Search Results (236)

Background/Objectives: The purpose of this study was to investigate the association between physical activity levels and life functioning among Korean older adults using data from the 2024 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: Data from 1418 adults aged ≥65 years were analyzed in this cross-sectional study. Participants were classified into Aerobic-only, Muscle-strengthening-only, Combined, and Inactive groups according to whether their self-reported physical activity met the World Health Organization’s recommendations. Associations with life functioning were examined using complex sample logistic regression analyses adjusting for demographic, lifestyle, and health-related covariates. Results: Compared with the Inactive group, the Aerobic-only (odds ratio [OR] 1.55, 95% confidence interval [CI] 1.11–2.18), Muscle-strengthening-only (OR 1.65, 95% CI 1.06–2.56), and Combined groups (OR 2.19, 95% CI 1.41–3.39) had significantly higher odds of having no limitations in overall life functioning. Similar associations were observed for lower-extremity function, while associations with other functional domains varied across physical activity groups. Conclusions: In this cross-sectional study, meeting the recommended levels of aerobic physical activity, muscle-strengthening exercise, or both was associated with higher odds of having no limitations in overall life functioning and lower-extremity function. Full article

Focus-measure recommendations for smear microscopy are typically established on one specimen type under one reference definition and one scoring rule, leaving their transferability untested. We benchmark 32 handcrafted focus measures on 26,100 z-stacks spanning five smear-microscopy domains at native acquisition dimensions under one frozen protocol. A fixed ten-voter plurality consensus (REF-B) supplies an identical reference target for every candidate, and two further constructions, single-voter exclusion (REF-A) and a non-derivative four-voter consensus (REF-C), quantify how far the recommendation depends on that target. Ten criteria covering consensus localization, curve shape, perturbation response and kernel cost form a declared cross-domain score; clustered bootstrap resampling, alternative aggregation, weight perturbation and controlled image resampling separate sampling variability from sensitivity to evaluation policy. Gradient responses lead under every analysis. Variance of Gradient ranks first under the primary policy in all 1000 clustered bootstrap replicates and in 67.9% of 1000 sampled weight configurations, while Brenner Gradient attains the lowest consensus deviation, 0.072 planes, at the lowest measured kernel cost. Localization ordering is preserved exactly when the reference is rebuilt from non-derivative voters alone (Spearman ρ = 1.000), although the reference plane itself shifts substantially. The benchmark gives a reproducible, auditable basis for selecting focus measures under stated reference, scoring and image-sampling conditions. Full article

Hypertension remains the leading modifiable cause of cardiovascular death, yet fewer than one in four treated adults achieves guideline-recommended blood pressure targets. Catheter-based renal denervation interrupts efferent and afferent renal sympathetic signalling and lowers blood pressure continuously and independently of medication adherence. After a decade of controversy following the neutral SYMPLICITY HTN-3 trial, a coherent body of second-generation sham-controlled randomised evidence, generated with radiofrequency, endovascular ultrasound, and perivascular alcohol platforms, has established a reproducible, modest, and durable antihypertensive effect with a favourable safety profile. Between 2024 and 2026, the field crossed three thresholds simultaneously: guideline endorsement on both sides of the Atlantic, including the first United States recommendation in the 2025 AHA/ACC guideline; a national coverage determination with coverage with evidence development; and the maturation of randomised and real-world follow-up to three years in cohorts exceeding 3000 patients. This state-of-the-art review synthesises the contemporary evidence base; quantifies the expected treatment effect and its heterogeneity; appraises safety across renal and vascular domains; examines emerging data in chronic kidney disease, diabetes, heart failure, and atrial fibrillation; and details the practical requirements for delivering renal denervation responsibly. We conclude by defining the research agenda that must now be addressed: the identification of responders, the development of an intraprocedural endpoint, a direct comparison with newly approved pharmacotherapy, and evidence of cardiovascular event reduction. Full article

Sixth-generation (6G) vehicular systems are expected to provide extreme reliability, ultra-low latency, and high data rates while simultaneously enabling accurate and timely perception of vehicles, road users, and surrounding environments. Conventional vehicle-to-everything (V2X) systems treat communication and environmental sensing separately and therefore fall short in dynamic, dense, and safety-critical driving scenarios. Integrated sensing and communication for V2X (ISAC-V2X) addresses this limitation by sharing hardware and spectrum for dual-functional operation. This survey consolidates the state of the art across eight thematic areas: fundamentals and taxonomy; vehicular channel models and sensing metrics; physical-layer techniques, including waveform design, beamforming, reconfigurable intelligent surfaces, non-orthogonal multiple access, and rate-splitting multiple access; security and privacy; networked and cell-free ISAC with multi-access edge computing; multi-modal perception using radar, LiDAR, camera, and radio-frequency data; artificial intelligence and ML for channel, beam, target, and sensing-data processing; and future research directions. Five consolidated research gaps are synthesized from the reviewed literature: end-to-end frameworks for networked ISAC-V2X under high mobility; unified multi-modal AI-native architectures for joint sensing, communication, localization, and security; incomplete standardization and interoperability; limited validation, testbeds, and reproducible benchmarks; and scalability, robustness, and cross-domain optimization. This survey concludes with standardization and testbed recommendations and presents a roadmap toward deployable 6G ISAC-V2X systems. Full article

This paper aimed to measure the perceived contribution of general education curricula to the Sustainable Development Goals at the University of Ha’il, Saudi Arabia, across four content-based domains: educational, social, environmental, and economic. Although higher education is increasingly recognized as a key setting for advancing Education for Sustainable Development, limited empirical evidence has examined how general education curricula contribute to sustainability across multiple content-based domains while simultaneously considering faculty and student perspectives. A cross-sectional, descriptive-analytical design was applied through a 40-item instrument, validated by an expert panel and administered to a stratified sample of 900 respondents (470 students and 430 faculty members) across eight colleges; overall reliability was high (Cronbach’s α = 0.968). Analyses comprised descriptive statistics, one-sample tests against the high-contribution benchmark, 95% confidence intervals, and a two-way analysis of variance with η² effect sizes. Perceived contribution was high overall (M = 4.07), highest in the educational domain (M = 4.28, 95% CI [4.24, 4.32]) and lowest in the economic domain, the only domain within the moderate band (M = 3.49, 95% CI [3.45, 3.53]; t = −10.44, p < 0.001). Neither respondent type (η² = 0.0002) nor college affiliation (η² = 0.0046) produced significant differences. The findings support the value of a multi-domain and dual-stakeholder approach to evaluating sustainability contributions within general education curricula and identify the applied economic domain as a priority for curricular reinforcement in alignment with Saudi Vision 2030. The four domains represent a content-based classification of the sustainability areas examined and are not empirically confirmed as independent latent factors; confirmatory validation on an independent sample is the recommended next step. Full article

Much of the discourse around FinTech regulation focuses on whether legal frameworks adequately facilitate private-sector innovation. This article argues that the more consequential and underexamined question is whether enacted frameworks are operationally adequate, sufficiently coherent, specific, and institutionally supported to govern the commercial realities of a mature FinTech sector. Using Saudi Arabia as its primary case, this study applies doctrinal legal analysis and thematic document analysis across six regulatory domains: licensing and sandbox governance, data protection, cybersecurity, consumer protection, Shariah compliance, and cross-border regulatory alignment, benchmarked against standards from the United Kingdom, United States, European Union, and United Arab Emirates. These jurisdictions are treated as sources of regulatory technique rather than as demonstrations of regulatory success. The analysis finds significant implementation gaps across all six domains: formal instruments have been enacted, but the transition pathways, proportionate calibrations, inter-agency coordination, and technology-specific rules necessary for operational adequacy remain underdeveloped. Drawing on Amstad’s regulatory objectives-principles-practices taxonomy, regulatory lifecycle theory, and institutional isomorphism, this study advances six targeted reform recommendations. The study concludes that regulatory maturation in emerging FinTech markets requires a deliberate transition from instrument adoption to implementation depth, from duck typing inherited frameworks to selectively coding the genuinely new governance that algorithmic finance demands. Full article

Machine learning (ML) models trained on bulk-crystal descriptors are increasingly used to prescreen catalysts by predicting adsorption energies, yet reported performances often rely on random K-fold cross-validation that permits the same bulk formula to appear in both training and test sets. We construct a reproducible benchmark that fuses 936 CatApp DFT adsorption energies with bulk descriptors from the Materials Project for H*, O*, and OH* on metal and alloy surfaces. We compare random K-fold cross-validation with GroupKFold grouped by parsed formula, the latter mimicking the realistic task of predicting adsorption on entirely new catalyst compositions. Under formula-grouped evaluation, random CV materially overestimates apparent generalization performance, with the largest and most robust effects for H* and OH* (protocol-inflation gaps up to approximately 0.8). The H* and OH* results are based on only 20 and 31 unique formulas, so their GroupKFold Spearman point estimates should be read as directional evidence rather than quantitative estimates. O* shows a smaller and statistically fragile protocol-inflation signal and, even where composition-plus-bulk features improve Random Forest and Ridge, the usable signal is best described as a very coarse pre-filter within a limited domain. Bulk descriptors are adsorbate-dependent: they improve O* prediction for Random Forest and Ridge, but degrade H* and OH*—a qualitative, directional observation given the small formula counts—whose binding is poorly captured by bulk crystal descriptors, consistent with the established view that it is governed by surface-localized electronic structure. These results outline a realistic performance boundary for bulk-to-surface ML in this benchmark: O* can be very coarsely prioritized from bulk descriptors within a limited domain, whereas H* and OH* are unlikely to be quantitatively predicted from bulk descriptors alone and would benefit from surface-aware models. We therefore recommend that bulk-to-surface adsorption-energy benchmarks report formula-grouped cross-validation alongside random cross-validation as a more robust and transparent practice. Full article

Background/Objectives: Nutrition is an important component of disease prevention and clinical care, yet nutrition training in medical education is often limited and may not adequately prepare future physicians for dietary counselling. Valid assessment tools are therefore needed to identify specific educational gaps and guide curriculum improvement. Unlike general nutrition knowledge instruments, the present questionnaire was specifically developed for medical students and integrates factual nutrition knowledge, applied food composition knowledge, and dietary habits within a multidimensional assessment framework. This study aimed to develop and preliminarily validate a multidimensional questionnaire assessing nutrition knowledge, food composition knowledge, and dietary habits in medical students. Methods: A cross-sectional psychometric validation study with a mixed-methods approach was conducted at the University of Santiago de Compostela, Spain. The instrument was developed by the research team using the revised General Nutrition Knowledge Questionnaire by Kliemann et al. as a conceptual reference and was subsequently adapted to the educational context and expected baseline knowledge of medical students. Face validity was examined through student focus groups, and content validity was established by an expert panel. The initial questionnaire included 61 analyzable items across three domains. Internal consistency was evaluated using Cronbach’s alpha, construct validity by exploratory factor analysis with Promax rotation, and sensitivity analysis was performed to refine the scale. Results: A total of 150 medical students from all six academic years participated (mean age 21.26 years). The initial instrument showed high overall internal consistency with a Cronbach’s alpha = 0.824. After excluding 15 low-performing items, the final 46-item version demonstrated improved reliability (alpha = 0.849). Domain-specific reliability was moderate for general nutrition knowledge (alpha = 0.632) and acceptable for food composition knowledge (alpha = 0.751) and dietary habits (alpha = 0.776). The revised structure produced interpretable components with potential utility for educational diagnosis. Conclusions: The refined questionnaire showed preliminary psychometric validity as a multidimensional assessment tool for medical students. Its potential value lies in providing a framework for future assessment of nutrition-related educational needs rather than in directly producing curricular or behavioral change. Independent multicenter and cross-cultural validation is required before broader use can be recommended. Full article

Sustainable web development focuses on designing web pages that minimize their environmental impact by reducing digital carbon emissions while maintaining optimal website performance and user experience. This study emphasizes the necessity of adopting sustainable web development practices in the Balkan region, highlighting the role of institutional education and web developers in encouraging environmentally responsible web practices within a Technology-Enhanced Education context. A descriptive cross-country analysis was conducted on a total of 8976 websites across five Balkan countries—Albania, Greece, Serbia, Montenegro, and North Macedonia—selected from public domain registries and categorized by sector (education, organization, government, and commercial domains). Data were collected during December 2025. DNS verification was conducted to identify active domains, and hosting sustainability was determined through the Green Web Foundation API. “Green hosting” is operationally defined as hosting that is completely powered by renewable energy sources. Overall, the findings suggest that the prevalence of green hosting in the region is very low, at approximately 27.77%, with substantial variation across sectors. Educational institutions (.edu) and non-profit organizations (.org) have higher adoption rates, while public administrations (.gov) and small commercial websites generally fall behind. The country with the highest percentage of green hosting is Greece (64.07%), while the lowest is Albania, with less than 1%. These findings reveal significant gaps in knowledge and practices among developers and institutions, indicating an urgent need for targeted educational interventions. Crucially, this study connects empirical evidence directly to education. Recognized knowledge gaps guide curriculum development and the design of practical training modules to equip developers and institutional personnel with the skills to adopt sustainable web practices. This research establishes a regional comparative baseline and offers practical recommendations for incorporating sustainability into web development education. The findings endorse strategies and policies aimed at promoting environmentally sustainable digital infrastructure in the Balkan area. Full article

To systematically investigate the effects of C-shaped and rectangular steel frames on the seismic performance of assembled composite shear walls, this paper, based on the validation of existing pseudo-static test results, employs ABAQUS software to establish refined finite element models, and carries out parametric analyses on C-shaped steel-frame composite shear walls (CSCSWs) and rectangular steel-frame composite shear walls (RSCSWs). With shear-span ratio, axial-load ratio, boundary frame steel plate thickness, and concrete strength grade as variables, a total of 28 numerical models are designed to systematically examine the influence laws of each parameter on bearing capacity, ductility, energy dissipation capacity, and failure modes, and to reveal the performance differences in the confinement mechanisms of the two cross-sectional types. The results indicate that: as the shear-span ratio decreases from 3.0 to 1.0, the bearing capacity increases by up to 171%, but the ductility drops by up to 43%, and the failure mode shifts from flexure-dominated to shear-dominated; increasing the steel plate thickness can simultaneously enhance bearing capacity and ductility, with the peak load increasing by up to 52% and cumulative energy dissipation by over 110%, the mechanism being the synergistic enhancement of the flexural contribution of the boundary frame and the passive confinement effect on the core concrete; increasing the axial-load ratio can improve bearing capacity by about 24%, but significantly impairs ductility and energy dissipation capacity, and it is recommended that the design axial-load ratio be controlled between 0.26 and 0.43; the concrete strength grade has a limited effect on bearing capacity, and as the strength increases, brittle characteristics emerge, leading to a ductility decrease of about 12%; therefore, provided that the strength requirements are met, enhancing the concrete strength grade should not be taken as the primary technical approach for improving the seismic performance of such structures. Comparing the two cross-sectional types, the rectangular cross-section, by providing more uniform and effective lateral confinement, exhibits superior bearing capacity, ductility, and energy dissipation to the C-shaped cross-section across the entire parameter domain, and its performance advantages are more pronounced under conditions of high axial-load ratio and large shear-span ratio. Full article

As regulatory requirements increasingly shape automated lending decisions, fairness remains a critical challenge in high-stakes domains, particularly credit scoring. Although artificial intelligence models can achieve strong predictive performance, they may also reproduce biased outcomes that reduce financial inclusion or transfer harm to overlooked protected groups. Existing fairness interventions commonly operate at a single stage of the decision-making pipeline, despite bias often propagating across representational and decision layers. This study proposes iCert-Fair, a two-layer framework for technical fairness assessment and harm recovery in credit scoring. The first layer adopts a fairness-through-explainability paradigm, using SHAP-based explanations to identify direct and proxy dependence on protected attributes and guide structural dataset repair, while the second layer applies targeted threshold-policy adjustments to recover residual harm while preserving decision utility. Experiments on the German and Taiwanese credit datasets show that fairness gains are model- and dataset-specific and may be collective, concentrated, transferred, or recovered unevenly across protected attributes. The direct comparison with representative pre-processing, in-processing, and post-processing methods revealed that baseline methods targeting one protected attribute at a time frequently transferred residual harm to other monitored attributes. In contrast, the fairness-focused recommendations generated by iCert-Fair achieved larger collective fairness improvements across all considered protected attributes while avoiding residual harm. These gains were obtained while preserving predictive utility on the German dataset and with utility degradation remaining below 5% across the evaluated performance metrics on the Taiwanese dataset, alongside consistently lower false-negative risk. The empirical findings support the use of complementary structural and policy-level interventions and demonstrate the importance of jointly evaluating aggregate disparity, worst-case attribute-level harm, cross-attribute transfer, and predictive utility. Full article

To address the problems of complex process knowledge sources, heterogeneous representations, dispersed semantic associations, and limited reusability in the domain of machining distortion of thin-walled parts, this study proposes a knowledge graph construction method for the workpiece machining distortion domain, together with an intelligent decision-making framework driven by the collaboration of knowledge graphs and large language models. First, a domain ontology model is established around core concepts, including workpiece objects, deformation-driving factors, analytical resources, analytical methods, and optimization knowledge, thereby providing a unified semantic foundation for domain knowledge organization. Second, considering the characteristics of domain texts, such as dense technical terminology, ambiguous entity boundaries, and complex relation expressions, a dual-channel knowledge extraction method integrating BERT-BiLSTM-CRF and Universal Information Extraction (UIE) is developed to achieve high-precision extraction of entities and relations from unstructured texts. Knowledge fusion is further carried out through cross-validation, entity disambiguation, coreference resolution, and semantic alignment, and the extracted knowledge is ultimately stored and organized in Neo4j. Furthermore, an intelligent decision-making framework based on the collaboration of knowledge graphs and large language models is constructed. In this framework, a LoRA-tuned Qwen model is employed for user intent recognition and key information extraction, RapidFuzz WRatio is adopted for similar-node retrieval, and local subgraph construction, Label Propagation-based community detection, Betweenness Centrality-based key-node analysis, and evidence fusion are integrated to support process recommendation and intelligent question answering. Based on the proposed framework, an intelligent decision-making system is further developed for process recommendation and intelligent question answering in machining distortion scenarios. Experimental results show that the proposed dual-channel knowledge extraction model achieves an F1-score of 0.88, demonstrating its effectiveness in knowledge acquisition for the machining distortion domain. The constructed knowledge graph contains 4639 entities and 5822 relations, enabling a systematic representation of machining distortion knowledge. Case studies further demonstrate that the proposed method can generate interpretable recommendation results under complex process constraints in real industrial query scenarios. Overall, the proposed approach provides a feasible pathway for the structured organization, intelligent retrieval, and decision support of workpiece machining distortion knowledge. Full article

Background: The relationships of different physical activity domains [e.g., Occupation-related Physical Activity (OPA), Transportation-related Physical Activity (TPA), and Leisure-time Physical Activity (LTPA)] with sleep disorders (SD) remain poorly elucidated. This study investigated the associations of OPA, TPA, and LTPA with SD in American adults. Methods: Data were derived from 25,732 adults with a mean (standard deviation) age of 49.72 (17.53) years (12,692 male and 13,040 female) participating in the 2007–2018 cycles of the National Health and Nutrition Examination Survey (NHANES). The PA domains were assessed using the Global Physical Activity Questionnaire (GPAQ), and adherence to PA recommendations was determined according to the 2018 PA guidelines. SD were identified by self-reported or doctor-diagnosed questionnaire items. Survey-weighted logistic regression models were applied to evaluate the associations between PA domains and SD, and restricted cubic spline (RCS) analyses were conducted to examine potential nonlinear associations. Results: In the fully adjusted model, total PA was not significantly associated with SD (OR 1.01, 95% CI 0.89–1.13, p = 0.912). Regarding specific PA domains, TPA was associated with lower odds of SD (OR 0.79, 95% CI 0.67–0.93, p = 0.006), whereas OPA was associated with higher odds of SD (OR 1.15, 95% CI 1.02–1.30, p = 0.023). No significant association was observed between LTPA and SD (OR 0.96, 95% CI 0.85–1.09, p = 0.511). The multivariable-adjusted RCS analysis further indicated significant nonlinear associations between PA domains and SD (all p for non-linear <0.001). Conclusion: Our findings underscore a prominent “PA paradox” in sleep health among US adults, suggesting that active commuting (TPA) exerts a protective role against SD, whereas OPA serves as a potential behavioral risk factor. Future longitudinal studies and objective PA measurements are needed to validate these cross-sectional associations. Full article

Digital ecosystems, misinformation exposure, mental-health vulnerability and unequal access to care create distinctive challenges for young people. Although youth participation in health governance is increasingly advocated internationally, structured evidence from youth deliberative processes remains limited in Portugal. This study synthesises priorities expressed in two Portuguese deliberative initiatives coordinated by the Sociedade Portuguesa de Literacia em Saúde: the Mini-Assemblies of Health 2022–2023, with particular attention to the 3rd Mini-Assembly on Fighting Health Misinformation, and the Youth Health Choices Forum 2024. Both processes used a structured nominal-group logic to support idea generation, clarification, recording and prioritisation. The analysis used low-inference cross-session thematic aggregation to preserve propositional integrity and remain close to participants’ formulations. Five priority domains were identified: digital health communication and information credibility; curriculum-integrated and peer-mediated health literacy; low-friction mental-health access and stigma reduction; equity and functional service accessibility and governance, accountability and youth participation. Participant quotations are retained, in translated form, to preserve youth voice and to show how recommendations emerged from concrete deliberative formulations. The findings suggest that nominal group technique (NGT)-based youth deliberation can generate operational recommendations for policy and practice, including credibility mechanisms for digital health information, school-based health-literacy integration, autonomy-preserving access routes for mental-health support, and permanent youth participation structures. The findings support recognising young people not only as vulnerable recipients of health information but also as interpreters of digital health ecosystems and contributors to the design of more responsive health governance. Full article

Background: In primary care settings, cervical cancer screening and prevention are highly dependent on healthcare provider initiatives, particularly in countries like Türkiye where the HPV vaccine is not yet integrated into the national routine immunization schedule. Since HPV vaccines provide over 90% protection against cervical cancer, the proactive guidance of primary care providers is critical. This study evaluated family physicians’ knowledge levels and awareness of HPV infection and human papillomavirus (HPV) vaccines in primary care settings in Türkiye. Methods: A total of 238 family physicians working in Türkiye participated in this descriptive cross-sectional study using a convenience sampling method. Data were collected through an online questionnaire administered via Google Forms. The survey included a sociodemographic information form and a 33-item HPV knowledge scale. Data were analyzed using descriptive statistics, normality assessment, chi-square test, Mann–Whitney U test, Kruskal–Wallis test, and hierarchical logistic regression analysis. Results: Overall, 81.1% of participants recommended the HPV vaccine, and 83.6% believed it should be included in the national schedule. Notably, only 15.1% of the participating physicians had received the HPV vaccine themselves, whereas 40.6% of the unvaccinated subgroup (82/202) stated they were considering personal vaccination. HPV knowledge levels were generally high, but lower when regarding the current national program. Vaccine recommenders and female participants had significantly higher knowledge scores, while out-of-pocket vaccine cost emerged as a major barrier to clinical recommendation. In multivariable hierarchical logistic regression, individual knowledge domains did not emerge as independent standalone predictors after controlling for demographics, with only knowledge of the current national program showing a borderline trend (p = 0.066), although the inclusion of the knowledge variables as a collective block significantly improved the overall model explanatory power (p = 0.003). Conclusions: Family physicians in Türkiye showed generally high HPV-related knowledge and a high rate of HPV vaccine recommendation. This study clarifies that primary care advocacy is shaped by the combined influence of professional knowledge and overriding structural factors, rather than individual knowledge domains acting as independent standalone predictors. While future strategies must focus on developing targeted continuous medical education to bridge specific knowledge gaps and optimize opportunistic counseling, achieving optimal immunization coverage ultimately relies on integrating the vaccine into national programs to mitigate out-of-pocket cost barriers. Full article