High-risk Regions Research Articles

Application of Esophageal Sponge Cytology in Screening Esophageal Squamous Cell Carcinoma in a High-Risk Region of China.

To investigate the feasibility and accuracy of esophageal sponge cytology in screening esophageal squamous cell carcinoma (ESCC). From May 2021 to June 2022, an opportunistic screening was performed in people aged 40-75 from a high-risk region for ESCC. Using an esophageal cell collector that was independently developed in China for esophageal sponge cytology, a positive cytology was determined as detection of atypical squamous cells or more severe lesions. The safety, tolerability, and accuracy of esophageal sponge cytology were compared with those of pathological examination after endoscopy and biopsy. A total of 1581 eligible participants were involved in the screening program, including 61 (3.86%) with high-grade lesions pathologically confirmed by endoscopic biopsy. No serious adverse events were reported during sampling. Major adverse events included vomiting during sampling (n = 2, 0.13%) and sore throat after sampling (n = 36, 2.27%). The majority of participants showed good tolerability and accessibility (n = 1568, 98.80%) accessed by the visual analogue scale (VAS). Esophageal sponge cytology offered a satisfactory diagnostic accuracy in screening advanced esophageal epithelial lesions, with a sensitivity of 98.36% (95%CI: 90.02%-99.91%) and a specificity of 91.15% (95%CI: 89.97%-92.84%), and a negative predictive value up to 99. 92% (95%CI: 99.53%-99.99%). Esophageal sponge cytology is a highly feasible, safe, and accurate screening method for ESCC in a high-risk region of China. First Affiliated Hospital of Naval Medical University: NCT04609813.

Ticks jump in a warmer world: Global distribution shifts of main pathogenic ticks are associated with future climate change.

In recent decades, the threats of ticks and tick-borne diseases (TBDs) increased extensively with environmental change, urbanization, and rapidly changing interactions between human and animals. However, large-scale distribution of tick and TBD risks as well as their relationship with environmental change remain inadequately unclear. Here, we first proposed a "tick-pathogen-habitat-human" model to project the global potential distribution of main pathogenic ticks using a total of 70,714 occurrence records. Meanwhile, the effects of ecological factors and socio-economic factors driving the distribution pattern were evaluated. Based on this, the risk distribution of TBDs was projected by large-scale "tick-pathogen-disease" analysis. Furthermore, the distribution shifts of tick suitability were projected under different shared socio-economic pathways in the future. Our findings demonstrate that warm temperate countries (e.g., the United States, China and European countries) in the Northern Hemisphere represent significant high risk regions for ticks and TBDs. Specifically, solar radiation of January emerges as the main decisive factor determining the risk distribution pattern. Future shifts of tick suitability showed decrease trend under low greenhouse gas emission scenarios but increase trend under high scenarios. These suitability shifts were significantly correlated with future temperature- (9 species) and precipitation- (19 species) related factors. Collectively, in this study we first shaped the global risk distribution of main ticks and TBDs as well as tick suitability shifts correlated with future global climate change, which will provide helpful references for disease prevention and administration. The methods proposed here will also shed light on other emerging and recurrent zoonotic diseases (e.g., COVID-19, monkeypox) in the future.

Billy-Buddy against Cyberbullying

Cyberbullying has become a pervasive issue in the digital age, affecting individuals across demographics and causing significant psychological, emotional, and social harm. Despite various attempts to address this problem, existing solutions often fall short in providing comprehensive support, particularly in victim care, privacy preservation, and real-time intervention. This paper presents a holistic framework that integrates cutting-edge technologies such as Natural Language Processing (NLP), machine learning, and secure data handling to combat cyberbullying effectively. At the core of this framework is an empathetic AI-powered chatbot, “Billy,” designed to provide victims with real-time emotional support and actionable guidance. Billy uses advanced sentiment analysis to detect distress and offers tailored responses, helping victims navigate the emotional and procedural aspects of cyberbullying incidents. Additionally, the system facilitates anonymous reporting of perpetrators, ensuring victims’ privacy and safety through robust encryption and secure data management. The proposed framework includes a real-time cyberbullying detection mechanism capable of analyzing online interactions, identifying harmful content, and providing immediate feedback. Statistical tools analyze incident data to identify high-risk regions, enabling law enforcement to prioritize resources effectively. The system also incorporates educational initiatives to raise awareness about cyberbullying, promote safe online practices, and encourage proactive prevention.

The global, regional, and national burden of oral cancer, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

PurposeThis epidemiological study leverages data from the Global Burden of Disease (GBD) database spanning from 1990 to 2021 to analyze the global burden of oral cancer. The research aims to provide a comprehensive assessment of the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASDR), and disability-adjusted life years (DALYs) for oral cancer, examining trends over three decades.MethodsThe study used age standardized rate (ASRs) as an indicator of oral cancer epidemiological data. Trend analysis uses estimated annual percentage change (EAPC) to track changes in oral cancer indicators.ResultsThe study identifies a global increase in oral cancer incidence, mortality, and DALYs. From 1990 to 2021, the global incidence rate increased significantly from 3.26 (95% UI 3.14–3.41) to 5.34 (95% UI 4.94–5.70), the global mortality rate rose from 1.83 (95% UI 1.73–1.92) to 2.64 (95% UI 2.42–2.84), and the global estimate of DALYs increased from 55.05 (95% UI 52.38–57.97) to 74.44 (95% UI 67.50–80.44). High-risk regions include Palau and certain areas in Asia. Middle SDI regions show the most significant growth, while economically underdeveloped areas like parts of Africa show less significant trends.ConclusionThe research underscores the need for heightened awareness, surveillance, and prevention efforts, especially in regions with high oral cancer incidence. Policymakers are urged to implement screening programs and public health education to combat the disease.

Big Data-Driven Risk Analysis of Environmental Grievances in the Southeast Asia Palm Oil Industry for Sustainable Decision-Making

The expansion of the palm oil industry affects environmental sustainability. This study aims to assess palm oil's environmental grievances reported pre- and post-Covid-19. A hybrid of data-driven and multicriteria decision-making analyses was used to analyze unstructured data from nine companies' grievance logs. A total of 884 cases with the trend peaking in 2019. Predominantly deforestation, a total of 564 cases affecting ~66,716.23 ha in Indonesia, 312 cases affecting ~49,704.97 ha in Malaysia, 6 cases affecting ~43,500 ha in Papua New Guinea, and 2 cases in the Philippines. Network analysis reveals that the environmental grievances affected multiple companies, with WILMAR suppliers at the center. On average, companies take ~100 days to resolve. Clustering analysis shows Sime Darby Oil, WILMAR, KLK, and Mewah Group have influences on addressing grievances in high-risk provinces. Quantile-quadrant analysis reveals that provinces in Kalimantan, Pahang, and Sarawak are in the high-risk quadrant and therefore require immediate mitigation plans. This finding points toward the need for the formation of a private consortium among identified key players and local government in the high-risk region as a new strategy to improve management of environmental sustainability issues that predominantly involve deforestation.

Mapping site amplification with the dense recording of ambient vibration for the city of Lucerne (Switzerland): comparison between two approaches

Abstract Reliable site-specific amplification information can be retrieved using earthquake-based methods that involve the deployment of a permanent (or temporary) network of seismic recording stations. Such an endeavour may need to operate for years, especially within regions of high risk but low recurrence rates in seismic activity. Hence, time- and cost-effective approaches using ambient vibrations are gaining popularity. Among such techniques, the canonical correlation approach (CC) collates measured empirical amplification with its indicator computed from ambient vibrations (i.e. horizontal-to-vertical spectral ratios) for a training set of seismic stations, to predict site response at locations without earthquake recordings. Another method, the hybrid standard spectral ratio method (SSRh) takes advantage of simultaneous recordings of ambient vibrations that are adjusted using earthquake ground motion data using a limited number of instrumented sites to estimate local seismic soil response. We apply both methods in the Lucerne area (Switzerland), which is located on a soft sedimentary basin, and obtain consistent results that are comparable to amplification estimates derived solely from earthquake ground motion data. These results show significant linear amplification factors (8–10 or more) at the fundamental frequency of resonance of the sediments (0.8–2 Hz). However, both techniques show systematic differences in the spatial and frequency domains. The CC method tends to underestimate the amplification at the fundamental frequency, while the SSRh technique predicts higher amplification in the centre of the basin and lower amplification at the basin edges in comparison to the CC approach. The study discusses the impact of the limitations in the completeness of the calibration dataset, and variability introduced by the choice of the shear wave velocity model of the shallow subsurface and inelastic behaviour treatment for the CC method, as well as the influence of the measurement setup for the SSRh method.

Urban waterlogging vulnerability assess using SAR imagery and integrated terrain analysis

Waterlogging is a significant concern in urban areas and can result in severe disruptions and damage and it’s an urban problem. This study is conducted in Thoothukudi and Tamil Nadu, which are particularly sensitive to waterlogging because of their geographical and meteorological circumstances. Using synthetic aperture radar (SAR) images from 2015 to 2022, topographical analysis, land use/land cover (LULC) data, and geological insights, this research intends to identify and assess areas prone to water logging. The data source for this study comprises rainfall records from the Indian Meteorological Department (IMD), Sentinel-1 SAR imagery, Sentinel-2 multispectral images from the European Space Agency (ESA), and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM).Terrain analysis was undertaken using DEM to generate elevation, slope, and aspect maps, while SAR data were processed to extract water pixels, which included the extraction of water pixels from SAR data for each year and overlaying them. The overlaid image was correlated with topographic maps to identify the high-risk regions. Key places such as Muthayapuram, Milavittan, Bryant Nagar, and Thalamuthunagar were constantly highlighted as prone to floods. Additionally, the saltpan regions, defined by low-lying water table levels, endure continuous flooding, demonstrating the usefulness of combining SAR imaging with topographic analysis for urban water management. These findings provide useful insights for urban planners and policymakers, underlining the need for deliberate steps to reduce waterlogging, maintain public health, and minimize infrastructure damage, thus enabling sustainable development in Thoothukudi.

A systematic review of variables associated with snakebite risk in spatial and temporal analyses.

Snakebite is a priority neglected tropical disease, but incidence data are lacking; current estimates rely upon incomplete health facility reports or ad hoc surveys. Spatial analysis methods harness statistical associations between case incidence and spatially varying factors to improve estimates. This systematic review aimed to identify variables associated with snakebite risk in spatial and temporal analyses for inclusion in geospatial studies to improve risk estimation accuracy. We searched MEDLINE, Global Health, PubMed and Web of Science in January 2023 for studies published since 1980 assessing snakebite outcomes and spatially varying factors at the setting level. Study quality was assessed using an adapted Joanna Briggs Institute tool. The results are presented by narrative synthesis. Thirty-five studies were eligible; the majority were from Central and South America (18), then Asia (11). Climate and environment were most frequently assessed, with temperature, humidity and tree cover predominantly positively associated with snakebite risk, drought negatively associated and altitude negative/mixed. Crop and livestock variables mostly showed positive associations; population density and urban residence overwhelmingly displayed negative associations. This review identifies key variables that should be considered in future snakebite risk research. Limitations include low research availability from the highest risk regions. There is an evident need for greater research into snakebite risk variation, particularly in sub-Saharan Africa.

Assessing changing baleen whale distributions and reported incidents relative to vessel activity in the Northwest Atlantic.

Baleen whales are among the largest marine megafauna, and while mostly well-protected from direct exploitation, they are increasingly affected by vessel traffic, interactions with fisheries, and climate change. Adverse interactions, notably vessel strikes and fishing gear entanglement, often result in distress, injury, or death for these animals. In Atlantic Canadian waters, such negative interactions or 'incidents' are consistently reported to marine animal response organizations but have not yet been analyzed relative to the spatial distribution of whales and vessels. Using a database of 483,003 whale sightings, 1,110 incident reports, and 82 million hours of maritime vessel activity, we conducted a spatiotemporal vulnerability analysis for all six baleen whale species occurring in the Northwest Atlantic Ocean by developing an ensemble of habitat-suitability models. The relative spatial risk of vessel-induced incidents was assessed for present (1985-2015) and projected near-future (2035-2055) distributions of baleen whales. Areas of high habitat suitability for multiple baleen whale species were intrinsically linked to sea surface temperature and salinity, with multispecies hotspots identified in the Bay of Fundy, Scotian Shelf, Laurentian Channel, Flemish Cap, and Gulf of St. Lawrence. Present-day model projections were independently evaluated using a separate database of acoustic detections and found to align well. Regions of high relative incident risk were projected close to densely inhabited regions, principal maritime routes, and major fishing grounds, in general coinciding with reported incident hotspots. While some high-risk regions already benefit from mitigation strategies aimed at protecting North Atlantic Right Whales, our analysis highlights the importance of considering risks to multiple species, both in the present day and under continued environmental change.

Analysis of study Global Burden of Disease in 2021: global, regional, and national burden of nutritional deficiency from 1990 to 2021.

Nutrient deficiency disorders (NDs) harm growth, causing economic losses. Addressing NDs is a global priority, yet recent data is limited. This study examines latest NDs data across 204 countries and 21 regions from 1990 to 2021. Data from the 2021 Global Burden of Disease (GBD) study were used to analyze NDs-related incidence, prevalence, deaths, and disability-adjusted life years (DALYs) at global, national, and regional levels. Joinpoint regression analysis was applied to evaluate temporal trends, with Estimated Annual Percentage Change (EAPC) assessing long-term patterns. In 2021, the global burden of NDs remained substantial, with a total of 1,845,246,558 cases with an ASPR of 23,858.99 cases per 100,000 individuals (95% UI: 23,445.77-24,320.82). The ASIR was 7,725.1 per 100,000 people (95% UI: 7,404.01-8,109.01), while the ASMR was 3.03 per 100,000 persons (95% UI: 2.69-3.4). Additionally, age-standardized DALYs rate was 657.62 per 100,000 individuals (95% UI: 489.93-869.58). Regionally, areas with low SDI exhibited the greatest ASPR, ASIR, ASDR, and age-standardized DALYs rates, whereas high SDI regions had the lowest rates. Although global NDs burden has declined from 1990 to 2021, regional and demographic disparities remain. Enhanced healthcare access in high-risk SDI regions is essential to further mitigate NDs's global impact.

High-risk habitat radiomics model based on ultrasound images for predicting lateral neck lymph node metastasis in differentiated thyroid cancer

BackgroundThis study aims to evaluate the predictive usefulness of a habitat radiomics model based on ultrasound images for anticipating lateral neck lymph node metastasis (LLNM) in differentiated thyroid cancer (DTC), and for pinpointing high-risk habitat regions and significant radiomics traits.MethodsA group of 214 patients diagnosed with differentiated thyroid carcinoma (DTC) between August 2021 and August 2023 were included, consisting of 107 patients with confirmed postoperative lateral lymph node metastasis (LLNM) and 107 patients without metastasis or lateral cervical lymph node involvement. An additional cohort of 43 patients was recruited to serve as an independent external testing group for this study. Patients were randomly divided into training and internal testing group at an 8:2 ratio. Region of interest (ROI) was manually outlined, and habitat analysis subregions were defined using the K-means method. The ideal number of subregions (n = 5) was determined using the Calinski-Harabasz score, leading to the creation of a habitat radiomics model with 5 subregions and the identification of the high-risk habitat model. Area under the curve (AUC) values were calculated for all models to assess their validity, and predictive model nomograms were created by integrating clinical features. The internal and external testing dataset is employed to assess the predictive performance and stability of the model.ResultsIn internal testing group, Habitat 3 was identified as the high-risk habitat model in the study, showing the best diagnostic efficacy among all models (AUC(CRM) vs. AUC(Habitat 3) vs. AUC(CRM + Habitat 3) = 0.84(95%CI:0.71–0.97) vs. 0.90(95%CI:0.80-1.00) vs. 0.79(95%CI:0.65–0.93)). Moreover, integrating the Habitat 3 model with clinical features and constructing nomograms enhanced the predictive capability of the combined model (AUC = 0.95(95%CI:0.88-1.00)). In this study, an independent external testing cohort was utilized to assess the model’s accuracy, yielding an AUC of 0.88 (95%CI: 0.78–0.98).ConclusionThe integration of the High-Risk Habitats (Habitat 3) radiomics model with clinical characteristics demonstrated a high predictive accuracy in identifying LLNM. This model has the potential to offer valuable guidance to surgeons in deciding the necessity of LLNM dissection for DTC.Clinical trial numberNot applicable.

Mitigating Air Pollution and Protecting Public Health: Analyzing the Impact of National Clean Air Programme in Kota, Rajasthan

The clean air plan in India involves a set of rules, policies, and initiatives targeted at improving the air quality and public health by way of decreasing emissions from various sources. The study aims to evaluate the impact of National Clean Air Program (NCAP) on lowering air pollution levels and improving public health outcomes in Kota city, Rajasthan, highlighting progress, challenges, and the need for sustained emission control efforts. Kota's selection for this study highlights its significance as an educational hub, attracting students from all over India. The rapid population growth and increased vehicle emissions in the city cause adverse impacts on air quality. Improving air quality will not only enhance the health of residents and students but also contribute to a more conducive learning environment. The action plan of NCAP involves enforcing the construction and demolition waste management rules 2016, implementing emission control measures like water sprinkling and covered transport for construction activities, and extensive campaigns against open burning of biomass and waste. It also includes regular checks on industrial emissions, proper waste collection and disposal, and mandatory green belt development in residential areas. It employs a mixed-method approach, combining air quality monitoring data collected from the Central and State Pollution Control Boards from 2014 to 2023. It also examines trends in key pollutants, including NO2, SO2, and PM10, and analyzes the effect of regulatory measures such as emission controls and waste management rules. The study reveals a decreasing trend in NO2 (nitrogen dioxide) levels in Kota city, Rajasthan from 35.35 µg/m³ to 29.90 µg/m³ during 2014 to 2023, showing a significant drop during the COVID-19 lockdown. Similarly, PM10 (particulate matter) levels peaked at 153.28 µg/m³ in 2018 but saw a significant reduction to104.80 µg/m³ by 2020, indicating an improvement in air quality. However, SO2 (sulfur dioxide) concentrations slightly increased in 2019-2023 compared to 2014-2018. The air quality index (AQI) improved modestly but frequently surpassed 100, indicating hazardous air quality for vulnerable populations. The study concludes that while the NCAP in India has significantly improved air quality, challenges remain, with NO2 levels rebounding post-COVID-19 lockdown and persistent high particulate matter levels. It is recommended to ensure stricter enforcement of emission control measures, enhanced monitoring systems, and public awareness campaigns. Future work should focus on the long-term health impacts of particulate matter and strategies to achieve sustained air quality improvements in high-risk regions.

Determining the risk factors of malaria and anemia in children between 6 and 59 months using the joint generalized linear mixed model on the 2021 Nigeria Malaria Indicator Survey dataset.

Malaria and anemia are significant public health concerns that contribute to child mortality in African. Despite global efforts to control the two diseases, their prevalence in high-risk regions like Nigeria remains high. Understanding socioeconomic, demographic, and geographical factors associated with malaria and anemia, is critical for effective intervention strategies. The study aims to assess the risk factors for malaria and anemia in children under 5 years using the joint generalized linear mixed model (JGLMM). The Nigeria Malaria Indicator Survey (NMIS) 2021 dataset was used, with a sample of 10,120 children aged 6-59 months. A two-stage sampling method was applied. Descriptive statistics and chi-square tests examined factors associated with malaria and anemia prevalence. Missing data were handled using multiple imputations with chained equations (MICE). Lastly, the adjusted odds ratio was interpreted for the current study. SAS was used in analyzing the data and statistical significance was set at 5% significance level. The prevalence of malaria and anemia was 36.81 and 67.66%, respectively, in children between 6 and 59 months old in Nigeria. The JGLMM was used to examine malaria RDT and anemia findings in conjunction with demographic, geographic, and socioeconomic covariates. The following underlying risk factors for malaria and anemia in children were discovered in the study: region, altitude, age of child in months, toilet facility of the household, main wall material used for the house, main roof material used for the house, children under five who slept under a mosquito net, whether the child had fever in last 2 weeks before the survey took place, place of residence where the child resides, household wealth index, sex of child, and mother's education level. However, whether the mother knew of ways to prevent malaria was not statistically significant regarding anemia. This study highlights the importance of addressing fever as a key factor for anemia and improving housing conditions to reduce malaria and anemia prevalence. Policymakers should prioritize mosquito net distribution and healthcare access, particularly in rural areas. The study's novelty lies in its handling of missing data through imputation techniques, enhancing the reliability of findings.

First study on molecular identification of Anaplasma ovis in sheep in southern Kazakhstan

Background and Aim: Anaplasmosis in small ruminants is a tick-borne infection caused mainly by the obligate intraerythrocytic bacterium Anaplasma ovis. It is usually subclinical, with persistent infection in affected animals, but acute disease can occur, particularly in young animals. The pathogen is widespread in Central Asia and neighboring regions. In Kazakhstan, the infection was first detected in 1929. However, until now, diagnosis in the country has been based on traditional microscopic examination of blood smears. There were no reliable data on the prevalence and genetic diversity of Anaplasma spp. in sheep in Kazakhstan. This study aimed to determine the occurrence of Anaplasma spp. infection in sheep in southern Kazakhstan, a high-risk region for tick-borne diseases, using PCR and to identify the species by sequencing. Materials and Methods: A cross-sectional study was conducted on apparently healthy adult ewes from 77 settlements in 34 districts of Kyzylorda, Turkistan, Zhambyl, Almaty, and Jetisu, southern Kazakhstan. A total of 2553 whole blood samples collected in midsummer 2022 and 2023 were analyzed for Anaplasma spp. using polymerase chain reaction targeting the 404 bp groEL gene fragment. The amplification products from the 441 positive samples were sequenced using the Sanger sequencing method. Phylogenetic analysis of the obtained sequences was performed using the maximum likelihood model. Results: Overall, 1017/2553 (39.8%; 95% confidence interval: 37.9%-41.7%) ewes tested were positive for Anaplasma spp. Positive animals were found in 68/77 (88%) of the settlements from which samples were taken. The percentage of Anaplasma spp.-positive ewes varied significantly from 21.3% to 50.1% in the provinces. Altitude <500 m above sea level was identified as a risk factor for Anaplasma infection. All amplification products were identified as A. ovis through sequencing. Phylogenetic analysis of the groEL gene fragment sequences revealed the presence of two A. ovis genotypes; one was 100% identical to sequences from isolates from China and the other was >99.5% identical to isolates from Africa, Cyprus, and China. Conclusion: This first molecular study revealed a widespread of A. ovis infection in adult ewes in southern Kazakhstan. Altitude <500 m was identified as a risk factor. Therefore, clinical cases associated with A. ovis are expected in this region, especially in young animals. Future studies are needed to determine the clinical and economic impact of anaplasmosis on sheep production in the country, to investigate seasonal patterns of infection, and to identify tick species or other arthropods that act as local vectors. This information is useful for developing possible control measures and evaluating their effectiveness. Keywords: Anaplasma ovis, Kazakhstan, polymerase chain reaction, sequencing, sheep.

Valley Fever: Fine Mineral Dust Modeling Points to High-Risk Regions and Seasons in California.

Valley Fever: Fine Mineral Dust Modeling Points to High-Risk Regions and Seasons in California.

Global Research Trends in Cervical Cancer Survival in the Last Two Decades: A Bibliometric Analysis.

Cervical cancer poses a significant challenge to global health, particularly in low- and middle-income countries. Tracking the survival rates of cancer patients through data gathered by population-based cancer registries constitutes a crucial aspect of cancer management. In recent years, attention within bibliometric studies has been directed towards examining the correlation between inflammation and radiotherapy in cervical cancer. However, to date, there is no published literature investigating research trends in cervical cancer survival through bibliometric analysis. Thus, this study was undertaken to identify and analyse global research patterns and hotpots in this area. A systematic search was performed within the Web of Science Core Collection (WoSCC) database, employing the following search parameters: TITLE - (((survival) OR (survival rate) OR (survival analysis) OR (survival probability)) AND ((cervical cancer) OR (cervical carcinoma))). A comprehensive analysis of research trends was conducted utilising various tools on the WoSCC website and VOSviewer. A total of 840 papers pertaining to cervical cancer and survival were identified from 45 distinct departments or subjects. Notably, the People's Republic of China and the USA collectively accounted for half of all publications from 2000 to 2023. An extensive cohort comprising 4,759 authors affiliated with 1,454 institutions across 82 countries contributed to the progression of this research domain. Despite a substantial increase in research on cervical cancer survival over the last decade, it is essential to encourage and conduct research, particularly in high-risk regions, especially in countries classified as low- or middle-income.

Assessing Climate Change Impacts on Subalpine Plant Habitat Suitability in South Korea Using SSP Scenarios

This study evaluates the impacts of climate change on the habitat suitability of eight subalpine plant species in South Korea under four shared socioeconomic pathways (SSP) scenarios, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. Using high-resolution climate data and random forest-based species distribution models (SDMs), we predicted habitat changes between 2010 and 2090s. Key bioclimatic variables, including annual mean temperature (BIO1) and annual precipitation (BIO12), were identified as primary drivers of habitat shifts. SSP5-8.5 scenarios resulted in significant habitat losses and upward altitudinal shifts, with species such as <i>Pinus pumila</i> and <i>Abies nephrolepis</i> losing all suitable habitats by 2090s. In contrast, SSP1-2.6 indicated more stable conditions, preserving habitats for species like <i>Abies holophylla</i> and Taxus cuspidata, highlighting the potential benefits of emission reduction efforts. This study underscores the urgent need for adaptive conservation strategies and robust emission mitigation policies to protect high-risk species and regions, safeguarding subalpine biodiversity. These findings provide a scientific foundation for policymakers to design sustainable biodiversity conservation strategies and foster climate resilience in subalpine ecosystems.

Assessment of Steel Storage Tank Thickness Obtained from the API 650 Design Procedure Through Nonlinear Dynamic Analysis, Accounting for Large Deformation Effects.

This study evaluates the API 650 design procedure for steel storage tanks, incorporating nonlinear dynamic analysis with large deformation effects. Focusing on seismic vulnerability, the case study examines storage tanks proposed for construction in Naples, Italy, assessing their performance under site-specific seismic conditions. A target spectrum and 20 earthquake records were selected to reflect regional seismic characteristics. Initial tank thicknesses were calculated using API 650 guidelines and subsequently analyzed through nonlinear time-history simulations in SAP2000. Results reveal that thicknesses derived from API 650s linear average spectrum equations are insufficient for real seismic demands. Through a trial-and-error methodology, optimal thicknesses were determined to ensure satisfactory performance across all seismic records. Key findings highlight significant variations in mode participation, the frequent occurrence of elephant-foot buckling in tanks with lower H/R ratios, and the limitations of linear spectral analysis for realistic earthquake scenarios. Given the vital role of storage tanks in the oil and gas industry, this study emphasizes the need to integrate nonlinear time history analysis into design processes to enhance seismic resilience, particularly in high-risk regions.

Predicting Tuberculosis Risk in Cattle, Buffaloes, Sheep, and Goats in China Based on Air Pollutants and Meteorological Factors.

Tuberculosis is a zoonotic chronic respiratory infectious disease caused by the Mycobacterium tuberculosis complex. The outbreak and epidemic of tuberculosis can seriously threaten human and veterinary health. To investigate the effects of environmental factors on tuberculosis in domestic ruminants, we collected data regarding the prevalence of tuberculosis in cattle, buffaloes, sheep, and goats in China (1956-2024) from publicly published literature and available databases. We identified the key risk factors among six major air pollutants and 19 bioclimatic variables; simulated the risk distribution of tuberculosis in cattle, buffaloes, sheep, and goats in China using the maximum entropy ecological niche model; and evaluated the effects of environmental factors. The area under the curve of the model was 0.873 (95% confidence interval, 0.851-0.895). The risk factors that most significantly influenced the prevalence of tuberculosis were the nitrogen dioxide (NO2) level, mean temperature of the coldest quarter, cattle distribution density, sheep distribution density, ozone (O3) level, and precipitation of the driest month. The predicted map of tuberculosis risk in cattle, buffaloes, sheep, and goats indicated that the high-risk regions were mainly distributed in South, North, East, and Northwest China. Improved surveillance is needed in these high-risk areas, and early preventive measures must be implemented based on the risk factors identified to reduce the future prevalence of tuberculosis in cattle, buffaloes, sheep, and goats.

Regional disparities and correlates of alcohol use during pregnancy in India: Insights from the National Family Health Survey-5.

Alcohol use during pregnancy is a significant public health concern due to its adverse outcomes for the mother and developing fetus. This study aims to estimate the national and state-wise prevalence of alcohol use during pregnancy in India and examine associated social, demographic and health-related correlates using data from the National Family Health Survey (NFHS-5) conducted in 2019-2020. Data from NFHS-5, a large-scale, nationally representative survey, were analysed. The survey included comprehensive interviews with 724,115 women aged 15-49 years, covering all 28 states and 8 union territories of India. The main outcome was self-reported alcohol use during the respondents' current or most recent pregnancy. Explanatory variables included age, economic status, education level, tribal affiliation, urban/rural residence, planned/unplanned pregnancy, adequacy of antenatal care and tobacco use. Statistical analyses included chi-square tests for unadjusted comparisons and logistic regression for adjusted odds ratios (AOR). The prevalence of alcohol use during pregnancy was 1.26% nationally, with significant regional variations. The highest prevalence rates were in Arunachal Pradesh (13.03%), Chhattisgarh (5.77%) and Assam (5.62%). Key correlates included belonging to Scheduled Tribes (AOR 7.987, 95% CI 5.73-11.134), having no education (AOR 1.733, 95% CI 1.025-2.931) and tobacco use (AOR 3.389, 95% CI 2.647-4.338). Regional analysis showed the highest adjusted odds for the Northeast (AOR 19.753, 95% CI 4.87-80.116) region. Alcohol use during pregnancy in India shows significant regional and socio-demographic disparities. The findings highlight the need for targeted public health interventions and policies, particularly in high-risk groups and regions.