Search Results (21,551)

The increasing frequency and severity of extreme natural events, along with their escalating impacts, highlight the urgent need for robust tools to assess and strengthen national capacities for disaster preparedness and recovery. In this context, this paper introduces one of these tools, called the Recovery Gap Index (RGI), a comprehensive composite index designed to quantify and evaluate the post-extreme natural event response and recovery capabilities at the country level. The tool addresses the need for a systematic approach to quantify resilience and evaluate the impacts of consecutive events on vulnerable areas. The RGI synthesizes data from three well-established indices: the World Risk Index, INFORM, and Global Infrastructure Risk Model and Index (GIRI), covering critical dimensions related to sociodemographic factors, infrastructure, governance, technology, and economic resilience. By extracting key parameters from these diverse indices and aggregating them, the RGI provides a detailed assessment of each nation’s ability to manage the aftermath of extreme natural events. The index findings reveal significant regional disparities in recovery capacities, with European countries exhibiting stronger resilience, whereas many African and Asian nations face substantial challenges. Furthermore, this study proposes several potential future enhancements, such as the incorporation of early warning systems and insurance coverage metrics, aimed at improving its accuracy and practical application. The RGI aims to be a valuable tool for policymakers, disaster management professionals, and stakeholders, enabling them to make informed decisions and implement targeted interventions to further enhance global disaster resilience. Full article

Objectives: Chronic diseases are a significant public health issue, especially for socioeconomically vulnerable population groups. The purpose of this study is to compare the prevalence of chronic diseases in people receiving and not receiving BLS and to determine the prevalence of chronic diseases according to the physical activity and dietary habits of people receiving BLS. Methods: Data were derived from the sixth to ninth waves (2014–2022) of the Korea National Health and Nutrition Examination Survey (KNHANES), focusing on 15,041 participants aged 65 and older. Demographic characteristics, dietary intake, physical activity, and chronic disease status were assessed. Multivariate logistic regression analysis was used to calculate odds ratios for chronic diseases according to physical activity and dietary habits. Results: The BLS group exhibited higher prevalence rates of hypertension and diabetes, along with lower dietary intake of energy, protein, fat, carbohydrates, dietary fiber, and vitamin C, compared to the non-BLS group. A below-average intake of energy and carbohydrates was associated with increased odds of hypertension and diabetes, particularly in the BLS group. For dietary fiber, a significant association with diabetes was found only in the BLS group. Sedentary behavior exceeding 9 h per day was linked to higher odds of chronic diseases in both groups, with stronger associations in the BLS group. Limited walking frequency (less than 1 day per week) further exacerbated risks. Conclusions: BLS recipients demonstrated higher chronic disease prevalence, poorer dietary habits, and more sedentary behavior compared to non-recipients. The associations between lifestyle factors and chronic diseases were generally more substantial in the BLS group, suggesting the need for targeted interventions to improve dietary quality and physical activity patterns in this vulnerable population. Full article

Background/Objectives: Depressive disorders are diagnosed using categorical definitions provided by DSM-5 and ICD-11. However, categorization for diagnostic purposes fails to account for the inherently dimensional nature of depression. Artificial categorization may impede research and obstruct the achievement of optimal treatment outcomes. Methods: The current study utilized a Canadian historical dataset called the National Population Health Survey (NPHS) to explore a simple alternative approach that does not depend on categorization. The NPHS collected complete data from 5029 participants through biannual interviews conducted in 1994–2010. Data collection included the K6 Distress Scale as well as the Composite International Diagnostic Interview Short Form for Major Depression. Data from the National Population Health Survey (NPHS) were used to quantify vulnerability to depressive symptoms through longitudinal K6 Distress Scale assessments. Variability of symptoms across this dimension of apparent vulnerability was quantified using ordinal regression, adjusting for age and sex. Results: Predicted probabilities from these models were used in simulations to produce a visualization of the epidemiology and to explore clinical implications. Conclusions: Consideration of these two dimensional factors (estimated overall level of vulnerability to depression and variability over time) is already a component of clinical assessment and is also accessible to repeated measurement in settings adopting measurement-based care. More formal consideration of these elements may provide a complementary approach to categorical diagnostic assessment and an opportunity for greater personalization of care and improved clinical outcomes. Future studies should validate these findings in diverse clinical settings to ensure their applicability in real-world contexts. Full article

One of the important distribution areas of stone pine (Pinus pinea L.), a native tree species of the Mediterranean Basin in Türkiye, is the Kozak Basin. Pine nut production plays an important role in the livelihood of the rural people of the Kozak Basin. However, in recent years, as a result of mining activities, climate change, and damage caused by the alien invasive species, the western conifer seed bug (Leptoglossus occidentalis Heidemann 1910 (Hemiptera; Coreidae), the decrease in cone and seed yield in the basin has reached significant dimensions. This process has caused the local people’s income sources to decrease. In this study, land use and land cover (LULC) changes and population changes in the Kozak Basin were discussed during the process, where changing forest land functions, especially economic effects, triggered vulnerable communities due to various factors such as climate change and insect damage. LULC classes of the Kozak Basin and their changes in three time periods are presented using the maximum likelihood method. In addition, the exponential population growth rates of the local people in three different time periods were calculated and these rates were interpolated in the spatial plane with a Kriging analysis. In conclusion, the responses of vulnerable communities to the cone and seed yield decline in the Kozak Basin are manifested by LULC changes and migration from the basin. Therefore, in the management of P. pinea areas, the creation of regulations within the framework of sustainability understanding regardless of ownership difference, stakeholder participatory approach management, close monitoring of ecological events occurring in the basin, awareness of vulnerable communities, and alternative livelihoods can be supported. Full article

The widespread deployment of deep neural networks (DNNs) in critical real-time applications has spurred significant research into their security and robustness. A key vulnerability identified is that DNN decisions can be maliciously altered by introducing carefully crafted noise into the input data, leading to erroneous predictions. This is known as an adversarial attack. In this paper, we propose a novel detection framework leveraging segmentation masks and image segmentation techniques to identify adversarial attacks on DNNs, particularly in the context of autonomous driving systems. Our defense technique considers two levels of adversarial detection. The first level mainly detects adversarial inputs with large perturbations using the U-net model and one-class support vector machine (SVM). The second level of defense proposes a dynamic segmentation algorithm based on the k-means algorithm and a verifier model that controls the final prediction of the input image. To evaluate our approach, we comprehensively compare our method to the state-of-the-art feature squeeze method under a white-box attack, using eleven distinct adversarial attacks across three benchmark and heterogeneous data sets. The experimental results demonstrate the efficacy of our framework, achieving overall detection rates exceeding 96% across all adversarial techniques and data sets studied. It is worth mentioning that our method enhances the detection rates of FGSM and BIM attacks, reaching average detection rates of 95.65% as opposed to 62.63% in feature squeezing across the three data sets. Full article

People, communities, and economies in small island developing states are extremely vulnerable to climate change, disasters, and other crises. Renewable energy can play an important part in building the resilience of these communities. Three case studies were conducted in Fiji (i.e., a grid-connected secondary school with roof-top solar PV and biogas, an off-grid community with solar home systems, and a farm that uses solar PV for irrigation) to demonstrate how renewable energy initiatives build community resilience. This study used the community resilience framework, RETScreen tool, information gathered from key informants’ interviews, and secondary data sources to conduct qualitative and quantitative analyses. It found that seven community assets, i.e., human, social, cultural, financial, natural, built, and political assets, are enhanced, leading to an increase in absorptive, adaptive, and transformative capacities for these communities. Furthermore, current research shows that human capital is one of the key instruments in the adoption of new innovative technologies. The results from this study can be used by decisionmakers to promote and implement similar technologies in communities, which not only provide clean electricity and clean cooking energy for climate change mitigation but also build community resilience. Full article

Large storage tanks situated in coastal areas are vulnerable to environmental hazards, with earthquakes being one of the most destructive forces threatening their structural safety. Additionally, differential settlement can significantly alter conditions in the tank, including the inclination, thereby changing the direction of external applied excitation forces and affecting the liquid sloshing response. To investigate the coupled effects of structural settlement and external excitation, model tests were conducted in series to analyze liquid sloshing behavior in a tilted tank subjected to harmonic excitation. The results revealed that the liquid response under combined environmental loads displayed distinct characteristics compared with that under single excitation. While the inclination angle had minimal influence during the unstable sloshing stage, it became crucial during the stable stage, particularly for third-order resonant responses, leading to intensified sloshing. More specifically, as the tilt angle of the storage tank from 0° to 8°, the steady-state wave height at third-order resonance increased by approximately 69%. This highlights the amplified risks to the structural stability and safety posed by differential settlement. Furthermore, variations in steady-state wave heights due to differential settlement conditions were investigated. The water level elevation along the tank walls varies as the inclination angles increase, which leads to potential risks to the stability of liquid storage under forced motion, especially under symmetric structural designs, and increases the likelihood of structural instability, oil spills, and other coastal disasters. These results provide valuable insights into the safety risks and sustainable utilization of coastal infrastructure, serving a basis for assessing and mitigating the risks associated with structural settlement and seismic excitations. Full article

Drug resistance remains a significant barrier to effective cancer therapy. Cancer cells evade treatment by reprogramming their metabolism, switching from glycolysis to oxidative phosphorylation (OXPHOS), and relying on alternative carbon sources such as glutamine. These adaptations not only enable tumor survival but also contribute to immune evasion through mechanisms such as reactive oxygen species (ROS) generation and the upregulation of immune checkpoint molecules like PD-L1. This review explores the potential of targeting metabolic weaknesses in drug-resistant cancers to enhance therapeutic efficacy. Key metabolic pathways involved in resistance, including glycolysis, glutamine metabolism, and the kynurenine pathway, are discussed. The combination of metabolic inhibitors with immune checkpoint inhibitors (ICIs), particularly anti-PD-1/PD-L1 therapies, represents a promising approach to overcoming both metabolic and immune evasion mechanisms. Clinical trials combining metabolic and immune therapies have shown early promise, but further research is needed to optimize treatment combinations and identify biomarkers for patient selection. In conclusion, targeting cancer metabolism in combination with immune checkpoint blockade offers a novel approach to overcoming drug resistance, providing a potential pathway to improved outcomes in cancer therapy. Future directions include personalized treatments based on tumor metabolic profiles and expanding research to other tumor types. Full article

Food insecurity is a growing public health concern, particularly among vulnerable groups such as adolescents, and it has been linked to poor nutritional outcomes and increased risk of chronic diseases. The Mediterranean diet (MedDiet) is recognized for its numerous health benefits, yet few studies have explored the association between food insecurity and adherence to the MedDiet among adolescents, especially in Mediterranean regions. Objective: This study aimed to investigate the association between food insecurity and adherence to the MedDiet in a sample of adolescents from Spain. Methods: Data were acquired from 2021–2022 school years from adolescents aged 12–17 years enrolled in different secondary schools in Valle de Ricote, Region of Murcia, Spain. Food security was assessed via the Spanish Child Food Security Survey Module (CFSSM-S), and adherence to the MedDiet was assessed via the Mediterranean Diet Quality Index for Children and Adolescents (KIDMED). A total of 836 participants were involved, and statistical analyses were conducted via linear regression models adjusted for lifestyle, anthropometric, and sociodemographic covariates. Results: After adjusting for potential confounders, the mean KIDMED score was 7.0 (95% confidence interval [CI] 6.7 to 7.2) in the food-security group, 6.8 (95% CI 6.3 to 7.3) in the low-security group, and 5.9 (95% CI 4.9 to 6.9) in the very-low-security group. Notable differences were observed between participants with food security and their counterparts with very low food security (p = 0.040). Compared with those with food security (57.2%, 95% CI 51.5% to 62.8%), a significantly greater likelihood of having nonoptimal adherence to the MedDiet was identified in adolescents with low food security (61.6%, 95% CI 50.4% to 71.8%) and in those with very low food security (77.4%, 95% CI 54.5% to 90.7%). We identified a significant difference only between adolescents with food security and their peers with very low food security (p = 0.036). Conclusions: The findings suggest that very low food security negatively impacts MedDiet adherence in adolescents. Compared with their food-secure peers, adolescents with very low food security showed significantly poorer diet quality. These results highlight the importance of addressing food insecurity through low-cost, high-nutrition programs aimed at improving healthy eating habits, particularly for children and adolescents living in low-food-security households. Full article

The data on hosts of Ellobiopsis in Central Asia waterbodies are nearly non-existent. All research in this direction was conducted in other regions (Europe and Brazil). Parasitological studies were carried out in different seasons in the North and Middle Caspian Sea. Twenty-one taxa were registered in zooplankton, and only dominants of community calanoids Acartia (Acanthacartia) tonsa and Calanipeda aquaedulcis were infected with Ellobiopsis sp. Calanoida C. aquaedulcis was reported for the first time as a host for Ellobiopsis. The number of parasites per host was equal to one. The body length of parasites varied from 0.10 to 0.80 mm. The highest infection degree was recorded in C. aquaedulcis (5.71%), and it varied from 2.61% to 3.35% in Acartia. The individuals in the juvenile developmental stages were infected in Calanipeda, while in Acartia, individuals in all developmental stages were vulnerable to infection. The infected calanids had reduced body lengths. The findings suggest the possible influence of Ellobiopsis sp. on quantitative variables of hosts in the Middle Caspian, especially on biomass, by reducing the body sizes of hosts. However, no effect on the abundance and biomass of the host and the structure of the zooplankton of the North Caspian Sea has been detected. Full article

Although Caenorhabditis elegans is commonly used to assess the neurotoxicity of environmental pollutants, studies that explore the intricate biology of its nervous system, particularly those addressing long-term effects and aging in adult worms, are rare. These models offer significant advantages for understanding the full spectrum of neurobiological impacts. Here, we investigated the effects of silica nanomaterials on the γ-aminobutyric acid (GABA) neural system in young to middle-aged nematodes and found a unique degeneration pattern characterized by loss of anterior- and posteriormost GABAergic D-type motor neurons. Four-day-old nematodes were identified as a vulnerable age group, where the pollutant-accelerated neurodegeneration that is typically seen in old C. elegans. Proteomics of 4-day-old C. elegans revealed significant alterations of protein abundance, including the downregulation of proteins such as glutamate dehydrogenase (gdh-1) and glutamate oxaloacetate transaminase (got-1.2), which are essentially involved in GABA metabolic pathways. Consistent with these findings, we demonstrated locomotion deficits in C. elegans exposed to nanoscale silica by establishing a semi-automated behavioral arena. Our setup not only visualizes but also automatically quantifies vulnerabilities at the individual worm level. This novel neurodegeneration model now enables the simulation of real-world pollutant mixtures and environmental conditions, capturing the complexity of the exposome. Full article

Social vulnerability plays a vital role in understanding how various societal characteristics influence communities during extreme events. This study aimed to systematically identify key indicators and methodological approaches used in Social Vulnerability Index (SVI) research by utilizing the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The study specifically addresses gaps in indicator selection and emphasizes incorporating land-related and diverse variables for improved applications across various contexts. Social variables essential for SVI development were collected, and their applications across studies were analyzed. A total of 30,443 articles were identified from multiple databases, with 72 meeting the inclusion criteria after rigorous evaluation. Key aspects such as methodologies, weighting schemes, and primary variables used in SVI computation were outlined. Principal component analysis emerged as the most commonly employed method, though diverse approaches have gained traction in recent years. Significant variability was observed in the variables across studies, with demographic indicators being the most frequently utilized. The identified variables were categorized into 21 domains, comprising 61 indicators. While the findings of this study focus on improving the understanding of SVI development and its diverse applications, they also hold potential for informing sustainable land management and disaster resilience strategies, particularly in tailoring interventions to region-specific vulnerabilities. Full article

High-risk myeloid neoplasms encompass a group of hematologic malignancies known to cause significant cytopenias, which are accompanied by the risk of end-organ damage. They tend to have an aggressive clinical course and limit life expectancy in the absence of effective treatments. The adoption of precision medicine approaches has been limited by substantive diversity in somatic mutations, limited fraction of patients with targetable genetic lesions, and the prolonged turnaround times of pertinent genetic tests. Efforts to incorporate targeted agents into first-line treatment, rapidly determine pre-treatment molecular or cytogenetic aberrations, and evaluate functional vulnerabilities ex vivo hold promise for advancing the use of precision medicine in these malignancies. Given the relative accessibility of malignant cells from blood and bone marrow, precision medicine strategies hold great potential to shape future standard-of-care approaches to patients with high-risk myeloid malignancies. This review aims to summarize the development of the targeted therapies currently available to treat these blood cancers, most notably acute myeloid leukemia, and also evaluate future opportunities and challenges related to the integration of personalized approaches. Full article

Soil degradation and erosion pose significant threats to agricultural sustainability in fragile ecosystems, such as the Loess Plateau in northern China. This study examines the long-term impacts of fertilization regimes and land-use systems on soil health, focusing on soil aggregate stability, fertility, and crop productivity. Six treatment combinations were evaluated in our study, including three continuous alfalfa fields (AL-CK, AL-P, and AL-NPM) and three continuous wheat fields (WH-NPM, WH-NP, and WH-P), each representing a combination of land use and three fertilization treatments: (1) no fertilization (CK), (2) inorganic fertilization (120 kg ha⁻¹ N, 60 kg ha⁻¹ P-NP), and (3) a combination of organic and inorganic fertilization (75 t ha⁻¹ cow manure-NPM). Soil samples were collected from three depths (0–10 cm, 10–20 cm, and 20–30 cm) to assess physical and chemical properties. We evaluated the long-term effects of different fertilization treatments on soil stability, fertility, and crop yield to explore the interactions among soil’s physical and chemical properties under two land-use types and to assess the effectiveness of combined organic and inorganic fertilization strategies in improving soil health and mitigating erosion in vulnerable landscapes. The study revealed significant depth-specific variations with surface layers (0–10 cm) showing the greatest improvement under NPM treatments, particularly in continuous alfalfa fields, which exhibited higher soil fertility, improved soil structure, and crop yield. In contrast, continuous wheat fields with minimal fertilization demonstrated significantly lower soil quality and productivity. Using the combination of mineral fertilizers and organic amendments, such as cow manure, proved to be the most effective strategy for significantly enhancing nutrient availability and overall soil health. Partial Least Squares Modeling (PLS-M) and Mantel analysis highlighted the critical role of fertilization management in maintaining soil quality, boosting crop productivity, and mitigating erosion in high-risk areas. This study emphasizes the importance of integrated nutrient management for sustainable land use and soil conservation in erosion-prone regions. Full article

This study investigates the position of Côte d’Ivoire’s cocoa industry within the global production chain and identifies key influencing factors from 1960 to 2024. Using a Vector Error Correction Model (VECM), the research evaluates the effects of economic and climate variables—cocoa bean production, global cocoa prices, GDP contributions, domestic cocoa grindings, rainfall, and temperature—on cocoa exports. The findings reveal that a 1% increase in global cocoa prices decreases exports by 0.45%, indicating significant price sensitivity. Cocoa bean production accounts for 42.39% of export variance over the long term, while GDP contributions (0.88%) and domestic cocoa grindings (0.34%) enhance competitiveness and value addition. Rainfall negatively impacts productivity, underscoring vulnerabilities to climate variability, whereas temperature has a short-term positive effect on export performance (0.12%). Short-term dynamics demonstrate rapid adjustments toward equilibrium, with adjustment speeds of 41.23% for Côte d’Ivoire and 37.21% for Ghana. The study highlights Côte d’Ivoire’s dependence on raw cocoa exports and its susceptibility to price volatility and climate risks. By comparing Côte d’Ivoire with Ghana, the analysis underscores the advantages of robust domestic processing policies. To ensure long-term sustainability, the study recommends expanding domestic cocoa processing, adopting agroforestry practices to mitigate climate risks, and investing in infrastructure to boost competitiveness and resilience. Full article