and high-risk groups. We calculated the screening-associated hazard ratios(HRs) and absolute risk reductions(ARRs) for CRC incidence and mortality according to risk stratification.Results: During a median follow-up of 11.03 years and 12.60 years, we observed 5,158 CRC cases and 1,487 CRC deaths, respectively. CRC incidence and mortality were significantly lower among screened than non-screened participants in both the intermediateand high-risk groups [incidence: HR: 0.87, 95% confidence interval(CI): 0.81±0.94;0.81, 0.73±0.90;mortality: 0.75, 0.64±0.87;0.70, 0.58±0.85], which composed approximately 60% of the study population. The ARRs(95% CI) were 0.17(0.11±0.24) and 0.43(0.24±0.61), respectively, for CRC incidence, and 0.08(0.05±0.11) and 0.24(0.15±0.33), respectively, for mortality. Screening did not significantly reduce the relative or absolute risk of CRC incidence and mortality in the low-risk group. Further analysis revealed that screening was most effective for men and individuals with distal CRC among the intermediate to high-risk groups.Conclusions: After integrating both genetic and non-genetic factors, our findings provided priority evidence of risk-stratified CRC screening and valuable insights for the rational allocation of health resources.

Prediabetes: An overlooked risk factor for major adverse cardiac and cerebrovascular events in atrial fibrillation patients

BACKGROUND Prediabetes is a well-established risk factor for major adverse cardiac and cerebrovascular events(MACCE).However,the relationship between prediabetes and MACCE in atrial fibrillation(AF)patients has not been extensively studied.Therefore,this study aimed to establish a link between prediabetes and MACCE in AF patients.AIM To investigate a link between prediabetes and MACCE in AF patients.METHODS We used the National Inpatient Sample(2019)and relevant ICD-10 CM codes to identify hospitalizations with AF and categorized them into groups with and without prediabetes,excluding diabetics.The primary outcome was MACCE(all-cause inpatient mortality,cardiac arrest including ventricular fibrillation,and stroke)in AF-related hospitalizations.RESULTS Of the 2965875 AF-related hospitalizations for MACCE,47505(1.6%)were among patients with prediabetes.The prediabetes cohort was relatively younger(median 75 vs 78 years),and often consisted of males(56.3%vs 51.4%),blacks(9.8%vs 7.9%),Hispanics(7.3%vs 4.3%),and Asians(4.7%vs 1.6%)than the non-prediabetic cohort(P<0.001).The prediabetes group had significantly higher rates of hypertension,hyperlipidemia,smoking,obesity,drug abuse,prior myocardial infarction,peripheral vascular disease,and hyperthyroidism(all P<0.05).The prediabetes cohort was often discharged routinely(51.1%vs 41.1%),but more frequently required home health care(23.6%vs 21.0%)and had higher costs.After adjusting for baseline characteristics or comorbidities,the prediabetes cohort with AF admissions showed a higher rate and significantly higher odds of MACCE compared to the non-prediabetic cohort[18.6%vs 14.7%,odds ratio(OR)1.34,95%confidence interval 1.26-1.42,P<0.001].On subgroup analyses,males had a stronger association(aOR 1.43)compared to females(aOR 1.22),whereas on the race-wise comparison,Hispanics(aOR 1.43)and Asians(aOR 1.36)had a stronger association with MACCE with prediabetes vs whites(aOR 1.33)and blacks(aOR 1.21).CONCLUSION This population-based study found a significant association between prediabetes and MACCE in AF patients.Therefore,there is a need for further research to actively screen and manage prediabetes in AF to prevent MACCE.

Identifying the Hydrochemical Characteristics,Genetic Mechanisms and Potential Human Health Risks of Fluoride and Nitrate Enriched Groundwater in the Tongzhou District,Beijing,North China

Fluoride and nitrate enriched groundwater are potential threats to the safety of the groundwater supply that may cause significant effects on human health and public safety,especially in aggregated population areas and economic hubs.This study focuses on the high F^(−)and NO_(3)^(−)concentration groundwater in Tongzhou District,Beijing,North China.A total of 36 groundwater samples were collected to analyze the hydrochemical characteristics,elucidate genetic mechanisms and evaluate the potential human health risks.The results of the analysis indicate:Firstly,most of the groundwater samples are characterized by Mg-HCO_(3) and Na-HCO_(3) with the pH ranging from 7.19 to 8.28 and TDS with a large variation across the range 471-2337 mg/L.The NO_(3)^(−)concentration in 38.89%groundwater samples and the F^(−)concentration in 66.67%groundwater samples exceed the permissible limited value.Secondly,F^(−)in groundwater originates predominantly from water-rock interactions and the fluorite dissolution,which is also regulated by cation exchange,competitive adsorption of HCO_(3)−and an alkaline environment.Thirdly,the effect of sewage disposal and agricultural activities have a significant effect on high NO3-concentration,while the high F^(−)concentration is less influenced by anthropogenic activity.The alkaline environment favors nitrification,thus being conducive to the production of NO_(3)^(−).Finally,the health risk assessment is evaluated for different population groups.The results indicate that high NO_(3)^(−)and F^(−)concentration in groundwater would have the largest threat to children’s health.The findings of this study could contribute to the provision of a scientific basis for groundwater supply policy formulation relating to public health in Tongzhou District.

Predicting potential invasion risks of Leucaena leucocephala(Lam.)de Wit in the arid area of Saudi Arabia

The presence of invasive plant species poses a substantial ecological impact,thus comprehensive evaluation of their potential range and risk under the influence of climate change is necessary.This study uses maximum entropy(MaxEnt)modeling to forecast the likelihood of Leucaena leucocephala(Lam.)de Wit invasion in Saudi Arabia under present and future climate change scenarios.Utilizing the MaxEnt modeling,we integrated climatic and soil data to predict habitat suitability for the invasive species.We conducted a detailed analysis of the distribution patterns of the species,using climate variables and ecological factors.We focused on the important influence of temperature seasonality,temperature annual range,and precipitation seasonality.The distribution modeling used robust measures of area under the curve(AUC)and receiver-operator characteristic(ROC)curves,to map the invasion extent,which has a high level of accuracy in identifying appropriate habitats.The complex interaction that influenced the invasion of L.leucocephala was highlighted by the environmental parameters using Jackknife test.Presently,the actual geographic area where L.leucocephala was found in Saudi Arabia was considerably smaller than the theoretical maximum range,suggesting that it had the capacity to expand further.The MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC curve.Precipitation and temperature were the primary factors influencing the potential distribution of L.leucocephala.Currently,an estimated area of 216,342 km^(2)in Saudi Arabia was at a high probability of invasion by L.leucocephala.We investigated the potential for increased invasion hazards in the future due to climate change scenarios(Shared Socioeconomic Pathways(SSPs)245 and 585).The analysis of key climatic variables,including temperature seasonality and annual range,along with soil properties such as clay composition and nitrogen content,unveiled their substantial influence on the distribution dynamic of L.leucocephala.Our findings indicated a significant expansion of high risk zones.High-risk zones for L.leucocephala invasion in the current climate conditions had notable expansions projected under future climate scenarios,particularly evident in southern Makkah,Al Bahah,Madina,and Asir areas.The results,backed by thorough spatial studies,emphasize the need to reduce the possible ecological impacts of climate change on the spread of L.leucocephala.Moreover,the study provides valuable strategic insights for the management of invasion,highlighting the intricate relationship between climate change,habitat appropriateness,and the risks associated with invasive species.Proactive techniques are suggested to avoid and manage the spread of L.leucocephala,considering its high potential for future spread.This study enhances the overall comprehension of the dynamics of invasive species by combining modeling techniques with ecological knowledge.It also provides valuable information for decision-making to implement efficient conservation and management strategies in response to changing environmental conditions.

Automatic detection of small bowel lesions with different bleeding risks based on deep learning models

BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some unresolved challenges.AIM To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups.METHODS The proposed model represents a two-stage method that combined image classification with object detection.First,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid images.Then,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was marked.We constructed training and testing sets and compared model-assisted reading with physician reading.RESULTS The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single module.The sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’diagnoses.The image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.

Development of Localized Assessment of Municipal Wastewater Disposal Risks

A means to develop a comparative assessment of the risks of available wastewater effluent disposal options on a local scale needs to be developed to help local decision-makers make decisions on options such as direct or indirect potable reuse options. These options have garnered more interest as a result of water supply limitations in many urban areas. This risk assessment was developed from a risk assessment developed at the University of Miami in 2001 and Florida Atlantic University (FAU) in 2023. Direct potable reuse and injection wells were deemed to have the lowest risk in the most recent study by FAU. However, the injection well option may not be available everywhere. As a result, a more local means to assess exposure risk is needed. This paper outlines the process to evaluate the public health risks associated with available disposal alternatives which may be very limited in some areas. The development of exposure pathways can help local decision-makers define the challenges, and support later expert level analysis upon which public health decisions are based.