Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network

Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.

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.

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.

A multi-source information fusion layer counting method for penetration fuze based on TCN-LSTM

When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

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.

Conceptual Strategy for Mitigating the Risk of Hydrogen as an Internal Hazard in Case of Severe Accidents at Nuclear Power Plant Considering Existing Risks and Uncertainties Associated with the Use of Traditional Strategies

Hydrogen challenge mitigation stands as one of the main objectives in the management of severe accidents at Nuclear Power Plants (NPPs). Key strategies for hydrogen control include atmospheric inertization and hydrogen removal with Passive Autocatalytic Recombiners (PARs) being a commonly accepted approach. However, an examination of PAR operation specificity reveals potential inefficiencies and reliability issues in certain severe accident scenarios. Moreover, during the in-vessel stage of severe accident development, in some severe accident scenarios PARs can unexpectedly become a source of hydrogen detonation. The effectiveness of hydrogen removal systems depends on various factors, including the chosen strategies, severe accident scenarios, reactor building design, and other influencing factors. Consequently, a comprehensive hydrogen mitigation strategy must effectively incorporate a combination of strategies rather than be based on one strategy, taking into consideration the probabilistic risks and uncertainties associated with the implementation of PARs or other traditional methods. In response to these considerations, within the framework of this research it has been suggested a conceptual strategy to mitigate the hydrogen challenge during the in-vessel stage of severe accident development.

Cholinesterase Activity as an Indicator of Health Risks among Kou Valley Farmers

Introduction: Pesticides are currently an essential component of agricultural production techniques for controlling pests and weeds. In Burkina Faso, non-compliance with good practice in the use of pesticides poses a real health problem for the population. This study examines the health risks associated with pesticide management in rice-growing areas. Material and Methods: A field survey was conducted in Bama, involving farmers, focusing on their socio-demographic characteristics, pesticide usage, and health effects. Cholinesterase levels were measured in subsample of farmers using a portable device. Data were analysed using Microsoft Excel, calculating means and percentages for various practices. Health consultations, protection methods, and pesticide management were studied. Erythrocyte acetylcholinesterase activity was compared before and after treatment. Data were categorised into classes based on inhibition levels, and correlation analyses determined relationships between variables such as age, years of experience, and cholinesterase activity. Results: The results indicate that rice cultivation is mainly carried out by a fairly young population, with nearly 63% being under the age of 50. Common poor practices in pesticide use include improper storage and reuse of leftover pesticides. Seven types of pesticides were identified, including organophosphates such as glyphosate, which was used in 26.7% of cases. This organophosphate has resulted in class B poisoning, causing a 30% - 50% reduction in erythrocyte cholinesterase activity. The health effects of pesticide use are felt by agricultural farmers through various symptoms of poisoning. Conclusion: To reduce the occurrence of pesticide poisoning, it is essential to launch information and awareness campaigns among the population and farmers to promote safe practices in pesticide use in Bama, Burkina Faso.

Runout prediction of potential landslides based on the multi-source data collaboration analysis on historical cases

Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.

Predictive factors for percutaneous nephrolithotomy bleeding risks

Objective:This study aimed to identify predictive factors for percutaneous nephrolithotomy(PCNL)bleeding risks.With better risk stratification,bleeding in high-risk patient can be anticipated and facilitates early identification.Methods:A prospective observational study of PCNL performed at our institution was done.All adults with radio-opaque renal stones planned for PCNL were included except those with coagulopathy,planned for additional procedures.Factors including gender,co-morbidities,body mass index,stone burden,puncture site,tract dilatation size,operative position,surgeon's seniority,and operative duration were studied using stepwise multivariate regression analysis to identify the predictive factors associated with higher estimated hemoglobin(Hb)deficiency.Results:Overall,4.86%patients(n=7)received packed cells transfusion.The mean estimated Hb deficiency was 1.3(range 0-6.5)g/dL and the median was 1.0 g/dL.Stepwise multivariate regression analysis revealed that absence of hypertension(p=0.024),puncture site(p=0.027),and operative duration(p=0.023)were significantly associated with higher estimated Hb deficiency.However,the effect sizes are rather small with partial eta-squared of 0.037,0.066,and 0.038,respectively.Observed power obtained was 0.621,0.722,and 0.625,respectively.Other factors studied did not correlate with Hb difference.Conclusion:Hypertension,puncture site,and operative duration have significant impact on estimated Hb deficiency during PCNL.However,the effect size is rather small despite adequate study power obtained.Nonetheless,operative position(supine or prone),puncture number,or tract dilatation size did not correlate with Hb difference.The mainstay of reducing bleeding in PCNL is still meticulous operative technique.Our study findings also suggest that PCNL can be safely done by urology trainees under supervision in suitably selected patient,without increasing risk of bleeding.

A Web-Based Approach for the Efficient Management of Massive Multi-source 3D Models

Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.

Roles of Community Pharmacists in Screening and Disseminating of Information about Non-Steroidal Anti-Inflammatory Drugs Risks: Implications for Drug Safety Assessment

Background: The increasing use of non-steroidal anti-inflammatory drugs (NSAIDs) both on prescription and over the counter raises a major global health concern because of the risks associated with their use if no proper guidance is given by the health care provider. This study assessed the roles of community pharmacists in screening and disseminating information about the risks associated with NSAID use in Zambia. Methodology: This was a national cross-sectional study in which a structured self-administered questionnaire was administered to 245 registered community pharmacists in Zambia. Stata/BE, version 15.1 (Stata Corporation, College Station, Texas, USA) and multivariate logistic regression model was used to determine factors associated with information dissemination about ADRs of NS-NSAIDs. Results: 231 of the 245 distributed questionnaires were returned giving a response rate of 94.3%. All (100%) participating community pharmacists claimed to have practiced dispensing NSAIDs. However, only 26 (11.0%) and 71 (30.8%) regularly screened for risk factor of selective COX-2 NSAIDS (SC2-NSAIDS) and non-selective NSAIDS (NS-NSAIDs) respectively. Information dissemination on adverse drug reactions (ADRs) of SC2-NSAIDS was regularly provided by only 22 (9.5%) of pharmacists while that of NS-NSAIDs was regularly provided by 49 (21.2%). In the multivariate logistic regression model, being the owner of a pharmacy (AOR: 5.4, CI: 1.84 - 16.4) was significantly associated with information dissemination about ADRs of NS-NSAIDs while an hour increase in the working hours per day (AOR: 0.9, CI: 0.64 - 0.95) was associated with less likelihood of information dissemination. Conclusion: Pharmacists working in community pharmacies in Zambia did not regularly screen and disseminate information about the risks associated with NSAID use. Therefore, pharmacists should be able to screen and monitor patients at risk and be aware of the majority of risk factors while dispensing NSAIDs to minimize the associated complications.

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.

Blast injury risks to humans within a military trench

In land warfare,trenches serve as vital defensive fortifications,offering protection to soldiers while engaging in combat.However,despite their protective function,soldiers often sustain injuries within these trenches.The lack of corresponding blast data alongside empirical injury reports presents a significant knowledge gap,particularly concerning the blast pressures propagating within trench spaces following nearby explosions.This absence hinders the correlation between blast parameters,trench geometry,and reported injury cases,limiting our understanding of blast-related risks within trenches.This paper addresses the critical aspect of blast propagation within trench systems,essential for evaluating potential blast injury risks to individuals within these structures.Through advanced computational fluid dynamics(CFD)simulations,the study comprehensively investigates blast injury risks resulting from explosions near military trenches.Employing a sophisticated computational model,the research analyzes the dynamic blast effects within trenches,considering both geometrical parameters and blast characteristics influenced by explosive weight and scaled distance.The numerical simulations yield valuable insights into the impact of these parameters on blast injury risks,particularly focusing on eardrum rupture,lung injury,and traumatic brain injury levels within the trench.The findings elucidate distinct patterns of high-risk zones,highlighting unique characteristics of internal explosions due to confinement and venting dynamics along the trench.This study underscores the significance of detailed numerical modeling in assessing blast injury risks and provides a novel knowledge base for understanding risks associated with explosives detonating near military trenches.The insights gained contribute to enhancing safety measures in both military and civilian contexts exposed to blast events near trench structures.

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.

Occurrence of Extreme Rainfall and Flood Risks in Yopougon, Abidjan, Southeast Côte d’Ivoire from 1971 to 2022

Yopougon, located in the western part of the Autonomous District of Abidjan, is the most heavily populated municipality in Côte d’Ivoire. However, this area is prone to floods and landslides during the rainy season. The study aims to assess recent flood risks in the municipality of Yopougon of the Autonomous District of Abidjan. To achieve this objective, the study analyzed two types of data: daily rainfall from 1971 to 2022 and parameters derived from a Numerical Field and Altitude Model (NFAM). The study examined six rainfall parameters using statistical analysis and combined land use maps obtained from the NFAM of Yopougon. The results indicated that, in 67% of cases, extreme rainfall occurred mainly between week 3 of May and week 1 of July. The peak of extreme rainfall was observed in week 2 of June with 15% of cases. These are critical periods of flood risks in the Autonomous District of Abidjan, especially in Yopougon. In addition, there was variability of rainfall parameters in the Autonomous District of Abidjan. This was characterized by a drop of annual and seasonal rainfall, and an increase of numbers of rainy days. Flood risks in Yopougon are, therefore, due to the regular occurrence of rainy events. Recent floods in Yopougon were caused by normal rains ranging from 55 millimeters (mm) to 153 mm with a return period of less than five years. Abnormal heavy rains of a case study on June 20-21, 2022 in Yopougon were detected by outputs global climate models. Areas of very high risk of flood covered 18% of Yopougon, while 31% were at high risk. Climate information from this study can assist authorities to take in advance adaptation and management measures.

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.

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.

Rights Risks of Using Affective Computing Technology in Public Governance and Their Regulation

As the frontier of intelligent computing technology,affective computing has been used in border inspection,case investigation,crime assessment,public opinion management,traffic management and other scenarios of public governance.However,there are still public risks associated with its failure to meet the basic requirements of modern public governance,and these risks are rooted in its technical characteristics.The technical characteristics of turning emotions into signals can give rise to such problems as degrading the right to informed consent,de-governance,and undermining human dignity when applied in public governance,and consequently can lead to social rights anxiety.Additionally,the affective modeling characteristics of affective computing tend to incur the rights risks of insufficient algorithm accuracy,algorithmic discrimination,and algorithmic black boxes.To avoid these risks,it is necessary to adopt the dynamic consent model as the premise for applying affective computing in public governance,and to regulate the auxiliary application of affective computing in public governance in a hierarchical manner,to achieve a balance between the application of affective computing technology and the protection of citizens'rights and the maintenance of public ethics.

Impact of Exercise on Depression in Older Adults:Potential Benefits,Risks,and Appropriate Application Strategies

As the global elderly population increases,depression within this group has become a significant public health concern.Although exercise has been recognized for its potential to improve depression in the elderly,the benefits,risks,and implementation strategies remain contentious.This review attempts to examine the impact of exercise on depression in older adults,including potential benefits,risks,and suggestions for application.Our analysis highlights the benefits of aerobic and resistance training,which can significantly alleviate depressive symptoms and enhance overall quality of life.Despite these benefits,the review acknowledges the complexity of the exercise-depression interaction in the elderly,necessitating personalized exercise regimens.Potential risks,such as muscle and joint pain,are pointed out,emphasizing the importance of tailored,supervised exercise programs.The review calls for future research to focus on identifying the most effective types of exercise and regimens for this population,considering factors such as age,gender,and existing health conditions.Lastly,it advocates for the inclusion of exercise in comprehensive treatment plans for depression in older adults,viewing it as a promising step toward achieving holistic mental health care in a growing demographic.