Search Results (2,042)

Background/Objectives: Smartphone-based leisure reservation platforms increasingly shape how individuals participate in leisure, yet little is known about how such technology-mediated engagement influences users’ awareness of multidimensional health benefits. The purpose of this study is to investigate how regular users of smartphone-based leisure reservation platforms perceive multidimensional health benefits associated with their leisure activities. Methods: Based on a constructivist/interpretivist approach, this study applied Interpretative Phenomenological Analysis (IPA). Ten participants with at least one year of platform use completed semi-structured interviews. Data were analyzed through iterative coding and theme development, with trustworthiness ensured through member checking, peer debriefing, and triangulation. Results: Participants reported three dimensions of health awareness. (1) App-enabled accessibility as a catalyst for physical health awareness (i.e., physical health benefits) included improved vitality and increased motivation to maintain exercise routines. (2) App-based planning and anticipation in supporting mental well-being (i.e., mental health benefits) involved stress reduction, emotional recovery, enjoyment, and heightened self-care awareness. (3) Platform-mediated social encounters and the construction of social health (i.e., social health benefits) reflected expanded social networks, strengthened interpersonal relationships, and a greater sense of belonging fostered through shared leisure experiences. Conclusions: Smartphone-based leisure platforms play a meaningful role in enhancing users’ awareness of multidimensional health benefits. By improving accessibility, diversifying leisure options, and facilitating social interaction, these platforms support holistic well-being. The findings contribute to understanding technology-mediated leisure and offer practical implications for designing digital leisure services that promote physical, mental, and social health. Full article

This study investigates the determinants of turnover intention among real estate sales professionals in Lebanon and the United Arab Emirates (UAE), two markets that represent contrasting economic realities within the MENA region. Drawing on Herzberg’s Two-Factor Theory, Vroom’s Expectancy Theory, and March and Simon’s Push-Pull Model, this study adopts a multidimensional framework to assess the effects of compensation, job stress, career growth opportunities, and work–life balance on employee retention. A quantitative method was employed using a structured questionnaire administered to 832 respondents (425 in the UAE and 407 in Lebanon), and data were analyzed using Structural Equation Modeling. The results reveal that job stress is the most influential predictor of turnover intention, particularly in Lebanon, followed by work–life balance, compensation, and career growth opportunities. These findings underscore the importance of psychological well-being and structural incentives in talent retention. By offering empirical evidence from an underexplored regional labor market, the study contributes to the global turnover discourse and provides comparative insights into the labor dynamics of both a crisis-prone and a high-growth economy. The results carry significant practical implications for HR managers, firm owners, and policymakers, highlighting the necessity of adopting holistic and context-sensitive retention strategies that extend beyond financial rewards to include flexible work arrangements, career development frameworks, and supportive workplace cultures. Full article

CeO₂ doping is a well-established strategy for enhancing the properties of zirconia (ZrO₂) ceramics, with the prior literature indicating an optimal doping range of around 10–15 wt.% for specific attributes. Building upon this foundation, this study provides a systematic investigation into the concurrent evolution of mechanical, tribological, and thermophysical properties across a broad compositional spectrum (0–20 wt.% CeO₂). The primary novelty lies in the holistic correlation of these often separately examined properties, revealing their interdependent trade-offs governed by microstructural development. The 15Ce-ZrO₂ composition, consistent with the established optimal range, achieved a synergistic balance: hardness increased by 27.6% to 310 HV₁, the friction coefficient was minimized to 0.205, and the wear rate was reduced to 1.81 × 10⁻³ mm³/(N m). Thermally, it exhibited a 72.2% reduction in the thermal expansion coefficient magnitude at 1200 °C and a low thermal conductivity of 0.612 W/(m·K). The enhancement mechanisms are consistent with solid solution strengthening, grain refinement, and likely enhanced phonon scattering, potentially from point defects such as oxygen vacancies commonly associated with aliovalent doping in oxide ceramics, while performance degradation beyond 15 wt.% is linked to CeO₂ agglomeration and duplex microstructure formation. This work provides a relatively comprehensive insight into the dataset and mechanism, which is conducive to the fine design of multifunctional ZrO₂ bulk ceramics. It is not limited to determining the optimal doping level, but also aims to clarify the comprehensive performance map, providing reference significance for the development of advanced ceramic materials with synergistically optimized hardness, wear resistance, and thermal properties. Full article

Type 2 diabetes mellitus (T2DM) is a multifaceted metabolic disorder marked by impaired insulin action, pancreatic β-cell dysfunction, and the involvement of several interconnected mechanisms, including inflammation, oxidative stress, and epigenetic alterations. Despite progress in conventional therapies, achieving durable glycemic control and minimizing complications remain major challenges. This review discusses the emerging role of bioactive phytochemicals—such as curcumin, berberine, resveratrol, flavonoids, and polysaccharides—in modulating essential molecular pathways including AMPK, PI3K/AKT, and cAMP/PKA, which contribute to enhanced insulin sensitivity, glucose regulation, and β-cell protection. These natural compounds also influence gut microbiota modulation and epigenetic mechanisms, offering additional metabolic and anti-inflammatory benefits. This review synthesizes evidence from peer-reviewed studies published between 2000 and 2024, incorporating bibliometric trends showing an increasing research focus on phytochemicals for T2DM management. However, limitations such as low solubility, instability, and poor absorption restrict their clinical application. Advances in nanotechnology-based delivery systems, including nanoparticles, liposomes, and nanoemulsions, have shown potential to overcome these barriers by improving stability, bioavailability, and targeted delivery of phytochemicals. The integration of gut microbiota modulation with nanocarrier-enabled phytochemical therapy supports a precision medicine approach for managing T2DM. Preliminary clinical evidence highlights significant improvements in glycemic control and inflammatory status, yet further large-scale, well-controlled trials are essential to ensure safety, optimize dosages, and standardize combination regimens. Overall, phytochemical therapies, reinforced by nanotechnology and microbiota modulation, present a promising, safe, and holistic strategy for T2DM management. Continued interdisciplinary research and clinical validation are crucial for translating these advances into effective therapeutic applications and reducing the global diabetes burden. Full article

Amid escalating ecological degradation, social fragmentation, and rising mental health challenges—especially in rural and agricultural communities—there is an urgent need to reimagine systems that support both planetary and human flourishing. This viewpoint examines an emerging paradigm in agriculture that emphasizes the role of farmers’ inner development in fostering practices that enhance ecological health, community well-being, and a resilient food system. A key goal is to draw more academic attention to growing community calls for more holistic, relational, and spiritually grounded approaches to food systems as an important focus for ongoing research. Drawing on diverse case studies from Japan, India, and Europe, we examine how small-scale and natural farming initiatives are integrating inner development, universal human values, and ecological consciousness. These case studies were developed and/or refined through a program led by the Conscious Food Systems Alliance (CoFSA), an initiative of the United Nations Development Programme (UNDP) that seeks to integrate inner transformation with sustainable food systems change. The initiatives are intended as illustrative examples of how agriculture can transcend its conventional, anthropocentric role as a food production system to become a site for cultivating deeper self-awareness, spiritual connection, and regenerative relationships with nature. Participants in these cases reported significant shifts in mindset—from materialistic and extractive worldviews to more relational and value-driven orientations rooted in care, cooperation, and sustainability. Core practices such as mindfulness, experiential learning, and spiritual ecology helped reframe farming as a holistic process that nurtures both land and life. These exploratory case studies suggest that when farmers are supported in aligning with inner values and natural systems, they become empowered as agents of systemic change. By linking personal growth with planetary stewardship, these models offer pathways toward more integrated, life-affirming approaches to agriculture and future academic research. Full article

The present literature review identifies substantial research and applied potential in the combined utilization of internationally recognized information security standards, Bayesian networks, and AI-based assistants to enhance cyber resilience in Unmanned Aerial Systems (UAS) operations within the specific category defined by the SORA (Specific Operations Risk Assessment) methodology. The analysis reveals that while the existing literature individually addresses key components such as ISO/IEC 27001, NIST SP 800-53, MITRE ATT&CK, Bayesian models, and AI techniques, integrated methodologies that unify these elements into a comprehensive and operationally applicable framework are lacking. Particularly underrepresented is the connection to the Cyber Safety Extension of SORA, as well as the synergistic application of quantitative analysis and automation through intelligent systems. The review concludes that a systematic effort is required to develop a holistic framework that reflects the dynamic regulatory demands, operational environments, and contemporary threats facing drone technologies. Full article

Computer vision and deep learning are essential in diverse fields such as autonomous driving, medical imaging, face recognition, and object detection. However, enhancing low-light remote sensing images remains challenging for both research and real-world applications. Low illumination degrades image quality due to sensor limitations and environmental factors, weakening visual fidelity and reducing performance in vision tasks. Common issues such as insufficient lighting, backlighting, and limited exposure create low contrast, heavy shadows, and poor visibility, particularly at night. We propose QWR-Dec-Net, a quaternion-based Retinex decomposition network tailored for low-light image enhancement. QWR-Dec-Net consists of two key modules: a decomposition module that separates illumination and reflectance, and a denoising module that fuses a quaternion holistic color representation with wavelet multi-frequency information. This structure jointly improves color constancy and noise suppression. Experiments on low-light remote sensing datasets (LSCIDMR and UCMerced) show that QWR-Dec-Net outperforms current methods in PSNR, SSIM, LPIPS, and classification accuracy. The model’s accurate illumination estimation and stable reflectance make it well-suited for remote sensing tasks such as object detection, video surveillance, precision agriculture, and autonomous navigation. Full article

This comprehensive review synthesizes current advances and persistent challenges in integrating worker safety and food safety through human-robot collaboration (HRC) in poultry processing. Rapid industry expansion and rising consumer demand for ready-to-eat poultry products have heightened occupational risks and foodborne contamination concerns, necessitating holistic safety strategies. The review examines ergonomic, microbiological, and regulatory risks specific to poultry lines, and maps how state-of-the-art collaborative robots (“cobots”)—including power and force-limiting arms, adaptive soft grippers, machine vision, and biosensor integration—can support safer, more hygienic, and more productive operations. The authors analyze technical scientific literature (2018–2025) and real-world case studies, highlighting how automation (e.g., vision-guided deboning and intelligent sanitation) can reduce repetitive strain injuries, lower contamination rates, and improve production consistency. The review also addresses the psychological and sociocultural dimensions that affect workforce acceptance, as well as economic and regulatory barriers to adoption, particularly in small- and mid-sized plants. Key research gaps include gripper adaptability, validation of food safety outcomes in mixed human-cobot workflows, and the need for deeper workforce retraining and feedback mechanisms. The authors propose a multidisciplinary roadmap: harmonizing ergonomic, safety, and hygiene standards; developing adaptive food-grade robotic end-effectors; fostering explainable AI for process transparency; and advancing workforce education programs. Ultimately, successful HRC deployment in poultry processing will depend on continuous collaboration among industry, researchers, and regulatory authorities to ensure both safety and competitiveness in a rapidly evolving global food system. Full article

Digital technologies have become increasingly crucial during and, after the COVID-19 pandemic, have sparked significant scientific interest around their impact on sustainable well-being. Despite extensive research, conclusive evidence on whether digital technologies enhance or undermine sustainable well-being remains elusive. Saudi Arabia has made significant progress in its technological infrastructure, but comprehending the implications of this progress still poses a challenge. Drawing on the prior literature and grounded in the theoretical perspective of the Capability Approach, this study proposes five dimensions of digital inclusion (accessibility, usability, digital skills, affordability, and connectivity) and examines their collective influence on students’ sustainable well-being, specifically happiness and life satisfaction. This study employs a cross-sectional design, with data collected from 238 university students in Saudi Arabia using convenience sampling. Ten hypotheses were tested using partial least squares structural equation modeling in SmartPLS-4. This study supports the conceptualization of digital inclusion as a multidimensional construct comprising five key dimensions. The results indicate that affordability, usability, connectivity, and digital skills have a substantial impact on happiness, whereas accessibility, usability, connectivity, and digital skills have a considerable effect on life satisfaction. Nonetheless, the correlations between accessibility and happiness, as well as between affordability and life satisfaction, were not found to be supported. This implies that these dimensions might have different effects on the affective and cognitive aspects of sustainable well-being. These results suggest that digital inclusion may play a role in shaping individuals’ interactions with technology and their perceived sustainable well-being. This study proposes and evaluates a strategic framework that may guide efforts to promote digital inclusion and support sustainable well-being among university students. It provides valuable insights for policymakers, educational institutions, and industry stakeholders seeking to enhance digital access and capabilities. The findings highlight the potential value of developing strategies that address students’ digital needs as part of a holistic approach to sustainable well-being. The findings also highlight the importance of viewing digital inclusion as an interconnected framework, rather than as a set of discrete, unrelated factors. By demonstrating how digital inclusion promotes sustainable well-being, this study contributes to the broader sustainability agenda by highlighting digital equity as an essential component of socially sustainable development in the Saudi context. Full article

The paper introduces ‘transformative’ curriculum initiatives such as education for sustainable development (ESD) and global citizenship education (GCED), which address ‘macro’ challenges such as climate change, together with ‘holistic’ approaches to student learning such as ‘social and emotional learning’ (SEL) and education for ‘life skills’, ‘21st century skills’, ‘transversal competencies’, AI-related ethics, and ‘health and well-being.’ These are reflected in Section 6 of the 2023 UNESCO Recommendation on Education for Peace, Human Rights and Sustainable Development. It is suggested that such broad goals put forward at global policy level may serve as inspiration for national context-specific programming, while also needing better integration of national insights and cultural differences into global discourse. The paper aims to provide insights to education policy-makers responsible for national curriculum, textbooks and other learning resources, teacher training and examination processes, helping them to promote the human values, integrity and sense of agency needed by students in a time of multiple global and personal challenges. This requires an innovative approach to curricula for established school subjects and can be included in curricula being developed for AI literacy and related ethics. Research into the integration of transformative and holistic dimensions into curricula, materials, teacher preparation, and assessment is needed, as well as ongoing monitoring and feedback. AI-supported networking and resource sharing at local, national and international level can support implementation of transformative and holistic learning, to maintain and strengthen the human dimensions of learning. Full article

Artificial intelligence (AI) is increasingly regarded as a transformative enabler of sustainable logistics and supply chain management, particularly in the context of global energy transition and decarbonization efforts. This study provides a comprehensive conceptual and exploratory assessment of the multidimensional role of AI, highlighting both its potential to enhance energy efficiency and reduce greenhouse gas emissions, as well as its inherent environmental costs associated with digital infrastructures such as data centers. The findings reveal the dual character of digitalization: while predictive algorithms and digital twin applications facilitate demand forecasting, process optimization, and real-time adaptation to market fluctuations, they simultaneously generate additional energy demand that must be offset through renewable energy integration and intelligent energy balancing. The analysis underscores that the effectiveness of AI deployment cannot be captured solely through economic metrics but requires a holistic evaluation framework that incorporates environmental and social dimensions. Moreover, regional disparities are identified, with advanced economies accelerating AI-driven green transformations under regulatory and societal pressures, while developing economies face constraints linked to infrastructure gaps and investment limitations. The analysis emphasizes that AI-driven predictive models and digital twin applications are not only tools for energy optimization but also mechanisms that enhance systemic resilience by enabling risk anticipation, adaptive resource allocation, and continuity of operations in volatile environment. The contribution of this study lies in situating AI within the digital–green synergy discourse, demonstrating that its role in logistics decarbonization is conditional upon integrated energy–climate strategies, organizational change, and workforce reskilling. By synthesizing emerging evidence, this article provides actionable insights for policymakers, managers, and scholars, and calls for more rigorous empirical research across sectors, regions, and time horizons to verify the long-term sustainability impacts of AI-enabled solutions in supply chains. Full article

Mastectomy, while a life-saving intervention for breast cancer, often leads to profound psychological and emotional challenges for affected women. Feelings of loss altered body image, and anxiety about recurrence can significantly impact mental well-being. This study aimed to explore and describe the experiences of women after mastectomy at Mankweng Tertiary Hospital in Limpopo Province, South Africa. In this study, a qualitative phenomenological design was used. Data were collected through semi-structured in-depth interviews with women who had undergone mastectomy. Fifteen participants were purposively sampled, and thematic analysis was used to identify key patterns and meanings in their narratives. The findings revealed that the participants initially described feelings of being ‘disabled’, incomplete, and anxious about cancer recurrence or their ability to perform maternal functions such as breastfeeding. However, over time, many developed resilience and acceptance, seeing surgery as a life-saving measure and an opportunity for renewal. The adjustment of women after mastectomy is a complicated emotional transition from crisis and loss to adjustment and empowerment. The results identify the need for holistic psychosocial support that combines counseling, peer networks, and education for their family members addressing their emotional healing, body image, and social reintegration. Full article

The global population aged 65 and older is expected to double from 761 million in 2021 to 1.6 billion by 2050. Despite often being treated separately in clinical practice and policy, oral health and mental health are fundamentally interconnected in older adulthood, forming a bidirectional relationship that exacerbates disability, social inequity, and systemic healthcare challenges. This narrative review aims to summarize the two-way relationship between mental and oral health and emphasize their combined impact on systemic health, social engagement, and independence among ageing populations. The bidirectional relationship has profound clinical significance. Untreated oral diseases induce chronic pain and cause social embarrassment, aggravating pre-existing depression and anxiety. Periodontal disease can worsen systemic conditions such as diabetes, cardiovascular disease, and dementia via a shared inflammatory pathway. Conversely, mental health issues—including depression, anxiety, cognitive decline, and the use of psychotropic medications—reduce motivation for oral care, prompt dental neglect, and affect salivary function, deteriorating oral health. Despite clear connections, systemic gaps persist, including fragmented healthcare systems, financial barriers, stigma, lack of awareness, and caregiver burnout. To address these challenges, strategies such as developing integrated care models to unify dental and mental health services, reforming policies to prioritize oral and mental health parity, advocating anti-stigma campaigns to clear the misconceptions, and implementing community-based healthcare programmes to reach underserved older adults are essential. By recognizing oral health as a vital component of mental resilience, societies can transform ageing into an era of empowered well-being, where the mouth–mind connection promotes holistic health rather than functional decline. Full article

Background/Objectives: This cross-sectional study examined how training age, chronological age, and biological maturity influence motor and perceptual–cognitive performance in youth soccer players, with relevance for health and well-being through sport participation. Methods: Forty-one male athletes (age = 14.86 ± 0.81 years) completed a two-day field-based assessment following a holistic framework integrating motor (sprinting, jumping, and agility) and perceptual–cognitive components (psychomotor speed, visuospatial working memory, and spatial visualization). Biological maturity was estimated using the maturity offset method. Results: Regression analyses showed that biological maturity and training age significantly predicted motor performance, particularly sprinting, jumping, and pre-planned agility, whereas chronological age was not a predictor. In contrast, neither maturity nor training experience influenced perceptual–cognitive skills. Among cognitive measures, only psychomotor speed significantly predicted reactive agility, emphasizing the role of rapid information processing in dynamic, game-specific contexts. Conclusions: Youth soccer training should address both physical and cognitive development through complementary strategies. Physical preparation should be tailored to maturity status to ensure safe and progressive loading, while systematic training of psychomotor speed and decision-making should enhance reactive agility and game intelligence. Integrating maturity and perceptual–cognitive assessments may support individualized development, improved performance, and long-term well-being. Full article

Road safety ranks among the most apparent concerns in present-day urban existence, with risky driving the most prevalent cause of road crashes. In this paper, we present an external camera video-based automatic hazardous driving behavior detection model for use in smart cities. We addressed the problem with a holistic approach covering data collection to hazardous driving behavior classification including zig-zag driving, risky overtaking, and speeding over a pedestrian crossing. Our strategy employs a specially generated dataset with diverse driving situations under diverse traffic conditions and luminosities. We advocate for a Multi-Speed Transformer model with dual vehicle trajectory data timescale operation to capture near-future actions in the context of extended driving trends. A new contribution lies in our symbiotic system which, apart from the detection of unsafe driving, also assumes the responsibility of triggering countermeasures through a real-time continuous loop with vehicle systems. Empirical results demonstrate the Multi-Speed Transformer’s performance with 97.5% in accuracy and 93% in F1-score over our balanced corpus, surpassing comparison baselines including Temporal Convolutional Networks and Random Forest classifiers by significant amounts. The performance is boosted to 98.7% in accuracy as well as 95.5% in F1-score with the symbiotic framework. They confirm the promise of leading-edge neural architectures paired with symbiotic systems in enhancing road safety in smart cities. The ability of the system to provide real-time risky driving behavior detection with mitigation offers a real-world solution for the prevention of accidents while not restricting driver autonomy, a balance between automatic intervention, and passive monitoring. Empirical evidence on the TRAF-derived corpus, which includes 18 videos and 414 labelled trajectory segments, indicates that the Multi-Speed Transformer reaches an accuracy of 97.5% and an F1-score of 93% under the balanced-training protocol, and in this configuration it consistently surpasses the considered baselines when we use the same data splits and the same evaluation metrics. Full article