Search Results (16,831)

With the rapid development of recycling and secondary utilization of end-of-life battery materials, it is crucial to clarify the impact of full-lifecycle degradation on the thermal safety limits of lithium-ion batteries. This study focuses on a 16 Ah NCM613|graphite pouch battery. First, it analyzes the evolution of capacity decay, thickness expansion, and internal resistance during cycling at room temperature (25 °C) and high temperature (45 °C). Furthermore, an adiabatic accelerated calorimeter (ARC) is employed to investigate the influence of different states of health (SOH) levels (95% and 85%) on the battery’s thermal runaway characteristics. The findings indicate that, macroscopically, batteries in all states follow similar voltage–temperature failure pathways, with mass loss rates confined to a narrow range of approximately 16%, emphasizing the low catastrophic potential of mid-nickel chemistry. However, the microscopic kinetic mechanisms exhibit significant anisotropy: although thickness and internal resistance display no apparent abrupt increase during the late stage of room temperature aging, the capacity exhibits a highly nonlinear plunge behavior. The severe internal lithium plating side reaction triggered by this phenomenon causes the self-heating onset temperature to drop rapidly from 130.0 °C in the fresh state to 79.7 °C. Concurrently, the activation energy of the exothermic side reaction, fitted using a simplified Arrhenius equation, exhibits a non-monotonic variation with aging progress. In the early stages of aging at 95% SOH, due to high temperatures promoting more significant growth of the interfacial film or moderate film formation at room temperature enhancing interfacial thermal stability, the activation energies for both aged batteries increase, and the energy barrier at high temperatures is slightly higher than at room temperature; however, during the deep aging stage at 85% SOH, due to the degradation of active material components and the emergence of lithium plating characteristics, the energy barrier significantly decreases, with high-temperature-aged batteries exhibiting a greater reduction, highlighting the cumulative negative impact of prolonged high-temperature exposure on thermal safety. The research provides a core scientific basis for establishing a battery safety early warning and dynamic health management system covering the entire lifecycle. Full article

Sandwich composite floor panels are widely used in aircraft interior structures because of their lightweight and high stiffness-to-weight characteristics. However, the guided-wave response of such panels is strongly influenced by their multilayer configuration, honeycomb core, attenuation behavior, sensor-path geometry, and excitation frequency. In this study, an active guided-wave-based Structural Health Monitoring (SHM) configuration was experimentally evaluated on an aerospace-type sandwich composite floor panel using a piezoelectric (PZT) sensor network. The specimen consisted of glass fiber reinforced polyetherimide (GFR-PEI) face sheets and a phenolic-coated aramid honeycomb core. Controlled bonded patch-induced surface perturbations were sequentially applied over 25 predefined panel regions to introduce repeatable local mass-loading and damping changes. Guided-wave measurements were performed using an Acellent ScanGenie system over a frequency range of 75–600 kHz with 25 kHz increments and twelve directed actuator–receiver paths. The results showed that the measured Damage Index (DI) response depends strongly on excitation frequency, sensing path, and perturbation location. The 400–450 kHz range produced relatively higher DI values under the tested configuration, and 425 kHz yielded the highest mean DI among valid measurements. However, the valid sensing coverage at 425 kHz was only 50%; therefore, this frequency was not interpreted as the most robust overall monitoring frequency. Lower frequencies around 100–150 kHz provided full sensing coverage while maintaining relatively high DI values. Frequencies above 550 kHz showed reduced measurement reliability due to increased attenuation and poor usable signal response. Overall, the study provides a comparative sensitivity assessment of a guided-wave-based PZT network on a sandwich composite floor panel under controlled bonded patch-induced perturbations, rather than a direct validation of realistic internal sandwich-panel damage mechanisms. Full article

Background: Quality of life (QoL) among university students is an important indicator of overall health and academic success. Although these factors are interrelated, few studies have simultaneously examined their structural associations with QoL among university students in Saudi Arabia. This study investigated the associations among demographic characteristics, lifestyle behaviors, psychological distress, and quality of life using structural equation modeling (SEM). Methods: We conducted a cross-sectional study among undergraduate students enrolled in public universities in Riyadh, Saudi Arabia. The survey included demographic characteristics, the Depression Anxiety Stress Scale-21 (DASS-21), the World Health Organization Quality of Life-BREF (WHOQOL-BREF), and measures of sleep quality, sleep duration, and physical activity. Confirmatory factor analysis was performed to evaluate the measurement model. We fitted SEM to examine associations among demographic characteristics, lifestyle behaviors, health status, and quality of life. Results: A total of 198 undergraduate students were included in the analysis. The measurement model demonstrated satisfactory psychometric properties. The SEM demonstrated acceptable model fit (χ²/df = 2.00, Comparative Fit Index = 0.937, Tucker–Lewis Index = 0.914, Root Mean Square Error of Approximation = 0.071, Standardized Root Mean Square Residual = 0.070). Male students reported poorer sleep quality (β = −0.405, p < 0.001), shorter sleep duration (β = −0.208, p = 0.019), and lower physical activity (β = −0.299, p < 0.001) than female students. Students with a GPA of 4.50 or above reported higher physical activity than those with lower GPAs (β = 0.182, p = 0.027). Better sleep quality (β = 0.169, p = 0.024) and very good or excellent self-rated health (β = 0.492, p < 0.001) were positively associated with quality of life, whereas sleep duration was not significantly associated with quality of life (p = 0.225). Conclusions: Quality of life among undergraduate students was associated with multiple interconnected demographic and lifestyle factors. Our findings highlight the importance of integrated university health-promotion strategies that simultaneously address sleep health, healthy lifestyle behaviors, and psychological well-being to improve students’ overall quality of life. Longitudinal studies should be conducted to clarify the temporal relationships among these factors. Full article

School behavioral health (SBH) systems coaching is a developing approach to implementation support for the delivery of high-quality behavioral health support in schools through a multi-tiered prevention and intervention framework. Articulating coaching components and understanding how, when, and why external coaching supports systems change and implementation are essential, but research on the nature, scope, mechanisms, and effectiveness of external coaching for school behavioral health is limited. In the current study, we describe the development and implementation of the School Behavioral Health Academy (SBHA) Coaching program in South Carolina and present findings from a qualitative formative evaluation study. Thematic analysis of key informant interviews with district and school program implementation leaders (N = 8) provides evidence of perceived improvements in systems practices and positive staff and student outcomes related to participation in SBHA Coaching. Articulated barriers and facilitators point to potential mechanisms of change and implementation determinants. Participants described perceived changes and needs related to SBH understanding, infrastructure, norms, and mindsets, as well as the coaching skills and methods they found influential. Results are interpreted in relation to behavior change theory, systems change theory, and the Implementation Drivers Framework. Future directions for program development, research, and practice are discussed. Full article

Objective: The long-term management of cardiovascular diseases (CVDs) requires comprehensive rehabilitation strategies aimed at optimizing functional recovery and promoting behavioral changes. These interventions may include digital technologies that emerged as promising approaches to facilitate lifestyle changes, such as dietary behavior and physical activity (PA). Aim: This review aimed to synthesize the current evidence for the potential impact of remotely delivered nutrition interventions with or without a combination of PA interventions on biochemical biomarkers, cardiovascular indexes, anthropometric parameters, levels of PA, exercise and functional capacity, adherence to the Mediterranean Diet (MD), diet quality and quality of life, rehospitalization, urgent visits, death and acute events in adults (≥18 years) with CVDs. Secondary outcomes were accessibility, safety, usability, and adherence. Methods: The PubMed, Web of Science, and Scopus databases were comprehensively searched up to 2026 for Randomized Controlled Trials (RCTs) published in English, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The methodological quality was assessed using the revised Cochrane Risk of bias tool for RCTs (RoB2). Results: 11 RCTs met the inclusion criteria. Sample sizes ranged from 66 to 879 participants. The duration of the interventions varied from 4 weeks to 12 months. The interventions were delivered remotely using a range of digital health technologies, including web-based programs, mobile phones, wearable devices, smartphone applications, and mini-apps. Favorable changes were observed in diet quality and in adherence to MD and PA levels, with no intervention-related adverse events reported. The RoB2 assessment indicated that the majority of included studies (6 out of 11) were classified as having some concerns regarding risk of bias. Conclusions: Remotely combined nutrition and PA interventions are a feasible and effective approach for improving mainly patient-reported outcomes in adults with CVDs. These findings support integrating remote multimodal rehabilitation into routine cardiovascular care and highlight the potential of telehealth-based models to enhance patients’ access to rehabilitation services. Full article

Background: The objective of this study was to evaluate the preliminary effectiveness of a self-administered digital mental health intervention, COPE2Thrive, in improving symptoms and functional impairment in youth in a diverse community setting. Methods: Outcome measures included self-reported Kiddie-Computerized Adaptive Testing (K-CAT) scores on seven diagnostic domains, and self-reported scores of six domains and the total score of the Weiss Functional Impairment Rating Scale (WFIRS)—Self Report. All youth were eligible to participate unless they were currently in another therapy. Primary analyses followed the stepped-wedge randomized design, comparing participants assigned to one of three randomized intervention sequences. Secondary analyses treated the study as an open-label intervention study and evaluated pre- to post-treatment change among participants who engaged in the intervention, using the last observation carried forward for non-completers. Results: We successfully recruited a majority non-White sample that was 31.5% Black, 31.5% Hispanic/Latino, and 19.6% Asian. Of the eligible participants, 30.5% enrolled in the study, 23.4% completed the intervention, and 12.5% participated in the follow-up. Racial and ethnic minority subjects were less likely to have received outside behavioral health therapies, both in the screening sample and among those who participated in the intervention. There was no statistically significant improvement in the total score or any of the domain scores on the K-CAT or the WFIRS-S, either in the RCT or in the open-label analysis. Conclusions: Given the low acceptability of the program and the absence of clinically significant improvement in this pilot study, the findings suggest that the intervention, as implemented, may have limited utility for addressing youth distress in diverse communities. Full article

This study presents a slide-based video cognitive behavioral therapy (CBT)-informed psychoeducational intervention for chronic kidney disease (CKD) and end-stage kidney disease (ESKD) patients. The intervention addresses the lack of mental healthcare interventions for CKD patients, who experience disproportionate mental health challenges. The intervention is available in English and Spanish. The intervention includes four modules on the following: 1. depression; 2. anxiety; 3. locus of control and social support; and 4. treatment adherence, each with exercises. The intervention was tested with a sample of 45 CKD and ESKD patients, including individuals with CKD not receiving hemodialysis (HD) and individuals with ESKD receiving HD. Results showed a statistically significant within-participant reduction in PHQ-9 scores from pre- to post-intervention. The intervention did not yield significant pre- to post- changes in patients’ anxiety or locus of control. Associations between treatment adherence and depression, anxiety, locus of control, social support, and resilient coping were not statistically significant after applying the Bonferroni correction. Participant feedback was positive; they identified breathing exercises as the most helpful component, followed by medication adherence strategies, and referenced family members as supports. These preliminary results show that this CBT-informed intervention may have the potential to address depression in CKD/ESKD patients. Full article

Forecasting vibration-derived health indicators is distinct from fault diagnosis and remaining-useful-life estimation, yet controlled comparisons that preserve temporal order, physical scale, and dependence among forecast errors remain limited. This study presents a systematic empirical benchmark for point forecasting univariate root-mean-square (RMS) vibration sequences from two public rotating-machinery datasets with different experimental meanings: “Vibration, Acoustic, Temperature, and Motor Current Dataset of Rotating Machine Under Varying Load Conditions for Fault Diagnosis” (DB1), which provides separately recorded operating and fault conditions, and the “Intelligent Maintenance Systems (IMS) Bearings” record (DB2), from which one run-to-failure recording is used. Twelve methods span naive, statistical, supervised deep-learning, and zero-shot foundation-model families. Every method receives the same 128-step observed context and is evaluated at horizons of 1, 8, and 32 steps on common forecast origins after chronological point-level splitting and training-only scaling. Original-scale errors, per-lead behavior, paired skill, circular moving-block-bootstrap intervals, conditioned cross-regime tests, controlled corruptions, and a desktop central processing unit (CPU) reference workload provide complementary evidence. On DB1 0 Nm Normal, the lowest observed mean absolute error (MAE) is 0.0202 g at the one-step horizon (long short-term memory (LSTM)), 0.0283 g at the eight-step horizon (TimeMixer), and 0.0290 g at the 32-step horizon (inverted Transformer (iTransformer)), although the leading supervised intervals overlap. On DB2 2nd_test, persistence is lowest at the one- and eight-step horizons (0.00788 and 0.01491 dataset acceleration units), while drift is lowest at the 32-step horizon (0.02948); several statistical and zero-shot intervals overlap these leaders. The benchmark combines an explicitly specified waveform-to-target construction, a leakage-safe common-origin design across four model families, dependence-aware inference, and matched robustness and efficiency analyses. The findings show that model value is dataset- and horizon-dependent and that sophisticated forecasters should be judged against strong local baselines under the intended operating context. Full article

Early childhood dental caries (ECC) remains one of the most prevalent and preventable chronic diseases affecting young children globally, yet behavioral and contextual determinants of its onset during the first 1000 days of life remain poorly understood and infrequently modeled in Latin American populations. This study presents a novel application of the PRECEDE diagnostic framework to conceptualize Early Childhood Dental Caries during the first 1000 days (1000ECDC) as a behaviorally rooted, socio-ecologically conditioned health problem. Drawing on a formative longitudinal pilot study (n = 10 mother–infant dyads, Caracas, Venezuela) and a complementary narrative literature review, we develop the first PRECEDE-based conceptual model linking maternal prenatal and postnatal behaviors to dental caries risk in a Latin American context. The model identifies dietary and feeding behaviors, oral health care practices, and healthcare service utilization as primary behavioral risk factors, modulated by predisposing factors (low oral health knowledge, limited self-efficacy, cultural norms), enabling factors (socioeconomic constraints, fragmented health systems), and reinforcing factors (social norms, family influence). Exploratory pilot findings indicated that more than 60% of children had advanced dental caries lesions at 24-month follow-up, consistent with regional estimates and underscoring the urgency of early intervention. This model provides practitioners and policymakers with a structured, evidence-informed diagnostic tool to guide the design of early-life oral health promotion programs, with particular relevance for low-resource Latin American settings. Future validation through expert consensus and prospective studies is warranted. Full article

Background/Objectives: The aim of this study is to determine the extent to which early breast cancer detection behaviors in Türkiye are associated with age, education, income, and chronic disease status, and to evaluate the relationship of healthcare service utilization (contact with family physicians/general practitioners and specialists) with these behaviors. Methods: A cross-sectional secondary data analysis was conducted using nationally representative microdata from the Turkish Statistical Institute’s (TUIK) 2022 Turkiye Health Survey. The analysis included 5554 women aged 40–69. Descriptive statistics were calculated using the FERTFACTOR sample weight. Fully adjusted modified Poisson regression models were constructed for recent mammography (within the last 2 years) and monthly breast self-examination (BSE) (adjusted prevalence ratio, aPR), while Classification and Regression Tree (CART) analysis with five-fold cross-validation was applied to identify targetable risk profiles. (The maximum tree depth was set at 3, and the minimum terminal node size at 250 individuals.) Results: The rates of undergoing a recent mammogram and performing monthly BSE were 23.5% and 25.0%, respectively. Both early detection behaviors were more frequent among women who had contact with both a family physician/general practitioner and a specialist physician within the past 12 months. While contact with a specialist physician was independently associated with both behaviors, education level was positively associated with them, whereas the presence of a chronic disease was associated only with having a recent mammogram. In the CART analysis, the initial split occurred based on BSE behavior, and the prevalence of recent mammography varied approximately eightfold across the terminal nodes (cross-validated AUC = 0.681). Conclusions: In Türkiye, behaviors related to the early detection of breast cancer are associated with age, education, and contact with healthcare services. Fewer than one in four women were up to date with mammography, underscoring a substantial early detection gap. Contact with a specialist physician showed the strongest association; however, given the cross-sectional design, causality cannot be inferred and reverse causation cannot be excluded. Systematizing early detection recommendations within primary care and implementing targeted strategies for low-socioeconomic groups may help increase participation in screening. Full article

Background/Objectives: Oral diseases are a major public health challenge and share behavioral and socioeconomic determinants with other noncommunicable diseases. Although physical activity has been proposed as one of these shared determinants, evidence at the population level remains limited. This study investigated the association between physical activity and oral health indicators using nationwide Brazilian surveillance data. Methods: An ecological study was conducted using aggregated data from the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey (VIGITEL) and the Brazilian National Oral Health Survey (SB Brasil) (2022–2023). Physical activity participation and weekly volume were evaluated against untreated dental caries, toothache, pain intensity, tooth loss, and the Decayed, Missing, and Filled Teeth (DMFT) index. Weighted multivariable linear regression models with heteroskedasticity-consistent standard errors were applied. Results: The analysis included 28,707 VIGITEL participants and 14,753 SB Brasil observations. After adjustment, physical activity participation was inversely associated with untreated dental caries, whereas weekly physical activity volume showed no association with any oral health outcome. No significant associations were observed for tooth loss, dental pain, pain intensity, or the DMFT index. Conclusions: Higher population-level participation in physical activity was associated with a lower prevalence of untreated dental caries but not with other oral health indicators. These findings may suggest that physical activity and oral health share common behavioral and social determinants, supporting integrated public health strategies targeting upstream risk factors. Full article

Oral cancer, predominantly represented by oral squamous cell carcinoma (OSCC), remains a major global health burden due to its aggressive clinical behavior, high recurrence rates, and limited improvement in survival over recent decades. Despite advances in treatment modalities, patient outcomes remain poor largely due to late diagnosis, therapeutic resistance, and profound tumor heterogeneity. In particular, metabolic reprogramming has emerged as a central hallmark of oral carcinogenesis, enabling tumor cells to adapt to hypoxic and nutrient-deprived microenvironments while promoting proliferation, invasion, and treatment resistance. Traditional experimental models, including two-dimensional cell cultures and in vivo animal models, have provided important mechanistic insights. However, they fail to fully recapitulate the metabolic, structural, and cellular complexity of human tumors. Consequently, there is growing interest in more physiologically relevant platforms, such as three-dimensional spheroids, organoids, and patient-derived models, which better preserve tumor architecture and microenvironmental interactions. In parallel, multi-omics approaches are increasingly being integrated to dissect the molecular and metabolic complexity of oral cancer at unprecedented resolutions, while nanotechnology-based systems are emerging as promising tools for targeted drug delivery and improved therapeutic precision. This review discusses experimental models in oral cancer research, focusing on their ability to capture metabolic alterations and tumor heterogeneity. We further highlight their translational potential together with multi-omics integration and nanotechnology-based strategies for improving biomarker discovery, therapeutic stratification, and the development of more effective treatment approaches. Full article

Background and Objectives: Musculoskeletal pain (MSP) is highly prevalent among undergraduate students and may originate during early adulthood, increasing the risk of chronicity later in life. Modifiable factors such as reduced muscle flexibility and prolonged sedentary behavior have been proposed as contributors; however, longitudinal evidence among student populations remains scarce. This study aimed to prospectively examine changes in MSP prevalence and hip muscle length over one year and to identify independent predictors of MSP. Materials and Methods: A prospective longitudinal study was conducted among 62 first-year undergraduate students assessed at baseline and at one-year follow-up. MSP was evaluated using a modified Standardized Nordic Questionnaire, and demographic data including physical activity and sitting behavior were recorded. Hamstring and iliopsoas muscle length were measured by passive straight-leg raise and modified Thomas tests, respectively. Changes over time were analyzed using paired t-tests and McNemar tests. Multivariable logistic regression was also performed to identify predictors of MSP at follow-up. Results: Most participants were female (79%, n = 49), with a mean age of 25.8 ± 6.0 years and body mass index of 23.6 ± 4.4 kg/m². Significant reductions in hamstring (p < 0.001; d = −0.55 to −0.70) and iliopsoas muscle length (p < 0.001; d = −1.32 to −1.46) were observed over one year. Health science students manifested a significant decrease in hamstring length over time compared to their counterparts in other programs (p ≤ 0.002). MSP prevalence increased across all body regions, particularly in the low back (46.8% to 71.0%) and cervical spine (46.8% to 61.3%). Baseline MSP was the only independent predictor of MSP at follow-up (upper quadrant: OR = 12.89, 95% CI: 2.38–69.65, p = 0.003; lower quadrant: OR = 6.35, 95% CI: 1.39–28.90, p = 0.018). Conclusions: A significant increase in the prevalence of MSP was observed alongside a reduction in hip muscle length among undergraduate students over a one-year period. The findings suggest that students enrolled in health science programs are more susceptible to musculoskeletal alterations, whereas baseline MSP is a strong predictor of future symptoms. Full article

Refugees and asylum seekers in Germany face significant barriers to accessing routine dental care, leading to untreated conditions that escalate into costly emergency hospital admissions and increased public healthcare expenditures. This study evaluates the economic impact of an NGO-led dental care facility designed to address this critical gap in care for uninsured populations. Using a retrospective cost-effectiveness analysis, we compare three scenarios: (1) the NGO intervention, (2) the “status quo” reliance on emergency care, and (3) a dental clinic arm-based model. We test the hypothesis that NGO-led interventions reduce public healthcare costs by curbing preventable emergency admissions, thereby addressing systemic policy and market failures. Results demonstrate that the NGO facility is a cost-effective solution, generating a return of €0.60 for every euro invested, while the alternative scenarios yielded no financial returns. By providing equitable, preventive dental care, the NGO model reduced emergency admissions by addressing delayed treatment-seeking behaviors and structural access barriers. These findings confirm that NGO-led interventions can mitigate market failures by serving as a Pareto-improving solution, optimizing resource allocation and reducing long-term fiscal burdens. The study underscores the potential of NGOs to complement public health systems in achieving equitable and sustainable healthcare delivery. Policymakers should consider scaling such models to alleviate disparities in underserved populations while curbing avoidable costs linked to emergency care. This research contributes critical evidence for integrating NGO-led initiatives into healthcare strategies, particularly in contexts marked by fragmented access and systemic inefficiencies. Full article

As population aging accelerates, providing psychosocial support for adults in the retirement transition has become increasingly important. For this population, a central challenge is adapting to changes in social roles, daily routines, and social relationships, yet existing social robot research has paid insufficient attention to these companionship-related needs. From an embodied cognition perspective, this study developed a needs-driven design pathway for a social companion robot for this population in urban China. Sixteen key needs were identified through user interviews and prioritized through a Kano survey with 184 valid responses from urban community-dwelling adults in the retirement transition. Based on the classification and prioritization results, these needs were synthesized into four design strategies: emotional responsiveness and trust building, social connectedness and sustained engagement, low-burden interaction and daily life support, and safety, health, and privacy protection. Privacy and safety were treated as foundational conditions for product design and practical deployment. The strategies were subsequently mapped to technical features and hardware elements through quality function deployment (QFD), using an expert-panel evaluation procedure and sensitivity analysis to determine module-level configuration priorities. A single-session, laboratory-based concept evaluation was conducted with 50 participants using concept renderings and interaction-flow videos. Concept 3, whose overall configuration emphasized coordinated voice, screen-based visual, and expression/action feedback, received a significantly higher mean participant-level Behavioral Intention (BI) score than Concept 2, which placed greater emphasis on spatial mobility assistance through a mobile wheel module (8.94 ± 0.97 vs. 8.51 ± 1.21; adjusted p = 0.003). These evaluation findings informed the final concept configuration and provided preliminary support for its companionship-oriented multimodal interaction approach. Full article