Search Results (17,609)

The study evaluated the drinking water quality of Rouxville (RX) in Mohokare Local Municipality in the Free State, using chemical, physical, and microbiological parameters in comparison with South African National Standard 241 (SANS 241:2015). Drinking water samples were collected monthly from five sample sites, including the water treatment plant (WTP) and four end-user points, over a period of three years (2021–2023). Microbiological parameters revealed persistent non-compliance, with total coliforms and Escherichia coli (E. coli) frequently exceeding recommended limits by SANS 241 at multiple sites. The highest total coliform concentration of 201 CFU was recorded at the Rouxville Water Treatment Plant during the third year (2023) of sampling, while E. coli reached a maximum of 11 CFU at an end-user point, indicating the presence of possible pathogens in the water system. Colour exceeded the recommended limit (15 Pt-Co mg/L) at all sampling sites, with the highest value of 133 Pt-Co mg/L recorded at Rolelethunya Library. Chemical parameters mostly complied with SANS 241 limits, elevated values of total alkalinity and aluminium were observed at certain sites, particularly during the third year (2023) of sampling. The Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) was also used to determine the overall water quality of the sample sites. The findings revealed that several sample sites had non-compliant parameters. The CCME-WQI revealed that the drinking water quality of Rouxville was either in the marginal or fair category, indicating that the water quality may be occasionally or frequently threatened, posing public health risks. These findings highlight the urgent need to ensure regular maintenance of WTP and ensuring continuous microbial monitoring. Full article

Aging is associated with a high prevalence of insomnia, which is linked to somatic and neuropsychiatric diseases, as well as metabolic and immunological dysfunction. This study aims to identify alterations in the transcriptome profiles and functional metabolic pathways in older adults with different types of sleep disorders. This cross-sectional study included 1002 participants (60–90 years) who were screened for sleep disorders using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. Two types of sleep disorders were identified in the study cohort, i.e., sleep onset insomnia and sleep maintenance insomnia. Both types of insomnia were further analyzed for associations with clinical characteristics, laboratory testing results, and socioeconomic backgrounds. The transcriptomic profiles of peripheral blood samples were examined in 236 individuals, supplemented with differential gene and dsRNA expression analyses (DESeq2). Both sleep onset insomnia and middle insomnia were associated with depression, chronic pain syndrome, and osteoarthritis, while only middle insomnia was associated with cardiometabolic diseases. No associations were observed between sleep onset insomnia or reduced sleep duration and transcriptomic profiles. In contrast, 244 genes were differentially expressed in patients with middle insomnia, indicating the activation of pathways related to viral infection response and inhibition of protein synthesis. Additionally, differential expression analysis of double-stranded RNA (dsRNA) identified 2139 significant changes. Middle insomnia in older adults is associated with transcriptomic changes indicative of an activated antiviral immune response, likely resulting from changes in dsRNA expression levels. The chronic inflammation arising from these transcriptomic alterations may underlie the observed association between middle insomnia and cardiometabolic conditions. Full article

The Internet of things (IoT) is rapidly pervading daily life and linking everything. Although higher connectivity offers many benefits, including higher productivity, robotic processes, and decision-making guided by data, it also poses a number of security dangers. Modern risks to data authenticity and confidence are getting harder to handle through typical central safety solutions. In this paper, we present a detailed investigation of the latest innovations and approaches for assessing reputation and confidence in the blockchain-empowered Internet of Things (BIoT) area. A comprehensive literature search was conducted across major electronic databases, including IEEE, Springer, Elsevier, Wiley, MDPI, and top indexed conference proceedings. The publication year was restricted to the period from 2018 to 2025. The methodological quality of a total of 122 studies met the inclusion criteria assessed using predefined quality measures. We figure out existing flaws at each layer of IoT architecture, illustrating how autonomous, transparent, and impenetrable blockchain ledgers address these flaws. Plus, we analytically compare public, private, consortium, and hybrid blockchain networking architectures to emphasize the underlying compromises among security, reliability, and decentralization. We also assess how reputation evaluation techniques evolved over time, moving from classical fuzzy logic and weighted average models to modern mature game theory and machine learning (ML) models, addressing their limitations in terms of computational overhead, scalability, adaptability, and deployment feasibility in IoT systems. Additionally, we outline future directions for BIoT system trust assessment and identify research limitations and potential solutions. Our research indicates that although ML-driven models offer more accurate predictions for identifying illicit node activities, they are still constrained by limited unbalanced data and high processing overhead. Full article

To address the efficiency and cost limitations of traditional manual cataloging, this study proposes a large language model-driven automated cataloging workflow in which the Metadata Extraction Agent (MEA), Description Cataloging Agent (DCA), Subject Analysis & Indexing Agent (SAIA), and Quality Control Agent (QCA) collaborate to perform cataloging tasks. Experiments are conducted using a dataset of over 33,000 CNMARC bibliographic records from a University Library, together with data from the Chinese Library Classification (5th edition). Meanwhile, the agent-based workflow framework directly employs large language models without additional enhancement techniques, thereby providing a useful experimental benchmark for evaluating future AI-assisted cataloging systems. The results show that the framework performs well in metadata recognition, bibliographic description, and macro-level classification tasks, and can relatively stably generate standardized records. However, limitations remain in fine-grained semantic indexing and the interpretation of complex contexts. Therefore, in light of the capability limitations revealed by the experimental results, the study argues that fully automated end-to-end cataloging relying solely on generative AI is not yet entirely feasible. Future improvements should integrate techniques such as retrieval-augmented generation, supervised fine-tuning, and structured reasoning prompts, while establishing traceable mechanisms to enhance the reliability of intelligent cataloging. Full article

Background/Objectives: Although lifestyle patterns, including sleep and meal timing, have been associated with diet quality, previous studies have frequently relied on time-averaged data, which can obscure day-to-day intake variability. Using data from a food-logging mobile application, we aimed to elucidate the association between mealtime irregularity and nutrient intake variability. Furthermore, we explored whether the association between meal timing and diet quality differs depending on mealtime regularity. Methods: Chrononutritional characteristics were calculated for 742 female mobile application users who provided daily dietary records for approximately 1 month. Nutrient intake variability was evaluated using the coefficient of variation (CV). Diet quality was assessed based on the energy-adjusted ratio of nutrient intake to the reference values from the Dietary Reference Intakes for Japanese. Generalized additive models adjusted for age, body mass index, and physical activity were employed for analyzing associations. Results: Greater mealtime irregularity was associated with higher CVs in the daily intake of most nutrients investigated. Regarding diet quality, a marginal interaction was observed between mealtime regularity and dinner timing (p for interaction = 0.062). Specifically, the irregular mealtime group demonstrated a significant linear decline in diet quality with later dinner times (p for trend = 0.0112), whereas no significant decline was observed in the regular mealtime group (p for trend = 0.5219). Conclusions: Our findings suggest that mealtime regularity, alongside meal timing, is a significant factor involved in nutrient intake variability and diet quality, underscoring its significance as a health-related behavior in chrononutrition. Full article

Background: Hypertension and smoking are well-known risk factors for aortic dissection (AD), but it is unclear whether other lifestyle factors influence the risk. The aim of this study was to investigate the association between diet quality, physical activity, and risk of AD. Methods: The study included 28,094 participants from the Malmö Diet and Cancer Study, recruited between 1991 and 1996 and followed through national health registers until 31 December 2022. Diet quality was assessed using a six-component Diet Quality Index. Incident AD was identified through ICD-9/ICD-10 codes in the Swedish National Patient Register. Associations were analyzed using Cox proportional hazards models. Results: During a median follow-up of 26.6 years, 130 participants developed AD. Higher age (HR 1.76/one standard deviation increment, 95% CI 1.41–2.20), male sex (HR 1.58, 95% CI 1.06–2.34), hypertension (HR 1.57, 95% CI 1.01–2.44), and current smoking (HR 3.04, 95% CI 1.86–4.98) were each independently associated with increased AD risk. No significant associations were found for diet quality and physical activity with AD risk. Conclusions: No associations were found between diet quality and physical activity and AD risk. Blood pressure control and smoking cessation are key preventive measures to reduce incidence of AD. Full article

Immortelle (Helichrysum italicum (Roth) G. Don, family Asteraceae) essential oils (HiEOs) and hydrosols (HiHYs) are widely used in cosmetic, pharmaceutical, and agricultural formulations. However, their composition and quality vary depending on geographical origin and production practices, while standardized reference values—particularly for hydrosols—are still lacking. The aim of this study was to investigate and compare the physicochemical properties and chemical composition of commercial HiEOs and HiHYs from the Adriatic and continental regions of Croatia. Samples were analysed using standard pharmacopoeial methods and gas chromatography–mass spectrometry (GC–MS). Physicochemical analyses (relative density, acid value, refractive index, pH, turbidity, and essential oil content) showed that all samples were within generally accepted quality ranges, with no significant differences observed between regions using the Mann–Whitney U test. HiEOs were dominated by sesquiterpene hydrocarbons (53.15–55.60%), whereas HiHYs contained predominantly oxygenated monoterpenes (43.54–69.86%). The main compounds identified in both fractions were α-pinene, neryl acetate, γ-curcumene, and β-selinene, which formed a consistent chemical signature and served as practical biomarkers for the quality of H. italicum EO and hydrosol. Principal Component Analysis (PCA) distinguished sample groupings based on physicochemical properties and chemical composition, indicating regional variability without exceeding accepted quality limits. This study presents the first comparative dataset of Croatian commercial HiEOs and HiHYs, and defines practical parameter ranges to support standardized specifications, ensure consistent quality, and enhance the industrial applicability of immortelle-based products. Full article

Camellia oleifera Abel, recognized as a woody oil-producing tree species, possesses considerable economic significance. To improve the breeding efficiency of C. oleifera, it is crucial to elucidate the genetic foundation underlying the mechanisms regulating fruit traits. In this study, a total of 6,252,197 high-quality single-nucleotide polymorphisms (SNPs) were identified from 109 germplasm accessions. Through genetic structure analysis, these accessions were categorized into two distinct populations. The average fixation index (Fst) was found to be 0.0153, indicating weak population differentiation. The genome-wide association analysis (GWAS) identified 157 significant loci. From these loci, 110 candidate genes were selected, which were associated with disease resistance, reproduction, development, and RNA biosynthesis. Twenty-three genes were involved in metabolic pathways, including genetic information-processing protein families, metabolic protein families, terpenoids, and polyketides. The identification of gene loci closely related to fruit traits not only provides genetic data for studying the molecular mechanisms of fruit traits but also offers new research avenues for molecular breeding of C. oleifera. Full article

Managing supply chain risks is a core pillar of operational and supply chain resilience building in the global industrial chain system, which is essential for the high-quality and sustainable development of manufacturing firms. Against the backdrop of escalating global economic uncertainties and interconnected supply chain vulnerabilities, mitigating the adverse impact of supply chain risks on firms’ overseas market expansion has become a critical research and practical issue in the field of operational and supply chain risk management. Based on the textual analysis of annual reports of listed firms, this study constructs a systematic supply chain risk measurement indicator system through standardized text preprocessing, multi-dimensional feature keyword lexicon construction, context co-occurrence frequency calculation and so on. We further validate the effectiveness of the indicator system by comparing its trend with the global economic uncertainty index, confirming that it can capture firm-specific supply chain risk information effectively. Employing text analysis, this study constructs a systematic supply chain risk measurement indicator system for A-share manufacturing firms and empirically verifies that elevated supply chain risks significantly constrain their overseas market expansion. Three interrelated operational mechanisms, namely surging operating costs, tightened financing constraints, and slumping R&D investments, drive this inhibitory effect. Notably, firms can effectively offset this negative effect by broadening overseas operational scope and intensifying overseas digital and technological innovation. Heterogeneity analyses further reveal that the inhibitory effect is more pronounced for five types of firms: those with lower overseas revenue, located in less market-oriented regions, operating in upstream value chain sectors, with lower current liabilities, and with a lower degree of digital transformation. Full article

Accurate and interpretable air quality prediction remains a critical challenge for environmental health management due to complex, nonlinear interactions among emissions, meteorology, and atmospheric chemistry. This study presents a hybrid physics informed and multimodal deep learning framework for city-scale air quality and health risk prediction. The framework combines a Gaussian plume dispersion model with a residual CNN-LSTM network that learns data driven corrections while preserving physical consistency. Multimodal open datasets, including ground based pollutant sensors, meteorological records, and satellite derived aerosol and temperature features, are jointly fused to improve spatiotemporal fidelity. An Exposure Health Index module further links predicted pollutant fields with respiratory morbidity indicators, providing a quantitative bridge between atmospheric variability and health outcomes. Using open source datasets from Riyadh, Jeddah, and Dammam, the proposed approach achieves up to 25% lower mean absolute error and $R^2$ values above 0.85 compared with physics only and purely data driven baselines. Explainability analyses using SHAP and spatial attention highlight physically plausible drivers and confirm feature relevance. The results demonstrate that physics guided residual learning can unify deterministic dispersion modeling and multimodal inference, providing a transparent, scalable, and reproducible foundation for air quality forecasting and health risk assessment. Full article

The Distinctness, Uniformity, and Stability (DUS) testing guidelines for mung beans (Vigna radiata L.) offer a standardized framework for new variety assessment. Although these guidelines are essential for variety management, the actual efficiency and breeding value of the 31 specified DUS characteristics in improving yield potential remain largely underexplored and lack systematic validation. To address this critical research gap, 180 genetically diverse mung bean accessions were analyzed using principal component analysis (PCA) and correlation analysis. The results revealed intrinsic relationships among characteristics and identified key variation dimensions centered on “plant morphology”, “pod characteristics”, and “seed characteristics”. Cluster analysis classified the 180 accessions into four distinct clusters. Cluster 2, in particular, offers a clear selection reference for breeding materials targeting high-yield and quality. The DTOPSIS (Dynamic Technique for Order Preference by Similarity to Ideal Solution) multi-criteria decision-making model was applied, with index weights assigned using an objective weighting method. Following systematic evaluation, Yingge 2 was identified as an outstanding phenotype. Breeders may refer to its quantitative characteristics in subsequent breeding cycles. Linear regression analysis was employed to construct a yield prediction model, identifying leaf greenness, pod number per plant, and hundred-grain weight as three core DUS characteristics with statistically significant effects on final yield (p < 0.05). This study performed a systematic, multi-dimensional analysis and comprehensive evaluation of mung bean germplasm resources based on DUS characteristics, with the aim of identifying key yield-related DUS traits, screen elite germplasm for high-yield breeding, and providing a theoretical basis and practical reference for the efficient improvement and selective breeding of new mung bean varieties. Full article

Background: We aimed to (i) identify the factors associated with performance in non-elite runners, (ii) present the terms and definitions/attributes used to characterize runners, and (iii) identify how performance has been operationalized. Methods: Our search was conducted using the databases PubMed, Web of Science, Medline Ovid, Cochrane, PsycInfo, Scielo, Scopus, and SportDiscus in October 2023 and updated in February 2026. Original articles that assessed factors associated with performance in non-elite runners competing in distances ranging from 5 km to ultramarathons were included. The findings were summarized by race distance. The Joanna Briggs Institute Analytical Cross-Sectional Studies critical appraisal tool was used for quality assessment. Results: A total of 4151 studies were identified, and 66 studies were included in the final selection. “Recreational” and “athletes” were the most used terms, and finish time was the most common indicator of performance. Performance decline was influenced by arm circumference and mid-axillary skinfold thickness, smoking, body mass index, alcohol consumption, and weather characteristics. Training variables, physiological determinants, and social variables were positively related to performance. Conclusions: The field struggles with a lack of clarity regarding the nomenclature and criteria used to categorize runners. The relevance of a predictor differs according to race distance, with physiological aspects becoming less important at higher distances (i.e., marathon and ultramarathon). Full article

Objectives: To investigate the potential associations between the daily consumption of unprocessed/minimally processed foods and serum phosphorus levels, CD3+, and CD45+ cell counts in clinically stable people living with HIV (PLHIV). Methods: This is a descriptive cross-sectional study. A total of 92 PLHIV of both sexes participated. Sociodemographic information, physical activity level, anthropometric and body composition data, dietary habits, and blood samples were collected. Results: The mean age of participants was 43.0 ± 12.0 years, with a body mass index of 26.5 ± 6.3 kg/m². The majority were male (60.8%), single (64.1%), had low educational attainment (55.4%), were non-smokers (64.1%) and did not consume alcoholic beverages (51.1%), and were physically active (70.7%). A positive association was observed between the daily consumption of unprocessed/minimally processed foods and serum phosphorus levels (p = 0.01), as well as CD3+ (p = 0.04) and CD45+ (p = 0.04) cell counts. Furthermore, positive correlations were identified between this dietary pattern and serum phosphorus (p = 0.001; r = 0.33) and the percentages of CD3+ (p = 0.03; r = 0.21) and CD45+ (p = 0.03; r = 0.22). Conclusions: The present study suggests that habitual consumption of unprocessed/minimally processed foods is positively associated with serum phosphorus levels, CD3+, and CD45+ cell counts in PLHIV. While these associations do not imply causality or enhanced antiviral immunity, they highlight the potential role of diet quality in the metabolic and immunological maintenance of stable patients. Full article

A detailed numerical optimization of side-pumped cerium- and neodymium-codoped yttrium aluminum garnet (Ce:Nd:YAG) solar laser architectures was performed using Zemax^® and LASCAD^TM, aiming for both high-power multimode and TEM₀₀-mode performances. Multiple rod configurations and laser resonator geometries were evaluated to maximize absorbed pump power, improve mode overlap, and ensure thermal stability. For multimode operation, the optimal design was a four-rod cross side-pumped configuration employing 4.0 mm diameter, 25 mm length rods, which numerically delivered a solar laser output power of 134 W (resulting in a collection efficiency of 49.1 W/m² and solar-to-laser conversion efficiency of 4.91%), representing a 1.50-times improvement over the best previously reported value of 89.29 W. For TEM₀₀-mode generation, the best performance was obtained with a three-rod horizontal side-pumped configuration using 2.5 mm diameter, 34 mm length rods, achieving a collection efficiency of 21.1 W/m² and solar-to-laser conversion efficiency of 2.11%, surpassing the record 16.49 W/m² reported in earlier literature. Thermal analyses revealed low peak temperatures, reduced thermally induced stress, and minimized refractive-index gradients in both architectures, confirming that multirod side pumping significantly improves the thermal environment and enables stable operation at high absorbed pump powers. These results demonstrate that carefully engineered multirod geometries can simultaneously enhance collection efficiency, beam quality, and thermal robustness, highlighting multirod side-pumped solar lasers as a promising pathway for further power scaling and next-generation high-performance solar laser systems. Full article

Background: This longitudinal study examined the clinical outcomes of physiotherapy interventions in patients with chronic low back pain, specifically observing the interactions between demographic characteristics, physical metrics, and psychological variables. Methods: A cohort of n = 150 patients, Final n = 123 (18% attrition rate), was assessed using a one-group pre-test/post-test design, with primary outcome measures including Health-Related Quality of Life, the Perceived Stress Scale, and the Numerical Pain Rating Scale. Participants received eight standardized sessions over 4 weeks, including electro-physical agents combined with individualized kinesiotherapy. Data analysis/synthesis was performed via Multiple Correspondence Analysis (MCA) to map associations between categorical variables and treatment responses. Results: The predominant clinical profile found was a middle-aged female with moderate educational attainment, presenting with a Body Mass Index in the overweight range and moderate-to-high baseline pain intensity. MCA revealed distinct phenotypic trends: longer Work Experience was associated with lower baseline Quality of Life (QoL) and heightened stress/pain levels. In contrast, patients characterized by higher education and significant Work Experience demonstrated notable post-intervention QoL gains. High baseline QoL served as a predictor for sustained improvement and pain attenuation, while elevated pre-intervention pain scores were consistently linked to perceived unmet clinical needs and exacerbated stress. Conclusions: MCA successfully mapped non-linear clusters—such as the “Socio-Psychological Barrier” profile—that traditional univariate methods fail to visualize, suggesting that “individualized care” must prioritize health literacy among patients experiencing extensive work-related strain. Full article