Search Results (26,847)

This study evaluates the impact of Dynamic Soil–Structure Interaction (DSSI) on the efficiency of an algorithm based on the existing literature on Vibration-Based Structural Health Monitoring (VBSHM). The algorithm is designed for Level 3 detection, that is, to accurately estimate the presence, location in height, and extent of structural damage simultaneously. Using computer simulations of a hypothetical two-dimensional six-story symmetrical reinforced concrete building, the study analyzes the algorithm’s performance under increasing soil flexibility. Efficiency is measured through four key metrics: the number of false positives and negatives, a weighted stress index, the iterations required for damage intensity estimation, and the accuracy of the identified versus simulated stiffness reduction. Results indicate that the algorithm remains effective even when input motions correspond to actual soft-soil ambient vibration recordings modified by kinematic DSSI effects, despite frequency contents differing from white-noise conditions. Conversely, inertial DSSI negatively impacts performance, leading the VBSHM algorithm to underestimate damage as soil deposits become softer. Full article

People spend the majority of their time indoors; however, most previous studies on the health effects of particulate matter (PM) and ozone (O₃) have used outdoor concentrations as a proxy for personal exposure, which may introduce misclassification bias. Since indoor PM and O₃ originate primarily from outdoors, estimating their indoor infiltration levels provides a closer approximation of true personal exposure. This study used data on approximately four million deaths occurring over an eight-year period in Jiangsu Province, China. The infiltration factor method and time-series analysis were employed to assess the linear and nonlinear associations of short-term indoor exposure to outdoor-origin PM₁, PM_2.5, PM₁₀, and O₃ with all-cause, cardiovascular, and respiratory mortality. In addition, the interactions between indoor PM and O₃ were investigated. The results indicate that indoor exposure to outdoor-origin PM and O₃ was positively associated with mortality, and these associations were stronger than those observed for direct outdoor exposure. Each 10 μg/m³ increase in the 2-day moving average concentration of indoor PM₁, PM_2.5, PM₁₀, and O₃ was associated with a 1.82% (95% confidence interval [CI]: 1.64, 2.01), 1.02% (95% CI: 0.91, 1.13), 0.69% (95% CI: 0.62, 0.77), and 1.79% (95% CI: 1.60, 1.99) increase in all-cause mortality, respectively. No threshold was observed in the exposure-response associations. Furthermore, significant multiplicative and additive interactions were identified between infiltrated PM and O₃. Consequently, greater attention should be directed toward indoor air quality, particularly the coordinated management of combined exposure to indoor PM and O₃, in order to better protect public health. Full article

Despite Mozambique’s substantial natural gas reserves, most households rely on solid biomass for cooking, with serious consequences for public health, livelihoods, and the environment. The domestic use of these resources could improve energy efficiency, security, and sustainable development. This mixed-methods study uses household interviews, descriptive statistics, multinomial, and conditional logit models, analyzing data from a random survey of 434 households in energy-rich peripheries of northern Inhambane and Maputo City to ascertain the determinants of household cooking energy choice. Results reveal that rising income increases the odds of choosing electricity, LPG, and biomass over natural gas. In energy-rich peripheries, the odds of selecting biomass over natural gas are reduced by 96.2% compared to non-energy-rich regions. Educational and urban habitation are positively correlated with the adoption of electricity and liquefied petroleum gas (LPG). Price serves as a significant negative predictor of fuel selection (OR ≈ 0.000001), whereby each unit increase in price per GJ substantially diminishes the likelihood of opting for alternatives over domestic gas. Monthly fuel expenditure positively predicts electricity, LPG, and biomass adoption (OR = 1.0042), with effects accumulating meaningfully across realistic spending ranges. Households that experienced energy system incidents were more than twice as likely to switch away from natural gas (OR = 2.072), reflecting the critical role of infrastructure reliability in fuel choice. Given natural gas’s potential as a clean cooking transition fuel, the government should prioritize investment in gas infrastructure, expand domestic supply, and promote public awareness of the health and environmental benefits of clean cooking energy. Full article

Background: Adults closest to children, including parents and caregivers, teachers, and therapists, are major determinants of child mental health outcomes. However, access to high-quality psychological training for these groups remains severely limited and inequitable. Artificial intelligence (AI) tools may offer a scalable, accessible, and low-cost route to training delivery. This review aimed to provide the first systematic synthesis of evidence on AI tools used to train caregivers, educators, and therapists/practitioners in psychological approaches relevant to child and adolescent mental health. Methods: A systematic review was conducted in accordance with PRISMA guidelines (PROSPERO: CRD420261336167). Five databases, MEDLINE, PsycINFO, Embase, Web of Science, and ERIC, were searched from inception to March 2026, supplemented by reference hand-searching and forward citation tracking. Studies were eligible if they evaluated an AI-based training tool used with adults in caregiving, educational, or therapeutic roles involving children or adolescents aged 0–18 years, delivered a defined psychological approach, and reported at least one training outcome. Owing to substantial methodological and outcome heterogeneity, findings were synthesised narratively, and meta-analysis was not undertaken. Results: Twenty-four studies from nine countries, published between 2019 and 2026, met inclusion criteria. Studies were grouped into caregiver training (Group A, 5 papers), educator training (Group B, 3 papers), and therapist/practitioner training (Group C, 16 papers). Identified AI modalities included natural language processing (NLP)-based chatbots, generative AI/large language model (LLM) systems, AI-integrated virtual reality (VR), and AI-based feedback and analysis tools. Feasibility and acceptability findings were generally positive across groups. However, the evidence base was limited by pervasive methodological weaknesses, including small samples, with most studies enrolling fewer than 30 participants, reliance on unvalidated self-report outcomes, and the absence of follow-up data beyond one month. Conclusions: AI tools show early promise as scalable approaches to psychological training, particularly for procedural skill acquisition and enhancement of practitioner self-efficacy. However, the current evidence base is insufficient to support claims of effectiveness. A structural credibility–accessibility paradox characterises the field: tools with the strongest controlled evidence are the least scalable, while the most accessible tools have the weakest empirical support. Adequately powered, independent randomised controlled trials (RCTs) using validated outcomes, active comparators, and follow-up extending over multiple months are needed across all three population groups. Full article

Background: Mental health concerns are notably common among students attending universities in Saudi Arabia, and low engagement with psychological services has been widely documented in this population group. Telemental health has emerged as a promising alternative under Vision 2030’s digital transformation agenda, although the determinants of university students’ intentions to use these services have received limited empirical attention in Saudi Arabia. Objective: This study examined attitudes toward telemental health services, perceived barriers to seeking psychological help, and predictors of behavioral intentions to use telemental health services among university students in Saudi Arabia, based on the Technology Acceptance Model and Theory of Planned Behavior. Methods: A cross-sectional design was employed using an online, self-administered questionnaire. A total of 236 undergraduate students from three large universities in Riyadh were recruited using convenience sampling methods. We examined demographic variables, telemental health attitude variables (ease of use, usefulness, subjective norms, trust in telemental health, relative advantage, intentions, and attitudes), and barrier subscales (fear of stigma, trust in mental health professionals, difficulties in self-disclosure, perceived devaluation, and lack of knowledge) among university students. Descriptive statistics, Welch’s t-tests, and multiple linear regression analyses were conducted using SPSS (version 29). Results: Participants demonstrated moderately positive attitudes toward telemental health (M = 74.15, SD = 16.11) and reported moderate overall barriers (M = 50.76, SD = 14.44), with trust in mental health professionals being the most prominent barrier. The regression model explained 58.0% of the variance in behavioral intentions (F(19, 211) = 15.35, p < 0.001). Attitude was the strongest predictor (β = 0.534, p < 0.001), followed by trust in telemental health, sex, and difficulty in self-disclosure. Conclusions: Culturally tailored awareness campaigns, trust-building communication, and gender-sensitive service design are recommended to promote the adoption of telemental health by Saudi university students. These efforts align with Vision 2030’s digital health priorities and may support the equitable expansion of mental healthcare access in this population. Full article

Background: Pelvic organ prolapse (POP) significantly impacts women’s quality of life. Two established surgical approaches exist: laparoscopic sacropexy (LSC) and vaginal sacrospinous fixation (SSLF). This study compared surgical outcomes, complication rates, and quality of life between these techniques. Methods: This retrospective monocentric study included 58 patients treated between 2020 and 2023: 41 underwent LSC, and 17 underwent SSLF with vaginal hysterectomy. All procedures were performed by a single surgeon. Primary outcomes included operative time, complications, and hospital stay. Quality of life was assessed using the German Pelvic Floor Questionnaire (Deutscher Beckenboden-Fragebogen), King’s Health Questionnaire (KHQ), and patient satisfaction surveys. Results: Patient groups differed significantly in ASA scores (p = 0.023) and comorbidities, with SSLF patients showing higher morbidity. LSC demonstrated longer operative times (91 (75–115) vs. 73 (61–87) min, p = 0.05) but significantly fewer complications (0% vs. 17.6%, p = 0.02). Both methods showed significant improvements in bladder function, prolapse symptoms, and pelvic floor dysfunction scores (all p < 0.001). A within-group improvement in sexual function scores was observed in the LSC group (p = 0.002) but not in the SSLF group (p = 0.5); the between-group comparison of change scores was not significant (p = 0.8). No significant differences were found between groups regarding hospital stay duration or overall patient satisfaction (LSC: 95% vs. SSLF: 87% satisfied, p > 0.05). Conclusions: Both surgical approaches effectively treat POP with high patient satisfaction. LSC was associated with fewer observed complications and a within-group improvement in sexual function scores; SSLF was associated with shorter operative time and was applied in patients with higher morbidity. These associations may partly reflect baseline differences between groups and are considered hypothesis-generating. SSLF remains suitable for patients with higher morbidity when minimizing operative time and avoiding Trendelenburg positioning is advantageous. Full article

Background: Lifestyle factors such as diet and physical activity significantly impact on the risk of obesity in individuals with Down syndrome (DS). However, in the absence of national nutritional guidelines in individuals with DS, further work is needed to understand their dietary and physical activity patterns. In this work we retrieved caregivers’ responses on those aspects. Methods: We analyzed data from a cross-sectional online survey of caregivers of individuals with DS conducted as part of the GO-DS21 project and reported in the accompanying paper (nutrients-4216283) (n = 764). We explored physical activity patterns, dietary habits, beliefs around weight-loss interventions and caregiver confidence that family members with DS would engage in a healthier lifestyle. Associations were examined using correlation analysis, and cumulative and binary logistic regression models. Results: Caregivers reported that most individuals with DS exercised 1–3 times per week, with frequency declining with age. Males were more likely to exercise daily than females. Caregiver exercise frequency was positively correlated with that of their DS family member (ρ = 0.521, p < 0.001), suggesting clustering of shared health behaviors within households. In adjusted models, caregivers who exercised regularly had up to thirteen-fold higher odds of having a physically active family member with DS (aOR = 13.02, 95% CI: 7.40–24.06, p < 0.001). Fried food consumption and higher snack frequency were independently associated with perceived obesity status, while sugar-sweetened beverage consumption was not. Caregivers favored exercise as a weight-loss strategy, while anti-obesity drugs were endorsed by only 11% of caregivers primarily and were more likely to be endorsed when obesity was perceived (aOR = 4.21, 95% CI: 2.44–7.39, p < 0.001). Finally, caregiver confidence that their family member with DS would engage in healthier behaviors was associated with perceived obesity status and strongly associated with higher physical activity levels (aOR 14.68, 95% CI: 6.59–33.40, p < 0.001). Conclusions: In this large European caregiver survey, reported consumption of selected energy-dense foods was generally low, although fried food intake and higher snack frequency were associated with perceived obesity. Physical activity patterns were closely aligned between caregivers and individuals with DS, suggesting shared household health behaviors. These findings highlight the importance of involving caregivers and family environments in lifestyle interventions aimed at supporting physical activity and weight management in individuals with DS. Full article

From an ecological epidemiology perspective, wildlife nasal cavities may serve as critical ecological niches for the maintenance and spread of bacterial pathogens relevant to both animal and human health. This study investigated Streptococcus spp. as the most prevalent genus in the nasal cavities of 82 wild boars (Sus scrofa), sampled across six hunting districts in Avellino Province (Southern Italy), assessing the diversity of the colonizing streptococcal populations and their antimicrobial resistance profiles. The sampled population consisted of 43 males (52%) and 39 females (48%). A total of 173 Gram-positive isolates were recovered, with 74 identified as Streptococcus spp. by MALDI-TOF MS. These isolates originated from 59 positive swabs (72%; 59/82). Streptococcus gallolyticus was the most prevalent species (41%; 30/74), followed by Streptococcus porcinus (27%; 20/74) and Streptococcus suis (19%; 14/74). No statistically significant geographic association was found across sampling districts (p = 0.491), whereas a significant association was found between bacterial species and antimicrobial resistance profiles (χ² = 16.70, p < 0.001). Specifically, all Streptococcus porcinus isolates (100%; 20/20) exhibited resistance to sulfamethoxazole–trimethoprim and tetracycline, while high tetracycline resistance was also noted in Streptococcus suis (93%; 13/14) and Streptococcus gallolyticus (83%; 25/30). Overall, 69% (51/74) of isolates were classified as MDR and 5% (4/74) as XDR. These findings suggest the potential role of wild boars as reservoirs for antimicrobial-resistant streptococci, emphasizing the need for continuous surveillance under a One Health framework. Full article

Background: In March 2026, a meningococcal cluster centred on the University of Kent, England, caused two deaths and resulted in over 20 reported cases within the first week, including confirmed and suspected invasive cases. Subsequent UKHSA updates in early April 2026 reported 21 laboratory-confirmed MenB cases (18 linked to the outbreak strain) and two deaths, with the outbreak subsequently spreading to a second Canterbury university, Canterbury Christ Church University, and confirmed as Neisseria meningitidis serogroup B (MenB). Sub-Saharan Africa (SSA) bears a disproportionate global burden of meningococcal disease, yet university settings remain a critically understudied outbreak amplifier. This narrative review extracts epidemiological and policy lessons from the Kent event and applies them to the SSA context. Methods: We conducted a narrative review following the SANRA criteria, searching PubMed, Embase, Scopus, Google Scholar, and African Journals Online (2000–2026), with supplementary grey literature retrieved from World Health Organisation (WHO), Africa Centre for Disease Control, and United Kingdom Health Security Agency (UKHSA). Outbreak data were drawn from official UKHSA public-health statements (grey literature, archived), the University of Kent communications, and peer-reviewed expert commentary. Results: The Canterbury outbreak exposed six reproducible vulnerabilities: unprotected serogroup circulation (confirmed MenB, not covered for the current university-age cohort), nightlife-linked transmission amplification, delayed serogroup identification, poor student symptom-recognition, inadequate institutional response capacity, and, critically, multi-institutional spread via shared nightlife venues (confirmed extension to Canterbury Christ Church University within five days). Each vulnerability is demonstrably more severe in SSA universities, which face a broader multi-serogroup threat environment (NmA, B, C, W, X), virtually no university-entry vaccination requirement, and critical evidence gap of campus-specific meningococcal evidence in the published literature. Conclusions: This review proposes a five-pillar preparedness framework for SSA tertiary institutions, derived from a synthesis of the Kent outbreak and broader epidemiological evidence, intended to inform policy discussion and future research. Moreover, these should be embedded within a broader age-linked prevention strategy that begins before university entry, particularly during the transition into secondary school in high-risk settings. Priority measures include meningococcal vaccination at key educational transition points, prophylactic antibiotic pre-positioning, serogroup-capable surveillance, symptom-recognition training, and pan-continental alert A predominantly reactive response may carry substantial risk in SSA settings. Full article

Accurate State of Health (SOH) estimation and Remaining Useful Life (RUL) prediction on uninterruptible power supply (UPS) batteries are critical for ensuring system reliability. However, battery degradation processes exhibit significant non-linearity and non-stationarity, posing challenges for traditional deep learning models in capturing long-term dependencies and handling sensor noise. In this paper, we propose BatteryMoE, a novel normalization-free sparse Mixture-of-Experts (MoE) Transformer designed for robust battery prognostics. Distinct from standard Transformers, BatteryMoE incorporates three key physics-aware architectural innovations: (1) It introduces a dynamic error function mechanism to replace traditional normalization layers, constructing a normalization-free architecture that enhances robustness against high-variance battery data. (2) It adopts an imaginary-enhanced Rotary Positional Embedding that utilizes the full complex-valued attention score to capture both local charge–discharge patterns and global long-term degradation trends, significantly improving RUL extrapolation. (3) A sparse MoE strategy is employed to dynamically activate specialized experts for different aging stages (e.g., linear degradation vs. capacity plunge), balancing model capacity with robust predictive performance. Extensive experiments conducted on five widely used datasets show that BatteryMoE achieved significant results. Full article

Leptospirosis is a zoonotic disease caused by spirochete bacteria of the genus Leptospira, with a wide global distribution. In Ecuador, leptospirosis is endemic, particularly in low-resource tropical areas, and multiple animal reservoirs have been identified either in rural or urban areas, including stray dogs. In this study, a total of 81 domestic dogs presenting clinical manifestations compatible with leptospirosis were recruited at the Municipal Center for Animal Welfare in Guayaquil, Ecuador, in 2023. A survey regarding clinical, demographic, and environmental risk factors was filled in by every dog’s owner; urine and blood samples were collected for pathogenic Leptospira diagnosis by qPCR for lipL32, rrs, and secY gene targets. A very high (62.96%) positivity rate for Leptospira infection was found. Almost 90% of the dogs were not vaccinated against Leptospira. Although the animals exhibited multiple clinical signs, none showed a statistically significant association with Leptospira positivity, confirming the nonspecific presentation of the disease and its potential for misdiagnosis. The consumption of bulk food emerged as a significant environmental risk factor only in the multivariate logistic regression and not in the univariate analysis, suggesting the need for improved food safety practices. Moreover, we reported very frequent close-contact behaviors between owners and dogs. Overall, our study underscores the potential role of owned urban dogs as reservoirs of Leptospira in the city of Guayaquil in Ecuador, emphasizing the need for public health policies to increase awareness and improve diagnosis in domestic animals under a comprehensive One Health vision. Full article

Background: Bladder cancer disproportionately affects non-high-income countries, yet clinical trials underrepresent global diversity. We assessed global availability of bladder cancer trials, their alignment with disease burden, and barriers to equitable care. Methods: We queried ClinicalTrials.gov for adult bladder cancer trials from June 2019 to June 2024, excluding observational and non-oncologic trials. Trial characteristics were summarized descriptively, and country data came from the Global Cancer Observatory. Countries were classified per World Bank Ranking (WBR) into high-income (HICs), upper middle-income (UMICs), lower middle-income (LMICs), and low-income countries (LICs). Trials were categorized as HIC-only, non-HIC, or mixed-income trials. Fisher’s exact and Kruskal–Wallis tests compared groups. Multivariable logistic regression assessed associations between trial availability and WBR, national health expenditure, and gross national income (GNI). Univariable linear regression and ANOVA assessed the association between the mortality-to-incident ratio and WBR. Results: Of 611 trials, 75.1% were HIC-only, 16.9% non-HIC, and 8.0% mixed-income trials. Non-HIC trials were mainly academic-sponsored (80.6%), while all mixed-income trials had pharmaceutical sponsorship (p < 0.001). Non-HIC trials had lower enrollment, less pharmaceutical funding, fewer multinational collaborations, and fewer basket, multi-arm, early-phase designs (all p < 0.001). Mixed-income trials were larger, led by HICs, had broader eligibility criteria, more novel therapies, and more frequent use of overall survival endpoints. Trial availability was lower in UMICs (p = 0.011), LMICs (p = 0.024), and absent in LICs, and positively associated with higher national health expenditure (p = 0.007) and GNI (p = 0.001). Conclusions: Bladder cancer trials remain concentrated in HICs. Mixed-income trials expand access in non-high-income countries, but are exclusively led by HICs and require balanced sponsorship, early-phase research, and lasting local benefits. Full article

Endogenous growth theory explains the asymmetric dynamic relationship between economic and social development through human capital accumulation and innovation, institutional quality, and demand channels. The objective of this paper is to assess the dynamic relationship between social and economic development in developing countries, where institutional imperfections and development instability create the most pronounced asymmetries. A composite social development index, obtained using the entropy method, operationalizes social development as the expansion of human capabilities in three dimensions: health, education, and material security. A panel vector error correction model (PVECM), estimated using the generalized method of moments (GMM) on panel data from 18 countries in Central Asia, the Middle East, and North Africa for the period 2001–2023, revealed asymmetric dynamic relationships: improved social indicators are associated with a short-term slowdown in economic indicators and more favorable economic dynamics in the medium term. In contrast, economic growth is accompanied by a positive lagged response in social development, although the short-term response may reflect the costs of social adjustment. The influence of control variables confirms the positive role of agglomeration for economic development, revealing the social costs of rapid urbanization and demographic pressure on social development. Estimates of the error correction coefficients indicate a slow adaptation of the system to long-term equilibrium, high inertia, and institutional rigidity of macrosocial processes. Impulse response functions confirm the dynamic and delayed nature of the interaction between economic and social development and positive shocks in the medium term. The obtained empirical results substantiate the need for institutional regulation of policy decisions on human capital accumulation and innovation, as well as social reforms. Full article

Background/Objectives: Clinical phenotyping from narrative electronic health records (EHRs) often relies on multi-stage pipelines involving span-level extraction, ontology mapping, and aggregation. Large language models (LLMs) may enable direct document-level abstraction of clinically meaningful phenotype features from complete notes. We evaluated whether GPT-5.2 could approximate human annotation for note-level multiple sclerosis (MS) phenotyping and compared its performance with human annotators, a locally run open-source LLM, HPO-based extraction tools, and a supervised clinical transformer encoder. Methods: We analyzed 100 de-identified MS neurology progress notes from a single academic medical center. Each note was annotated for the presence or absence of 17 predefined neurological phenotype categories. Two human annotators independently labeled all notes using a multi-label note-level framework in Prodigy, and disagreements were adjudicated to create a reference annotation set. GPT-5.2 was evaluated in a zero-shot setting using structured JSON output. Comparator methods included Llama-3.1 8B, Doc2Hpo, ClinPhen, PhenoSnap, and BioClinical ModernBERT. Performance was assessed using agreement, precision, recall, F1, Matthews correlation coefficient, and false-positive and false-negative assignments per note. Results: Human–human agreement was generally high, although lower for rare or ambiguously documented features. GPT-5.2 achieved the strongest automated performance, with macro-precision 0.734, macro-recall 0.921, macro-F1 0.801, and macro-averaged MCC 0.777, approaching human annotator performance. GPT-5.2 showed the lowest false-negative count per note but more false-positive assignments than either human annotator, reflecting a sensitive but more inclusive annotation profile. Llama-3.1 8B performed competitively among automated methods, whereas HPO-based extraction tools and BioClinical ModernBERT showed lower performance on this low-resource note-level task. Secondary review of GPT-5.2 discordant assignments found no clear hallucinations and suggested that some apparent false positives reflected phenotype evidence missed in the human-derived reference set. Conclusions: GPT-5.2 achieved near-human performance for document-level recognition of MS phenotype categories from narrative neurology notes. Direct note-level abstraction may provide a scalable approach for research and population-health phenotyping of large EHR note corpora. Full article

Air and water pollution pose critical threats to public health and environmental stability, particularly in rapidly urbanizing developing nations. This study investigates synergistic interactions between air and water pollutants across 14 cities in Hunan Province, China (2020–2024), using multiparametric statistical approaches. The results show that the coefficient of variation (CV) of particulate matter (PM) with diameters less than 2.5 μm (PM_2.5, CV = 46.9%) and turbidity (TU, CV = 47.4%) showed the highest variability among the air and water quality parameters, respectively. Annual trends revealed significant increases in ozone (O₃) alongside decreases in carbon monoxide (CO) and nitrogen dioxide (NO₂) concentrations. Concurrently, freshwater systems exhibited rising electrical conductivity (EC), water temperature (WT), and pH, paired with declining levels of ammonia nitrogen (NH₃-N), total phosphorus (TP), and turbidity (TU). Principal component analysis (PCA) and Spearman correlation analyses showed significant positive correlations between PM and nitrogen species (TN, NH₃-N), but negative correlations with TP, suggesting potential cross-media pollution interactions. Cross-correlation analysis revealed significant time-lagged relationships (1–5 months) between atmospheric pollutants and aquatic nutrients, suggesting that atmospheric deposition may serve as a contributing pathway for cross-media contamination. The study not only provides empirical evidence for integrated pollution control strategies in urbanizing watersheds, but also offers a transferable framework for addressing similar air–water quality interactions on a global scale. Full article