High-risk Areas Research Articles

Knowledge, Attitude, and Practices Regarding the Prevention and Control of Malaria in KhyberPakhtunkhwa: An Observational Study

ABSTRACT Background: This Knowledge, Attitudes, and Practices (KAP) study aims to assess local awareness andpreventive behaviors concerning malaria in high-risk areas like Karak District. By evaluating understandingtransmission, symptom recognition, and treatment-seeking behaviors, the study seeks to inform and enhancemalaria control strategies as malaria is one of the most serious global public health challenges, contributingsignificantly to illness and mortality. The insights gained will aid in developing targeted interventions andimproving the effectiveness of malaria control programs. Objective. To assess knowledge, attitude, and practices regarding the prevention and control of malaria inlocal population of District Karak. Methods:This cross-sectionalstudywas conductedinTehsilTakht-e-Nasrati,Karakdistrict,KhyberPakhtunkhwa(KPK), using convenience sampling to survey 372 household heads. Data was collected through structuredinterviews, and only respondents who understood Urdu or Pashto were included. Descriptive statistics andFisher's exact tests were used for analysis, with a significance level of p ≤0.05. SPSS version 19 was utilizedfor analysis. Results: The study found that individuals aged 26-35 years were most affected by malaria. Additionally,72.31% of participants were employed and awareness and preventive practicesshowed that 56.45% of participantsdeemed avoiding outdoor sleeping important, 43.28% advocated for insecticide use and mosquito control,and 42.20% used protective measures, with 42.47% employing bed nets or indoor spraying. Conclusions. The study reveals a solid understanding of malaria prevention among the population yetemphasizes the need for improved implementation of protective measures and targeted government actionsto enhance malaria control.

Pressure Difference Measuring System for Clean Rooms

This article presents the development and implementation of a pressure difference measuring system tailored for clean rooms, essential in medical facilities to control airflow and reduce nosocomial infections. The study evaluates various pressure sensors, leading to the selection of intelligent sensors that meet specific performance criteria. Key features and operating principles of the system are outlined, including sensor types, measurement techniques, and system architecture. A detailed comparison of sensors such as BMP180 and BMP280 highlights their suitability based on parameters like resolution, power consumption, and communication interfaces. The system’s structure includes dual pressure sensor units connected to a main control unit, enabling real- time pressure monitoring across different room zones. The sensors, equipped with a microcontroller for initial data processing, relay information to the control unit for further analysis and display. Designed with a calibration feature, the system ensures measurement accuracy by allowing recalibration under identical atmospheric conditions. Operating on low voltage, the system provides safe and reliable performance with applications extending to isolation rooms and environments requiring precise pressure regulation. Integrating the measuring system with ventilation systems significantly mitigates the risk of airborne disease transmission, contributing to the maintenance of sterile environments. The article concludes that this cost-effective, intelligent pressure monitoring solution not only enhances safety in healthcare settings but also supports regulatory compliance and improves overall infection control measures in high-risk areas.

Multiple Indicator Vulnerability to Energy Poverty: Assessing Spatial Variability Across Chile

This study investigates the multifaceted issue of energy poverty, focusing on its spatial and socioeconomic dimensions, with a particular emphasis on the case of Chile. Despite global initiatives like Sustainable Development Goal 7, which advocates for universal access to affordable and reliable energy, millions remain vulnerable to energy poverty. In Chile, this phenomenon is exacerbated by geographic and climatic variability, resulting in significant disparities in energy access, affordability, and efficiency. Using a multidimensional framework adapted from Bouzarovski and Petrova, we assessed energy poverty through factors including household income, fuel costs, energy infrastructure reliability, and regional climate needs. This analysis integrated composite indicators to map vulnerability at the regional level, highlighting high-risk areas primarily in the central and southern regions, where low incomes and dependency on biomass for heating amplified exposure occur. The findings reveal that approximately 4 million Chileans face a high risk of energy poverty, underscoring the need for regionally tailored policies that address both immediate economic constraints and structural energy inequalities. This research contributes to a comprehensive understanding of energy poverty in Chile and offers policy recommendations aimed at reducing socioeconomic disparities and achieving sustainable, equitable energy access.

Specialty-specific hand hygiene compliance: 5-year study from a large public sector teaching hospital, South India

: Hand hygiene (HH) is essential for preventing healthcare-associated infections (HAIs), especially in ICUs and cancer care centers. These settings often involve immunocompromised patients and invasive devices, making HH critical for patient safety. Despite its recognized importance, consistent adherence to HH practices by healthcare workers (HCWs) remains a significant challenge. This study aimed to evaluate HH compliance in a tertiary care hospital in South India using a customized Android application aligned with WHO guidelines. : This observational study was conducted across high-risk areas of a tertiary care hospital from June 2019 to May 2024. The hospital's high-risk units, under medical, surgical, and pediatric alliances, were included. An Android application based on the Ibhar platform and WHO hand hygiene audit guidelines was used for data collection. The study recorded HH opportunities, Complete HH Adherence (HHCAR), Partial HH Adherence (HHPAR), and Total HH Adherence (HHTAR). The data were analyzed for location-specific, profession-specific, and moment-specific compliance rates. : A total of 196,252 HH opportunities were recorded, with the surgical alliance accounting for the highest number. Pediatric units had the highest compliance, with an HHTAR of 89% and an HHCAR of 66%. Nurses demonstrated the highest compliance among professions, with an HHTAR of 82.8%. Compliance was higher after patient care moments compared to before. Statistically significant differences were noted across different specialties and moments. : This large-scale study highlights the variation in HH compliance across different specialties and the need for targeted training sessions. Given the resource constraints in many tertiary care centers, focusing audits on high-risk areas is practical. The use of software-based applications like Ibhar enhances data collection and analysis, making the audit process more efficient. Regular HH audits and behavioral changes are essential to improve and sustain high standards of HH compliance, ultimately contributing to better infection control practices.

Development of an optimal route planning algorithm using hot zones

The authors in the article address the problem of planning optimal routes in a dynamic environment using OpenStreetMap (OSM) geographic data for the territory of Ukraine. Amid conflict situations and active hostilities, there is a need to adapt classical route-finding algorithms to account for specific terrain constraints. The main aim of the research is to develop an adaptive A* algorithm that considers high-risk areas ("hot zones") which can significantly impact the efficiency and safety of the calculated route. To achieve this goal, the authors conducted an analysis of existing shortest path search algorithms using the classic A* algorithm and its heuristic function, which considers the distance between route points. The study explores a modified version of the A* algorithm that includes an additional cost factor for "hot zones." The proposed approach introduces an adaptive multiplier that restricts route planning through dangerous areas. To validate the proposed method, OSM data containing only basic road information, without military restrictions, was used. This limitation highlights the importance of additional analysis of factors such as safety and risk in route planning. The results demonstrate the effectiveness of the developed adaptive A* algorithm in constructing routes in a dynamic environment, particularly with the ability to avoid dangerous ("hot") zones. The study's conclusions confirm that adding a cost factor in "hot zones" improves route accuracy and enhances travel safety. The developed algorithm can be applied to automated route planning in scenarios where it is crucial to consider variable risk factors and specific terrain conditions.

MODELING APPROACH TO URBAN VULNERABILITY TO FLOODING IN THE METROPOLITAN AREA OF ANNABA

Historically, natural hazards have been a constant presence in Mediterranean regions. Earthquakes, eruptions, and floods frequently impact various territories, underscoring this reality. Consequently, governments have prioritized the establishment of prevention, management, and alert systems, making fundamental applied research essential for the ongoing development of these nations. Algeria has experienced numerous natural disasters in the past, particularly those associated with major earthquakes, such as the El Asnam earthquake on October 10, 1980, the Boumerdes earthquake on May 21, 2003, the Bab El Oued floods on November 10, 2001, and more recently, the Ghardaia floods on October 1, 2008.The general living conditions in Algeria, especially in urban areas, are characterized by insufficient management of various issues, largely due to rapid growth. This has at times led to unregulated and uncontrolled urban expansion, with developments on riverbeds, unstable slopes, and other high-risk areas. Such urbanization fails to consider the persistent presence of natural hazards, which are further intensified by climate change.Our objective is to identify the primary causes of natural risks and disasters in urban areas. This study includes an illustrative case in the intermunicipal area of Annaba, located in northeastern Algeria, where flood risk remains significant. The study aims to assess the impact of climate change and the support provided for crisis prevention and management within a sustainable framework.

Improving Tsunami Risk Analysis by Integrating Spatial Resolution and the Population’s Evacuation Capacities: A Case Study of Cartagena, Chile

AbstractIntensive human activity in global coastal areas has led to increasing exposure to hazards. Cartagena Bay in Chile, an area with a long history of tsunami disasters, has undergone significant urbanization and experiences heavy tourist activity during the summer. While some studies have examined risk in Cartagena by focusing on hazard and vulnerability characteristics, challenges remain in delivering more spatially accurate studies and incorporating the population’s coping capacities. We undertook a tsunami risk assessment of Cartagena Bay that disaggregates social vulnerability to the census block level and assesses the inhabitants’ pedestrian evacuation potential through an agent-based model. Our findings indicate that urban coastal areas in Cartagena Bay might face substantial tsunami risk in a worst-case scenario, with 31.0% to 54.1% of its territory—depending on the scale of analysis—classified as high-risk areas. Of the examined urban blocks, 31.4% have average evacuation times exceeding 17 min (the critical time required by the tsunami to reach its run-up), and the most disadvantaged census block is 1,971.9 m away from its nearest shelter. We also demonstrated that a more spatially accurate vulnerability analysis is more conservative too. For instance, zones with high-risk levels decreased by 42.8% when the study scale moved from the block to the zone level of analysis. Similarly, areas with low risk increased by 80%. In comparison to previous studies, our findings show that tsunami risk in Cartagena Bay is significantly lower if coping capacities such as evacuation potential are included in the analysis.

Construction of a composite cooling network for the mitigation of urban heat risk in Fuzhou

Climate change has intensified urban heat risks through extreme heat and heat island effects. Using Fuzhou as a case study, we conducted assessments of heat risk and cool island quality to identify core heat risk sources (CHRSs) and core cold sources (CCSs). Based on the degree of resistance to surface heat transfer, we constructed a comprehensive resistance surface. This was followed by the construction of a composite cooling network using the minimal cumulative resistance and circuit theory models, along with the identification of key nodes to enhance the protection of cool island resources and ensure network stability. Our findings revealed that the central urban area had the highest heat risk, followed by the eastern coastal areas, showing a trend of further expansion towards the southeastern coast. Relatively high-quality cool island resources were distributed in the western mountainous area. We identified 21 CHRSs and 32 CCSs. The composite cooling network included 94 heat transport corridors and 96 cool island synergy corridors, with 148 cooling nodes and 78 barrier nodes. The average land surface temperature of transport and synergy corridors was 27.89°C and 25.34°C, respectively, significantly lower than the high-risk areas (31.14°C). Transport corridors enable heat transfer from CHRSs to CCSs, while synergy corridors can achieve further cooling by enhancing the synergy among cool islands.

Survival Risk Analysis for Four Endemic Ungulates on Grasslands of the Tibetan Plateau Based on the Grazing Pressure Index

Ungulates are essential for maintaining the health of grassland ecosystems on the Tibetan plateau. Increased livestock grazing has caused competition for food resources, threatening ungulates’ survival. The survival risk of food resources for ungulates can be quantified by the grazing pressure index, which requires accurate grassland carrying capacity. Previous research on the grazing pressure index has rarely taken into account the influence of wild ungulates, mainly due to the lack of precise spatial data on their quantity. In this study, we conducted field investigations to construct high-resolution spatial distributions for the four endemic ungulates on the Tibetan plateau. By factoring in the grazing consumption of these ungulates, we recalculated the grassland carrying capacity to obtain the grazing pressure index, which allowed us to assess the survival risks for each species. The results show: (1) Quantity estimates for Tibetan antelope (Pantholops hodgsonii), Tibetan wild donkey (Equus kiang), Tibetan gazelle (Procapra picticaudata), and wild yak (Bos mutus) of the Tibetan plateau are 24.57 × 104, 17.93 × 104, 7.16 × 104, and 1.88 × 104, respectively; they mainly distributed in the northern and western regions of the Tibetan plateau. (2) The grassland carrying capacity of the Tibetan plateau is 69.98 million sheep units, with ungulate grazing accounting for 5% of forage utilization. Alpine meadow and alpine steppe exhibit the highest grassland carrying capacity. (3) The grazing pressure index on the Tibetan plateau grasslands is 2.23, indicating a heightened grazing pressure in the southern and eastern regions. (4) The habitat survival risk analysis indicates that the high survival risk (the grazing pressure index exceeds 1.2) areas for the four ungulate species account for the following proportions of their total habitat areas: Tibetan wild donkeys (49.76%), Tibetan gazelles (47.00%), Tibetan antelopes (40.76%), and wild yaks (34.83%). These high-risk areas are primarily located within alpine meadow and temperate desert steppe. This study provides a quantitative assessment of survival risks for these four ungulate species on the Tibetan plateau grasslands and serves as a valuable reference for ungulate conservation and grassland ecosystem management.

Impact of several seismic scenarios on the dynamic responses of self-steady structures of different heights

Seismic load resistance is a crucial aspect of safety for self-stabilizing reinforced concrete (RC) structures, which are particularly vulnerable to damage caused by destructive earthquakes. These structures, often used in high seismic risk areas, require special attention to ensure their stability and durability under significant dynamic demands. This study focuses on the dynamic responses of low- and medium-rise RC buildings subjected to various seismic response spectra, including those from historic earthquakes such as El-Centro, Kobe, and Boumerdès (recorded at the Dar El-Beida station in Algeria), as well as the spectrum provided by the Algerian seismic code RPA 99/version 2003. The analysis examines three structures with 1, 3, and 6 stories to evaluate the influence of these spectra on key parameters: shear forces, maximum displacements, the ratio between dynamic and static base shear, and overturning moments. These investigations contribute to a deeper understanding of structural behavior under diverse seismic scenarios. The findings emphasize the need to complement the RPA99/v2003 code with studies based on real earthquakes to better address various structural periods and ensure optimal seismic design practices.

An explainable AI framework for spatiotemporal risk factor analysis in public health: a case study of cardiovascular mortality in South Korea

ABSTRACT Understanding environmental disease risk factor analysis at the district level is essential for gaining valuable insights into regional disease variations, offering a broader perspective compared to individual-level studies. Recently, explainable artificial intelligence (XAI) has received increasing attention in the analysis of factors affecting public health. However, previous purely data-driven XAI-based risk factor analyses faced challenges in capturing regional effect of environmental variables, leading to confusion regarding key spatiotemporal risk factors. Therefore, this study proposes a framework that includes two complementary XAI-based risk factor analyses following two assumptions. Regionally rescaled environmental variables must account for the unequal effects on environmental factors, which are likely influenced by variations in adaptation capacity to weather conditions and differences in exposure-response relationships to air pollutants. District-level disease distribution highlights geographic disparity in sociodemographic vulnerability, whereas temporal variation in diseases by district underscores temporal environmental impacts. Based on these two hypotheses, we rescaled environmental variables using two complementary schemes: one that employs the district-level disease distribution as the target variable, and another that utilizes the temporal residual of the disease within each district. We evaluated this framework by analyzing the association between cardiovascular age-standardized mortality rate (CVD-ASMR) and various risk factors in South Korea from 2010 to 2019, using high-performing random forest and light gradient boosting models with additive Shapley explanation. Compared to previous purely data-driven XAI-based analyses, the proposed schemes achieved significantly better results in capturing regional exposure-response relationships. In two complementary schemes, the most explainable factor to districts with high CVD-ASMR was low education level related to sociodemographic vulnerability, whereas the most explainable factors to high temporal CVD-ASMR patterns were low greenness and high air pollution levels. In addition, the two complementary schemes enabled us to reasonably analyze the interaction effect of the two risk factors, i.e. temperature and air pollutants. Furthermore, high CVD-ASMR and its high temporal variation were observed in situations of high sociodemographic vulnerability with poor air quality. These findings provide insightful public health planning for sustainable cities and society by pinpointing high-risk areas and tailoring strategies to address regional environmental challenges.

Spatial dynamics of Culex quinquefasciatus abundance: geostatistical insights from Harris County, Texas

Mosquito-borne diseases pose a significant public health threat, prompting the need to pinpoint high-risk areas for targeted interventions and environmental control measures. Culex quinquefasciatus is the primary vector for several mosquito-borne pathogens, including West Nile virus. Using spatial analysis and modeling techniques, we investigated the geospatial distribution of Culex quinquefasciatus abundance in the large metropolis of Harris County, Texas, from 2020 to 2022. Our geospatial analysis revealed clusters of high mosquito abundance, predominantly located in central Houston and the north-northwestern regions of Harris County, with lower mosquito abundance observed in the western and southeastern areas. We identified persistent high mosquito abundance in some of Houston’s oldest neighborhoods, highlighting the importance of considering socioeconomic factors, the built environment, and historical urban development patterns in understanding vector ecology. Additionally, we observed a positive correlation between mosquito abundance and neighborhood-level socioeconomic status with the area deprivation index explaining between 22 and 38% of the variation in mosquito abundance (p-value < 0.001). This further underscores the influence of the built environment on vector populations. Our study emphasizes the utility of spatial analysis, including hotspot analysis and geostatistical interpolation, for understanding mosquito abundance patterns to guide resource allocation and surveillance efforts. Using geostatistical analysis, we discerned fine-scale geospatial patterns of Culex quinquefasciatus abundance in Harris County, Texas, to inform targeted interventions in vulnerable communities, ultimately reducing the risk of mosquito exposure and mosquito-borne disease transmission. By integrating spatial analysis with epidemiologic risk assessment, we can enhance public health preparedness and response efforts to prevent and control mosquito-borne disease.

Where drinks and danger meet: Analyzing the spatial link between Bars and crime in Detroit

Alcohol consumption has long been linked to various crimes, including homicide, assault, sex-related offenses, family violence, and chronic aggressiveness in adults. While the association between alcohol use and violent crime is well-documented, few studies have examined the spatial co-occurrence of bar locations - a primary venue for alcohol sales - and crime incidents across precise geographical locations and over time. This study employs the global colocation quotient (GCLQ) and the local colocation quotient (LCLQ) to analyze the spatial correlation between five types of liquor establishments (bar, lounge, live house, nightclub, and pub) and seven types of crimes (aggravated assault, burglary, larceny-theft, murder, motor vehicle theft, rape, and robbery) in Detroit, Michigan from 2017 to 2022. Findings demonstrate stable spatial relationships between bars and crimes across different years, with downtown bars showing a lower crime association, bars in clusters showing diverse patterns, and isolated bars in higher risk. The analysis reveals discrepancies in risk among different types. The safety index of the neighborhood surrounding bars is assessed through colocation analysis, demonstrating a correlation with bar-related security. Based on these insights, the study recommends heightened supervision for bars in high-risk areas and developing tailored prevention measures.

Gr-1 blockade remodels the immunosuppressive microenvironment induced by incomplete microwave ablation of hepatocellular carcinoma

BackgroundAblation is one of the main methods for local treatment of hepatocellular carcinoma (HCC). Different from radiofrequency ablation (RFA), microwave ablation (MWA) is not limited by tissue conductivity, and can use multiple electrodes at the same time to improve ablation efficiency. In addition, MWA can form a larger ablation area, which makes it possible to completely ablate large HCC. However, MWA may be incomplete due to factors such as larger tumors or tumors in high-risk areas. The mechanism by which the cellular and tumor immune microenvironment (TIME) is involved in the in vitro effects of incomplete microwave ablation (iMWA) needs to be further elucidated.MethodsH22 tumor-bearing C57BL/6 mice were treated with iMWA with several combinations of ablation power and time duration. The effects of iMWA on the genes of HCC cancer cells and the TIME were investigated by RNA sequencing, mass cytometry, immunohistochemistry, and immunofluorescence. The effect of iMWA in combination with anti-Gr-1 on HCC tumor growth was also evaluated.ResultsThermal stress generated by iMWA induced coagulative necrosis and apoptosis in the region of the ablation center of HCC. RNA sequencing analysis showed that iMWA can boost chemokine CXCL5, which was further confirmed by quantitative real time polymerase chain reaction (qRT-PCR). Mass cytometry results showed that relative to Ctrl group, iMWA-treated led to decreased CD4+ T, CD8+ T, Natural killer (NK), macrophages including both M1 and M2 types but increased monocytes and bone marrow-derived suppressor cells (MDSC). Therefore, inhibiting MDSC is the main target in the later stage of iMWA. In vivo results showed that the tumor volume and weight of iMWA+ anti-Gr-1 group were significantly reduced compared with iMWA+ anti-IgG group. In addition, the merged expressions of CD11b and Gr-1 proteins were found reduced in the iMWA+ anti-Gr-1 group compared with the iMWA+ anti-IgG group by immunofluorescence staining. Immunohistochemistry suggested that CD8 was enriched in the iMWA+ anti-Gr-1 group but not in the iMWA+ anti-IgG group.ConclusionOur data suggests that iMWA and Gr-1 blocking combined therapy can further inhibit HCC growth and significantly improve the CD8+ T cells in the mouse subcutaneous tumor model, which brings good news to HCC patients.

Global, regional, and national burden of liver cancer due to alcohol use, 1990-2021: results from the Global Burden of Disease study 2021.

Liver cancer is a major global health burden, with alcohol use being a well-established risk factor. This study aims to analyze the global, regional, and national incidence, prevalence, mortality, and disability-adjusted life years (DALYs) attributable to liver cancer due to alcohol use from 1990 to 2021. Data on liver cancer due to alcohol use were collected from the 2021 Global Burden of Disease (GBD) study. The changing trend of liver cancer among alcohol users was described using the linear regression model. In addition, we employed a hierarchical cluster analysis to study the evolving patterns across diverse GBD regions and conducted a frontier analysis to explore the nexus between the burden and sociodemographic progress. In 2021, alcohol-related liver cancer globally accounted for 99 544 incidence cases, 132 033 prevalence cases, 92 228 death cases, and 2 316 027 DALYs cases. Males and middle-aged adults emerged as high-risk populations, while regions with a higher sociodemographic index (SDI) were identified as high-risk areas. From 1990 to 2021, both the number of cases and age-standardized rates (ASRs) increased. Our frontier analysis revealed unattained health gains between 1990 and 2021, highlighting disparities in disease burden among countries with varying SDI levels. This analysis further demonstrated an inverse correlation between SDI and alcohol-related liver cancer ASRs, with the ASRs stabilizing once the SDI exceeded 0.40. Alcohol use is a significant contributor to the global burden of liver cancer. Comprehensive policies and interventions targeting alcohol use are needed to reduce the burden of alcohol-related liver cancer.

Effects of urbanization on the ephemeral lake flood risks under subtropical humid monsoon climate

Study regionPoyang Lake region, China. Study focusThis study focuses on addressing severe summer monsoon floods in the Poyang Lake region under subtropical monsoon climate conditions. Employing the Seasonal Water Yield analysis within the Integrated Valuation of Ecosystem Services and Tradeoffs framework to investigate and assess the impacts of subtropical monsoon climate and urban dynamics on regional flood risk. By combining simulation results with analysis of regional urban distribution, the study aims to identify sensitive changes in flood hazard characteristics. Ultimately, the research seeks to enhance regional flood resilience to address climate change and urban development challenges. New hydrological insights for the regionUpon analyzing the model simulation results, we discovered that the subtropical humid monsoon climate contributes significantly, accounting for 35.98 % of surface runoff variability during the ephemeral lake region's flood season. Rapid urbanization amplifies the negative impact of land use change on surface runoff (with a contribution rate of 26.00 %). In urban agglomeration areas, surface runoff increased by 30 mm, and the area with surface runoff production of 60–90 mm increased by 120.33 km2. Implementing proactive ecological management measures around lakes and riverbanks has mitigated flood risks across 22 administrative regions, reducing high-risk flood areas by 92.15 km². Restoration of lake flood storage capacity has significantly bolstered resilience against flood disasters.

Vulnerability of Global Pine Forestry's Carbon Sink to an Invasive Pathogen-Vector System.

The substantial contribution of northern forest growth to the global increase of biomass carbon stock is well documented. However, the ecological consequences of pest- and disease-related losses in these forests have not received comparable attention. This study highlights that pine species are major contributors to carbon stocks in Northern Hemisphere. The total carbon storage of Pinus in the Northern Hemisphere was estimated at 70,726 teragrams of carbon (TgC; 17.7% of the total forest carbon 478,012 TgC), accounting for 4.9%, 28.4%, and 12.5% of the total carbon storage in the forests of Asia, Europe, and North America, respectively. However, pine trees were under threat from an invasive complex involving the pine wood nematode (Bursaphelenchus xylophilus) and Japanese pine sawyer beetle (Monochamus spp.). Since 1977, this complex resulted in a carbon sink deficit of 1857 TgC (18% of the carbon currently stored in Europe's live tree biomass) in northern pine ecosystems. The carbon losses attributed to B. xylophilus exceeded those caused by wildfires, which are typically regarded as the primary factor of forest disturbances. Furthermore, the contributions of environmental variables indicate that the expected northward shift in precipitation patterns will exacerbate B. xylophilus threats, endangering 78% of the boreal forests across Eurasia by 2100. Among these high-risk areas, 62% contributed significantly to global carbon sink, and 42% was protected forests. Following the present trend, carbon losses caused by the B. xylophilus complex could exceed 39% of the total carbon storage in terrestrial ecosystems. This study provides comprehensive datasets that detail the global distribution and high-risk habitats of pine species and B. xylophilus vector beetles in affected countries. Our findings underscore the substantial risk of carbon losses posed by B. xylophilus to northern pine forests, with potential implications for global carbon dynamics and the achievement of international goals related to "carbon peak" and "carbon neutrality."

IoT-Enabled Fire Detection and Alert System Leveraging HSV Thresholding

Fire detection plays an important role in minimizing damage caused by forest fires and enhancing response times. In this proposed study, a real-time fire detection system using a USB camera and Raspberry Pi, has been developed utilizing the concepts of IoT and image processing. The system continuously monitors the environment for the presence of fire by analysing video frames captured by the camera. The HSV colour space model is utilized to detect fire-like colours based on predefined thresholds, ensuring accurate identification of fire regions. Upon detection, the system triggers an alarm, retrieves geolocation data, and sends real-time alerts to a designated webpage, providing the fire’s exact location and a notification for immediate action. This approach eliminates the need for manual intervention, making it suitable for deployment in high-risk areas. The system’s modular design allows for integration with additional technologies such as automated fire extinguishing systems or GSM-based notifications, expanding its potential applications in real-world scenarios.

Epidemiology and geographical patterns of common childhood cancers in Iran: Evidence from the National Cancer Registry

IntroductionCancer is projected to become the primary cause of death in the 21st century. Although childhood cancer is relatively rare, it remains a significant contributor to mortality among children. This study examines the geographical distribution of childhood cancer incidence in Iranian provinces using data from the National Cancer Registry between 2014 and 2018. Materials and methodsThis registry-based study analyzed data from 14,711 children under 20 diagnosed with common childhood cancers, sourced from the Iranian National Population-based Cancer Registry for the period 2014–2018. The age-standardized incidence rates (ASR) were calculated using direct standardization methods and reported per 1 million person-years. Spatial autocorrelation measures, including global and local indices such as Moran's I and Getis-Ord's G, were employed to identify high-risk and low-risk areas, assess overall spatial dependence, and pinpoint specific clusters and hotspots of incidence rates. ResultsASR for childhood cancer in Iran was 119.56 per 1 million individuals aged 0–19 years. Boys had a higher ASR (129.98) than girls (107.68). Childhood cancer cases increased from 2765 in 2014 to 3354 in 2018, with leukemia as the most common type, followed by brain and nervous system, lymphoma, bone, and connective and soft tissue cancers. Spatial analysis identified high-risk clusters in central Iran (Isfahan, Yazd, Tehran) and low-risk clusters in the northeast (Kermanshah, West and East Azerbaijan, Kurdistan). ConclusionThis study highlights high childhood cancer incidence in Iran, particularly among boys and in central regions, with elevated leukemia rates. These findings call for targeted prevention strategies and further research to address geographic and gender disparities and to improve care programs.

Identification of Forest Fire Zone in Junnar Forest Division, Pune District of Maharashtra

The Junnar division is a critical area for forest fires every year. March, April and May are the three months when most forest fires occur. Most of these fires are artificial. Grazing, smoking and collecting firewood are some examples. Therefore, we must face all the problems of the environment, humans and pollution on a large scale. The amount of forest in this area has been greatly reduced due to the annual fires. Therefore, the people here must face natural and economic problems like tiger attacks, shortages of wood, heavy rains and heat. Forest area is 5319 sq. km. Present study therefore aims to monitor the conditions of the study area using GIS and remote sensing methods, to locate forest fire hotspots and to investigate the effects of these fires on both the environment and people using parameters such as the Normalized Difference Vegetation Index, land use land cover, forest density distance from habitation, distance from road, slope and aspect map and elevation map. These thematic layers were weighted according to their importance and forest fire hotspots were identified. The total number of forest fire alerts is high. The final fire risk map created indicates that the low-risk area is 1848 sq. km. The moderate-risk area is 3372 sq. km. The high-risk area is 100 sq. km. Therefore, there is a need for proper management of forest fires. The proposed work focuses on assessing detailed processes such as forest fire impacts on the human living environment, using geospatial tools. Also, it is helpful for a sustainable environment in the study area.