Search Results (6,304)

Alpine wetlands are highly vulnerable to changes caused by global warming. Rapidly and accurately mapping alpine wetlands and analyzing the driving factors of their spatiotemporal changes are crucial for protecting and managing these resources. However, few studies have investigated classification methods and attribution analyses for alpine wetlands. To address this gap, a novel classification method has been developed, integrating the Google Earth Engine, alpine wetland features, and a random forest classifier, named GAWRF, to delineate wetlands in alpine regions. Additionally, an improved Partial Least Squares Structural Equation Model (PLS-SEM) was utilized to explore the mechanisms of spatiotemporal changes in wetlands of the Source Region of Three Rivers (SRTR) from 1990 to 2020. The results indicate (1) the high accuracy of the SRTR land cover maps from 1990 to 2020, with an overall accuracy of above 92.48% and a Kappa coefficient of over 0.91, satisfying the subsequent analysis of wetland spatiotemporal changes; (2) a net loss of 3.8% in the SRTR alpine wetlands, with a notable 7.9% net loss in marsh wetlands and nearly 32,010 km² lost by 2015; and (3) topography and permafrost change as key drivers (as identified by the PLS-SEM), with permafrost contributing 52% to the significant marsh wetland loss from 2010 to 2015. This study aims to provide fundamental information that is essential for the monitoring and conservation of alpine wetlands. Full article

Background: Systemic Candida infection (SCI) is the third most common cause of late-onset sepsis in Neonatal Intensive Care Units (NICU). While platelet involvement in fungal infections has been extensively studied, evaluation of the hemostatic mechanism in Candida infections, especially in neonates, has not been widely investigated. The aim of the current study was to evaluate the hemostatic profile of neonates with SCI through rotational thromboelastometry (ROTEM), a laboratory method that assesses the viscoelastic properties of blood. Methods: This is a single-centered prospective cohort study including a group of neonates with SCI (n = 21); the control group consisted of healthy neonates (n = 24). Demographics, clinical parameters, and laboratory data were recorded at the disease onset. Neonatal scores for the assessment of disease severity (Modified NEOMOD, nSOFA, and NeoBAT) were also calculated. ROTEM parameters of neonates with SCI were compared to those of healthy neonates. Results: ROTEM parameters differed between neonates with SCI and healthy neonates, indicating a hypocoagulable profile of infected neonates. Specifically, neonates with SCI had significantly prolonged clotting time (CT) and clot formation time (CFT), as well as lower clot amplitude at 10 min (A10) and maximum clot firmness (MCF) when compared to healthy neonates (p values < 0.05), findings that remained consistent after adjusting for confounding factors such as gestational age, birth weight, and sex. In addition, a strong correlation was noted between ROTEM parameters and disease severity based on the modified NEOMOD, nSOFA, and NeoBAT scores. Conclusions: ROTEM parameters revealed a hypocoagulable profile in neonates during the early stages of SCI, which is also associated with disease severity. The results of this study highlight the need for monitoring of hemostatic status of this vulnerable group of patients and indicate that ROTEM analysis may have a role in the early detection of the hemostatic derangements associated with SCI in neonates, in order to ensure timely diagnosis and targeted therapeutic intervention. Full article

Mounting evidence suggests an increasing heatwave risk in the Chinese mainland, posing notable threats to public health and the socioeconomic landscape. In a comprehensive analysis, considering both climate and socioeconomic factors, including Gross Domestic Product (GDP) and population dynamics, we systematically evaluated the spatiotemporal distribution of heatwave socioeconomic exposure in the Chinese mainland from 2000 to 2019, utilizing a more comprehensive heatwave hazard index (HHI) that synthesizes heatwave intensity, frequency, and duration as climate factor for the first time. Results show that (1) Heatwave exposure is pronounced in eastern China, particularly in Southeast (SE), North China (NC), and Southwest (SW) regions. From 2000 to 2019, heatwave exposure showed an overall upward trend, with the most rapid escalation observed in the SE, NC, and SW regions. Population exposure manifests as a clustered expansion pattern, while GDP exposure demonstrates a more centralized distribution. (2) Climatic factors exert the most notable influence on population exposure, while GDP predominantly impacts economic exposure. The combination of climate and socioeconomic factors contributes less to exposure rates, except in the Northeast (NE) and Southwest (SW) regions where it impacts GDP exposure most. (3) High-risk hotspot cities include Shanghai, Beijing, Chongqing, Guangzhou, Wuhan, Zhengzhou, Hangzhou, Xi’an, Tianjin, and Nanjing. These findings underscore the urgent need for targeted interventions and mitigation strategies in these vulnerable areas. Full article

Background: This study addresses the lack of research on Medicaid expansion’s impact on melanoma staging, treatment utilization, and outcomes by evaluating its effects under the Affordable Care Act (ACA), particularly focusing on staging at diagnosis, treatment use, and 3-year mortality outcomes. The objective is to determine whether Medicaid expansion led to earlier melanoma diagnosis and improved survival rates among non-elderly adults (ages 40–64) by analyzing data from the National Cancer Database (NCDB). Methods: A total of 12,667 patients, aged 40–64, diagnosed with melanoma from 2010 to 2020 were identified using the NCDB. Difference-in-difference (DID) analysis was performed to analyze tumor staging at presentation between Medicaid expansion states and non-Medicaid expansion states both prior to the expansion and after the expansion. Results: Of the total patients, 2307 were from the pre-expansion time period residing in Medicaid expansion states (MES) and 1804 in non-Medicaid expansion states. In the post-expansion time period there were 5571 residing in the MES and 2985 in the non-MES. DID analysis revealed a decrease in stage IV melanoma at diagnosis (DID −0.222, p < 0.001) between MES and non-MES before and after Medicaid expansion. After expansion, in stage IV, the occurrence of primary surgery was 0.42 in non-MES and 0.44 (difference 0.02); DID analysis was not statistically significant. The use of immunotherapy in MES was significantly higher than in non-MES after expansion (p < 0.001), although DID analysis did not reveal a statistically significant difference. DID analysis showed a statistically significant decrease in 3-year mortality (DID −0.05, p = 0.001) between MES and non-MES before and after Medicaid expansion. Conclusions: This study revealed the positive impact of the ACA’s Medicaid expansion on melanoma stage at presentation, highlighting the importance of public health policies in reducing disparities in mortality rates and early-stage diagnoses. Future research should explore additional barriers to care and evaluate the long-term outcomes of Medicaid expansion to optimize cancer care for vulnerable populations. Full article

Flood events pose significant risks to infrastructure and populations worldwide, particularly in Punjab, Pakistan, where critical infrastructure must remain operational during adverse conditions. This study aims to predict flood-prone areas in Punjab and assess the vulnerability of critical infrastructures within these zones. We developed a robust Flood Susceptibility Model (FSM) utilizing the Maximum Likelihood Classification (MLC) model and Analytical Hierarchy Process (AHP) incorporating 11 flood-influencing factors, including “Topographic Wetness Index (TWI), elevation, slope, precipitation (rain, snow, hail, sleet), rainfall, distance to rivers and roads, soil type, drainage density, Land Use/Land Cover (LULC), and the Normalized Difference Vegetation Index (NDVI)”. The model, trained on a dataset of 850 training points, 70% for training and 30% for validation, achieved a high accuracy (AUC = 90%), highlighting the effectiveness of the chosen approach. The Flood Susceptibility Map (FSM) classified high- and very high-risk zones collectively covering approximately 61.77% of the study area, underscoring significant flood vulnerability across Punjab. The Sentinel-1A data with Vertical-Horizontal (VH) polarization was employed to delineate flood extents in the heavily impacted cities of Dera Ghazi Khan and Rajanpur. This study underscores the value of integrating Multi-Criteria Decision Analysis (MCDA), remote sensing, and Geographic Information Systems (GIS) for generating detailed flood susceptibility maps that are potentially applicable to other global flood-prone regions. Full article

Climate prediction is of fundamental importance to various sectors of society and the economy, as it can predict the likelihood of droughts or excessive rainfall in vulnerable regions. Climate models are useful tools in producing reliable climate forecasts, which have become increasingly vital due to the rising impacts of climate change. As global temperatures rise, changes in precipitation patterns are expected, increasing the importance of reliable seasonal forecasts to support planning and adaptation efforts. In this study, we evaluated the performance of NOAA/GFDL models from CMIP6 simulations in representing the climate of South America under three configurations: atmosphere-only, coupled ocean-atmosphere, and Earth system. Our analysis revealed that all three configurations successfully captured key climatic features, such as the South Atlantic Convergence Zone (SACZ), the Bolivian High, and the Intertropical Convergence Zone (ITCZ). However, coupled models exhibited larger errors and lower correlation (below 0.6), particularly over the ocean and the South American Monsoon System, which indicates a poor representation of precipitation compared with atmospheric models. The coupled models also overestimated upward motion linked to the southern Hadley cell during austral summer and underestimated it during winter, whereas the atmosphere-only models more accurately simulated the Walker circulation, showing stronger vertical motion around the Amazon. In contrast, the coupled models simulated stronger upward motion over Northeast Brazil, which is inconsistent with reanalysis data. Moreover, we provided insights into how model biases may evolve under climate change scenarios. Future climate projections for the mid-century period (2030–2060) under the SSP2-4.5 and SSP5-8.5 scenarios indicate significant changes in the global energy balance, with an increase of up to 0.9 W/m². Additionally, the projections reveal significant warming and drying in most of the continent, particularly during the austral spring, accompanied by increases in sensible heat flux and decreases in latent heat flux. These findings highlight the risk of severe and prolonged droughts in some regions and intensified rainfall in others. By identifying and quantifying the biases inherent in climate models, this study provides insights to enhance seasonal forecasts in South America, ultimately supporting strategic planning, impact assessments, and adaptation strategies in vulnerable regions. Full article

In a world increasingly dependent on technology and in an era where connectivity is omnipresent, Web applications have become an essential part of our everyday life. The evolution of these applications, combined with the exponential increase in the number of users, has brought with it not only convenience but also significant challenges in terms of security. Ensuring the security of Web applications and their data is increasingly a priority for companies, although many companies lack the know-how, time, and money to do so. This research project studied and developed a system with the aim of automating the process of detecting vulnerabilities in Web applications by exploiting the benefits of the interoperability of the two forms of automation of the tool selected to carry out this analysis. The developed solution is low-cost and requires very little user intervention. In order to validate and evaluate the developed platform, experiments were carried out on applications with different types of vulnerabilities known in advance and on real applications. It is essential to guarantee the security of Web applications, and the developed system proved capable of automating the detection of vulnerability risks and returning the results in a relatively simple way for the user. Full article

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. Full article

Salt marshes are declining due to the dual pressures of coastal erosion and land reclamation. However, there remains a lack of quantitative analysis regarding this reduction process and its driving mechanisms. This study examines the dynamics and influencing factors of salt marsh vegetation along the eroding coastline of Sheyang County, Jiangsu Province, China, between 1985 and 2020, using remote sensing to analyze changes in artificial coastlines, water boundaries, vegetation front edge, and its topography. Our results showed an extensive seaward movement of artificial coastlines due to reclamation, coupled with severe reductions in salt marsh area and width. Coastal erosion further caused a 10.5% decline in vegetation elevation and a 46.7% increase in slope steepness, amplifying vulnerability to wave action. Native species were largely replaced by Spartina alterniflora, reducing ecological diversity. Currently, human pressure on the landward side has been alleviated; thus, addressing coastal erosion is vital to preventing the further loss of salt marshes. Sediment retention engineering and native vegetation restoration efforts can gradually facilitate the recovery of salt marshes. This study provided critical insights for sustainable coastal management under bidirectional pressures. Full article

The coastal zone of the Sea of Azov is a dynamic environment influenced by various natural and anthropogenic factors, including wind, wave action, beach material removal, and cultivation on cliff edges. The coastal zone of freezing seas is also influenced by ice cover during winter. This study investigates the dynamics of the Sea of Azov’s coastal zone during winter (2014–2023), focusing on the impacts of waves and ice, to identify the most vulnerable coastal areas. We analyzed high-resolution satellite imagery and employed mathematical modeling to obtain data on ice pile-up, fast ice formation, wind patterns, and storm wave dynamics within the shallow coastal zone. Long-term wind data revealed an increase in maximum wind speeds in December and January, while February and March showed a decrease or no significant trend across most coastal observation stations. Storm waves (significant wave height) during the cold season can reach heights of 3.26 m, contributing to coastal erosion and instability. While the overall ice cover in the Sea of Azov is decreasing, with fast ice rarely exceeding 0.85% of the total sea area, ice pile-up still occurs almost annually, with the eastern part of Taganrog Bay exhibiting the highest probability of these events. Our analysis identified the primary impacts affecting the shallow coastal zone of the Sea of Azov between 2014 and 2023. A map was generated to illustrate these impacts, revealing that nearly the entire coastline is subject to varying degrees of wave and ice impact. Exceptions include the eastern coast, which experiences minimal fast ice and ice pile-up, with average or lower dynamic loads, and the southern coast, where wind–wave action is the dominant factor. Full article

The proliferation of Internet of Things (IoT) devices and big data has catalyzed the emergence of data markets. Regulatory and technological frameworks such as International Data Spaces (IDS) have been developed to facilitate secure data exchange while integrating security and data sovereignty aspects required by laws and regulations, such as the GDPR and NIS2. Recently, novel attack vectors have taken a toll on many enterprises, causing significant damage despite the deployed security mechanisms. Hence, it is reasonable to assume that the IDS may be just as susceptible. In this paper, we conduct a STRIDE threat analysis on IDS to assess its susceptibility to traditional and emerging cybersecurity threats. Specifically, we evaluate novel threats such as Man-in-the-Middle (MitM) attacks, compromised end-user devices, SIM swapping, and potential backdoors in commonly used open-source software. Our analysis identifies multiple vulnerabilities, particularly at the trust boundary (TB) between users and the IDS system. These include the traditionally troublesome Denial of Service (DoS) attacks, key management weaknesses, and the mentioned novel threats. We discuss the hacking techniques, tools, and associated risks to the IDS framework, followed by targeted mitigation strategies and recommendations. This paper provides a framework for performing a STRIDE-based threat analysis of the IDS. Using the proposed methodology, we identified the most potent threats and suggested solutions, thus contributing to the development of a safer and more resilient data space architecture. Full article

Background/Objectives: Seasonal influenza is a significant global health concern, causing substantial morbidity and mortality, particularly among high-risk groups such as children under five years old. There is scarce local evidence from developing countries such as Jordan on the burden of influenza, which has limited preventive measures. This multi-center national cross-sectional study aimed to assess the epidemiological and clinical burden of influenza among hospitalized children under five years old in Jordan. Methods: Data were collected from 1000 participants across four hospitals between November 2022 and April 2023. Nasopharyngeal specimens were analyzed using multiplex RT-PCR to determine positivity for influenza A and B. Results: We found a 9.9% positivity rate, predominantly influenza A (8.4%), while influenza B was positive among 1.5% of the participants. Positivity rates were higher in older age groups, particularly children older than 2 years. Influenza-positive cases exhibited longer fever durations and higher rates of sore throat. There were no positive influenza cases among participants if they or any of their family members received the influenza vaccine, highlighting the vaccine’s protective role. Logistic regression analysis identified maternal smoking during pregnancy as a significant predictor of influenza positivity. Conclusions: The findings of this study underscore the need for enhanced vaccination efforts and public health policies targeting young children and pregnant women in Jordan. Expanding vaccination uptake could significantly mitigate the burden of influenza and its complications in this vulnerable population. Full article

Background: Antimicrobial resistance (AMR) is recognized as one of the most important global public health threats. There is an urgent need to reduce the spread of these multidrug-resistant bacteria (MDR-B), particularly in extremely vulnerable patients. The aim of this study was to investigate whether targeted gene amplification performed directly on clinical samples can be used simultaneously with a bundle of enhanced infection control measures in a Pediatric Intensive Care Unit (PICU) endemic to MDR-B. Methods: This study had three phases: (1) the baseline phase was performed prior to intervention when first screening and sample collection were performed; (2) the intervention phase was performed when various enhanced infection control measures (EICM) were applied; and (3) the maintenance phase occurred when EICMs were combined with the implementation of targeted molecular surveillance. The presence of four carbapenemase genes, bla_KPC, bla_OXA-48-like, bla_VIM, and bla_NDM, as well as the β-lactamase genes bla_TEM and bla_SHV, was evaluated by PCR after DNA isolation directly from stool samples. The results were compared to culture-based phenotypic analysis. Results and Conclusions: The implementation of EICM appeared to reduce the resistance burden in this sample endemic to an MDR-B clinical setting. The direct implementation of a targeted and customized rapid molecular detection assay to clinical samples seems to be an effective clinical tool for the evaluation of EICM measures. Full article

Suburban areas are often used for large-scale developments such as hypermarkets, warehouses, and logistics zones, which lead to the fragmentation of natural areas and the visual degradation of the landscape. This study aimed to evaluate ways to reduce the negative impact of these developments by introducing green infrastructure (GI) elements. The analysis focused on warehouses in the inner ring of the planned green infrastructure system in the Wrocław Functional Area (GI WFA). This study involved three stages: (1) selecting a landscape-functional unit (LaFU) vulnerable to landscape degradation; (2) analyzing changes from the development of large-scale warehouses between 2004 and 2021; and (3) assessing the effect of new GI elements using the Sectoral Landscape Interior Analysis (SALI) method. Three models of GI implementation were proposed and evaluated both from a plan view and from a moving observer’s perspective. The results showed that large-scale developments reduce biologically active areas and disrupt landscape harmony. Model III, which includes green roofs, trees, and semi-permeable surfaces, significantly increased greenery and reduced visual degradation. It is recommended to apply the model and its variations in other similar developments for the benefit of the natural environment and landscape. Full article

This study examines the relationships among social capital, residential satisfaction, and attitudes toward disadvantaged groups in South Korea, with a focus on the moderating effects of educational and employment vulnerability. Using data from the 2022 Seoul Survey, which included a sample of 39,340 individuals, the analysis employed Hayes’ Process Macro to assess both mediation and moderated mediation effects. The findings show that social capital significantly enhances residential satisfaction (β = 0.557, p < 0.001), which, in turn, positively influences attitudes toward disadvantaged groups (β = 0.411, p < 0.001). Notably, the impact of residential satisfaction on attitudes was stronger for individuals who were educationally and employment-vulnerable, underscoring the amplified role of housing conditions in shaping social attitudes for these groups. These results highlight the importance of strengthening social capital and implementing targeted housing policies to improve the well-being of vulnerable populations. Policy recommendations include integrating social capital-building initiatives with urban planning strategies and addressing the specific needs of vulnerable groups through tailored housing interventions to foster social cohesion and inclusivity. Future research should explore other dimensions of vulnerability and utilize longitudinal data to assess long-term impacts. Full article