Search Results (9,357)

In the digital era, online attention has become a key indicator of tourism competitiveness and destination visibility. This study proposes a two-dimensional framework to evaluate the competitive state of online attention by combining its current magnitude and growth dynamics. Using Baidu Index data, the study applies the Boston Consulting Group (BCG) matrix and the coefficient of variation to analyze online attention patterns of Beijing’s 5A–level tourist attractions from 2011 to 2025. The results show clear polarization in online attention. A small number of iconic attractions consistently dominate digital visibility, while many other sites exhibit unstable and uneven attention trajectories. These patterns reflect the cumulative effects of consumer behavior, information-seeking preferences, and algorithmically mediated content environments, which reinforce attention concentration and competitive inequality over time. External shocks, particularly the COVID–19 pandemic, caused sharp declines in online attention in 2020, followed by an uneven recovery in subsequent years, highlighting the volatility of digital attention systems. The study also demonstrates the managerial value of the proposed framework. By classifying attractions according to attention levels and growth potential, the framework supports differentiated marketing and demand–redistribution strategies. For instance, increasing the visibility of high-potential but under-visited attractions can help redirect visitors away from overcrowded “Star/GC” sites and encourage more balanced spatial and temporal visitation. Overall, this study proposes a quantitative and replicable framework that integrates digital attention dynamics, algorithmic filtering, and consumer behavior into destination competitiveness analysis. The framework supports evidence-based and sustainability-oriented destination management by informing adaptive marketing and demand management strategies that can help alleviate overtourism and balance visitor flows. However, the study relies on a single digital platform and lacks direct sustainability indicators. Future research should integrate multi-platform data and link online attention metrics to measurable environmental, social, and economic sustainability outcomes. Full article

Background: Gastric cancer survivors frequently encounter a “care gap” after discharge because of complex postgastrectomy syndromes. We evaluated “WECARE,” a bidirectional digital health platform designed to provide real-time symptom monitoring and multidisciplinary support. The primary goal of this study was to assess the efficacy of the platform by measuring the change in the Korean Quality of Life Questionnaire for Gastric Cancer Survivors (KOQUSS-40) total score over a six-month recovery period. Methods: This nationwide, multicenter pilot randomized controlled trial was conducted by the Korean Quality of Life in Stomach Cancer Patients Study Group (KOQUSS) across nine tertiary centers in Korea. A total of 88 patients who underwent curative gastrectomy were enrolled. Following an initial optimization phase involving 22 patients, the remaining 66 patients were randomized at a 1:1 ratio to the WECARE group or the control group. The WECARE group used a platform integrating the KOQUSS-40 algorithm for structured symptom reporting, real-time feedback on nutrition and exercise, and educational content on meal planning, symptom coping, and recovery. Assessments were performed at baseline and at 1, 3, and 6 months after discharge. Results: The WECARE group showed high feasibility and acceptability, with an adherence rate of 86.7% and an 82% satisfaction rate. At 6 months, the KOQUSS-40 total score (primary endpoint) did not differ significantly between the WECARE and control groups (85.3 ± 1.6 vs. 83.8 ± 1.6, p = 0.603). However, the WECARE group showed a numerically favorable recovery trajectory from the acute postoperative phase. Subgroup analysis revealed a positive trend in reflux symptom management in the WECARE group (p = 0.0856). In addition, more than 77% of users reported that the platform improved their self-management capabilities. Conclusions: The WECARE platform is a feasible and acceptable digital intervention for gastric cancer survivors. Although the primary endpoint was not significantly different, the favorable recovery trajectory, high adherence, and patient engagement support further evaluation in larger studies with longer follow-up and broader healthcare settings. Full article

Background: Digital health has accelerated telehealth uptake, yet evidence comparing video-based musculoskeletal assessment with traditional in-person examination is limited. This study evaluated the concurrent validity and interrater reliability of video-based physiotherapy assessment versus face-to-face assessment in patients with knee pain. Methods: Patients with knee pain underwent randomized consecutive in-person and video-based assessments by experienced musculoskeletal physiotherapists. Clinical diagnoses were categorized into seven groups (red flag, yellow flag, arthrogenic, tendinopathy, patellofemoral pain, muscle sprain, neurogenic). Primary outcomes were intermethod agreement and Cohen’s kappa; sensitivity, specificity, PPV, NPV, and interrater reliability for video assessments were also reported. Results: Forty-five participants (mean age 38 ± 6.5 years; 55.6% female) completed the study. In-person and video-based assessments produced identical diagnoses in 43/45 cases (Cohen’s κ = 0.92, p < 0.001). Telehealth accuracy was high across all diagnostic categories (90–100%). Interrater agreement between video-based assessors was 93.3% (κ = 0.89, p < 0.001). Agreement between assessments was moderately associated with KOOS (r = 0.312, p = 0.037). Conclusions: In this selected pragmatic sample, video-based physiotherapy assessment demonstrated high concurrent agreement and excellent interrater reliability with face-to-face assessment. Given the study’s sample size, repeated-measures design, and lack of an independent reference standard, these results indicate feasibility and intermethod agreement rather than diagnostic equivalence. Video assessment may be a feasible option for triage and management in selected settings, but further research in larger, more diverse populations and evaluation against independent reference standards is required. Full article

Home has been recognized as a health infrastructure through hospital-at-home, home care, and direct-to-consumer wellness and fitness products. However, the patient home environment has been largely overlooked by healthcare as a means to improve therapy outcomes for difficult-to-treat chronic conditions, such as migraine; high-impact pain; and treatment-resistant depression, anxiety, or insomnia. Growing research evidence enables the formulation of a therapeutic home environment standard consisting of three pillars: biophilic design, indoor environmental quality, and intentional self-care spaces that serve as habit cues and foster sleep hygiene, stress management, relaxation, physical activity, and social interactions. Together, these environmental and behavioral interventions can transform real-world inputs into clinical benefits through autonomic, circadian, and emotional regulation. We also highlight the converging roles of self-management, self-efficacy, self-regulation, and self-compassion in sustaining patient engagement and healing at home. The applicability of the therapeutic home environment as an adjunct is illustrated in the case of chronic migraine, a debilitating neurological condition commonly associated with comorbidities. Current challenges in achieving migraine freedom with FDA-approved pharmacotherapies, neuromodulation devices, and digital health technologies are underscored by the high prevalence of refractory, chronic, episodic, and pediatric migraine. Perspectives on developing a personalized, multimodal cure for migraine are illustrated through a hypothetical drug + digital combination therapy comprising anti-CGRP drugs and an AI-powered digital health platform that promotes daily self-care practices within the therapeutic home environments. In conclusion, achieving sustained freedom from high-morbidity conditions requires end-to-end care ecosystems that integrate pharmacological, cognitive, behavioral, and environmental interventions into real-world settings. Full article

Background: Telehealth has expanded access to care for people with chronic diseases, but little is known about how patients in Jordan become activated, motivated, and ready to use these services, particularly during early adoption. Aim: To explore how patients with chronic diseases in Jordan describe their initial activation, readiness, and experiences with telehealth services. Methods: This exploratory qualitative study used interviews with 14 purposively selected adults with chronic diseases from three hospitals in Jordan. Data was analyzed using Braun and Clarke’s six-step thematic analysis. Results: Four interrelated themes emerged. First, patients valued telehealth for preserving independence and ensuring continuity of care, particularly by reducing reliance on family members for transportation to health facilities. Second, readiness was shaped by geography, mobility, and finances. Although telehealth reduced transport costs and lost wages, patients still had to pay for devices and internet access, creating an economic paradox for poorer patients. Third, participation was supported by families but hindered by low digital literacy, platform changes, and unstable internet connectivity. Fourth, trust in telehealth was conditional and depended on patients’ perceptions of convenience and responsiveness. Conclusions: Readiness to use telehealth was relational, structural, experiential, and conditional rather than purely individual. Patients with chronic diseases in Jordan need hybrid care models that engage families and leverage affordable digital technologies to support sustained telehealth use for disease management. Full article

This study examines how different dimensions of leisure literacy relate to work–leisure boundary management and work performance in digitally connected workplaces, addressing the problem that leisure may function as either a restorative resource or a source of boundary conflict. Drawing on boundary theory, the study adopts an exploratory case-based survey design using data from 75 employees in a Taiwanese fire safety enterprise, combining self-reports, supervisor evaluations, and organizational records, with findings analyzed through correlation, subgroup comparison, and regression-based analyses. The results indicate differentiated pathways: positive leisure attitude is associated with work–leisure balance and higher self-rated performance, whereas excessive leisure involvement is associated with increased boundary conflict. These performance-related patterns were more consistently observed for self-rated than for supervisor-rated performance, so performance implications should be interpreted with appropriate caution. Leisure knowledge shows a regulatory role primarily in reducing conflict rather than directly enhancing balance. The results further suggest that comparative leisure/work importance conditions these relationships: when work and leisure are valued more equally, leisure literacy relates more directly to performance, whereas under value imbalance, boundary management becomes more salient, linking leisure literacy to work outcomes. Family life-cycle differences were also observed, although these are treated as contextual. Overall, the study suggests that leisure literacy may support sustainable work performance by shaping whether leisure functions more as a resource or as a source of friction. By extending boundary theory to the work–leisure interface, the study highlights boundary regulation as a relevant issue for sustainable human resource management in digitally connected environments, particularly under conditions of blurred work–leisure boundaries. Full article

Flow lines in aluminum alloy forgings are not merely post-deformation metallographic features; they are integrated indicators of material transport, microstructural evolution, defect susceptibility, and service performance. This review critically examines the mechanisms controlling flow-line evolution, with emphasis on constitutive flow behavior, dynamic recovery and recrystallization, second-phase redistribution, friction, thermal gradients, and die/preform design. It then evaluates how abnormal flow paths promote key defects, including folding/laps, flow-through discontinuities, vortex-like instability, and exposed flow lines, and distinguishes well-established mechanisms from topics that still rely on indirect evidence. Particular attention is given to the effects of flow-line morphology on anisotropy, notch sensitivity, corrosion-assisted damage, and fatigue life in forged aluminum alloys. Current control strategies, including preform optimization, FE-based backward tracing, multiphysics defect indices, frictional heat management, and isothermal forging, are also assessed. The available literature shows that stable contour-following flow lines are essential for the simultaneous control of defect formation, microstructural homogeneity, and durability, while major research needs remain in in situ validation, quantitative defect criteria, and digitally closed-loop process control. This review is therefore framed as a critical narrative synthesis rather than a formal systematic review; emphasis is placed on forging-centered studies that directly relate flow-path evolution to defect formation, anisotropy, fatigue, and process optimization, while evidence transferred from adjacent processes is treated as mechanistic support rather than equivalent proof. Full article

Background/Objectives: Overcrowding in emergency departments (EDs) remains a critical challenge in modern healthcare systems, driven in part by patient uncertainty regarding symptom urgency and a lack of accessible medical guidance. Recent advances in artificial intelligence, particularly large language models (LLMs), present a novel opportunity to support patient navigation and relieve pressure on ED infrastructures. Methods: A total of 238 unique patient questions were identified through a structured web search. Following deduplication and thematic clustering, 15 representative questions were selected. Each question was submitted to the three LLMs—ChatGPT (v3.5), DeepSeek, and Gemini—using a standardized prompt. Responses were assessed by clinical experts (N = 8) who were blinded to the model source. Reviewers selected the best overall response per question, as well as the individual responses of the three LLMs for each respective question. Results: ChatGPT was selected as the best-performing model in 60% of cases, with DeepSeek and Gemini selected in 23% and 17%, respectively. ChatGPT responses also achieved the highest proportion of “excellent” quality ratings and the lowest proportion of “unsatisfactory” outputs. Across all models, clarity was the most positively rated domain (79% agreement), followed by empathy (72%), length/detail appropriateness (71%), and completeness (65%). Over two-thirds of raters expressed willingness to integrate LLM-based tools into clinical practice for patient education and pre-triage counseling. Conclusions: Large language models demonstrate promising capabilities in responding to emergency care-related patient queries. Their ability to deliver medically sound and communicatively effective answers positions them as potential digital adjuncts in the management of low-acuity ED presentations and prehospital triage. Full article

Digital nudges refer to subtle modifications in digital choice architectures that are increasingly applied across domains such as healthcare, human–computer interactions, and behavioral science. However, existing approaches often overlook users’ needs, contextual factors, and ethical considerations related to transparency and autonomy. This systematic literature review, guided by PRISMA 2020, examines the integration of co-design methodologies in digital nudging across four dimensions: participants, application domains, nudge forms, and development methods. The findings show that co-design is primarily driven by end-users, supported by domain experts and technology specialists. Applications are concentrated in health-related contexts, particularly chronic disease management and mental health. The effectiveness of priming varied across studies, with some reporting short-term benefits and others indicating user fatigue, suggesting context-dependent impact and limited long-term effectiveness. Full article

This research article explores whether the climate transition risk (CTR) and climate physical risk (CPR) transmit greater shocks towards the sustainable, gold-backed, energy-related and Sharia-compliant cryptocurrencies during bullish market conditions as compared with the normal and bearish market conditions. We employ the novel quantile vector auto-regression (QVAR)-based connectivity framework. Overall findings suggested that CPR and CTR transmitted greater shocks towards cryptocurrency classes during extremely high and lower quantiles as compared with the median quantile. This U-shaped and non-linear climate risks shock transmission indicates that Sharia-compliant, energy-related and gold-backed cryptocurrencies become more vulnerable during extreme market conditions (higher and lower quantiles) and may not consistently serve as reliable hedging or diversification instruments, particularly during periods of heightened climate uncertainty. Overall findings suggested that both the CPR and CTR transmitted greater shocks towards energy-related, gold-backed, and Sharia-compliant cryptocurrencies as compared with the sustainable cryptocurrencies, across all the quantiles. Therefore, sustainable cryptocurrencies, particularly those with energy-efficient consensus mechanisms such as Stellar, Cardano and Ripple, exhibited resilience to climate risks and can therefore function as stabilizing core holdings in diversified portfolios. Fund managers should incorporate a rebalancing strategy that increases allocation to these climate-resilient, sustainable digital assets during periods of elevated climate risk. Fund managers should integrate CPR and CTR into the quantile-domain forecasting frameworks for predicting digital asset market returns to enhance financial stability. Portfolio managers should undertake dynamic and quantile-contingent climate risk hedging strategies that account for tail-risk exposure rather than relying on average market behavior. Full article

Under the dual carbon goals, green innovation acts as a key driver for the transformation and upgrading of China’s energy-intensive enterprises, and stands as an inevitable choice to propel China’s shift from a major energy-consuming nation to a powerful scientific and technological nation. To explore the driving mechanism of digital transformation on the green innovation efficiency of energy-intensive enterprises, this paper takes such enterprises from 2011 to 2022 as the research subject, designs three distinct scenarios (environmental protection, enterprise innovation and scientific research innovation), simulates heterogeneous development paths, and forecasts trends to 2030. The results show that green innovation efficiency rises steadily across all scenarios, with the strongest improvement under the scientific research scenario. By 2030, efficiency under this scenario is expected to reach 1.77 times that of the baseline scenario, while the other two scenarios also perform significantly better. These findings confirm the positive role of multi-dimensional policy interventions in strengthening digital-enabled green innovation efficiency. Accordingly, practical recommendations are put forward regarding how digital transformation can effectively drive the improvement of green innovation efficiency of energy-intensive enterprises from the aspects of policy formulation, enterprise management and innovation investment. Full article

The accelerated development of Smart Cities globally, driven by rapid urbanization and urgent climate challenges, underscores the critical role of advanced energy infrastructures integrated with emerging digital technologies. This article explores the evolution of smart cities from an energy-centric viewpoint, emphasizing the interdependence among energy systems, digitalization and cutting-edge communication technologies. Adopting a system-of-systems perspective, we examine how different urban subsystems, including energy grids, transportation networks and data management systems, interact to improve overall urban functionality and long-term viability. Through a structured analysis of recent literature, we highlight the transformative potential of renewable energy integration, intelligent energy management systems and the crucial transition from 5G to 6G communication infrastructures, which collectively promise significant enhancements in urban sustainability, efficiency and resilience. Additionally, we address key challenges such as cybersecurity vulnerabilities, fragmented standardization frameworks and the need for comprehensive data governance. Viewing smart cities as a complex system of systems, this article argues for a holistic and interdisciplinary approach, emphasizing enhanced interoperability, robust cybersecurity protocols and inclusive participatory governance frameworks. Full article

This paper proposes a human-centric digital twin (DT) framework balancing energy efficiency with occupant well-being in existing buildings, addressing the lack of actionable insights in data-driven facility management and comfort issues common in fully automated systems. A “Human-in-the-loop” approach using dual-KPIs integrates real-time IoT data and visualization to evaluate sustainable energy use via Indoor Environmental Quality (IEQ). A novel occupancy-inference method tracks efficiency in legacy buildings without granular metering, implemented through a case study of 26 office rooms. Results indicate that the framework successfully identifies significant energy wastage and comfort anomalies without compromising well-being. Integrating real-time analytics with human oversight enables more resilient management than fully automated alternatives, particularly for detecting non-operational heating waste. The occupancy inference method was validated against ground truth, achieving 81% accuracy, with limitations regarding decay lag discussed. This research offers a cost-effective diagnostic tool for legacy buildings lacking sub-metering, lowering DT adoption barriers, and shifting maintenance from reactive to data-driven strategies. The framework leverages human expertise and infers occupancy-normalized energy metrics from standard IEQ sensors, proposing a human-centric DT framework to bridge the gap between raw sensor data and actionable facility management insights. Full article

Due to climate change, the frequency and intensity of extreme rainfall events have increased in South Korea, resulting in recurrent urban flooding that exceeds the design capacity of conventional drainage systems. In the Dangjin Traditional Market area, comparable rainfall conditions in 2024 and 2025 caused repeated flooding, suggesting that structural improvements implemented without quantitative verification do not necessarily guarantee effective flood prevention. This study aims to support sustainable urban flood management by assessing the pre-implementation effectiveness of structural flood mitigation measures using a spatially explicit simulation approach. An ArcGIS-based rainfall–inundation simulation was conducted by integrating a 1 m LiDAR-derived digital elevation model, land cover data classified using a pixel-based Support Vector Machine, detailed building and channel datasets, and observed hourly rainfall from the July 2025 extreme event. Scenarios with and without the application of levee heightening and drainage capacity expansion were compared under identical rainfall conditions. The results indicate that the application of structural measures leads to a clear reduction in inundation extent and water depth. The proposed framework provides a practical simulation-based decision-support tool for verifying flood mitigation measures in advance and for promoting sustainable flood risk management in urban areas prone to recurrent flooding. Full article

Hybrid-electric regional aircraft require detailed thermal management digital twins to assess performance and feasibility while reducing physical test effort. The Functional Mock-Up Interface (FMI) enables partners to exchange subsystem models as Functional Mock-Up Units (FMUs) for gate-to-gate simulation while preserving intellectual property. However, FMU integration introduces numerical coupling challenges, interface overhead, and potential loss of accuracy depending on the integration method. Benchmarking against a DLR Thermofluid Stream (TFS) reference model showed that FMU-based co-simulation can significantly increase computational effort, specifically from 8 min up to 2.5 h. Control-based integration further implicates transient deviations due to filtering, although steady-state accuracy generally remains unchanged. Therefore, it is mandatory to evaluate and compare FMU integration strategies to show that digital twin performance targets remain achievable when design, solver settings, and filtering are only applied selectively and systematically. The results show clear design guidance: employ native fluid libraries when possible for speed and accuracy, use FMU paired with adapters and without filters for accuracy, and reserve filtering for numerical stabilization only. Using a control approach to integrate the FMU improves simulation speed compared to adapters but introduces a small error, which in turn reduces simulation accuracy. Full article