Search Results (24,313)

Background/Objectives: Excessive smartphone use has emerged as an important behavioral health concern during adolescence, a developmental period characterized by heightened psychosocial vulnerability. This study aimed to identify psychosocial and behavioral factors associated with excessive smartphone use among Korean adolescents using nationally representative data. Methods: Data were obtained from the 2024 Korean Youth Risk Behavior Web-based Survey (KYRBS), including 54,653 adolescents. Excessive smartphone use was operationally defined as average daily smartphone use of ≥300 min. Multivariable logistic regression was conducted to examine associated factors. An exploratory machine learning analysis using a Light Gradient Boosting Machine included 52,450 participants with complete predictor data. Results: Female sex, higher grade level, lower perceived socioeconomic status, higher perceived daily stress, higher anxiety symptoms, poorer sleep-related recovery, suicidal ideation, and more frequent vigorous physical activity were associated with higher odds of excessive smartphone use. The supplementary modeling approach showed patterns consistent with the regression findings, with grade level, socioeconomic status, and sex contributing prominently. Vigorous physical activity demonstrated a nonlinear association with predicted risk. Conclusions: Excessive smartphone use among adolescents appears to be shaped by developmental stage, socioeconomic context, and psychological vulnerability. These findings support prevention strategies that address emotional well-being and sleep health alongside broader structural and school-based approaches. Full article

The electrodeposition of rare earth metal alloys has attracted considerable interest, not only due to the challenges associated with the reduction in metal ions, but also because of their unique material properties and promising technological applications. This review presents a comprehensive analysis of the state-of-the-art in the electrochemical deposition of these alloys, focusing on various electrolytic systems, including aqueous solutions, organic molecular solvents, ionic liquids, and deep eutectic solvents. Despite inherent problematic factors such as low reduction potentials, competing hydrogen evolution reactions, and difficulties in controlling metal formation, recent advancements have enabled improved control over film formation, typically through the induced codeposition of lanthanides with iron-group metals. The influence of key factors, such as electrolyte composition and current/potential modes, on alloy codeposition, elemental and phase composition, structure, and deposition efficiency is discussed. The magnetic properties, electrocatalytic behavior, and corrosion resistance of the deposited films are also shown, highlighting their relevance for high-performance applications. Full article

Background/Objectives: Depression is a common and consequential comorbidity among adults with diagnosed diabetes. Prior research has largely emphasized individual health behaviors, with less attention to emotional burden, social context, or theory-driven interpretation. The Multi-Theory Model (MTM) of Health Behavior Change offers an integrative framework for examining behavioral, emotional, and environmental correlates of health outcomes. This study applied MTM to examine correlates of lifetime diagnosed depression among U.S. adults with diagnosed diabetes. Methods: This cross-sectional study analyzed 2023 Behavioral Risk Factor Surveillance System (BRFSS) data from 19,967 adults with diagnosed diabetes, representing approximately 30 million U.S. adults after survey weighting. Lifetime diagnosed depression was assessed based on respondents reporting that a health professional had told them they had a depressive disorder, representing a lifetime history of depression rather than current depressive symptoms. Independent variables were organized into behavioral, emotional, and environmental domains consistent with MTM. Survey-weighted descriptive analyses, Rao–Scott χ² tests, and nested survey-weighted logistic regression models were conducted. Results: The weighted prevalence of lifetime diagnosed depression among adults with diagnosed diabetes was 24.3%. In the fully adjusted MTM-guided model, emotional and environmental domains showed the strongest associations with lifetime diagnosed depression. Frequent mental distress was associated with substantially higher odds of depression (adjusted odds ratio ≈ 10.4, p < 0.001). High social or economic stress and fair or poor self-rated health remained independently associated (p < 0.001). Behavioral factors, including physical activity, smoking, and body mass index, were attenuated after adjustment. Conclusions: Lifetime diagnosed depression among adults with diagnosed diabetes was more strongly associated with emotional burden and adverse social conditions than with health behavior alone, supporting the integration of distress screening and context-responsive interventions into diabetes care. Full article

Scientific evidence shows that perception of adolescents’ psychological adjustment in residential care varies depending on the informant. This study examined discrepancies between adolescents’ self-reports and caregiver reports of psychological adjustment in 46 residential care institutions across Portugal. Data were collected from a sample of 511 adolescents (aged 12–24) and their institutional caregivers using the Strengths and Difficulties Questionnaire and the Socially Desirable Response Set-5. Descriptive statistics and paired-samples t-tests were conducted to compare mean scores between informants. Intraclass correlation coefficients and Cohen’s Kappa were calculated to assess agreement. Results revealed significant differences across all subscales and the total difficulties score, with adolescents consistently reporting more emotional, behavioral, and peer-related problems than caregivers, regardless of sex or age. Agreement ranged from poor to moderate, with the lowest concordance for internalizing symptoms. These discrepancies underscore the role of developmental factors in shaping self- and caregiver perceptions and highlight the importance of multi-informant, developmentally sensitive assessments in residential care. Practical implications include incorporating adolescents’ perspectives into evaluation and intervention, enhancing caregiver training to recognize internalizing issues, and implementing age- and gender-tailored mental health programs. Full article

Background/Objectives: Maternal postpartum depressive symptoms and the COVID-19 pandemic have both been identified as potential risk factors for socioemotional difficulties in children. This study aimed to assess behavioral outcomes in young children born to mothers previously screened for postpartum depressive symptoms, comparing cohorts evaluated during and after the pandemic using the Child Behavior Checklist (CBCL 1½–5). Methods: An observational follow-up cohort study was conducted on 52 mother–child dyads derived from a previously established maternal cohort screened with the Edinburgh Postnatal Depression Scale (EPDS). Two cohorts were defined according to the child’s birth period: during-pandemic (January–April 2022) and post-pandemic (October–November 2023) groups. Behavioral outcomes were assessed using CBCL 1½–5. Group differences were tested using parametric or non-parametric methods for continuous variables and χ2 or Fisher’s exact tests for categorical variables. Exploratory regression models and sensitivity analyses were also performed. Results: Children assessed in the post-pandemic cohort showed a lower prevalence of non-normal internalizing scores than those assessed in the during-pandemic cohort, whereas externalizing outcomes and Total Problems did not significantly differ between groups. In exploratory models, a child’s age showed a near-significant association with internalizing outcomes, suggesting that developmental stage at assessment may have contributed to the observed cohort difference. Maternal SARS-CoV-2 infection at delivery was not associated with children’s behavioral outcomes. Conclusions: These findings suggest a possible difference in internalizing behavioral profiles between children assessed in during-pandemic and post-pandemic cohorts. However, this pattern should be interpreted cautiously because the cohorts differed substantially in age at follow-up, and age-related factors may have affected symptom detectability. Continued longitudinal follow-up will be important to clarify whether the observed differences persist over time. Full article

Triple-negative breast cancer (TNBC) represents a clinically challenging breast cancer (BC) subtype, characterized by aggressive behavior, high recurrence risk, and limited therapeutic options. MEAK7 has been identified as an alternative mTORC1 signaling pathway regulator; however, its role in BC and TNBC remains uninvestigated. This study aims to assess MEAK7 expression, prognostic significance, and therapeutic potential. We employed public datasets, including TCGA, bc-GenExMiner v5.2, GEPIA3, DOSurvive platforms, Kaplan–Meier Plotter, UALCAN, TIMER2.0, STRING, ENCORI, HPA, miRDB, TargetScan, and CRISPRdb. MEAK7 expression was significantly elevated in BC tissues versus normal breast tissue. MEAK7 expression was pronounced in TNBC and basal-like subtypes, with hypomethylation of its promoter region in TNBC. Elevated MEAK7 expression correlated with reduced disease-free survival (DFS) in TNBC and basal-like. Multivariate Cox regression identified MEAK7 as a significant prognostic factor for overall survival, independent of age and tumor stage. MEAK7 showed CRISPR-targetable gRNA profiles with high on-target efficiency and minimal off-target effects. Analyses revealed negative correlation with tumor-suppressive RNAs (miR-149-3p, miR-135a-5p, and LINC00993) and positive correlation with aggressive regulators (miR-135b-5p and HIF1A-AS2). This study represents one of the initial comprehensive and multi-platform bioinformatic analyses demonstrating that MEAK7 exhibits elevated expression in breast cancer, particularly within the aggressive TNBC. The findings indicate that MEAK7 may serve as a promising prognostic biomarker in TNBC biology and suggest its viability as a molecular candidate for future investigation in targeted therapeutic strategies. Full article

Metaheuristic algorithms have become indispensable for solving high-dimensional, non-convex, and constrained optimization problems arising in science and engineering. However, no single method can simultaneously provide strong global exploration, accurate local exploitation, and robust performance across diverse problem classes. This paper proposes JADEFLO, a new hybrid nature-inspired metaheuristic that couples Adaptive Differential Evolution with Optional External Archive (JADE) and Frilled Lizard Optimization (FLO) in a two-stage search framework. In the first stage, JADE drives global exploration using p-best mutation, an external archive, and adaptive control of the mutation factor and crossover rate to maintain population diversity. In the second stage, FLO performs intensive local refinement by mimicking the hunting and tree-climbing behaviors of frilled lizards through dedicated exploration and exploitation moves. The resulting algorithm has linear time complexity with respect to the population size, dimensionality, and number of iterations. JADEFLO is evaluated on the IEEE CEC 2022 single-objective benchmark suite (F1–F12) and three constrained engineering design problems (Pressure Vessel, tension/compression spring, and speed reducer), using 30 independent runs and comparisons against more than thirty state-of-the-art metaheuristics, including GA, PSO, DE variants, GWO, WOA, MFO, and FLO. The results show that JADEFLO attains the best overall rank on the CEC functions, delivers faster convergence and higher accuracy on most test cases, and matches or improves the best-known designs with markedly reduced variance. These findings indicate that JADEFLO is a promising general-purpose optimizer and a flexible foundation for future extensions to multi-objective and large-scale optimization. Full article

The pore pressure coefficient B, defined as the change in pore pressure per unit increment of confining pressure under undrained conditions, is a fundamental parameter in soil mechanics. It characterizes the coupling between soil skeleton deformation and pore water pressure and plays a critical role in establishing the effective stress framework for frozen soils. Existing studies mainly focus on unfrozen soils, while the temperature sensitivity and stress-path dependence of B in frozen soils undergoing phase transition remain insufficiently understood. To address this gap, this study conducts temperature-controlled triaxial tests and constant strain-rate loading tests to investigate the evolution of B in frozen sandy silt over a temperature range of −11 °C to −2 °C under different stress histories. The results show that: (1) post-loading B-values at −5 °C to −8 °C are significantly higher than those at −2 °C and −10 °C, by 6.5% and 8.2%, respectively; (2) within the framework of Gassmann’s equation, a theoretical model incorporating the soil freezing characteristic curve and the coupled effects of ice–water phase transition and soil skeleton deformation is developed to explain the temperature-dependent behavior of unfrozen water and B; and (3) a predictive model incorporating a temperature correction factor is proposed, which accurately captures the variation trend of B in frozen sandy silt. This study elucidates the evolution mechanism of the pore pressure coefficient under multi-field coupling conditions and provides a theoretical basis for frost heave assessment and constitutive modeling in cold-region engineering. Full article

The modern high-pressure lifestyle has led to an increasing emphasis on the healing construction of residential spaces, while air, as an important environmental factor, has received little attention in terms of situational healing experiences within the context of residential culture. Employing grounded theory, this study develops a theoretical model to explain the mechanism through which indoor air environments influence the healing benefits of residential spaces. Guided by the dynamic interaction process of “physical attributes–embodied cognition–behavioral regulation–social context”, the analysis focuses on human embodied perception and emotional responses to indoor air environments as the foundation for healing effects. It highlights the joint role of behavioral regulation and social context, ultimately affecting four levels of healing benefits. Furthermore, it systematically elaborates a theoretical model for embodied interactive residential air experiences, expanding healing environment theory from a contextual air experience perspective, and providing new research paradigm and insights for promoting healing benefits in residential settings. Full article

In the automotive industry, the most critical factor affecting dimensional stability during the forming of Advanced High-Strength Steels (AHSSs) is the springback phenomenon. This study systematically investigates the springback behavior of four distinct dual-phase steel grades (DP450, DP600, DP800, and DP1000) in U-shaped body-in-white (BIW) structures across 180 distinct scenarios. The experimental design varied sheet thicknesses (1.2, 1.6, 2 mm), die clearance angles (5°, 10°, 15°), and bending radii (R6, R8, R10, R12, R14). Numerical simulations using Autoform R8 were validated against Atos 3D optical scanning data, achieving values exceeding 0.90 for all grades. Quantitative validation metrics showed exceptional fidelity for lower-strength grades with error margins below 1.1%, while the maximum deviation was limited to 3.1% for the ultra-high-strength DP1000 grade. The findings demonstrate that while increasing material strength substantially intensifies springback, the strategic augmentation of sheet thickness and optimization of die radius effectively mitigate these deviations, thereby enhancing process stability. Full article

Urban mental health is increasingly influenced by daily environmental exposures, yet limited empirical evidence exists regarding how the spatial configuration of blue–green environments, rather than their mere quantity, relates to emotional behavior in high-density cities. Guided by restoration theories and a perception-based perspective on landscape integration, this study analyzes the urban core of Shanghai by linking blue–green configurations to emotional states inferred from 20,907 geotagged social media facial photographs. Facial expressions serve to derive indices for emotional valence and arousal. The results demonstrate significant spatial clustering of emotional behavior, where hotspots are concentrated in higher-quality and more open settings, while coldspots cluster in dense areas with sparse vegetation. Emotional behavior also exhibits demographic heterogeneity, as females display higher valence and arousal than males. Furthermore, happiness tends to increase with age across both genders, whereas arousal declines specifically among male age groups. Crucially, emotional outcomes align more consistently with landscape integration and configuration than with isolated blue or green areas. Factors such as high connectivity, superior vegetation condition, and configurations featuring water embedded within green space are associated with favorable emotional responses. Conversely, extensive edge-dominated interfaces and high traffic exposure correlate with less favorable outcomes. These findings suggest a shift in blue–green planning from increasing total area toward optimizing spatial composition. Specifically, priority should be given to embedded and cohesive designs alongside the reduction of ambient stressors to foster emotionally supportive environments in dense urban cores. Methodologically, image-derived behavioral traces provide a scalable and ecologically grounded approach for investigating place-based affect at a city scale. Full article

This study presents a calibrated analytical micromechanical framework for predicting the linear elastic behavior of unidirectional glass fiber/epoxy and carbon fiber/epoxy composites over a wide range of fiber volume fractions. The approach combines the classical rule of mixtures for the longitudinal Young’s modulus with the semi empirical Halpin–Tsai equations to estimate the transverse Young’s modulus and the in-plane shear modulus. The framework is specifically formulated to support durability-oriented composite design through rapid and physically consistent estimation of elastic properties governing load transfer and stress distribution. Material parameters, including fiber and matrix Young’s moduli (Ef, Em), shear moduli (Gf, Gm), Poisson’s ratios (νf, νm), and fiber volume fraction (Vf up to 0.80), are taken from established material property databases and implemented within a literature-informed modeling scheme. To preserve physical realism at high fiber contents, a shear correction factor is introduced for Vf > 0.50 to account for microstructural interaction and fiber clustering effects. The predicted effective elastic constants (E₁, E₂, G₁₂, ν₁₂) exhibit consistent and physically meaningful trends across the full fiber volume fraction range. The model predictions were evaluated against trends widely reported in the composite micromechanics literature, and the results showed overall agreement in the nonlinear reduction in stiffness gains at elevated fiber volume fractions. Comparative results indicate that carbon fiber/epoxy composites achieve up to approximately 30% higher stiffness than glass fiber/epoxy systems at equivalent fiber contents, reflecting the influence of stiffness contrast on composite response. The analysis further indicates that stiffness saturation begins approximately in the Vf = 0.60–0.70 range, where the incremental gains in E2 and G12 become noticeably smaller for both composite systems. This behavior provides design-relevant guidance by showing that, beyond this range, further increases in fiber content may offer limited stiffness improvement relative to the associated manufacturing complexity. Overall, the calibrated Halpin–Tsai methodology offers a practical and computationally efficient tool for preliminary evaluation and design-stage optimization of the elastic performance of high-performance composite structures. Full article

As social media campaigns become increasingly important in grocery and supermarket retail communication strategies, there is little research on how consumers view campaign performance throughout their decision-making process, rather than isolated behavioral outcomes. This study examines how the five-stage decision-making process is influenced by consumer-perceived social media performance effectiveness (CP-SMPE), grounded in consumer decision-making theory and social media performance literature. The study uses a mixed-methods research design, combining qualitative interviews with the consumers and a quantitative survey of 300 grocery shoppers in Greece. Perceived return on investment, revenue contribution, lead generation, engagement, reach, cost efficiency, and quality of electronic word-of-mouth are components of social media performance conceptualized as a multidimensional construct. Exploratory factor analysis and PLS-SEM were employed to analyze quantitative data. The findings show that high perceived social media campaign performance influences all stages of the consumer decision-making process, both directly and indirectly, through sequential intermediate stages. It ultimately enhances purchase decisions and post-purchase outcomes. By adopting a consumer-centric, process-based perspective, this study contributes to research on digitally mediated retail decision-making by demonstrating how effective social media communication can support more informed, structured consumer choices. The findings suggest that social media communication can lead to more informed and potentially responsible consumption choices by improving information environments and decision support, even though sustainability outcomes are not directly measured. Full article

Over the past decade, road safety research has experienced rapid development due to the rapid expansion of large crash databases, the adoption of artificial intelligence techniques, and the demand for proactive and predictive safety solutions. This study conducts a data-driven review of recent research trends in transport safety. It focuses on main domains including crash severity analysis, human factors, vulnerable road users (VRUs), spatial modeling, and artificial intelligence applications. A systematic search of the Scopus database identified 15,599 relevant scientific papers published between 2016 and 2025. After constructing this corpus, titles, abstracts, and keywords were preprocessed using a natural language pipeline. The analysis employed BERTopic, a transformer-based topic modeling framework. The analysis identified 29 distinct research topics, further synthesized into five major thematic areas: (1) crash severity and injury analysis, (2) driver behavior and human factors, (3) vulnerable road users, (4) artificial intelligence, machine learning, and computer vision in intelligent transportation systems, and (5) spatial analysis and hotspot detection. A notable increase in publications related to artificial intelligence and machine learning has been evident since 2020. The results show a transition from descriptive, post-crash studies to integrated, multimodal, predictive analysis. Overall, the findings reveal a paradigm shift in the field. This study also identifies ethical and economic issues associated with the use of artificial intelligence in intelligent transportation systems, including data management, infrastructure requirements, system security, and model transparency. The results signify a transition from intuition-based models to explainable, spatially explicit, and data-intensive models, ultimately facilitating proactive risk assessment and informed decision-making. Full article

This study examines the role of Paradoxical Leadership (PL) in enhancing sustainable service performance in Egypt’s hotel industry, with Organizational Citizenship Behavior (OCB) serving as a key mediating mechanism. Moving beyond conventional performance frameworks, the research examines how the dual nature of PL behaviors encourages discretionary employee actions that advance social sustainability, employee well-being, responsible service delivery, and long-term organizational resilience. Employing a survey-based quantitative design, data were collected from 397 hotel employees in Egypt using a structured questionnaire assessing overall PL, its five core dimensions, and OCB. A structured questionnaire was used to measure overall PL, its five core dimensions, OCB, and sustainable service performance. The data were analyzed using SPSS Version 24 and WarpPLS 8, confirmatory factor analysis, reliability analysis, and regression-based mediation analysis to examine the relationships among the study variables. The findings reveal that PL positively influences sustainable service performance, while OCB not only enhances service outcomes but also significantly mediates the relationship between PL and performance. In addition, each dimension of PL—balancing self- and other-centeredness (SO), maintaining distance while fostering closeness (CD), treating employees uniformly while recognizing individuality (UI), preserving decision control while encouraging autonomy (CA), and enforcing work requirements while allowing flexibility (RF)—significantly strengthens employees’ citizenship behaviors. Full article