Search Results (8,157)

Sustainability and the Sustainable Development Goals (SDGs) are garnering significant attention due to growing global challenges, including poverty, inequality, environmental degradation, and climate change, with the latter addressed specifically through SDG 13. This study examined the level of self-reported awareness of six science-related SDGs—SDG 3 (Good Health and Well-Being), SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), SDG 13 (Climate Action), SDG 14 (Life Below Water), and SDG 15 (Life on Land)—among science teachers in the Arab sector in Israel as a function of background variables: gender, seniority, degree type, academic institution, school type, area of specialization, and the integration of these SDGs into the science curriculum. The study employed a mixed-methods approach: in the quantitative component, 204 science teachers responded to a Likert-scale questionnaire; the qualitative component consisted of semi-structured interviews with 30 middle school science teachers from the Arab sector. The findings indicated a moderate level of self-assessed awareness regarding SDGs. Significant differences in awareness were found according to teaching subject: environmental studies teachers demonstrated the highest awareness, followed by general science, biology, and physics teachers, with chemistry teachers ranking lowest. No significant differences were found for the remaining variables (p > 0.05). Qualitative findings indicated that while teachers perceived SDG-related content as implicitly present in the curriculum, explicit and systematic integration of the SDG framework is largely absent. Overall, the findings suggest that teachers are not adequately exposed to the SDGs. Therefore, it is recommended to incorporate these topics into teacher-training courses and professional development programs and to further integrate them into curricula. This study contributes to the growing body of research on SDG integration in science education, particularly within underexplored minority educational contexts. Full article

Background/Objectives: The COVID-19 pandemic posed significant challenges to quality of life, particularly for individuals living with chronic physical and/or mental conditions. Psychological factors such as fear of COVID-19, psychological distress, and resilience may be associated with quality-of-life outcomes during prolonged public health crises. This study aimed to examine quality of life and its psychological correlates among individuals with chronic conditions during the later phases and aftermath of the COVID-19 pandemic crisis. Methods: A cross-sectional study was conducted among 293 adults with chronic physical and/or mental conditions attending the General Hospital of Argolida, Greece. Participants completed validated self-report measures assessing quality of life (MVQOLI), fear of COVID-19 (FCV-19S), depression, anxiety, and stress (DASS-21), and psychological resilience (CD-RISC-25). Descriptive statistics, Spearman correlation analyses, and multivariable regression models were used to examine associations and identify factors associated with quality-of-life domains. Results: Higher levels of fear of COVID-19 and depressive symptoms were significantly associated with poorer quality of life across multiple domains. Depressive symptoms showed consistent negative associations with functional, interpersonal, transcendent, and overall quality-of-life scores. In contrast, psychological resilience was positively associated with interpersonal, transcendent, and overall quality of life. Regression analyses showed that depressive symptoms were negatively associated with overall quality of life, while resilience was independently associated with better quality-of-life outcomes. Conclusions: Psychological distress, particularly depressive symptoms and fear related to COVID-19, was associated with lower quality of life among individuals with chronic conditions during the later phases and aftermath of the COVID-19 crisis. Psychological resilience was positively associated with better quality-of-life outcomes, underscoring its relevance for supporting well-being during and after public health crises. Full article

Background/Objectives: Food insecurity affects college students at nearly twice the rate of US households, with documented impacts on student academic performance, physical and mental health, and socialization. While frameworks exist to conceptualize general food insecurity and food insecurity in specific contexts, researchers and practitioners lack resources to guide system-level responses to food insecurity on college and university campuses and assess those responses. In this study, we aimed to develop and validate a simple yet comprehensive framework for assessing food insecurity responses within the context of higher education. Methods: We adapted an eight-phase process for framework development: (1) map selected data sources within the multidisciplinary literature, (2) read and categorize selected sources, (3) identify and name concepts, (4) deconstruct and categorize concepts based on their features, (5) group similar concepts together, (6) synthesize concepts into a framework, (7) validate the framework using expert panel review, and (8) revise as necessary. Results: The developed Campus Food Aid Self-assessment (CFAS) framework consists of six dimensions: Student Services and Supports; Involvement; Advocacy; Awareness and Culture Efforts; Education and Training; and Research, Scholarship, and Creative Works. Expert panelists (n = 7) reviewed the proposed framework and confirmed the clarity, comprehensiveness, and representativeness of the proposed dimensions, conceptual definitions, and operational variables. Conclusions: With a comprehensive yet accessible structure, the CFAS framework supports the development, coordination, and improvement of campus-based strategies to address food insecurity and support positive student outcomes. Full article

Out-of-school tutoring, as a form of privatized compensatory education beyond formal schooling, has become increasingly prevalent, yet its role in fostering students’ holistic competencies remains insufficiently examined. Drawing on a student engagement perspective, this study investigates how different types of out-of-school tutoring, including academic, arts, and sports tutoring, are associated with the development of students’ holistic competencies. Data were drawn from a survey of 704 Grade 10 students in central China. Tutoring engagement during junior secondary school was measured using a self-developed Likert-scale instrument, while holistic competencies were obtained from official Comprehensive Quality Assessment records. The findings reveal differentiated effects across tutoring types. Academic tutoring shows no significant association with academic performance or other dimensions of holistic competence. In contrast, sports tutoring is positively associated with physical and mental health, and arts tutoring demonstrates a significant positive relationship with artistic literacy. Regarding engagement characteristics, simply increasing the number of programs or financial investment yields limited benefits. Instead, time investment and cognitive involvement in sports tutoring, as well as affective involvement in arts tutoring, are positively related to specific dimensions of holistic competence. These results suggest that the effectiveness of out-of-school tutoring depends less on participation amount and more on the nature of students’ engagement. The study highlights the uneven developmental returns of compensatory education and calls for a more balanced and development-oriented approach to tutoring participation. Full article

This study evaluates the effects of a 30-week mindfulness-enhanced resistance training (MRT) program on the physical and mental health of female college students and explores whether changes in self-esteem or mindfulness mediate the relationship between MRT and subjective well-being. Sixty-four healthy female college students were randomly assigned to either the MRT or resistance training (RT) group. Both groups participated in 90 min weekly sessions for 30 weeks. A 2 × 2 mixed-design ANOVA analyzed the intervention’s effects on physical health, mindfulness, self-esteem, and subjective well-being. PROCESS macro (Model 4) tested mediation effects. MRT and RT significantly improved physical health, with MRT showing superior improvements in waist-to-hip ratio, flexibility, and vital capacity. Only MRT improved mindfulness, self-esteem, and subjective well-being. Self-esteem changes fully mediated the relationship between MRT and subjective well-being. MRT as a comprehensive mind–body intervention significantly enhanced the physical health and subjective well-being of female college students, outperforming resistance training. Improvements in self-esteem mediated the relationship between MRT and increased subjective well-being. MRT can serve as an effective approach to promote the physical and mental health of female college students. Full article

During the interpretation of Borehole Radar (BHR) B-scan profiles, the accurate determination of the azimuth of geological targets in three-dimensional space is a critical issue for achieving precise anomaly localization and spatial structure inversion. However, existing directional BHR anomaly localization methods exhibit limited intelligence, insufficient adaptability to multi-site data, and weak generalization capability, rendering them inadequate for engineering applications under complex geological conditions. To address these challenges, a robust deep learning model, termed BSS-Pose-BHR, is developed based on YOLOv11n-pose for keypoint detection in directional BHR profiles. The model incorporates three key optimizations: Bi-Level Routing Attention (BRA) replaces Multi-Head Self-Attention (MHSA) in the backbone to improve computational efficiency; Conv_SAMWS enhances keypoint-related feature weighting in the backbone and neck; and Spatial and Channel Reconstruction Convolution (SCConv) is integrated into the detection head to reduce redundancy and strengthen local feature extraction, thereby improving suitability for keypoint detection tasks. In addition, a three-dimensional electromagnetic model of limestone containing a certain density of clay particles is established to construct a simulation dataset. On the simulated test set, compared with current mainstream deep learning approaches and conventional directional borehole radar anomaly localization algorithms, BSS-Pose-BHR achieves superior performance, with an mAP50(B) of 0.9686, an mAP50–95(B) of 0.7712, an mAP50(P) of 0.9951, and an mAP50–95(P) of 0.9952. Ablation experiments demonstrate that each proposed module contributes significantly to performance improvement. Compared with the baseline, BSS-Pose-BHR improves mAP50(B) by 5.39% and mAP50(P) by 0.86%, while increasing model weight by only 1.05 MB, thereby achieving a reasonable trade-off between detection accuracy and complexity. Furthermore, indoor physical model experiments validate the effectiveness of the method on measured data. Robustness experiments under different Peak Signal-to-Noise Ratio (PSNR) conditions and varying missing-trace rates indicate that BSS-Pose-BHR maintains high detection accuracy under moderate noise and data loss, demonstrating strong engineering applicability and practical value. Full article

Subcutaneous administration has become an increasingly important route for delivering protein therapeutics, driven by patient convenience and the growing use of self-administration devices. However, conventional subcutaneous injection systems are typically limited to injection volumes of approximately 1–2 mL, posing significant formulation challenges for protein drugs requiring high therapeutic doses. Monoclonal antibodies (mAbs), for example, often require concentrations exceeding 100 mg/mL to enable subcutaneous delivery, which introduces challenges related to limited solubility, elevated viscosity, and an increased risk of physical and chemical instability. Therefore, high-concentration protein suspensions have emerged as a promising formulation strategy to overcome these limitations and enable subcutaneous administration of high-dose proteins. In such systems, therapeutic protein solid particles are suspended in vehicles in which they are insoluble, giving rise to unique considerations related to particle properties, protein stability, and suspension behaviors such as viscosity, injectability, and sedimentation. Accordingly, multiple particle production approaches have been explored to enable the development of ultra-high-concentration protein suspensions (>200 mg/mL). This review article aims to provide a comprehensive overview of particle formation techniques and the relationships between key particle properties and suspension performance attributes relevant to the development of high-concentration protein suspensions for injectable applications, as well as future directions in this field. Full article

Cone-beam computed tomography (CBCT) offers advantages of low radiation dose and rapid acquisition but suffers from scatter-induced shading artifacts that limit diagnostic value compared to multi-detector CT (MDCT). While CycleGAN enables unpaired image translation, its uniform loss application struggles with localized artifact removal. We propose a two-stage learning framework with YOLO-based region correction loss. Stage 1 trains a standard CycleGAN to establish stable CBCT-MDCT domain mapping. Stage 2 fine-tunes the model by applying gradient magnitude minimization loss selectively to artifact regions detected by a pretrained YOLO detector, enabling focused correction while preserving anatomical structures. Using 11,000 2D CBCT slices from 17 patients (14 training, 3 testing) and 23,500 2D MDCT slices from 50 patients, our method achieves a 14.0% reduction in artifact score compared to baseline CycleGAN while maintaining high structural similarity (SSIM > 0.96). Independent evaluation using integral nonuniformity (INU) and shading index (SI) confirms consistent improvement across physics-based metrics. The self-regulating mechanism, where YOLO detection confidence naturally decreases as artifacts diminish, provides automatic adjustment without manual intervention. This work demonstrates that combining staged learning with object detection offers an effective solution for localized artifact removal in medical image translation, potentially improving diagnostic accuracy while preserving the low-dose benefits of CBCT. Full article

This study aimed to examine the associations of Health Belief Model (HBM) constructs with physical activity (PA) participation intention and self-reported PA participation among older adults in South Korea. Specifically, we examined whether perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and self-efficacy were associated with PA participation intention and PA participation, and whether intention accounted for indirect associations between HBM constructs and PA within the hypothesized model. A total of 408 older adults (Mage = 68.84, SD = 4.11) participated in the online survey. This study employed Structural Equation Modeling to examine the interrelationships among the proposed variables. The findings indicated a significant negative association between perceived barriers and PA participation intention and a significant positive association between self-efficacy and PA participation intention. Furthermore, intention was positively associated with PA and accounted for indirect associations linking perceived barriers and self-efficacy with PA. Overall, these findings suggest that perceived barriers and self-efficacy are salient belief domains linked to PA intention and behavior. Practical implications include further interventions to reduce perceived barriers and enhance self-efficacy to promote sustained PA engagement among older adults. Full article

Background: Favorable attitudes toward regular leisure-time physical activity may not always translate into intention if adolescents feel ambivalent about the behavior. This study tested whether felt ambivalence weakens the prospective attitude–intention association and the indirect effect of attitude on later behavior through intention. Methods: Chinese adolescents (N = 1714; Grades 7–12; mean age = 15.0 years) completed a three-wave survey at approximately two-week intervals. Wave 1 assessed attitudes toward regular leisure-time moderate-to-vigorous physical activity, felt ambivalence, and physical activity habit; Wave 2 assessed intention; and Wave 3 assessed leisure-time physical activity. Moderated mediation was tested in a structural equation model adjusting for habit, gender, and grade. Results: More favorable baseline attitudes predicted stronger intention two weeks later, and intention predicted greater self-reported leisure-time physical activity at follow-up. Felt ambivalence significantly moderated the attitude–intention pathway such that the association was weaker at higher levels of ambivalence. The conditional indirect effect of attitude on later leisure-time physical activity through intention was significant at low, mean, and high ambivalence, but decreased as ambivalence increased. Conclusions: Favorable attitudes may be insufficient when adolescents remain conflicted about physical activity. The present study provides prospective support for a theoretically relevant moderation pattern in which felt ambivalence weakens the attitude–intention pathway, but it does not establish ambivalence as a key explanatory mechanism. Full article

Background: Low back pain is a common musculoskeletal complaint among postpartum women due to physical changes that occur during pregnancy and delivery, which can lead to different disability levels. Therefore, the aim of this study was to evaluate the disability levels and associated factors of postpartum women within the first year after childbirth. Methods: A descriptive cross-sectional study design was used to gather data from post-partum women between 6 weeks and 12 months after childbirth using an online self-administered questionnaire. This questionnaire included demographic variables, the Nordic Musculoskeletal Symptoms Questionnaire, the Pain Intensity Numeric Rating Scale, and a back disability questionnaire. Results: Among 400 postpartum mothers, 71% reported low back pain, with 51.1% experiencing mild disability. Logistic regression showed significant predictors of disability, including cesarean delivery (6.49 times higher likelihood), having 4–5 children (1.98 times), and more than six children (3.45 times). Breastfeeding increased disability risk (2.44 times), while mixed feeding reduced it (0.52 times). The model explained 49.8% of disability variance (p < 0.001). Conclusions: Disability is a common problem among postpartum women, highlighting the importance of healthcare providers addressing these challenges. Full article

Quasi-resonant (QR) flyback inverters suffer from significant performance degradation under varying thermal conditions. This is because the thermal drift of passive components’ parameters deviates the switching instants from their optimal valley points, leading to increased switching losses and higher grid current distortion. To address this challenge, we propose an online self-tuning control strategy based on a Recurrent Neural Network (RNN) designed for embedded implementation. The RNN model continuously observes a sequence of non-intrusive operational data, including input voltage, input current, and grid current, and directly predicts the optimal time-delay compensation for the valley-switching logic. This end-to-end approach eliminates the need for online parameter identification, complex physical model calculations, or dedicated thermal sensors. The proposed framework was validated through comprehensive MATLAB/Simulink simulations. The results demonstrate that when operating across a wide temperature range (e.g., from 25 °C to 85 °C), the self-tuning control scheme enhances conversion efficiency by over 3.0% and reduces the grid’s current Total Harmonic Distortion (THD) from 5.8% to below 2.0%, thereby significantly improving the inverter’s lifetime performance and reliability. Full article

To evaluate the effectiveness of an adaptive physical education (APE) program using VR technologies, we studied the physical development and vitality indicators of college female students in two groups: those with and without functional health limitations (N = 70 each). Students with disabilities were randomly divided into experimental and control groups of 35 people each. The experimental group participated in physical education classes using VR. The health assessment included heart rate, blood pressure, and subjective health assessments. Physical development was assessed by the biological age index (BAI) by Voitenko, static balance duration, and breath-holding time. Psychological activity was assessed using the Mindfulness Attention Awareness Scale (MAAS), the Rezapkina Vitality Test, and the Subjective Vitality Scale (SVS). The delayed effect was assessed using a questionnaire. Students with functional impairments initially demonstrated a significant decrease in overall vitality, physical activity duration, and more negative health self-perception. After the virtual reality sessions, they showed a restoration of physical development and vitality indicators to levels close to healthy, as well as a decrease in BAI. The delayed effect was confirmed after three months. The use of virtual reality technologies in the APE program effectively improves the physical development and activity (vitality) of students with functional health impairments. Full article

Community social capital (CSC) and the community-built environment (CBE) are key resources associated with residents’ health, yet their combined associations with multidimensional health and well-being remain insufficiently understood. Drawing on large-scale data from the 2018 China Labor-force Dynamics Survey, this study analyzed a filtered sample of 14,127 respondents nested within 326 communities and employed multilevel models to examine the direct, interactive, and combined associations of CSC and CBE on four outcomes: residents’ self-rated health, subjective well-being, loneliness, and mental health. The results identified two CSC indicators: neighborhood mutual support and resident relationship quality, and two CBE indicators: community type and residential density, as key factors associated with multidimensional health, each showing significant associations with multiple health outcomes, with CSC indicators demonstrating relatively stronger and more consistent effect sizes than CBE indicators. The study further identified a dual mechanism involving key indicators of CSC (relationship quality and neighborhood mutual support) and CBE (community type and residential density). When one dimension was constrained, the other was associated with compensatory patterns in residents’ health, whereas high levels of both social and physical resources were associated with synergistic advantages. Stratified analyses revealed that individuals with low external social engagement appeared more sensitive to these environmental associations. This study emphasizes that sustainable community planning and governance should consider key social and physical indicators to support both social sustainability and built-environment sustainability. Depending on the level of community resources, it may be beneficial to leverage the compensatory and synergistic patterns among different community attributes to support improvements in residents’ health benefits. Particular attention may be warranted for individuals with low social engagement to build healthier and more sustainable communities. This research advances an integrated resource configuration framework that contributes to a shift in urban health governance from isolated environmental interventions toward an adaptive, balanced approach. Full article

Acute type A aortic dissection is a life-threatening condition requiring emergency surgery and complex postoperative management. Although survival rates have improved, many patients experience long-term functional impairments, reduced quality of life, and an elevated risk of complications. Despite strong evidence supporting cardiac rehabilitation in other cardiovascular populations, structured programs remain underutilized in patients with surgically resolved acute type A aortic dissection. Exercise-based cardiac rehabilitation appears feasible and can be delivered safely in carefully selected patients when appropriately adapted to individual needs and conducted under close supervision. Postoperative patients are often physically deconditioned, prone to hospital-acquired disability, and may misjudge exercise intensity. Therefore, individualized exercise prescription, guided by exercise testing when available, is important to support safe training thresholds. Early and gradual introduction of physical activity may help prevent complications associated with immobility, support blood pressure control, and contribute to improvements in functional capacity. However, training volume should be purposefully lower than in conventional program settings to reduce hemodynamic stress. Education on safe exercise parameters and self-monitoring plays a central role in enabling long-term adherence and promoting patient autonomy. Cardiac rehabilitation programs should incorporate dietary, nutritional, and psychological support. Although evidence specific to this patient population remains limited, available data suggest the feasibility and potential benefits of cardiac rehabilitation when delivered with appropriate precautions. Our review underscores the need for a tailored, multidisciplinary CR approach aimed at enhancing physical recovery, supporting cardiovascular stability, and improving overall quality of life in patients following surgery. Further research is required to define optimal program protocols. Full article