Search Results (848)

Against the backdrop of a technological revolution centered on green and low-carbon development, the deep integration of digitalization and greening has become a core engine for high-quality progress. Moving beyond linear perspectives of environmental governance, this study constructs tripartite evolutionary game models to dissect the strategic interactions among government, enterprises, and consumers. Focusing on the institutional context of e-commerce, we examine how platform-enabled transparency mechanisms (e.g., blockchain traceability and carbon labeling) shape these interactions through key parameters: greenwashing detection (θ), premium loss coefficient (η), and information screening cost (C_D). The analysis reveals that the long-term trajectory is fundamentally determined by the intrinsic economic viability of corporate transformation. Government intervention acts as an equilibrium selector, influencing the speed of convergence, while product value (consumer utility and premium) and platform transparency determine the sustainability of the equilibrium. Critically, the tripartite model shows that the optimal outcome—full enterprise transformation and consumer adoption—can be achieved without sustained government intervention when product fundamentals are sufficiently attractive. This demonstrates the potential for market self-regulation to sustain digital–green synergy. The study makes three contributions: it captures the full tripartite feedback loop, reveals the saturation effect of policy intensity, and embeds platform transparency mechanisms into an evolutionary framework. The findings reframe the government’s role as a temporary enabler and position e-commerce platforms as key governance intermediaries, offering a theoretical basis for adaptive governance strategies in digital commerce. Full article

Food waste presents a major challenge to global sustainability. Up to 60% of this waste occurs at the household level, at which point labeling confusion causes avoidable loss. The present study employed the motivation–opportunity–ability framework to conduct a narrative synthesis of 82 studies and pieces of gray literature, incorporating policies and industry practices to elucidate how food labeling modulates food waste behavior through interactions with consumer motivation, external opportunities, and individual abilities. Food labeling should be considered a systemic intervention tool spanning the entire food supply chain rather than mere carriers of information. The present findings indicate that although standardizing quality and safety label terminology mitigates cognitive confusion, it may have limited efficacy to reduce food waste. Extending shelf life and providing explicit storage guidance are critical strategies that are often undervalued and comparatively underexplored. Labels most effectively reduce waste when they simultaneously activate motivation, opportunity, and ability. When all three elements cannot be activated concurrently, stakeholders should prioritize improving external opportunities or enhancing individual abilities rather than stimulating motivation. Food labeling interventions can only be effective at waste mitigation if systemic and transdisciplinary synergy is achieved among all stakeholders in food supply chains. Full article

Understanding how users perceive and attend to the anthropomorphic appearance and empathic responses of artificial intelligence medical conversational agents (AIMCAs) can help reveal the key judgment cues underlying trust formation and use decisions, while also informing interface and dialog design. To this end, this study employs a 3 (appearance anthropomorphism: high, medium, low) × 2 (empathic response: present, absent) within-subject eye-tracking experiment, combined with subjective scales and brief post-task open-ended feedback. During a static prototype viewing task based on hypothetical consultation scenarios, we concurrently recorded trust, behavioral intention, and visual measures for key areas of interest (AOIs; appearance area, conversational content area, and overall interface area). Eye-tracking measures were normalized by AOI coverage proportion to improve cross-AOI comparability. The results show that both anthropomorphic appearance and empathic response significantly increased users’ trust in AIMCAs and their behavioral intention. An interaction between these two types of social cues was also observed, suggesting that when visual embodiment and linguistic style are aligned at the social level, users are more likely to form favorable overall judgments. At the level of visual processing, however, no interaction effect was found, and the eye-tracking measures showed only partial main effects, indicating that subjective synergy does not necessarily correspond to synergistic changes in attentional allocation. Overall, anthropomorphic appearance and empathic response exerted consistent facilitating effects on outcome variables, but displayed different patterns of attentional allocation and information prioritization at the visual level. Accordingly, AIMCA design should emphasize consistency between appearance cues and conversational strategies, optimize users’ initial judgments and interface comprehension, and use intention through verifiable information organization and clear boundary cues. Full article

With the rapid advancement of location-based services, next Point-of-Interest (POI) recommendation has emerged as a critical task in personalized mobility modeling and recommendation systems. It aims to predict users’ future locations based on their historical trajectories, thereby enhancing the personalization and intelligence of recommendation systems. Despite the promising progress, two key challenges remain insufficiently addressed. First, many existing methods overlook the dynamic evolution of user trajectories across multiple perspectives, resulting in entangled representations that fail to capture user intent accurately. Second, they often ignore the latent synergy across diverse perspectives, which limits the effective utilization of complementary information for recommendation. To address these issues, we propose a novel framework called MRHL. MRHL constructs multiple hypergraphs to represent distinct views of user behavior, including interaction frequency, time decay, and geographical proximity. An enhanced hypergraph convolutional network is employed to effectively model the high-order relationships within them. We propose a cascaded enhancement fusion mechanism that progressively integrates multi-view hypergraph representations to enrich the semantic information of user representations. In addition, a multi-relational contrastive learning strategy is developed to capture the consistent signals across different views, thereby enhancing the robustness and discriminative capability of user and POI representations. Extensive experiments on three public datasets consistently demonstrate that MRHL outperforms a range of strong baselines. Full article

Most empirical research on drinking water governance and regional transformations in Bangladesh has focused on developed and urban regions. We focus on coastal rural areas to address this gap and employ a three-step methodology for the systematic analysis of the broader and site-specific drinking water landscape, involving (i) stakeholder analysis and mapping to identify key actors and characteristics, (ii) field work to identify case study sites, meet stakeholders and identify local water technologies, and (iii) in-depth analysis, triangulating stakeholders, drinking water technologies and governance structures, to identify synergies, differences, gaps and overlaps within them. Taking four different but illustrative case study areas in the Southwestern coastal region of Bangladesh, we identify key stakeholders and capture the multiplicity and dynamism of governance models. We provide the first in-depth mapping of the drinking water landscape in coastal rural Bangladesh. Results reveal a fragmented rural water governance landscape, marked by failed or non-functional technologies due to disputes, poor maintenance, high costs, and lack of accountability after project completion, leaving communities to seek alternative water resources for themselves. We argue that informal water provision currently needs to exist beyond well-known governance models due to system inefficiencies and short legacies of implemented technologies. As the water deficit is predicted to increase, it is imperative to identify the complexities and inefficiencies in governance structures to construct collaborative, sustainable approaches to ensuring drinking water security. Full article

This study investigates how digital transformation influences corporate breakthrough innovation through supply chain spillovers. Using data from Chinese listed companies between 2006 and 2023, we find that upstream digital transformation significantly promotes downstream breakthrough innovation via three mechanisms: knowledge spillover, digital peer effects, and information synergy, the latter helping to mitigate the bullwhip effect. Robustness checks confirm the reliability of these results. Heterogeneity analyses reveal that the effect is stronger for firms with high absorptive capacity, operating in highly competitive industries, or with concentrated supplier bases. In contrast, downstream digital transformation also affects upstream firms, but the spillover is weaker, asymmetric, and operates only through peer effects. These findings enrich the literature on supply chain dynamics and innovation, offering practical insights for firms to harness digital synergy to expand their innovative capabilities. Full article

Background: Public catering is an underexplored One Health interface where structurally complex food-transport equipment may sustain reservoirs of antimicrobial-resistant bacteria. We investigated Escherichia coli from reusable institutional catering food-transport containers, focusing on a difficult-to-clean pressure-relief/ventilation valve compartment. Our objectives were to quantify phenotypic resistance using applied clinical breakpoints, assess inhibitor-synergy outcomes in ESBL confirmatory testing, and contextualize inhibitor-positive isolates by whole-genome sequencing (WGS). Methods: E. coli was isolated from containers sourced from 17 institutions and three central kitchens using ISO 16649-2. Minimum inhibitory concentrations (MICs) were determined by broth microdilution. Extended-spectrum β-lactamase (ESBL) confirmatory testing used cefotaxime/ceftazidime ± clavulanate; inhibitor positivity was defined as a ≥3 two-fold MIC decrease in the presence of clavulanate in isolates meeting CLSI screening thresholds. Inhibitor-positive isolates underwent WGS and CARD-based resistome profiling. Results: Resistance was most frequent to colistin (10, 10.8%), followed by doxycycline (8, 8.6%), florfenicol (7, 7.5%), enrofloxacin (4, 4.3%), and gentamicin (3, 3.2%). Third-generation cephalosporin resistance by clinical breakpoints was uncommon (cefotaxime: 2, 2.2%; ceftazidime: 1, 1.1%). Inhibitor-positive ESBL confirmatory phenotypes occurred in 30 isolates (32.3%), which were sequenced. WGS identified 45 resistance-associated genes across inhibitor-positive isolates but detected no classical ESBL genes; all carried chromosomal ampC/ampH alongside ubiquitous efflux-associated determinants. All WGS isolates belonged to phylogroup A, with serotype O154:H9 (20, 66.7%) and ST5549 (17, 56.7%) predominating. Conclusions: Institutional catering food-transport containers can harbor AMR E. coli, with colistin as the most frequent resistance phenotype and frequent inhibitor-positive ESBL confirmatory profiles that, in this set, were not explained by classical ESBL gene carriage. Integrating phenotype, WGS resistomics, and lineage structure supports targeted hygiene surveillance and risk-informed One Health monitoring in mass catering systems. Full article

Arch-suspended structures represent a distinctive form of hybrid suspension system. By combining an arch with a suspended floor system, this structural typology leverages the inherent advantages of both components while mitigating the limitations of each when used independently. This synergy effectively reduces peak internal forces and flexural deformations in structural members. Although widely applied in bridge engineering, research on arch-suspended building structures remains scarce. This paper investigates the construction techniques employed for a large-scale arch-suspended building. The stability of temporary support systems during construction is verified, and the mechanical behavior of critical joints—including the composite slab hanging pillar, arch support, and arch roof—is examined through both experimental testing and numerical simulation. The results demonstrate that a partitioned and segmented construction method is feasible for such complex structures. Structural internal forces and deformations can be effectively controlled by installing tubular temporary supports on both sides of the hanging pillars and lattice temporary supports at the base. Step-by-step unloading of these temporary supports ensures their stability throughout the construction process. Furthermore, the welds in the composite slab hanging pillar effectively transfer tensile forces from the middle plate to the side plates, enabling composite action and collaborative load-bearing among the steel plates. When subjected to loads of 2 times and 4.3 times the design load, localized plasticity was observed in the arch support and arch roof, respectively, while the overall structural integrity remained secure. This study provides a valuable reference for the design and construction of innovative long-span building structures, offering insights that can inform the development and practical application of arch-suspended systems in future architectural projects. Full article

Background/Objectives: Cardiac rehabilitation (CR) is a cornerstone of secondary prevention, traditionally delivered through supervised center-based models. However, significant logistical barriers and high healthcare costs necessitate a paradigm shift. This review aims to assess the impact of emerging digital frontiers, specifically telerehabilitation (CTR) and artificial intelligence (AI), on overcoming these challenges and improving clinical outcomes. Methods: This study is a narrative, clinically oriented review informed by a structured search of PubMed/MEDLINE and EMBASE for literature published between January 2015 and January 2026. Results: Evidence indicates that CTR is non-inferior to center-based programs in terms of exercise capacity and quality of life (QoL). Digital tools, such as wearable devices and mobile health (mHealth) applications, have significantly increased program participation and improved adherence to lifestyle modifications. Furthermore, the integration of AI facilitates early detection of cardiac events and personalized exercise prescription, while prehabilitation models have been shown to reduce postoperative hospital stays. Conclusions: Digitalization of CR may represent a cost-effective alternative that bridges the gap in global access. While technology serves as an essential diagnostic partner, a robust regulatory and privacy framework is required to protect data sovereignty. Ultimately, multidisciplinary synergy between human expertise and digital innovation is important for providing an equitable and personalized pathway to recovery. Full article

Hybrid renewable energy integration (HREI) in rural regions has received limited scholarly attention due to heterogeneous resource endowments, complex development conditions, and multiple coordination challenges. To better understand the factors affecting HREI implementation in rural China, this study develops a stakeholder-oriented analytical framework and applies an integrated DEMATEL–ISM approach. This study identifies 13 critical factors and groups them into four dimensions: complexity of the system, benefit coordination, efficiency coordination, and information coupling. An integrated DEMATEL-ISM approach is employed to examine the causal relationships among these factors and to construct their hierarchical structure. The analysis is informed by a six-member expert panel and a four-round Delphi process. The results show that five factors belong to the cause group and seven to the effect group, while one factor remains balanced. In terms of relative importance, the three highest-weighted factors are synergy degree among multiple agents (CS1, 0.111), information coupling mechanism (IC1, 0.096), and coordinated management of key resources (EC3, 0.093). In terms of net causal influence, complicated rural environment (CS4, R − C = 1.00) is the strongest driving factor, whereas construction and O&M costs (BC3, R − C = −0.77) is the most dependent effect factor. The proposed five-level hierarchical model further indicates that the complicated rural environment, the sustainability of government subsidy policies, and the supervision and service constitute the foundational layer of HREI development. This study provides stakeholder-oriented insights for understanding and promoting HREI in rural China. Full article

Amid the accelerating waves of global digitalization and the deepening interplay of cultural diversity, urban creative spaces have become pivotal arenas for the digital creative industry—yet a systematic, cross-culturally robust tool for assessing their sustainability remains conspicuously absent. Here, we address this gap by constructing a multi-dimensional evaluation framework derived from a systematic literature review, comprising five primary dimensions—AIGC technology integration, cultural heritage preservation, the economic benefits of the digital cultural industry, ecological synergy and social inclusiveness, and governance and policy support—along with 20 secondary indicators. To enhance methodological rigor, we integrate the Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) to determine indicator weights while mitigating the subjective biases inherent in traditional approaches and employ the TOPSIS method to quantitatively assess and rank the creative spaces of five representative cities: London, Shanghai, Los Angeles, Tokyo, and Berlin. Our findings reveal that London leads in comprehensive sustainability, followed closely by Shanghai, with sensitivity analysis confirming the high robustness of the rankings. The originality of this work lies in reconceptualizing AIGC not as a conventional digital instrument but as a core transformative driver embedded within the evaluation architecture, while the application of IFAHP substantially enhances the scientific validity and methodological reliability of the assessment. This research provides an operational diagnostic tool and actionable optimization pathways for advancing the sustainability of urban creative spaces worldwide, offering practical implications for fostering cultural innovation, bridging the digital divide, promoting social inclusiveness, and informing evidence-based urban governance policies. Full article

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss worldwide and is driven by complex pathophysiological processes, including oxidative stress, chronic inflammation, complement dysregulation, and vascular endothelial growth factor (VEGF)-mediated neovascularization. Nutritional interventions—particularly supplementation with carotenoids, omega-3 fatty acids, polyphenols, and essential micronutrients—have demonstrated clinical benefits in slowing disease progression, as evidenced by landmark trials such as AREDS and AREDS2. However, many AMD-relevant bioactives exhibit poor aqueous solubility, low chemical stability, and limited gastrointestinal bioavailability, which significantly constrain their therapeutic efficacy. Food-grade microgels have emerged as versatile colloidal delivery platforms capable of addressing these limitations through rational structural and physicochemical design. This review provides a systematic roadmap for developing food-grade microgels, organized into: (1) the molecular design of protein- and polysaccharide-based networks; (2) advanced fabrication strategies such as microfluidics and atomization; (3) spatiotemporal release programming within the gastrointestinal tract; and (4) multi-nutrient synergy for retinal protection. This approach highlights how controlled crosslinking, interfacial assembly, and tunable network architectures enhance nutrient stabilization. Particular emphasis is placed on spatiotemporal release programming within the gastrointestinal tract, including diffusion-limited gastric retention, pH- and bile-responsive swelling in the small intestine, and microbiota-triggered degradation in the colon. These mechanisms collectively enable region-specific release, improved micellar incorporation, enhanced systemic absorption, and more consistent retinal delivery. Furthermore, we discuss co-encapsulation strategies that accommodate both hydrophilic and lipophilic bioactives, thereby minimizing antagonistic interactions and enabling synergistic nutritional modulation of oxidative and inflammatory pathways implicated in AMD. A central novelty of this review is the integration of the gut–eye axis, framing microgel-based oral delivery as a systemic pathway to modulate retinal health via the intestinal environment. By bridging retinal disease biology with food colloid science, this review proposes food-grade microgels as a translational platform for next-generation nutraceutical interventions. The integration of programmable release behavior with clinically validated nutrient regimens offers a promising pathway toward more effective and mechanistically informed dietary management of AMD. Full article

Strengthening transparency has emerged as a pivotal issue in promoting the responsible development of artificial intelligence (AI). As the prevailing framework for corporate information disclosure, Environmental, Social, and Governance (ESG) reporting shares an inherent synergy with AI governance; both are rooted in the pursuit of sustainable development and the disclosure of specific matters to investors and broader stakeholders. This study analyzes the status of artificial intelligence (AI) information disclosure in the ESG (Environmental, Social, and Governance) reports of listed companies across the United States, Europe, and China, finding that: (1) ESG reports have emerged as a primary channel for business organizations to disclose AI-related information; (2) significant disparities exist in disclosure levels across four key AI-related domains—development, application, manufacturing, and consumption; and (3) disclosure density varies considerably across E, S, and G dimensions, with the Governance (G) pillar exhibiting the most comprehensive information. Based on an empirical analysis of the ESG-AI disclosure framework, this study proposes an optimization scheme for ESG-AI reporting, clearly defining mandatory ESG-AI disclosure obligations for listed companies and employing the “comply or explain” mechanism to balance corporate transparency with operational efficiency while adhering to the “Double Materiality” principle by disclosing model training energy consumption and ecological impacts under Environmental (E) matters, addressing employment, employee training, marketing labeling, and customer privacy under Social (S) matters, and elaborating on corporate AI strategies, risk management protocols, and governance policies under Governance (G) matters. Regarding procedural safeguards, taking China as a case study, centralized disclosure could be implemented through the National Enterprise Credit Information Publicity System, complemented by an assurance system for listed company reports to enhance the accessibility and accuracy of information disclosure. Full article

Quantum computing offers potential computational advantages, yet its integration into autonomous decision-making systems remains largely unexplored. This paper addresses the need for a unified framework that systematically combines quantum computation with agent-based artificial intelligence. We examine how quantum technologies can enhance the capabilities of autonomous agents and, conversely, how agentic AI can support the advancement of quantum systems. We analyze both directions of this synergy and present conceptual and technical foundations for future quantum–agentic platforms. Our work introduces a formal definition of quantum agents and outlines architectures that integrate quantum computing with agent-based systems. As concrete proof-of-concept implementations, we develop and evaluate three quantum agent prototypes: (i) a Grover-based decision agent for quantum search-driven action selection, (ii) a variational quantum reinforcement learning agent for adaptive policy learning in a multi-armed bandit setting, and (iii) an adaptive quantum image encryption agent that autonomously selects encryption strategies based on entropy-driven feedback. These prototypes demonstrate practical realizations of quantum agency in decision-making, learning, and security contexts under NISQ-era constraints. Furthermore, we discuss application domains including quantum-enhanced optimization, hybrid quantum–classical orchestration, autonomous quantum workflow management, and secure quantum information processing. By bridging these fields, we introduce a structured theoretical and architectural framework for quantum–agentic systems, providing formal definitions, system models, and early operational prototypes that illustrate the feasibility of quantum-enhanced agency under NISQ constraints. Full article

The revitalization of vitality in historic cultural districts can enhance a city’s cultural attractiveness and promote the upgrading of the urban cultural industry and sustainable development. Revealing the threshold and synergistic effects of different districts’ scene elements on district vitality helps to identify the distribution patterns of district vitality and provides a basis for managerial decision-making. This study first uses a geographic information system (ArcGIS) to overlay Baidu heatmaps with the street-network distribution in order to depict the spatiotemporal heterogeneity of district vitality and to compute vitality values by partitions at the district scale. Subsequently, based on an explanatory framework that integrates the physical space and subjective cognition, multi-source data such as street-view panoramas and points of interest (POIs) are quantified to obtain scene-element values for each unit area. Then, the scene-element values and vitality values are integrated into a consolidated database. Additionally, the LightGBM model and the SHAP method are employed to evaluate each element’s marginal contribution and relative importance to district vitality, thereby screening out the key scene elements. Finally, by means of SHAP dependence plots and interaction-effect analysis, the threshold intervals of the key elements and their synergistic relationships are identified, revealing the nonlinear threshold effects and synergies by which scene elements influence spatial vitality. The results show that during rest days, district vitality exhibits stronger diffusion, and the synergistic effect between Leisure-Facility Attractiveness and Street-Network Accessibility is the most prominent in enhancing vitality. High Exhibition-Facility Attractiveness is difficult to sustain crowds on its own; only when Leisure-Facility Attractiveness is likewise high does its effectiveness increase significantly. When Transport Accessibility is within the 0.20–0.40 interval, the positive effect of Leisure-Facility Attractiveness is significantly amplified. An excessive Traditional–Modern Facility Mix readily leads to homogenization of districts; therefore, when introducing modern business formats, local cultural characteristics must be retained. Overall, the generation of district vitality relies more on the synergy between material factors and subjective cognition than on improvements to any single element. The findings of this study provide suggestions for the planning of scene elements and the enhancement of vitality in historic cultural districts. Full article