Search Results (2,490)

With the gradual maturation of live-streaming e-commerce, some merchants invest substantial resources in hiring celebrity streamers, attempting to leverage their influence and credibility to enhance consumer trust and achieve long-term growth. However, against the backdrop of high return rates and low repurchase rates, whether this celebrity-driven operational model can truly achieve sustainable development remains questionable, and relevant research on this issue remains limited. Therefore, guided by Source Credibility Theory and informed by the post-consumption perspective of Expectation–Confirmation Theory, this study employs partial least squares structural equation modeling (PLS-SEM) to examine consumer trust formation and repurchase intention. The results indicate that perceived product quality, perceived interactivity, and perceived attractiveness significantly enhance consumer trust, which in turn positively influences repurchase intention. However, perceived discount has no significant effect on trust, suggesting that relying solely on low-price strategies may be insufficient to support trust-based repurchase intention. Furthermore, the MGA results show that streamer type does not significantly moderate the relationship between perceived characteristics and consumer trust. These findings suggest that celebrity identity alone may not be sufficient to reshape the trust-formation mechanism in live-streaming e-commerce. This study provides theoretical and practical insights for understanding consumer trust formation and promoting the sustainable development of live-streaming e-commerce. Full article

Background: Malnutrition causes complications and adverse effects in older people and is a burden on healthcare systems. Older people with, or at risk of malnutrition who receive nutrition care in hospitals do not appear to be adequately engaged with post-discharge nutrition care processes. Food-based approaches (exclusive of oral nutritional supplements) are commonly considered the ‘first’ or frontline approach by dietetic professionals in the community setting. The aim of this scoping review is therefore to identify and synthesise the literature on food-based nutrition care provided to older community-dwelling adults who have been identified as malnourished or at risk of malnutrition during a recent hospital admission. Methods: This scoping review follows the methodological framework by Arskey and O’Malley, revised by the Joanna Briggs Institute. Results are reported according to the PRISMA-ScR guideline. Studies evaluating food-based nutrition care interventions provided to patients post-discharge from a hospital admission returning to a community setting were included in this review. Results: A total of 4086 records were screened, and eleven articles from seven independent studies were included. Highly heterogeneous findings may suggest improvements in weight, dietary intake, quality of life, physical function, anxiety and/or depressive symptoms, and reduction in readmissions associated with interventions including food-based nutrition care. However, sample sizes were generally small and evaluated as part of multicomponent care. Conclusions: Additional research is required to support frontline, food-based approaches for older community-dwelling adults, with or at risk of malnutrition, who are recently discharged from hospital. In the interim, multi-component nutrition interventions may be considered to improve nutritional intake. Full article

The cost–performance relationship in mutual funds is a longstanding open question in financial economics, particularly when costs are assumed to exert a single, linear effect on returns. This study proposes an integrated causal machine learning framework to revisit this question using a panel of Hungarian open-ended public investment funds across all major asset classes—equity, bond, absolute yield, misc, money market, real estate, and commodity—covering 2017–2024. Six machine learning algorithms are benchmarked for return prediction, and Double Machine Learning, with fund-level cluster-robust inference and year fixed effects, is applied to estimate the effect of the Total Expense Ratio (TER) on next-year returns, under the identifying assumptions stated in the paper, while flexibly controlling for a set of observed fund-level confounders (size, NAV dynamics, volatility, past and cumulative performance, and fund age) without imposing a linear functional form. To move beyond average effects, a Causal Forest model—tuned using an out-of-fold, effect size-neutral selection criterion—estimates heterogeneous treatment effects across funds, and SHAP-based interpretation uncovers the mechanisms underlying this heterogeneity. The results show that, once the outcome is measured in the year following the one in which TER is observed and panel dependence is properly accounted for, the average TER effect is not robustly different from zero at the full-sample level; where a statistically robust effect emerges, it is negative rather than positive, concentrated in equity and absolute-yield funds, and largely confined to the period after 2022, which coincided with the war in Ukraine, rising interest rates, and heightened market volatility, although the research design does not identify which, if any, of these developments drove the change. Average-effect models are shown to conceal this heterogeneity, and the results are further shown to be sensitive to two methodological choices that might otherwise appear secondary—the timing convention linking cost and return, and the criterion used to select among competing heterogeneous-effects specifications—underscoring the importance of making such choices explicit. These findings demonstrate the added value of combining predictive and causal machine learning, together with identification-robust and panel-robust inference, for uncovering heterogeneity that conventional econometric approaches overlook and offer a transferable methodological template for causal machine learning applications in finance and other high-dimensional decision-making domains. Full article

The prolonged operation of semi-enclosed subway tunnels results in waste heat accumulation, energy wastage, and potential safety hazards. Integrating capillary heat exchangers (CHEs) with tunnel linings to form an energy tunnel is an effective approach to addressing these challenges. However, the current design methodologies for energy tunnels are still non-systematic, and the studies on the design optimization of CHE are still inadequate. To address these gaps, the shield energy tunnel demonstration project in Qingdao was selected as the research object, and a three-dimensional fluid–thermal coupled numerical model was established using the COMSOL simulation platform. A total of 48 CHE design configurations were analyzed to evaluate the heat transfer performance and temperature uniformity of the energy segment. The results indicate that the capillary bundle geometry and the installation position of the CHE are the dominant factors. Specifically, the I-shaped CHE achieves the highest heat transfer capacity, while the W-shaped CHE provides the best temperature uniformity. Installing the CHE within the inner arc protective layer, as opposed to the outer arc protective layer, significantly enhances the heat flux per unit area and improves temperature field uniformity. In addition, the reverse-return connection offers only a marginal advantage over the direct-return configuration, and the capillary group spacing exerts a relatively minor influence on both the heat transfer rate and temperature uniformity of the energy segment. This study provides a reference for the design and engineering application of subway shield energy tunnels. Full article

Urban floods pose an escalating threat to sustainable urban development, particularly in densely populated regions where demographic heterogeneity and differential responses to warnings shape flood vulnerability. However, the existing flood risk assessments of humans often neglect age-specific susceptibility and education-dependent behavioral responses. This study develops an agent-based flood risk model (AFRM) that couples the agent model with a hydrodynamic model to support sustainable urban flood management. Human agents are characterized by spatial distributions derived from population heatmap data, daily mobility patterns governed by a probabilistic finite-state machine, age-differentiated vulnerability thresholds (minors, adults, and seniors), and education-dependent probabilities of responding to warnings. The AFRM is established by integrating human agents and the urban flood process based on the NetLogo platform. Subsequently, the study assesses the dynamic human flood risk under various return periods, and explores the effects of age structures and early warning on urban flood risk assessment. Taking the Huayuan Road area of Zhengzhou City, China as a case study, the results demonstrate the following: (1) the AFRM achieves reasonable accuracy, with 7.17% mean absolute percentage errors across all risk levels; (2) neglecting age structures underestimates the flood risk assessment by 18% to 29%, as minors and seniors exhibit a higher susceptibility to flooding; and (3) early warnings reduced the medium- and high-risk exposure by 45% to 58%, highlighting the potential of warning lead time strategies to enhance urban flood resilience. This research provides the support for urban flood safety and sustainable development in a changing climate. Full article

Agricultural technological innovation is essential for sustainable agricultural modernization and rural development. However, agricultural technology enterprises often face persistent financing constraints because research and development (R&D) activities involve long investment cycles, high uncertainty, and delayed returns. Using a firm-level panel dataset of Chinese agricultural technology enterprises, this paper examines the effect of relational patient capital (RPC) on agricultural technological innovation by employing a two-way fixed-effects model. The results show that RPC significantly promotes agricultural innovation output. Mechanism analysis indicates that RPC enhances innovation through two channels. First, it facilitates firms’ digital transformation, thereby reducing R&D uncertainty and organizational costs. Second, it alleviates financing constraints by stabilizing cash flows to support R&D investment. The results remain robust after clustering standard errors, excluding the years affected by the COVID-19 pandemic, and employing lagged specifications. Heterogeneity analyses further reveal that the positive effect is more pronounced among small-scale enterprises and firms located in central and eastern China, where financing frictions and resource constraints are relatively more severe. By linking RPC to firm-level agricultural innovation, this study extends the literature on agricultural finance and innovation financing, highlighting the role of long-term, relationship-based capital in addressing market failures in agricultural R&D. The findings suggest that rural financial policies should encourage stable, long-term investment, strengthen financing support for small agricultural technology enterprises, and integrate patient capital with digital transformation initiatives to promote sustainable agricultural and rural development. Full article

Taxi fleets operate intensively, accumulate high annual mileage, and contribute disproportionately to urban greenhouse gas emissions, making them attractive candidates for transport electrification. Despite growing interest in electric mobility, integrated evaluations of the environmental, energy, and economic implications of taxi fleet electrification remain limited, particularly for medium-sized cities in Türkiye. This research examines the replacement of the commercial taxi fleet operating in the central districts of Denizli with battery electric vehicles (BEVs) through a framework that integrates operational emission estimation, electricity demand, charging infrastructure, and life-cycle cost analysis (LCCA). Operational emissions were quantified using the IPCC Tier 1 fuel-based approach together with a distance-based consistency check. Under the adopted assumptions, electrification reduced annual operational CO₂ emissions by 4217.48 tCO₂ (57.9%). The electrified fleet required 18.36 MWh of electricity per day (6.70 GWh annually), while estimated peak charging demand varied between 1.22 MW and 5.57 MW, depending on the charging strategy. Economic evaluation showed a positive net present value (NPV) of 1.32 million TL per vehicle, an internal rate of return (IRR) of 80.86%, and a discounted payback period (DPP) of 1.37 years. Although profitability varied with energy prices, vehicle costs, and annual mileage, fleet electrification remained economically feasible across all scenarios considered. These results suggest that electrifying commercial taxi fleets can support urban decarbonization while remaining financially attractive when accompanied by appropriate charging infrastructure and coordinated transport planning. Full article

This study addresses the research gap concerning how rural cultural–tourism integration contributes to regional economic resilience, a relationship that remains underexplored despite growing policy interest in rural revitalization. Using cross-sectional data for 285 Chinese prefecture-level cities in 2020, the study constructs a multidimensional ACT (agriculture–culture–tourism) indicator system and employs XGBoost regression with SHAP (SHapley Additive exPlanations) analysis to examine the nonlinear associations between ACT factors and economic resilience. Spatial analysis reveals significant positive spatial autocorrelation (Moran’s I = 0.412) and pronounced regional disparities. Machine learning results indicate that traditional village numbers and primary industry value-addedness are the most important predictors, with SHAP dependence analysis revealing threshold effects and diminishing marginal returns. An illustrative micro-level case study of 140 social media posts from Guangzhou provides interpretive evidence on how low-intensity, leisure-oriented tourism experiences mediate the translation of ACT resources into economic outcomes. The findings suggest that ACT integration is associated with stability-oriented resilience buffering rather than transformative growth, highlighting the importance of functional integration, product diversification, and institutional capacity for enhancing regional economic resilience. Full article

This paper tests whether reinforcement learning improves monthly commodity-sector rotation once the experiment is reconstructed from investable instruments, strong active benchmarks, realistic costs, and strictly chronological validation. Total returns for energy (DBE), gold (GLD), agriculture (DBA), and base metals (DBB) are obtained from CRSP; GSG and DBC are investable broad-commodity benchmarks. Twelve lagged market-state features generate month-$t+1$ decisions. The initial training sample contains 132 targets through December 2018, the original holdout contains 72 months through December 2024, and a frozen-policy temporal extension adds 17 months through May 2026. All active results deduct 10 basis points per unit of drift-adjusted turnover, and Sharpe ratios use contemporaneous Treasury-bill returns. Six-month momentum earns an 18.6% CAGR and 1.112 excess Sharpe; a fixed 10-seed PPO ensemble earns 9.6% and 0.438. An expanding supervised expert selector earns 16.0% and 0.755. In an explicitly exploratory memory-window sensitivity, a 60-month rolling selector reaches 23.4% and 1.033, but its mean advantage over momentum is not statistically established ($p=0.323$). The pattern is consistent with time variation, but it neither identifies an optimal window nor establishes that older observations are harmful. PPO’s temporal-extension surge is concentrated in March 2026 and reverses when that month is removed. Direct deep RL therefore does not robustly dominate; constrained expert selection remains a research candidate whose memory sensitivity requires prospective confirmation. Full article

Background: Delirium management remains inconsistently implemented in intensive care units (ICUs), and existing studies provide limited insight into how assessment capability, organisational opportunity, and emotional motivation interact in Chinese tertiary care settings. Aim: To explore ICU nurses’ perceived barriers and facilitators to delirium assessment and management using the Capability, Opportunity and Motivation model of Behaviour (COM-B). Methods: A qualitative descriptive exploratory study was conducted with 14 registered ICU nurses from two tertiary hospitals in Chongqing, China, between December 2025 and February 2026. Purposive sampling captured variation in clinical experience, educational background, and ICU type. The first author conducted face-to-face interviews in Mandarin Chinese and completed the initial coding. COM-B informed both the interview guide and the deductive organisation of the analysis, while six themes and 33 lowest-level factors were developed within the three domains. During revision, the fixed analytic structure was audited against all 14 Mandarin transcripts, and the second author independently applied the fixed codebook to five complete transcripts selected for maximum variation; disagreements were resolved by returning to the original Mandarin context and predefined coding boundaries. Results: Eighteen barriers and fifteen facilitators were identified across six themes within the COM-B domains. Capability was strengthened by clinical experience, senior nurses’ intuitive pattern recognition, and conversational assessment, but constrained by difficulty recognising hypoactive delirium, uncertainty when assessing older adults, inconsistent use of CAM-ICU, and insufficient targeted training. Opportunity was enhanced by staffing, environmental control, peer support, family engagement, and physician collaboration, but restricted by fragmented visibility, sensory overstimulation, workload, restrictive visiting, and delayed medical responses. Motivation reflected the tension between professional duty and accountability for safety on one hand and emotional burden, verbal abuse, and violence on the other. Cross-domain accounts showed that opportunity constraints could amplify anxiety and safety-first motivation, narrowing feasible behaviour toward containment, whereas social support could sustain relational care. Conclusions: Delirium management was shaped by interacting behavioural, organisational, and emotional conditions. Strengthening assessment capability alone is unlikely to produce consistent practice without staffing, workflow, environmental, and interprofessional support. Mapping the findings to Behaviour Change Wheel intervention functions highlighted training, environmental restructuring, enablement, and modelling as priority candidate functions for prospective evaluation; education alone was unlikely to be sufficient. Reporting Method: This study was reported in accordance with the Consolidated Criteria for Reporting Qualitative Research checklist. Patient or Public Contribution: No patient or public contribution was involved in the design, conduct or reporting of this study. Participants were registered intensive care unit nurses. Full article

Current research on photovoltaic–storage–charging (PSC) systems operating in market-oriented environments mainly focuses on individual service types, such as charging services or ancillary services, without fully considering the interactions among multiple market mechanisms. In particular, the competition and coordination of shared flexible resources across different markets are seldom explicitly modelled, while the economic opportunities associated with spot market participation are often overlooked. These limitations may lead to an incomplete assessment of the operational flexibility and economic value of PSC systems. To overcome these shortcomings, this paper develops a coordinated scheduling approach for PSC systems participating in multiple markets under market-rule constraints. A unified modelling framework is established to describe the allocation of shared resources among charging services, ancillary service provision, and spot market trading activities. Based on this framework, the scheduling problem is formulated with the objective of maximizing the total economic return of the system. Using charging services and peak-shaving services as representative applications, the proposed method determines both the optimal deployment of flexible regulation resources and the corresponding electricity trading decisions. Numerical results under the representative case study demonstrate that the coordinated utilisation of resources across multiple markets can improve the economic performance of the PSC system compared with single-market participation. The findings further demonstrate the effectiveness of the proposed framework in unlocking and quantifying the flexibility value of PSC systems. Full article

Background: Transitional age youth aged 18–25 years are more likely to engage in risky behaviors, displaying significantly higher alcohol and illicit drug use levels than adolescents and older adults. College students are particularly vulnerable at this critical life juncture as transitioning to adulthood may impact emotional health and well-being, contributing to anxiety, depression, and feelings of hopelessness, all of which are linked to increased risk of substance use and disorders. Objective: This study characterizes the design and status of the MAPme Project, a prospective project centered on substance use and emotional wellness during and beyond college. Herein, we describe the 2018–2024 pilot cohort that was followed during the first two years of college, remotely during the COVID-19 pandemic, and upon the return to campus. We also describe our latest 2025+ cohort with ongoing data collection. Participants: The 2018–2024 cohort comprised 301 college freshmen who completed online assessments at baseline (Wave 1). The 2025+ cohort has currently enrolled 618 students and counting. Methods: We provide descriptive information on both cohorts, along with preliminary associations of pre- and early collegiate substance use outcomes, psychopathology, sleep patterns, and personality traits. Results: Approximately 64% of first-year students reported use of a substance in the 90 days leading up to college in 2018. Alcohol and cannabis were the most prevalent substances used in both cohorts with males consuming more alcohol than females. Females reported greater levels of daily stressors and mood symptoms. Other health and personality characteristics and observed associations between psychosocial risk and protective factors are described. Prior studies demonstrate the ability to test research hypotheses in the social, health, and clinical areas of psychology with robust statistical power. Conclusions: Substance use and emotional well-being vary considerably upon entry into college/university and at any particular moment in time. The MAPme Project encourages the engagement of students to address challenges associated with lack of awareness, inclusivity, and acceptance of scientific research. Overcoming barriers of inclusivity and empowering the community is key to the successful adoption and implementation of campus health and community-oriented research programs and systematically enhancing research training. Full article

Lithuania is a success case in the prosumer-driven deployment of distributed solar photovoltaic (PV) systems. Supported by generous investment subsidies and a net-metering scheme, behind-the-meter solar PV capacity expanded at an exponential rate. This study examined how the rapid growth of prosumer-based solar PV generation has affected the broader electricity market, prosumers, and electricity suppliers. Using electricity market data, the research evaluated impacts on electricity market price formation, electricity suppliers’ profits, prosumer costs, and the prosumers’ investment decisions. The results indicate that, during the early stages of deployment, distributed solar PV systems improved market outcomes by reducing average electricity market prices and enhancing consumer welfare. However, as the installed solar PV capacity increased rapidly, structural imbalances emerged. High solar output during low-demand periods contributed to increased electricity market price volatility, including frequent close-to-zero and even negative price episodes, while periods of low solar availability—particularly during windless winter days—were associated with sharp price spikes. These dynamics generated negative revenue streams for electricity suppliers and weakened investment signals for market-based generation projects. While prosumers, who are predominantly middle- and upper-income households, benefited substantially from reduced electricity costs and stable returns, the findings suggest that non-participating consumers, including vulnerable households, may have faced higher electricity costs. The study highlights the need for adaptive support mechanisms and market design reforms to ensure an equitable and investment-friendly energy transition. Full article

In the mining process of shallow-buried and close-distance coal seam groups in western China, the interconnected collapse fractures between the overlying goaf and the surface form large-area composite goafs, which aggravate surface air leakage and elevate oxygen levels within the goaf. This, in turn, leads to hazardous conditions such as CO over-limits and O₂ deficiency at the working face’s return air corner, which seriously threatens the respiratory health of underground operators and the safe production of mines. Taking the 104 working face of a coal mine in Shenfu-Dongsheng Mining Area as the engineering background, this paper comprehensively adopts SF₆ tracer gas test, fuzzy cluster analysis, and CFD numerical simulation methods to systematically study the distribution characteristics of three-dimensional air leakage channels in composite goafs and their influence mechanism on gas migration in goafs, and proposes a dynamic pressure equalization ventilation (PEV) regulation technology system. The research results show that a multi-dimensional three-dimensional air leakage channel of “surface-interlayer-own layer-roadway” exists in the research area, in which the surface fracture air leakage velocity is about 0.068 m/s, and the interlayer and internal goaf air leakage velocity is about 0.384 m/s. The atmospheric pressure difference between the working face and the surface is the main controlling factor inducing the O₂ deficiency disaster of the working face. Every 100 Pa change in atmospheric pressure difference causes an O₂ concentration fluctuation of about 0.30% at the return air corner, and the critical pressure difference for activating PEV is determined to be 300 Pa. Setting the PEV regulation point at the return air outlet of the working face and adopting the combined dynamic regulation system of fans and air windows can realize accurate pressure balance between the working face and the overlying composite goaf. Full article

Background: Residential radon exposure is a leading risk factor for lung cancer, and climate change may exacerbate this risk by increasing radon entry into homes. In North Carolina (NC), disparities in lung cancer outcomes and low radon awareness disproportionately affect racially and ethnically diverse and low-income populations. However, little is known about how use of conventional address-based sampling (ABS) compares with community-engaged recruitment strategies for enrolling historically underrepresented populations into such research. Community-engaged approaches are used to improve participation in environmental health research, yet few studies compare their effectiveness with traditional approaches in NC. This manuscript compares recruitment outcomes between ABS and community-engaged approaches within the CLOVER study to address this gap. Materials and Methods: The Climate Impact on Lung Cancer via Exposure to Radon (CLOVER) study is a cross-sectional study examining climate-impacted radon exposure and lung cancer risk in NC. Participants were recruited using either ABS through a commercial address database or targeted community-engaged approaches implemented through partnerships with community organizations and culturally responsive, in-person outreach events. After providing informed consent, participants completed a household survey and a 7-day home radon test. Recruitment outcomes—consent, survey completion, and radon test return—were stratified by race and ethnicity and compared across strategies. Results: Of 236 consented participants, community-engaged recruitment enrolled a higher proportion of Non-Hispanic (NH) Black, Hispanic/Latino, and American Indian participants than ABS (57.3% vs. 41.9%). Community-engaged recruitment also had a higher consent rate than ABS (10.2% vs. 1.3%). Of the 145 participants who completed the survey, ABS participants completed surveys at a higher rate than community-engaged participants (73.3% vs. 54.7%), while of the 86 who returned the radon test kits, community-engaged participants did so at twice the rate of ABS participants (44.7% vs. 22.1%). Conclusions: Community-engaged recruitment enrolled a more racially and ethnically diverse sample and achieved higher consent and return rates than ABS, though ABS participants completed surveys at a higher rate. These findings highlight the importance of community partnerships and in-person recruitment strategies to improve participation of historically underrepresented populations in environmental health research and support equitable approaches to radon mitigation and lung cancer prevention. Full article