Search Results (7,878)

Mass-based circularity indicators, such as ISO 59020:2024, quantify material recovery as a share of total throughput but do not account for chemical composition or functional performance, as a consequence of their sector-agnostic design. In copper metallurgical systems, trace tramp elements (e.g., As, Sb, Bi, Fe, Sn, Ni) present in WEEE-derived scrap, anode slimes, and refinery residues can significantly reduce electrical conductivity. Even at nominal purities of ≥99.7 wt.% Cu, conductivity may drop to 85.0–88.0% IACS, as illustrated by selected reported cases—a level of functional degradation that remains undetected by mass-based accounting. Analysis of Grade A cathode standards (EN 1978:2022, LME Cu-CATH-1, ASTM B115-10:2021) shows that impurity limits as low as 2 ppm (Bi) constrain the achievable share of secondary feed in closed-loop recycling. For a specific flash-smelting–refinery configuration, modeling indicates that secondary feed shares above approximately 30% may lead to impurity accumulation beyond the stated specification constraints unless low-impurity primary copper is introduced. This study introduces the Quality-Adjusted Circularity Indicator (QACI), a conceptual, specification-constrained indicator framework that applies a dilution factor f_dil derived from a binary blending mass balance to adjust ISO 59020:2024 inflow-based circularity indicators using a feed-composition blending constraint anchored to Grade A specification limits. The QACI functions as a feed-composition screening indicator operating at the anode blending stage and does not represent a correction of the full electrorefining system. Parametric scenario analysis across six stylized impurity configurations shows that, at identical mass-based circularity (C_mass = 25%), the QACI ranges from 7.1% to 25.0%. This corresponds to a 1.3- to 3.5-fold difference between the mass-based and quality-adjusted indicator values under the stated feed-composition assumptions, illustrating the potential overestimation introduced when feed-quality constraints are not considered. This ratio quantifies the divergence between two indicator values under stylized conditions and should not be interpreted as a directly measured fold-difference in actual loop-closure performance. Positioned within the ISO 59020:2024 Annex C complementary method space, the QACI is positioned as a first-order screening approach of existing circularity metrics that may inform future research discussion of quality-differentiated approaches in EU secondary metals policy. Full article

This study examines how international tourists’ perceptions of environmental, social, and governance (ESG) practices influence their willingness to pay a premium for community-based homestays. Grounded in signaling theory, ESG perception is conceptualized as a credibility signal that reduces perceived uncertainty in community-based accommodation settings. Data were collected from 300 international tourists visiting Mae Kampong Village, Chiang Mai, Thailand, and analyzed using partial least squares structural equation modeling (PLS-SEM). To strengthen predictive assessment, the model was additionally evaluated using PLSpredict, Q²_predict, and the Cross-Validated Predictive Ability Test (CVPAT). The results indicate that ESG perception significantly enhances community sustainability image, trust, and booking intention. Trust partially mediates the relationships between ESG perception and both booking intention and willingness to pay a premium, while booking intention demonstrates the strongest effect on willingness to pay a premium. Community sustainability image does not directly influence booking intention but instead operates indirectly through trust. Environmental concern significantly influences willingness to pay a premium, although its moderating effect is not supported. The findings suggest that tourists in community-based homestay environments rely heavily on trust-based psychological assurance when making accommodation decisions. This study extends ESG tourism research into community-based accommodation contexts and highlights the importance of trust in high-uncertainty tourism environments. The findings also emphasize the importance of transparent ESG communication and trust-building strategies for strengthening sustainable tourism competitiveness. Full article

Despite the growing popularity of digital payment methods and online shopping environments, little is known about the psychological mechanisms through which they affect consumer buying patterns. Drawing on the Stimulus–Organism–Response (SOR) framework, this study introduces the concept of spendception and examines its dual dimensions: perceived spendception ease (PSE) and perceived spendception control (PSC). These dimensions serve as mechanisms linking digital twin environments (DTEs) to impulse buying. Data were collected from 571 Generation Z consumers engaged in social commerce in Shanghai, China. Structural equation modeling (SEM) and machine learning techniques were employed to test the proposed relationships and evaluate predictive validity. The results reveal that DTE significantly increases impulse buying behavior both directly and indirectly through PSE. Specifically, PSE serves as a significant mediator by reducing the psychological friction associated with spending, thereby encouraging impulse buying decisions. In contrast, PSC acts as a significant moderator that weakens the positive relationship between DTE and impulse buying by enhancing consumers’ perceived ability to regulate their spending behavior. These findings demonstrate that spendception operates through two opposing psychological mechanisms: spending facilitation and spending control. This study contributes to the literature by conceptualizing spendception as a distinct transaction-centered construct and by extending the SOR framework through a dual-mechanism explanation of how digital commerce environments simultaneously encourage and restrain impulsive consumption. Full article

Background/Objectives: Effective clinical leadership is a critical driver of healthcare quality, patient safety, and organisational performance. However, evidence on the leadership competencies of healthcare professionals in formal management roles remains fragmented. It is dispersed across professional groups, healthcare contexts, and conceptual frameworks, limiting opportunities for synthesis and cumulative knowledge development. This systematic review examined three questions: how clinical managers perceive their leadership competency; what challenges they encounter in exercising leadership roles; and what development mechanisms the literature identifies. Methods: A systematic review was conducted following PRISMA 2020 guidelines and registered in PROSPERO (CRD420261305279). Four databases were searched: Ovid MEDLINE, CINAHL, EMCARE, and Web of Science from January 2010 to February 2026. Two reviewers independently screened studies; methodological quality was assessed using the Mixed Methods Appraisal Tool (MMAT). Reported competencies were mapped to the five domains of the Clinical Leadership Competency Framework (CLCF) using narrative integrative synthesis. Results: Forty-nine studies were included across quantitative, qualitative, and mixed-methods designs from 24 countries. Competencies in the Working with Others and Demonstrating Personal Qualities domains were reported as strengths across the largest number of included studies. Competencies in Managing Services, Improving Services, and Setting Direction were reported as areas of weakness or developmental need across multiple studies. Leadership challenges included inadequate preparation, role ambiguity, limited authority, and organisational constraints. Development needs spanned formal training, strategic competency building, mentoring, and sustained organisational support. Conclusions: Clinical leadership competency is unevenly distributed across CLCF domains. This pattern reflects not only individual developmental gaps but also the organisational and contextual conditions that shape how leadership is enacted in practice. The findings support a contextual-relational model of clinical leadership. Both individual capability and enabling organisational conditions must be addressed to strengthen leadership effectiveness across healthcare systems. Full article

Spatial data supply chains (SDSCs) transform authoritative observations into widely reused spatial products, but users typically lack machine-actionable provenance describing lineage, processing configurations, and custodianship. We introduce GeoPROV, a domain-specialised provenance model that profiles the W3C PROV framework and aligns with OGC GeoSPARQL to support standards-based representation and querying of spatial provenance. GeoPROV extends the Entity–Activity–Agent pattern with spatially meaningful entity types, explicit supply-chain roles, and first-class configuration artefacts. The model is formalised through a conceptual UML model and implementation-ready physical schema. We instantiate a provenance repository using the Geoscape Administrative Boundaries dataset and evaluate GeoPROV under three SDSC-relevant workloads: bounded upstream lineage traversal, downstream impact analysis, and GeoSPARQL-enabled spatial provenance queries. GeoPROV-based provenance infrastructures provide predictable, scalable performance when applying bounded traversal, index-aware spatial filtering, and validation-before-persistence. Overall, GeoPROV offers a reproducible, interoperable, and operationally viable foundation for spatial provenance, addressing key transparency, trust, and governance requirements in contemporary SDSCs. Full article

Background: While region-based models have informed pain neuroscience, chronic pain is now increasingly conceptualized as a network disorder. This narrative review aimed to critically examine the conceptual evolution of chronic pain models from region-based representations toward large-scale functional network frameworks across adult and pediatric populations while exploring how emerging artificial intelligence (AI)-driven approaches may support future precision pain medicine. Methods: A structured literature search was performed in PubMed, Scopus, and Web of Science, focusing on the scientific output addressing adult and pediatric chronic pain, pain-related neuroplasticity, functional network alterations, neuromodulation, and AI-based applications in pain medicine. Results: The reviewed literature supports a progressive conceptual shift from region-based representations of pain toward network-oriented models involving dysfunctional interactions among the salience, default mode, central executive, and sensorimotor networks. Although emerging evidence suggests developmental network alterations in pediatric chronic pain, current conclusions remain limited by the relative scarcity of longitudinal neuroimaging studies. Emerging AI applications demonstrate promising potential for objective pain assessment, trajectory prediction, and personalized therapeutic decision-making. Conclusions: The transition from the pain matrix to functional network models represents one of the most important conceptual advances in contemporary pain neuroscience. A network-based perspective may accelerate AI-enabled pain biomarkers and individualized interventions. Full article

Background: Large language models and other generative artificial intelligence (AI) tools are increasingly being embedded in digital healthcare services, including mobile health applications, telerehabilitation, remote monitoring, and hybrid care pathways. In this review, digital healthcare refers to technology-mediated healthcare services in which digital platforms, mobile applications, wearables, remote communication, and AI-enabled interfaces support health assessment, self-management, rehabilitation, clinical decision support, or service delivery. When AI-generated exercise guidance moves from general education to individualized recommendations about dose, progression, contraindications, or rehabilitation, it may become directly actionable and safety-relevant. Objectives: This review aimed to clarify when AI-generated exercise guidance in digital healthcare may warrant safety-relevant governance attention and to outline implementation considerations for explainability, human oversight, and service-level governance. It addresses a gap in the literature: general AI-governance and exercise-prescription discussions rarely specify how point-of-use explanations, review thresholds, and escalation safeguards can be organized for directly actionable AI exercise guidance. Methods: We conducted a governance-oriented narrative review of peer-reviewed literature and representative regulatory or guidance documents. This review was not designed as a systematic review, scoping review, or exhaustive evidence map; transparent source mapping was used to support conceptual synthesis. Searches and source mapping focused on generative AI, large language models, explainable AI, clinical decision support, digital health, mobile health, exercise prescription, rehabilitation, trust, automation bias, and human oversight. Sources were included when they informed the safety, explainability, governance, or real-world implementation of patient-facing AI-generated exercise guidance. Extracted material was grouped by evidentiary role and synthesized through framework synthesis and governance mapping to distinguish literature-supported observations, author interpretation, and proposed implementation tools. Results: The included sources were first organized into five thematic groups: digital exercise delivery and exercise-prescription evidence; explainability, trust, and automation bias literature; professional responsibility, ethics, and patient disclosure literature; regulatory and policy documents; and digital literacy, patient/clinician attitudes, and equity literature. The synthesis then proceeded from safety relevance to explanation needs, human oversight and escalation needs, and selected regulatory and policy signals before translating these strands into conceptual and implementation-oriented outputs rather than empirically validated instruments. AI-generated exercise guidance was most safety-relevant in scenarios involving individualized dose, progression, contraindication-sensitive action, or rehabilitation strategy. Across the included sources, generic transparency alone was not sufficient to support reviewable use; relevant explanation elements included evidence sources, risk warnings, reasoning paths, and reasonable alternatives. Oversight considerations varied with embodied risk, clinical ambiguity, user vulnerability, and likelihood of direct enactment. Implementation considerations linked interface design, clinical review, escalation, auditability, and post-deployment monitoring. Conclusions: AI-generated exercise guidance in digital healthcare may warrant governance attention as a patient-safety and accountability issue when it influences actionable exercise decisions. The proposed framework offers a conceptual basis for designing more reviewable and accountable mobile and remote exercise-support services. Future work can validate these outputs in patient-facing services, clinician review workflows, usability studies, implementation pilots, and safety evaluations. Full article

Pedestrian safety at signalized intersections is a key component of sustainable urban mobility, as safer walking environments support active transportation, reduce crash risk, and improve the inclusiveness of urban transport systems. This study presents a structured review of pedestrian–vehicle conflicts based on a systematic PRISMA-guided literature search, synthesizing 60 studies with emphasis on operational conditions, behavioral factors, infrastructural characteristics, and surrogate safety measures. The review examines the application of surrogate safety measures (SSMs), including Time-to-Collision (TTC), Post-Encroachment Time (PET), Pedestrian Path Deviation (PPD), and Deceleration-to-Safety Time (DST). The findings reveal significant variability in threshold definitions and methodological approaches, which limits the comparability and transferability of results across different traffic contexts. Building on this synthesis, the paper proposes an integrated conceptual framework linking behavioral, operational, and infrastructural determinants to conflict occurrence and severity. The analysis shows that existing studies often treat these factors in isolation, reducing the generalizability of current models. Overall, this review identifies key methodological inconsistencies in surrogate safety indicators and emphasizes the need for standardized yet context-sensitive thresholds and locally validated conflict models to improve the comparability and transferability of pedestrian–vehicle conflict assessments. Full article

Lymphoid neoplasms such as multiple myeloma (MM), indolent non-Hodgkin lymphoma, and chronic lymphocytic leukemia are increasingly managed as chronic, relapsing conditions characterized by prolonged surveillance, repeated treatment transitions, and cumulative self-management demands. These trajectories expose patients and caregivers to persistent illness uncertainty, fluctuating fear of progression, symptom and comorbidity burden, communication challenges, and treatment-related workload. This theory-informed framework development paper uses an overview of selected psycho-oncological, hematological, nursing, theoretical, and patient-reported outcome literature to propose the LUMINA framework: Longitudinal illness trajectory, Uncertainty fields, Multidimensional symptom and comorbidity load, Information and interaction context, Navigation work and self-management load, and Adaptive outcomes and alignment. LUMINA is intended as a hypothesis-generating conceptual structure to organize clinically relevant domains, clarify potential relationships among uncertainty, symptom burden, communication, navigation work, and adaptive outcomes, and guide future assessment, validation, and intervention research in chronic lymphoid neoplasms. The framework builds on prior theories of illness uncertainty, treatment burden, workload–capacity balance, fear of recurrence/progression, and lymphoma-specific qualitative work on uncertainty management and psychosocial adaptation. Potential research applications include structured assessment, shared decision-making research, and domain-matched supportive-care concepts; however, these applications remain theoretical and require empirical testing. Future studies should evaluate feasibility, acceptability, construct validity, domain overlap, predictive validity beyond quality of life, and the clinical utility of LUMINA-informed research profiles. Until such validation is available, LUMINA should be interpreted as a conceptual model rather than a validated clinical tool or care pathway. Full article

Background and Objectives: Artificial intelligence (AI) is increasingly integrated into healthcare management and pharmaceutical marketing workflows, yet determinants of AI adoption intention among non-clinical professionals remain under-studied in Central and Eastern Europe. This cross-sectional study quantified AI adoption intention (AAI) across three professional groups and examined its organizational, cognitive, attitudinal, and regulatory correlates. Methods: We surveyed 127 Romanian professionals (43 hospital administrators, 42 pharmaceutical marketing professionals, 42 community pharmacy managers) using a 46-item structured instrument. The instrument combined items adapted from UTAUT/TAM and organizational-readiness measures with study-specific AI-marketing, AI-literacy, and regulatory-literacy items; Analyses included ANOVA with Tukey HSD, Spearman correlations, age-adjusted OLS regression with HC3 robust standard errors, bootstrap indirect-effect analysis, moderation, exploratory k-means clustering, and exploratory logistic/ROC analysis. Results: AAI differed across groups: pharmaceutical marketing 4.33 ± 0.50, hospital administrators 3.39 ± 0.47, and pharmacy managers 2.88 ± 0.54; all pairwise Tukey contrasts p < 0.001. In the multivariable model (R² = 0.833)—interpreted cautiously because conceptually related adoption constructs may overlap despite acceptable collinearity diagnostics—perceived usefulness, organizational readiness, and perceived ease of use were the strongest associated factors, while data governance concern was the main negative correlate. Perceived usefulness statistically accounted for 61.7% of the AI literacy–AAI indirect association, and regulatory literacy moderated the AI literacy–AAI association. An exploratory age-adjusted logistic model showed high within-sample discrimination for top-tertile AAI but should be interpreted as convergent validity among survey constructs rather than as a validated screening tool. Conclusions: AI adoption intention in Romanian medical management and pharmaceutical marketing is associated mainly with perceived usefulness and organizational readiness, tempered by data governance concern and regulatory knowledge. Longitudinal, multi-site, real-world implementation studies with external validation are needed. Full article

Background: The oral squamous cell carcinoma (OSCC) is a very aggressive cancer that is the product of tumor cell interactions with the microenvironment. The tumor microenvironment (TME) has a severe impact on OSCC progression, metastasis, and resistance to treatment by altering gene expression via various cellular and molecular signal transductions. Aim: This review systematizes the information on gene regulation in the OSCC TME (cellular components, signaling pathways that regulate tumor progression and resistance). Methods: We used PRISMA guidelines to search PubMed, Scopus, Web of Science, and Google Scholar (up to April 2025) with OSCC studies addressing the subject of gene regulation and tumor microenvironment. The quality of human or experimental models was evaluated using the Newcastle–Ottawa Scale and the qualitative synthesis was performed because of heterogeneity. Results: The significant regulatory functions of tumor-associated macrophages, cancer-associated fibroblasts, immune cells, and non-coding RNAs were found, especially in the pathways like JAK/STAT, EGFR, Wnt/ -β catenin, and PI3K/AKT/mTOR. Conclusions: The conceptualization of gene regulatory networks in the OSCC TME identifies the emerging biomarkers and targets of therapy. Merging multimodal omics and single-cell studies can further contribute to the precision strategies to enhance the outcomes of OSCC. Full article

Higher construction costs (CCs) linked to carbon reduction methods have hindered the adoption of low-carbon approaches in the built environment. The simultaneous minimisation of upfront embodied carbon (EC) and CCs has not received much attention in building design optimisation (BDO) research; most studies prioritise operational energy, operational carbon, and operational cost reduction. This paper develops an integrated conceptual framework for low-carbon, cost-effective BDO, particularly targeting upfront EC and CCs, to fill this research gap and meet industry demands. A systematic literature review was conducted following PRISMA guidelines, synthesising 41 peer-reviewed articles published between 2015 and 2026. Thematic and content analyses were employed to extract and categorise key methodological components, including optimisation problem characterisation, objective-driven design variable selection, constraint modelling, algorithm selection, and evaluation and validation approaches. Subsequently, the developed conceptual framework was validated through semi-structured expert interviews with participants comprising BDO researchers and building designers in the construction field. A cross-mapping of optimisation objectives, optimised parameters, and design variables was developed to clarify their interrelationships, alongside structured criteria for optimisation algorithm selection. Based on these insights, a conceptual framework named “ICCO-BD (Integrated Upfront Carbon and Construction Cost Optimisation for Building Design) framework” is proposed and validated, integrating problem formulation, parametric modelling, multi-objective optimisation, and systematic Pareto-based evaluation into a coherent end-to-end workflow, enabling improved time efficiency through reduced redesign iterations, enhanced solution quality via better pareto front exploration, and more robust decision-making through clearer trade-off interpretation. While expert feedback indicated strong conceptual relevance and practical applicability, the framework remains conceptual in nature and requires further empirical verification through real-world case studies and optimisation applications before broader industry implementation. Full article

Soccer is a complex sport with significant physical, physiological, psychological, technical, and tactical demands on players. This review presents an ergonomics-based model of soccer performance, emphasizing that no single component operates in isolation. Building on the foundational ergonomic framework, this review integrates contemporary evidence on training load monitoring, ecological dynamics, and cognitive-perceptual performance dimensions not systematically addressed in prior frameworks. Elite outfield players cover 9–14 km·h⁻¹ per match, with high-speed running (19.8–24.8 km·h⁻¹) making up about 20% of total distance and sprinting (>25 km·h⁻¹) around 2%. These outputs vary by playing position, tactical formation, possession dynamics, and environmental conditions. Longitudinal data from the English Premier League indicate a 35% increase in high-speed running over the past decade, suggesting intensifying physical demands. Physiological responses, including average heart rates of 156–175 bpm, reflect the aerobic and anaerobic demands on players. The review also examines benchmarks like VO₂max, sprint velocity, and anthropometry, highlighting their utility and limitations as performance indicators. Regarding training load management, the review evaluates frameworks such as the Acute:Chronic ratio and high-speed running exposure protocols, noting limitations and risks of over-relying on external load metrics. Periodization approaches, including tactical periodization, are discussed for integrating physical, technical, tactical, and psychological components in training. The proposed ergonomic model conceptualizes elite soccer performance as an emergent property of interacting physical, physiological, tactical, psychological, and environmental subsystems, with direct implications for training design, selection, and load management. Selection decisions should consider cognitive and perceptual competencies like decision-making, anticipation, and situational awareness, alongside physical and physiological profiles, aligned with the team’s game model. Full article

Faculty governance in higher education depends on transparent participation, reliable quorum enforcement, accountable record keeping, and strict alignment with institutional regulations. Conventional departmental council processes provide formal authority and academic deliberation, but they often rely on manual documentation, fragmented records, and procedural enforcement that is difficult to verify after the fact. This work presents an integrated hybrid Decentralized Autonomous Organization (DAO) framework for faculty governance that combines regulatory alignment analysis, a working smart-contract prototype, and scenario-based simulation. The framework is designed for university departmental councils and is structured across three layers: off-chain community governance, on-chain protocol governance, and off-chain execution governance. It expands prior conceptual work by incorporating governance dimensions related to roles, incentives, membership, communication, decision-making, identity, auditability, conflict-of-interest handling, and institutional ratification. The evaluation simulates 1488 proposals across twelve scenarios covering four faculty sizes (15, 30, 50, and 100 members) and three adoption levels (low, moderate, and high). Scenario results indicate that adoption intensity is the dominant driver of governance performance: mean participation increases from about 33% under low usage to about 85% under high usage, quorum achievement rises from about 6% to about 96%, and execution rises from about 19% to about 70%. Relative to a modeled conventional workflow baseline, the DAO-supported process reduces decision-cycle time by about 76%, improves audit completeness by about 30%, and increases traceability from about 0.63 to 1.00. The results indicate that DAO-assisted faculty governance can strengthen transparency, procedural consistency, and auditability while preserving legally mandated university authority, but its practical value depends on sustained participation, privacy safeguards, cost control, and clearly defined hybrid control points. Full article

Understanding advanced pre-tertiary mathematics, particularly three-dimensional vectors, demands robust spatial reasoning skills that many students find challenging to develop through traditional pedagogical methods. This study proposes and evaluates an innovative educational tool that leverages large vision models to automate the conversion of handwritten vector equations into accurate 3D graphical representations. By interpreting students’ handwritten input using advanced computer vision, the system provides immediate, interactive visual feedback to bridge the cognitive gap between abstract symbolic notation and tangible geometric concepts. We evaluated the system using a dataset of 1000 handwritten vector equations typical of the Singapore-Cambridge GCE ‘A’ Level H2 Mathematics syllabus. Our findings demonstrate that while GPT-4o serves as a capable baseline, achieving 84.6% accuracy with multi-shot prompting, newer variants such as GPT-4.1-mini offer superior performance, reaching 91.4% accuracy with significantly higher computational efficiency. The results confirm that AI-powered visualisation tools can effectively interpret complex spatial mathematical layouts when guided by optimal prompt engineering. Implementing such technology in educational settings presents a viable, scalable, and cost-effective method to democratise learning support, fostering independent study and enhancing students’ conceptual comprehension of spatial mathematics. Full article