Search Results (44,492)

Background: Fasting plasma glucose, glycated hemoglobin (HbA1c), and oral glucose tolerance testing remain central to the diagnosis and monitoring of dysglycemia, but they mainly reflect the average glycemic exposure or discrete time-point measurements and may not capture intraday and interday glucose fluctuations. Glycemic variability (GV) has been associated with oxidative stress, endothelial dysfunction, inflammation, and diabetes-related complications, although much of the evidence derives from experimental, clinical, and diabetes-care settings rather than occupational cohorts. Aim: This narrative review examines the physiological basis, measurement, and potential occupational relevance of GV and continuous glucose monitoring (CGM) in working populations. Methods: Literature was narratively selected from biomedical databases, major guidelines, consensus statements, and occupational-health sources, prioritizing reviews, clinical guidelines, cohort studies, mechanistic studies, and CGM studies. No systematic search, risk-of-bias assessment, or quantitative synthesis was performed. Main findings: CGM is an established technology in selected diabetes-care contexts and provides metrics such as coefficient of variation, time in range, time above range, and time below range. Its use in occupational medicine, however, remains investigational outside selected clinical circumstances. Work-related factors such as shift work, circadian disruption, sleep loss, psychosocial stress, irregular meal timing, sedentary behavior, and variable physical workload may influence glucose regulation, but direct evidence linking these exposures to CGM-measured GV in workers remains limited. Implications: Potential applications include research on occupational determinants of metabolic health, monitoring of workplace lifestyle interventions, and individualized management of workers with diabetes in safety-sensitive roles, provided that consent, confidentiality, clinical follow-up, equity, and data-governance safeguards are ensured. Conclusions: GV assessment may complement traditional metabolic markers in selected occupational-health contexts, but routine CGM-based surveillance of general worker populations is not currently supported by sufficient evidence. Further longitudinal and interventional studies are required. Full article

Purpose—The flexspline of a harmonic drive constitutes a thin-walled structure with discontinuous gear rim and cylinder configuration, where cyclic stresses induce stress concentration, followed by crack initiation, propagation, and ultimately fatigue failure. This paper reviews advancements in understanding its mechanical properties and fatigue failure mechanisms, aiming to establish a foundation for enhancing operational longevity and guiding future research. Design/Methodology/Approach—The study integrates meshing theory, tooth shape parameters, cylinder stress influencers, and assembly/meshing stress considerations. Theoretical analysis, finite element simulations, and experimental methods are employed to examine stress patterns and fatigue dynamics. Structural parameters and tooth profiles are systematically analyzed for their impact on stress distribution and fatigue life. Findings—Flexspline fatigue failure arises from tooth root stress concentration and cylinder bending stress accumulation. The double-circular-arc tooth profile boosts load capacity by 35% relative to the involute profile, yet demands high-precision machining to preserve meshing performance. Increasing cylinder length mitigates stress concentration but reduces torsional stiffness, while optimized root fillet radii can lower the stress concentration coefficient by 28%. Assembly interference and meshing contact stress accelerate crack initiation, as validated by transient dynamics simulations. Surface strengthening processes (e.g., shot peening) enhance fatigue life by up to 66% through residual compressive stress regulation. Originality/Value—This paper synthesizes multi-scale research on flexspline design, structural optimization, and fatigue mechanisms, proposing novel approaches such as “manufacturability-oriented optimization” and digital twin-driven monitoring. By linking dynamic loads, material properties, and geometric parameters, it bridges theoretical gaps and provides actionable insights for high-precision harmonic drives in robotics and aerospace, advancing reliability in precision transmission systems. Full article

We examine the measurement of country-level institutions in international accounting research. Despite a large body of literature linking national institutions to financial reporting outcomes, the construct validity and reliability of the institutional measures used in cross-country studies have rarely been assessed. We show that widely cited measures of investor protection, legal quality, and equity market development have been adopted without validity or reliability assessment and used inconsistently across published studies, with the same indicator labelled as a measure of different constructs in different papers. Using forty-eight candidate indicators from six international databases for seventy countries, we conduct an exploratory factor analysis followed by a confirmatory factor analysis and identify three latent constructs that pass conventional thresholds for convergent reliability and discriminant validity. The constructs are empirically distinct, indicating that measures routinely treated as interchangeable in published work measure different latent dimensions. We offer a validated three-factor measurement model that researchers can use to operationalise country-level institutions in future cross-country studies and discuss the implications for the interpretation of existing studies. Full article

Purpose: Competency-Based Education (CBE) represents a fundamental shift from traditional credit-hour systems, emphasizing mastery of defined skills and knowledge outcomes over time-based seat requirements. Despite growing institutional adoption, a comprehensive synthesis of CBE’s implementation frameworks, outcome evidence, and equity implications in the post-2015 context remains limited. Prior systematic reviews of CBE either predate the digital transformation era, focus on single disciplines, or examine only specific implementation dimensions. This review addresses those gaps by synthesizing the full breadth of CBE evidence published between 2015 and December 2025. Methods: This systematic review adheres to PRISMA 2020 guidelines. Four databases (Google Scholar, ERIC, Scopus, and institutional case-study repositories) were searched using four keyword clusters: “Competency-Based Education,” “Traditional Teaching and Students’ Competencies,” “Credit System and Students’ Achievement Measures,” and “Competency-Based Education and Workforce. After removing 125 duplicates and applying eligibility criteria (2015–December 2025; post-secondary focus), 73 sources were retained: 68 peer-reviewed articles and 5 accredited institutional case-study reports. A six-theme thematic synthesis was conducted following the work by Braun and Clarke; inter-rater reliability was κ = 0.79 on a 20% subsample (n = 15). Results: Six themes emerged: (1) Student-Centered Learning Philosophy, (2) Outcome-Based Assessment, (3) Flexible Pacing and Mastery Standards, (4) Implementation Frameworks, (5) Institutional Case Studies (University of Wisconsin Flexible Option, SNHU College for America, Purdue Global ExcelTrack, Northeastern Align, and Western Governors University), and (6) Challenges and Benefits of CBE. Evidence suggests that CBE is associated with improved adult-learner retention, workforce development alignment, and recognition of prior learning; however, these benefits are methodologically constrained, and equity implications remain structurally plausible but empirically unconfirmed. Resistance within institutions, misalignment with accreditation standards, and resource demands are the primary barriers to implementation. Conclusions: CBE provides a credible alternative to credit-hour systems for post-secondary institutions serving diverse learner populations, supported by a growing but methodologically constrained evidence base in which selection bias cannot be excluded as a contributing explanation for observed outcome advantages. Successful implementation requires phased institutional change, comprehensive faculty development, and proactive engagement with accrediting bodies. Future research should prioritize longitudinal outcome data, equity analyses by learner subgroup, and AI-driven adaptive assessments within CBE frameworks. Equity benefits are structurally plausible by design but remain empirically unconfirmed; no included study provides demographic subgroup data sufficient to verify equitable distribution of outcomes. Full article

With the advent of the Fourth Industrial Revolution, the adoption of digital transformation technologies has accelerated across industries. Digital transformation has become a critical task for businesses, with success depending on strategic responses to rapidly changing environments, where establishing a technology development roadmap is pivotal. This study proposes a framework for a technology roadmap aimed at promoting effective digital transformation and applies it to the Korean water industry. Key technological management areas requiring digital transformation were identified, followed by an evaluation of development trends, preferences, technology levels, and potential through expert surveys. Data were quantitatively analyzed using Euclidean distance and frequency analysis. Results indicate that the most urgent areas for digital transformation in the Korean water industry are natural environment management and prediction, water supply and customer service, water intake and resource facilities, and water purification. Essential technologies to be prioritized in each area were also derived. Unlike previous studies that only compared technological priorities, this research contributes by providing a multi-layered analysis that considers preferences, levels, and potential, constructing a more robust roadmap. Full article

Colorectal Cancer (CRC) is a prevalent global malignant tumor, and conventional therapies and drugs for CRC are limited by poor targeting and severe toxic side effects. Existing reviews on hydrogel-based CRC treatments mainly focus on synthetic materials or single-responsive systems concerning drug loading and local delivery. Natural polysaccharides possess inherent anti-inflammatory, antioxidant and antitumor activities, and polysaccharide hydrogels (PSHs) prepared from them exhibit favorable biocompatibility, tunable structures and potential targeting capability, which can synergistically enhance the efficacy of loaded drugs and thus become a research hotspot. This article summarizes the pathogenesis and conventional treatments of CRC, introduces monocomponent and composite PSHs as well as physical and chemical crosslinking methods, and emphasizes their tumor microenvironment (TME)-responsive mechanisms, combined drug effects and clinical applications. It also analyzes the challenges in safety evaluation and practical application, and summarizes recent advances in the use of artificial intelligence (AI) for PSHs design, regulation, performance prediction and implementation. This paper serves as a reference for follow-up research and clinical translation of hydrogels prepared from natural polysaccharides for the treatment of CRC. Full article

Deep Neural Networks (DNNs) are increasingly being used in the design of industrial safety-critical autonomous applications such as autonomous vehicles, industrial robotics, and medical instrumentation and control systems. Ensuring reliable and robust operation of the DNN-based safety-critical systems is challenging because of the complex structure of DNN hardware accelerators utilized for inference that are susceptible to the effects of multi-faults, common-cause fault models, data uncertainties, and unpredictable erroneous behavior. Additionally, transient, permanent, and timing faults affect the accelerator design of processing elements, memory arrays, and datapaths, propagate through DNN computations, and potentially can cause catastrophic failures at the system level. The objective of this survey paper is to systematically evaluate the state-of-the-art fault-tolerant DNN accelerator architectures with particular emphasis on their applicability to safety-critical autonomous systems in industry. The survey investigates architectural perspective, fault modeling, and platform-level trade-offs, runtime resilience, validation practices, and certification readiness, following a PRISMA methodology with evidence-driven synthesis and unbiased study selection. Database searches across IEEE Xplore, Scopus, and Web of Science identified 200 records, of which 82 studies were included based on predefined inclusion and exclusion criteria emphasizing industrial safety-critical relevance, fault modeling at the hardware level, and the implementation at the architectural level. The results indicate that there was a clear shift from traditional redundancy-based approaches to cross-layer and adaptive approaches that provide better trade-offs between performance, reliability, and hardware overhead. The current studies presented are based on simplified fault models, incomplete validation- procedures, and limited consideration of system-level and certification needs, which often do not consider critical failure modes such as Silent Data Corruption (SDC). This has resulted in a significant gap between research-level solutions and industrial deployment requirements. This survey underscores the need for scalable, integrated, and certification-aware design approaches to help connect fault modeling, architectural resilience, validation, and safety assurance to develop reliable and deployable DNN accelerator systems for next-generation industrial safety-critical autonomous applications. Full article

This paper presents the Master’s Dissertation Marking Framework (MDMF), a longitudinally developed framework designed to support fairer and more transparent master’s dissertation assessment. The framework was developed through a multi-phase, design-based research framework, comprising a literature review, a survey and in-depth interviews (2022) conducted prior to the emergence of generative AI, and follow-up empirical phases between 2023 and 2025. Across these phases, the framework evolves from an initial focus on procedural consistency and bias mitigation to a broader sociotechnical perspective that incorporates ethical boundaries, professional judgement, institutional responsibility, and the disruptive effects of generative AI on assessment practice. The paper traces the progression of the framework to MDMF Version 5, the final iteration, which consolidates six interdependent components: ethical boundaries and AI policy clarity; fairness and equity issues; pre-marking tasks and calibration; marker allocation; marking processes, culture, and well-being; and technology as both enabler and disruptor. Drawing on empirical evidence from academic staff involved in MSc dissertation marking in the post-generative-AI context, the framework brings together these components to address both longstanding and emerging challenges in assessment. The findings demonstrate that fairness in dissertation marking cannot be achieved through procedural mechanisms or technological solutions alone. Instead, the MDMF supports fairer assessment by structuring human judgement, enabling calibration, and clarifying ethical boundaries in AI-mediated contexts. The framework offers a coherent yet adaptable model for institutions seeking to maintain valid and defensible assessment practices in the age of generative AI. Full article

Social media has emerged as a crucial environment for examining public sentiment during disasters, providing immediate insights into collective emotions and urgent expectations. This research examines the emotional reactions expressed on Turkish posts shared on the X platform (formerly Twitter) following the 6 February 2023 earthquake by employing an integrated method that combines topic modeling and topic-based sentiment analysis. Data were collected between 10 February 2023 and 28 February 2023. A large dataset consisting of 305,000 tweets was compiled, and 296,836 tweets remained for analysis after preprocessing and filtering procedures. Latent Dirichlet Allocation (LDA), enhanced with term frequency-inverse document frequency weighting and bigram extraction techniques, was applied to identify prominent themes, including rescue operations, appeals for assistance, communication about missing persons, and disaster management. The sentiment polarity within each topic was determined using a hybrid deep learning model incorporating Bidirectional Encoder Representations from Transformers (BERT) embeddings Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory (BiLSTM) layers, and FastText representations. This model reached a classification accuracy of 94%, with F1-scores of 0.91 and 0.95, recall values of 0.90 and 0.96, and precision values of 0.92 and 0.95, achieving higher performance than the evaluated baseline models. The findings indicate that supportive, solidarity-oriented, and resilience-related communication patterns were among the most frequently observed positive sentiment expressions, whereas negative sentiments appeared more frequently in discussions regarding delays in aid delivery and perceived shortcomings in institutional response. This study presents a scalable and flexible framework for analyzing sentiment in Turkish-language crisis communication, providing insights that may support disaster response monitoring and decision-making processes as well as the development of systems for tracking public reactions in real time. Full article

This empirical study examines differences in environmental, social, and governance (ESG) ratings across global firms. We investigate whether ESG ratings vary across three critical dimensions: geographic location, industry type, and firm size. Using Refinitiv ESG ratings for 1982 firms across four continents over the 2015–2025 period, with cross-validation against S&P Global ESG scores for the subset of 1397 firms covered by both providers over the same period, we test three primary hypotheses and a set of pillar-specific subsidiary hypotheses through ANOVA, MANOVA, and multivariate regression. Our findings reveal significant variation in ESG ratings across continents (joint MANOVA: F = 51.73, p < 0.001, partial η² = 0.074), with European firms exhibiting the highest ratings, followed by a near tie between North American and Asian firms, and Australian firms in the lowest position. Industry classification shows a significant manufacturing > services pattern in environmental and social pillar ratings but no difference in the governance rating, consistent with the pillar-specific reformulation of the industry hypothesis. Firm size has the largest effect (F = 191.74, η² = 0.247), with larger firms receiving systematically higher ratings across all three pillars. Multi-provider validation indicates substantial agreement between Refinitiv and S&P Global (Pearson r = 0.738), with the central findings replicating across providers. These results contribute to understanding the institutional, geographic, and organizational factors associated with corporate ESG ratings and have implications for how researchers and practitioners interpret cross-provider rating differences and pillar-level versus aggregate reporting. Full article

This study addresses the power dispatching of a DC-coupled three-phase grid-connected photovoltaic (PV) and energy storage-integrated system by proposing a peak shaving and valley-filling control architecture based on time-of-use (TOU) pricing. This research involves achieving maximum power-point tracking (MPPT) for PVMAs using a boost converter combined with the perturb and observe (P&O) method. A lithium-iron phosphate battery pack is integrated into the DC link via a bidirectional buck-boost converter, where charging and discharging control is executed according to peak and off-peak periods to regulate and stabilize the DC link voltage. Furthermore, bidirectional power flow control for peak and off-peak electricity consumption is realized using hysteresis current control and sinusoidal pulse-width modulation (SPWM) technologies within a smart inverter. By integrating the aforementioned power control architecture, the grid system can store energy from the utility during off-peak hours and release the stored energy during peak hours to reduce the load demand on the utility side. Initially, a simulation environment was established using Matlab/Simulink (2024b version) software, followed by control verification of the proposed system on a physical platform. The simulation and experimental results confirm that the integrated control architecture can precisely control the system’s DC link voltage at 800 V and stabilize the grid-connected AC voltage at an effective value (RMS) of 380 V. Moreover, under conditions of peak/off-peak switching and load variations, the system effectively demonstrates its stability and efficacy in performing valley filling and peak shaving. The proposed strategy achieves a power factor above 0.99 and a total harmonic distortion (THD) below 5%, regulates the DC-link voltage at 800 V with a steady-state error within 1.75%, and prevents up to 66.4 kWh of over-contract energy consumption per day under a 35 kW contract capacity, thereby contributing to sustainable energy management and economic savings. Full article

French coastal systems are characterized by strong environmental gradients and increasing anthropogenic pressures, resulting in rapid land cover transformations across coastal landscapes. This study investigates land cover dynamics along the northern, western, and southern French coasts using Sentinel-2 summer image time series acquired between 2015 and 2025. The research aims to identify the most dynamic coastal regions and determine where land cover transitions are most pronounced. A harmonized workflow was developed in GRASS GIS for preprocessing Sentinel imagery, generating seasonal composites, classifying land cover using a Random Forest (RF) supervised algorithm, and detecting changes through time. All imagery was processed using CORINE Land Cover (Level 1) classification nomenclature and projected to Lambert-93 (EPSG:2154). Comparative analyses were performed among the three coastal regions using statistical indicators of change intensity, persistence, and transition rates. The results reveal substantial regional differences in coastal dynamics, with the southern Mediterranean coast exhibiting the highest transformation rate (22.9% of total area changed, at 2.29% yr${}^{-1}$), followed by the northern English Channel coast (18.6%; 1.86% yr${}^{-1}$) and the western Atlantic coast (14.2%; 1.42% yr${}^{-1}$). Urbanization and natural vegetation loss were identified as dominant transition types across all regions. The study demonstrates the effectiveness of Sentinel-2 time series and open-source GRASS GIS methods for long-term coastal monitoring and provides a reproducible framework for large-scale assessments of coastal land cover dynamics in Europe. Full article

The final stage of urban logistics does not end at the building entrance but continues within complex, vertically structured indoor environments, where conventional ground-based delivery systems face limitations in efficiency, flexibility, and scalability. This study introduces the concept of last-meter delivery, defined as unmanned aerial vehicle (UAV)-enabled transport from the building envelope to the recipient within global navigation satellite system (GNSS)-denied, building-regulated indoor space, and systematically reviews the literature from two traditionally separate domains: indoor-UAV operation in GNSS-denied spaces, and outdoor-UAV-based logistics. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 297 studies are synthesized through a two-stream thematic synthesis. The review makes three contributions. First, a unified analytical framework is developed across four dimensions (spatial mobility, logistical capability, social acceptance, and operational coordination) through which the two bodies of literature are shown to be largely complementary, with the gaps in one stream coinciding with the strengths of the other. Second, indoor aerial delivery is found to be subject to a distinct set of operational constraints, including micro-scale navigation accuracy, strict geometric safety envelopes, close human–UAV interaction, and privacy sensitivity, implying that indoor transport-UAVs cannot be realized through simple miniaturization of outdoor platforms but require precision-oriented, human-centric, and building-aware design. Third, the four dimensions are translated into a building-management-oriented indicator framework covering spatial compliance, handover standardization, building information modeling (BIM) integration, occupant consent, and liability allocation, reframing last-meter requirements in terms that are actionable for building planners and facility managers. By framing these challenges within the last-meter perspective, this review identifies the gap between current last-mile theories and emerging in-building aerial logistics and provides a structured foundation for future research. Full article

Background: While the consumer experience of psychosis has received significant attention in Western research, a substantial gap exists regarding the experiences of women in the Kingdom of Saudi Arabia (KSA). In this context, religious, cultural, familial, and gender-specific factors uniquely shape the experience of psychosis, help-seeking behaviors, and recovery. This study aimed to explore the lived experiences of Saudi women with psychosis across three phases: first-episode onset, hospitalization or follow-up, and community living after discharge. Methods: This hermeneutic phenomenological study, guided by van Manen’s methodology, employed all six lifeworld existentials: lived space, lived body, lived time, lived self-other, lived thing, and lived cyborg. Semi-structured interviews were conducted with 21 women diagnosed with psychosis at two hospitals in Riyadh, KSA. Data collection included 13 audio-recorded interviews and eight documented via field notes, supplemented by creative methods such as drawings, poems, and written texts analyzed using van Manen’s vocative method. All Arabic data were professionally translated and verified for accuracy. Results: Three overarching themes emerged. First, women’s lived experiences of first-episode psychosis highlighted the process of understanding causes and developing insight during onset. Second, experiences during admission and follow-up revealed the impact of clinical encounters, nursing care, and the critical need for therapeutic healing spaces. Third, living with psychosis in the community emphasized the complexities of medication adherence, family dynamics, and the pursuit of recovery through education, employment, and religious practice. Conclusions: The participants articulated user-based recovery perspectives, including empowerment, shared decision-making, and hope, which contrasted sharply with the service-based approaches they received. Culturally specific stressors and pervasive stigma shaped every phase of their journey. To the authors’ knowledge, no prior study has examined this population using a hermeneutic phenomenological framework; these findings provide a women-focused, culturally situated evidence base for developing gender-specific recovery models and enhanced discharge planning within the KSA mental health system. Full article

Background: Recent research has drawn attention to potential systemic inflammation in patients with inherited epidermal differentiation disorders (EDD)—rare genetic skin conditions that may contribute to vascular dysfunction. Objective: This study assessed selected vascular, inflammatory, and biochemical parameters in 20 patients with selected EDD and 20 matched healthy controls. Methods: Assessments included Doppler ultrasound, ankle-brachial index, intima-media thickness (IMT), and laboratory profiling focused on lipid metabolism and systemic inflammation. Results: EDD patients showed significantly lower LDL cholesterol and higher interleukin-17A (IL-17A) than controls. IMT values were similar across groups and disease types, but correlated positively with age, body weight, waist circumference, triglycerides, and glucose, and negatively with reactive lymphocytes. No link was found between IMT and self-reported cardiovascular symptoms. Conclusions: In patients with selected EDD, we observed a distinct biochemical profile characterized by lower LDL cholesterol and higher IL-17A concentrations, without accompanying structural arterial changes—carotid IMT and ABI did not differ from controls and remained stable at short-term follow-up. These alterations may reflect disease-specific disturbances of lipid and inflammatory homeostasis rather than classical atherosclerosis. Although they could be of theoretical relevance to long-term vascular health, no structural arterial abnormality was demonstrated. Longitudinal studies incorporating endothelial function testing are needed to clarify their significance. Full article