Search Results (33,346)

As the global transition toward carbon neutrality accelerates, the sustainability of power electronics has received growing attention from both academia and industry. Nevertheless, standardized methodologies for evaluating the sustainability of power electronic systems—particularly traction inverters—remain limited, largely due to the absence of comprehensive databases and unified assessment frameworks. Leveraging industrial extensive design experience, this paper presents an enhanced methodology for sustainability evaluation of traction inverters. The proposed framework combines advanced component-level modelling with multi-physics-based analysis to more accurately quantify the environmental impacts associated with different power semiconductor technologies. A Random Forest (RF)-based algorithm is employed for junction temperature (T_J) estimation, offering reliable thermal data crucial for sustainability assessment. Experimental validation on a prototype automotive inverter confirms the accuracy and robustness of the RF-based T_J estimation approach, ensuring realistic thermal–environmental coupling within the evaluation workflow. From a thermal perspective, the sizing of power electronics key components (PEKCs) is performed with high precision, enabling a more accurate estimation of power electronics-related material (PERM) usage. Combined with a preliminary CO₂-equivalent (CO₂e) emissions database, this allows sustainability assessment to be integrated directly into the design stage of the traction inverter. The effectiveness of the proposed approach is demonstrated through a comparative evaluation of three representative inverter topologies. Full article

Diabetes develops through a mix of clinical, metabolic, lifestyle, demographic, and environmental factors. Most current classification models focus on traditional biomedical indicators and do not include environmental exposure biomarkers. In this study, we develop and evaluate a supervised machine learning classification framework that integrates heterogeneous demographic, anthropometric, clinical, behavioral, and environmental exposure features to classify physician-diagnosed diabetes using data from the National Health and Nutrition Examination Survey (NHANES). We analyzed NHANES 2017–2018 data for adults aged ≥18 years, addressed missingness using Multiple Imputation by Chained Equations, and corrected class imbalance via the Synthetic Minority Oversampling Technique. Model performance was evaluated using stratified ten-fold cross-validation across eight supervised classifiers: logistic regression, random forest, XGBoost, support vector machine, multilayer perceptron neural network (artificial neural network), k-nearest neighbors, naïve Bayes, and classification tree. Random Forest and XGBoost performed best on the balanced dataset, with ROC AUC values of 0.891 and 0.885, respectively, after imputation and oversampling. Feature importance analysis indicated that age, household income, and waist circumference contributed most strongly to diabetes classification. To assess out-of-sample generalization, we conducted an independent 80/20 hold-out evaluation. XGBoost achieved the highest overall accuracy and F1-score, whereas random forest attained the greatest sensitivity, demonstrating stable performance beyond cross-validation. These results indicate that incorporating environmental exposure biomarkers alongside clinical and metabolic features yields improved classification performance for physician-diagnosed diabetes. The findings support the inclusion of chemical exposure variables in population-level diabetes classification and underscore the value of integrating heterogeneous feature sets in machine learning-based risk stratification. Full article

The rapid deterioration of global infrastructure necessitates precise and automated crack detection technologies for proactive maintenance. However, deep learning-based segmentation models often suffer from a scarcity of diverse, high-quality labeled datasets. This study proposes StyleSPADE, a novel conditional image generation model that integrates semantic masks and style images to synthesize realistic crack data with diverse background textures while preserving precise geometric morphology. To validate the effectiveness of the generated data, we conducted extensive semantic segmentation tasks using Transformer-based (Mask2Former, Swin-UPerNet) and CNN-based (K-Net) models. Experimental results demonstrate that StyleSPADE-based augmentation significantly outperforms baseline models, achieving a Crack IoU of 0.6376 and an F1-score of 0.7586. Furthermore, we implemented a Stacking Ensemble strategy combining high-recall and high-precision models, which further improved performance to a Crack IoU of 0.6452. Our findings confirm that StyleSPADE effectively mitigates the data scarcity problem and enhances the robustness of crack detection in complex environmental conditions. This framework contributes to improving the efficiency and safety of infrastructure management by enabling reliable damage assessment in data-limited environments. Full article

This paper presents an energy-focused analysis of structural materials used in passenger cars, with a particular emphasis on the impact of construction materials on total energy consumption throughout the vehicle’s life cycle. Three production periods (2000, 2010, and 2020) were analysed for B- and C-segment vehicles using inventory data from Life Cycle Assessment databases, the scientific literature, and certified dismantling stations. The embodied energy of key material groups—steel, aluminium, plastics, and other materials—was calculated based on representative mass shares and material-specific energy intensity indicators. The computational model was supplemented with statistical analyses (Kolmogorov–Smirnov test, Levene’s test, ANOVA, and Tukey’s post hoc tests) to verify whether observed temporal trends were statistically significant. The results indicate that total material-related energy inputs increased from approximately 57 GJ to 64 GJ per vehicle, while the specific energy intensity per kilogram decreased from 47.6 MJ/kg to 42.6 MJ/kg. Aluminium exhibited a pronounced reduction in unit energy intensity due to the rising share of secondary materials, whereas plastics and other materials showed substantial increases. Steel remained the largest contributor in absolute terms because of its dominant mass share. This study highlights the growing importance of the production phase in the environmental balance of modern vehicles, particularly in the context of the rising share of lightweight materials and recycling-based components. The results emphasise the importance of energy-efficient material use and underscore the significance of material selection and recycling strategies in reducing energy demand within the automotive sector. Full article

Freshwater ecosystems are increasingly threatened by pollution, hydromorphological alteration, invasive species, and loss of ecological connectivity, complicating the monitoring and conservation of native fish communities. Environmental DNA (eDNA) has emerged as a sensitive, non-invasive, and cost-effective tool for detecting species, including rare or low-abundance taxa, overcoming several limitations of traditional methods. However, its rapid expansion has generated methodological dispersion and heterogeneity in protocols. This systematic review and bibliometric analysis synthesize 131 articles published between 2020 and 2025 on the use of eDNA in freshwater fish conservation. Due to the strong methodological heterogeneity among studies, the evidence was synthesized through a structured qualitative approach under PRISMA standards. Results show rapid growth in scientific output since 2023. eDNA has proven highly effective in identifying key ecological patterns such as migration and spawning, detecting critical habitats, and supporting temporal and spatial assessments. It has also facilitated early detection of invasive species including Oreochromis niloticus, Oncorhynchus gorbuscha, and Chitala ornata, and improved monitoring of threatened native species, reinforcing conservation decision-making. Despite advances, challenges persist, including variability in eDNA persistence and transport, gaps in genetic reference databases, and a lack of methodological standardization. Future perspectives include detecting parasites, advancing trophic analyses, and integrating eDNA with ecological modeling and remote sensing. Full article

Microplastics (MPs) are recognised as emerging vectors for hydrophobic organic contaminants in aquatic environments due to their relatively large surface area and the diversity of their polymer chemistries compositions. This study investigates the sorption behaviour of two priority polycyclic aromatic hydrocarbons (PAHs), pyrene (PYR) and fluoranthene (FLU), onto six common MPs: poly(m-xylene adipamide) (PA-MXD6), high- and low-density polyethylene (HDPE, LDPE), polypropylene (PP), polyethylene terephthalate (PET), and polylactic acid (PLA). Sorption isotherms and kinetics were evaluated under simulated freshwater conditions at environmentally relevant concentrations (1–50 µg·L⁻¹). Despite the low MP concentration used (0.2 g·L⁻¹), over 80% of the initial PAH content was removed by polyolefins, and more than 50% by all other MPs. Sorption capacity was strongly dependent on particle surface area. Langmuir, Henry, and Freundlich isotherms models were fitted, with linear behaviour prevailing at low concentrations. Analysis using the Dubini–-Radushkevich model confirmed that sorption involves chemisorption contributions, mainly through π–π interactions and hydrophobic interactions (polyolefins). Mechanistically, molecular diffusion within the MP matrix was not governing the sorption process, as diffusion coefficients varied with particle size instead of polymer chemistry. Instead, sorption appears to be governed by PAH diffusion through the hydrodynamic boundary layer and subsequent retention on the MP surface. Empirically, kinetic data fitted the pseudo-second-order model, further supporting that the sorption process involves chemisorption. These findings highlight the role of MPs as vectors for PAHs in freshwater systems and their potential application in contaminant removal. Expressing sorption per unit surface area is recommended for accurate assessment. This work contributes to understanding the environmental behaviour of MPs and their implications for pollutant transport and toxicity. Full article

Background: Migraine is a prevalent neurological disorder associated with significant morbidity and social burden. Although various triggers for migraine have been identified, the relationship between smoking and migraine remains unclear. This study aimed to compare migraine characteristics between people with and without smoking in Saudi Arabia. Methods: A cross-sectional study using an online survey tool had been conducted in Saudi Arabia. The survey assessed migraine characteristics, smoking behaviour, demographics, and comorbidities. Statistical analyzes were performed to investigate the occurrence of migraine, smoking behaviour, and demographic factors. Descriptive statistics summarized the data, with various statistical tests employed to compare variables between groups. Results: A total of 229 participants were included in the study, with a majority being young adults (48.47%), predominantly females (66.81%), and holding a bachelor’s degree (63.32%). The study found that 19.2% of individuals with migraine were current smokers, with an average smoking duration of 9.7 years. While some reported relief from migraine pain, others experienced increased pain intensity or frequency. No significant differences were found in migraine characteristics between smokers and non-smokers, but younger individuals and males with migraine were more likely to smoke. The study highlights the complex relationship between smoking and migraine, with varying effects on individuals. Conclusions: The study underscores the lack of significant differences in migraine characteristics between smokers and non-smokers, suggesting that smoking does not play a pivotal role in the clinical presentation of migraines. This insight prompts a shift in research focus towards other potential contributors to migraines, such as genetic predispositions, environmental factors, and comorbidities. Understanding these associations can inform public health strategies aimed at alleviating migraine-related burdens. Full article

We report the first observation of room-temperature phosphorescence (RTP) of quinine sulfate (QS) in poly (vinyl alcohol) (PVA) films. Steady-state and time-gated measurements were performed to characterize the phosphorescence spectra, anisotropies, and lifetimes to estimate the phosphorescence properties. The RTP response of organic emitters in polymer matrices is particularly sensitive to ambient humidity and oxygen levels. Hence, to assess the environmental stability of the system, QS-doped PVA films were cast from a single batch and divided into paired specimens, one of which was encapsulated with a pressure-sensitive laminate, while the other one was left non-laminated. Over 14 days under ambient laboratory conditions, the absorbance and fluorescence of both films remained unchanged, whereas the exhibited phosphorescence diverged significantly. The unlaminated film exhibited a progressive loss of afterglow intensity, a noticeable red shift in the phosphorescence spectrum, and a pronounced shortening of the phosphorescence lifetime, while the laminated film retained its initial RTP intensity, spectral profile, and lifetime throughout the entire experiment. Full article

The northern coast of Mauritania presents a strategic opportunity for clean energy investment due to its remarkable potential for green hydrogen production through wind energy. To determine the best location for wind-based green hydrogen production, this paper established a Multi-Criteria Decision-Making framework (MCDM) that combines the Analytic Hierarchy Process (AHP) and Evidential Reasoning (ER) to assess five coastal sites: Nouakchott, Nouamghar, Tasiast, Boulanoir, and Nouadhibou. Four main criteria (i.e., economic, technical, environmental, and social) and twelve sub-criteria were taken into account in the assessment. To ensure reliability and contextual accuracy, the data used in this study were obtained from geographic databases, peer-reviewed literature, and structured expert questionnaires. The results indicate that site 5 (Nouadhibou) is the most suitable location for green hydrogen generation using wind energy. Sensitivity analysis confirms the robustness of the ranking results, validating the reliability of the proposed hybrid framework. The findings of this study provide critical, data-driven decision-support insights for investors and policymakers, guiding the strategic development of sustainable wind-based green hydrogen projects along Mauritania’s coastline. Full article

Background: Chronic urticaria (CU) is characterized by recurrent wheals and/or angioedema persisting for more than six weeks. While disease triggers are often unidentified, seasonal and environmental factors may modulate disease activity; however, evidence regarding their clinical impact remains limited. Objective: This study aimed to evaluate the effects of seasonal, meteorological, and pollutant-specific environmental factors on urticaria control using the Urticaria Control Test (UCT), and to compare these effects between chronic spontaneous urticaria (CSU) and chronic inducible urticaria (CIU) in relation to inflammatory serum biomarkers. Materials and Methods: This prospective observational study was conducted at the Allergy and Clinical Immunology outpatient clinic of Kirikkale University Faculty of Medicine between 1 June 2023 and 1 April 2024. Patients with CU were classified as CSU or CIU according to international guidelines. Each participant was evaluated during summer and winter seasons. Area-level air pollution data and meteorological parameters were obtained from national monitoring systems. Disease control was assessed using the UCT, and inflammatory biomarkers were analyzed. Results: Urticaria control showed significant seasonal variation, with lower UCT scores during summer and higher scores during winter in both CSU and CIU patients. Among environmental factors, ozone (O₃) was the only pollutant consistently associated with poorer urticaria control, whereas particulate matter and traffic-related pollutants, despite being higher in winter, showed no clinically relevant association. Summer months were characterized by increased inflammatory activity, including elevated leukocyte counts, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), and D-dimer levels, particularly in CSU patients. D-dimer emerged as an independent marker associated with poor disease control during summer. Conclusions: CU demonstrates marked seasonal variation, with disease worsening during summer months. Pollutant-specific effects, particularly O₃ exposure, rather than overall air pollution burden, appear to be clinically relevant in urticaria control. Inflammatory and coagulation-related biomarkers may provide additional insight into disease activity. These findings support a season-aware and individualized management approach and highlight the need for future studies incorporating individual-level exposure assessment and biomarker-guided strategies. Full article

Growing concern over the environmental impact of conventional plastics has driven the development of biodegradable alternatives. In this context, natural polymers such as starch have emerged as sustainable options. Commercial montmorillonite, implemented as a reference nanomaterial, allows for the enhancement of the properties of biodegradable materials. In this study, commercial cassava starch powder plasticized with water and 35% glycerol, along with commercial nanoclay at concentrations of 0%, 2%, and 4%, was used as film reinforcement. The manufacturing process employed extrusion to evaluate the effectiveness of the nanomaterial in improving the mechanical and functional characteristics of the films. Films with varying concentrations of glycerol and nanoclay were produced to determine the optimal formulation by assessing their rheological, thermal, and mechanical properties. These films were subjected to comprehensive analysis using internationally standardised techniques, including Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), Fourier Transform Infrared Spectroscopy (FTIR), and morphological characterisation via Scanning Electron Microscopy (SEM). Among the properties evaluated, water vapour permeability (WVTR) was of particular interest. Results showed that higher nanoclay content improved moisture retention, thus enhancing the films’ water barrier properties. Mechanical testing indicated that the film with the highest nanoclay concentration, F-g35-NC4, displayed tensile strength values of 0.23 ± 0.02 MPa and elongation of 66.90% ± 4.85, whereas F-g35-NC0 and F-g35-NC2 exhibited lower values. Conversely, the highest tear resistance was also recorded for F-g35-NC4, reaching 0.740 ± 0.009 kg. Contact angle measurements revealed a hydrophilic tendency, with values of 89.93° ± 8.78°. Finally, WVTR analysis confirmed that increased nanoclay content enhanced moisture retention and improved the water barrier performance, with a value of 0.030 ± 0.011 g/m²·day, supporting potential applications in the packaging sector. Full article

This study focuses on the diversity of phytoplankton in the Koh Yaa region of Thailand and their relationship with environmental variables, aiming to assess whether human activities (primarily tourism) pose potential threats to the marine ecosystem and provide scientific support for eco-sustainable tourism management decisions in the region. In April, August, and December 2024, corresponding to peak season, off-season, and shoulder season, a total of 156 discrete samples were collected from four coastal sites to analyze water quality parameters such as temperature, pH, total nitrogen (TN), and total phosphorus (TP), along with plankton diversity and abundance. Statistical analyses including two-way ANOVA with Duncan’s Multiple Range Test (DMRT), Pearson correlation analysis, and principal component analysis (PCA) were applied. The results showed a declining trend in plankton abundance over time, peaking at 1009 × 10⁶ cells/m³ in April and dropping to 281 × 10⁶ cells/m³ by December. A total of 15 types of phytoplankton were identified across four phyla: Bacillariophyta, Cyanobacteria, Dinoflagellata, and Chlorophyta. Notably, Chaetoceros from Bacillariophyta accounted for 47% of phytoplankton, while Oscillatoria from Cyanobacteria made up 29.6%. The diversity index and evenness index improved from 1.34 and 0.46 in April to 1.88 and 0.64 in December, respectively. Environmental factors like pH, temperature, and TP significantly affected phytoplankton abundance (p < 0.01), with TP levels ranging from 0.27 to 0.69 mg/L. These results indicate possible pollution in this region, and changes in phytoplankton abundance were linked to seasonal climate variations—especially during peak tourist seasons—which may exacerbate eutrophication affecting community structures. Full article

Against the backdrop of rising global carbon emissions, promoting active transportation modes such as walking and cycling has become a key strategy for countries worldwide to meet carbon reduction targets and advance the goals of sustainable development. In China, the concept of low-carbon mobility has gained rapid traction, leading to a significant increase in public demand for non-motorized travel options like walking and cycling. From the perspective of inclusive urban development, gender imbalances in sample representation during design and evaluation processes have contributed to homogenization and a lack of diversity in urban slow-traffic environments. To address this issue, this study adopts a problem-oriented approach. First, we collect street scene images of slow-traffic environments through self-conducted field surveys. Concurrently, we gather satisfaction survey responses from 511 urban residents regarding existing slow-traffic streets, identifying three key environmental evaluation indicators: safety, liveliness, and beauty. Second, an experimental analysis is conducted to compare machine-generated assessments based on self-collected street view data with manual evaluations performed by 27 female participants. The findings reveal significant perceptual differences between genders in the assessment of slow-moving environments, particularly regarding attention to environmental elements, challenges in utilizing non-motorized lanes, and overall environmental satisfaction. Moreover, notable discrepancies are observed between machine scores and manual assessments performed by women. Based on these findings, this study investigates the underlying causes of such perceptual disparities and the mechanisms influencing them. Finally, it proposes female-inclusive strategies aimed at enhancing the quality of slow-traffic environments, thereby addressing the current absence of gender considerations in their design. This research seeks to provide a robust female perspective and empirical evidence to support improvements in the quality of slow-moving environments and to inform strategic advancements in their design. The findings of this study can provide a theoretical and empirical basis for the optimization of gender-inclusive non-motorized transportation environment design, policy formulation, and subsequent interdisciplinary research. Full article

The increasing demand for sustainable agriculture requires innovative strategies to enhance nitrogen use efficiency while minimizing environmental losses associated with conventional fertilizers. This study aimed to develop and compare ammonium chloride- and ammonium nitrate-modified nanobiochar as controlled-release nitrogen carriers and to elucidate their effects on nitrogen retention, soil properties, and physiological nitrogen utilization in spinach (Spinacia oleracea L.). Nitrogen-modified nanobiochar was synthesized using ammonium chloride (NB-AC) and ammonium nitrate (NB-AN) at three nitrogen rates (0.03, 0.06, and 0.12 g N g⁻¹ NB) and applied to soil at 1% (w/w). Soil properties, nutrient dynamics, and plant growth and physiological traits were analyzed after 15 and 30 days. Nitrogen modification significantly improved soil nitrogen retention and nutrient availability compared with unmodified nanobiochar. The highest nitrogen loading treatments (NB-AC3 and NB-AN3) notably improved spinach growth, photosynthetic efficiency, pigment content, nitrogen metabolism enzymatic activities, and accumulation of key metabolites (soluble sugars, flavonoids). Nitrogen-release assessments indicated a pronounced controlled-release with reduced nitrogen leaching and greater retention, particularly under NB-AN3. Overall, this study demonstrates that nitrogen-modified nanobiochar functions as an effective nitrogen carrier that enhances nitrogen utilization and growth. These findings provide mechanistic insights into its potential as a sustainable alternative to conventional nitrogen fertilizers. Full article

Advancing the Sustainable Development Goals (SDGs)—framed around social, environmental, and governance dimensions—offers societies across the world the possibility of achieving long-term prosperity and ensuring that future generations enjoy a high quality of life. Governments pursue the 17 SDGs in accordance with their own socioeconomic and cultural contexts, institutional capacities, and available resources. Because countries differ substantially in structure and capability, their progress toward these goals varies, making the systematic measurement and analysis of SDG performance essential for appropriate timing and efficient resource allocation. This study proposes a hybrid assessment system to evaluate the sustainable development performance of upper-middle-income developing countries under both fuzzy and non-fuzzy environments. This integrated evaluation system consists of four main stages. In the first stage, evaluation criteria and alternative countries are specified, relevant data are obtained, and an initial decision matrix is developed. In the second stage, an efficiency analysis is conducted to identify countries that are efficient and those that are not. In the third stage, evaluation criteria are weighted using AHP and Fuzzy AHP methods. In the final stage, the TOPSIS and Fuzzy TOPSIS methods are used to rank efficient countries depending on sustainable development performance criteria. As a result, six countries were identified as inefficient countries based on sustainable development: China, Kazakhstan, Mongolia, Paraguay, Namibia and Turkmenistan. The AHP and Fuzzy AHP methods produced similar criterion weight values compared to each other. The criteria were prioritized from most important to least one as follows: Life expectancy, expected years of schooling, mean years of schooling, gross national income per capita, CO₂ emissions per capita, and material footprint per capita. While some countries achieved similar rankings using the TOPSIS and Fuzzy TOPSIS methods, most countries achieved different rankings because of the multidimensional nature of sustainable development. When the rankings obtained from the fuzzy and non-fuzzy approaches were compared, a noticeable level of overlap was observed, with a Spearman’s rank correlation coefficient of 68.73%. However, the fuzzy TOPSIS method is considered more reliable for assessing sustainable development performance due to its ability to handle data uncertainty, imprecision, and the multidimensional nature of SDG indicators. The results of this study demonstrate that analyses related to sustainable development, which may not contain precise and clear values and have a complex structure encompassing many areas such as social, environmental, and governance, should preferably be conducted within a fuzzy logic framework to ensure more robust and credible evaluations. Full article