Search Results (1,138)

Against the backdrop of China’s “Dual Carbon” strategy, transitioning to high-quality energy development (HQED) is imperative for balancing decarbonization with economic resilience. This study explores the transformative role of the digital economy as a primary driver of this transition. Using provincial panel data from 2013 to 2023, we employ a two-way fixed effects model to quantify the impact of digital economy on high-quality energy development. Our empirical results demonstrate that the digital economy significantly bolsters high-quality energy development, a finding that holds across rigorous robustness and endogeneity checks. Mechanism analysis reveals three critical transmission pathways: fostering technological innovation, accelerating industrial structure upgrading, and promoting industrial sophistication. Furthermore, heterogeneity analysis indicates a pronounced positive effect in the Eastern and Central regions, whereas the impact in the Western region remains limited, highlighting a “digital divide” in energy transition. These findings suggest that policymakers should prioritize digital infrastructure in lagging regions and leverage digital tools to bridge the gap between industrial upgrading and energy efficiency. Full article

Accurately assessing urban green perception is crucial for sustainable urban development and human well-being, yet conventional approaches often depend on simplistic objective metrics and non-immersive, screen-based subjective surveys, undermining ecological validity. This study develops and validates a multidimensional assessment framework that integrates Large Vision Models (LVMs) and Mixed Reality (MR) to couple objective environmental features with immersive human perception. The framework comprises 30 objective and 6 subjective indicators; state-of-the-art LVMs including DINOv2 and Depth Anything were applied to accurately extract objective features from Street View Imagery (SVI); and the MR device, Meta Quest 3, was utilized for the immersive collection of high-quality subjective data. In an empirical study with 74 volunteers in Shenzhen, China, machine learning models trained on MR-based data achieved 20–50% higher R² for subjective perception than models trained on traditional screen-based data. The validated framework was then applied to 61,131 SVIs citywide to map the spatial distribution of multidimensional green perception and to quantify relationships between objective and subjective indicators. Going beyond technical validation, this study demonstrates how the framework serves as a critical tool for urban planning and landscape upgrading. By diagnosing perceptual deficits where greening quantity does not translate into quality experiences, the framework supports a paradigm shift from quantity-oriented greening to perception-oriented spatial optimization. These findings offer actionable insights for policymakers to prioritize interventions that effectively enhance public health and environmental equity in high-density cities. Full article

India’s inbound tourism potential has not been fully realised, even though it has rich heritage resources, expanding air networks, and sustained policy attention. To identify the key determinants of foreign tourism demand, this study applies a novel interpretable machine learning framework, XGBoost with SHAP and ALE plots, on a panel dataset of 61 source countries to India between 2002 and 2024. Using a gravity-based tourism demand model, the analysis uncovers nonlinearities and interactions in tourism demand based on origin-country income, India’s hotel capacity, domestic and international aircraft movements, UNESCO heritage sites, mega-events, inflation, and governance indicators. Accumulated local effects (ALEs) and SHAP values were used as interpretable tools. The results show that source-country income and air connectivity are the most influential drivers of arrivals, while heritage sites and hotel rooms display clear saturation and diminishing returns, and governance and inflation exert only mild or nonlinear effects. Mega-events provide small and inconsistent short-run gains without strong persistence. The findings indicate that India’s future tourism gains lie less in further capacity expansion and more in strengthening air connectivity, strategically targeting emerging middle-income markets, and upgrading quality, governance, and price stability to convert existing assets into sustained spatially dispersed arrivals. Full article

Circular economy (CE) decouples value creation from virgin resource use and waste in the medical device sector, which faces stringent patient-safety, quality, and regulatory obligations. Green Additive Manufacturing (AM) offers a precise, digitally driven route to implement CE through dematerialization, on-demand localized production, topology optimization, and material circularity. In this study, a comprehensive CE framework is tailored to medical device manufacturing that integrates eco-design, material circularity, remanufacturing, and regulatory compliance across the product life cycle. Methods include an International Organization for Standardization (ISO) 14040/44-aligned life cycle assessment, process energy metering, sterilization-compatibility studies, mechanical/biocompatibility verification to relevant standards, and a techno-economic/circularity analysis with Monte Carlo uncertainty quantification. Three case studies are explored using bio-based PA11 (selective laser sintering), recycled polyethylene terephthalate glycol (fused deposition modeling), and low-volatile organic carbon biocompatible photopolymer (stereolithography): (1) a patient-specific wrist orthosis, (2) a dental surgical guide, and (3) a single-use catheter Y-connector. Results indicate 38–68% reductions in embodied greenhouse-gas emissions, 22–54% energy savings per functional unit, and up to 80% mass recapture through in-process powder/runner reuse while maintaining clinical performance and regulatory conformity. Design-for-circularity patterns (DfC) were created for DfDisassembly, DfSter, DfTraceability, DfUpgrade, and DfPowder-Loop and provide a governance architecture combining ISO 13485 QMS, ISO 10993 biological evaluation, the European Union’s Medical Device Regulation (Regulation (EU) 2017/745), and the United States Food and Drug Administration’s guidance on Additive Manufactured (3D-printed) medical devices, guidance with unique device identification for closed-loop returns. The paper concludes with an Industry 5.0 roadmap for hospital-proximate micro-factories, materials passports, and digital product passports enabling verified circular flows at scale. Full article

Rapeseed meal (RSM), a major agricultural byproduct, is limited in application due to high anti-nutritional factors like glucosinolates, while microbial fermentation can improve its nutritional and flavor profiles. This study combined physicochemical analyses, volatile metabolomics, and quantitative proteomics to investigate flavor evolution and protein dynamics during RSM fermentation. Results showed RSM reached optimal quality at 40 h fermentation, with increased soluble protein and peptides, decreased glucosinolates, and HS-SPME-GC-MS and electronic nose analysis identified that esters, terpenoids, ketones as dominant volatile compounds, 3(2H)-furanone, dihydro-2-methyl-, Benzenemethanethiol is a key volatile differential metabolite. Proteomics analyzed a total of 51 differentially expressed proteins (DEPs), which are mainly involved in organonitrogen compound, peptide and protein metabolic. Additionally, these DEPs were identified to have significant correlations with 13 differentially accumulated volatile metabolites. These findings provide a theoretical basis for the high-value valorization of rapeseed meal, proposing feasible pathways for its use as a condiment base or a functional ingredient in bakery products. Full article

This study draws on panel data from 31 Chinese provinces spanning 2012–2023 to develop a comprehensive indicator system capturing both the digital economy and agricultural product supply chain resilience. Anchored in the perspective of sustainable agricultural development, the analysis examines how the digital economy contributes to enhancing the resilience and long-term stability of agricultural product supply chains amid rising external uncertainties. The results show that the digital economy significantly improves supply chain resilience not only within a province but also across neighboring regions, indicating a clear digital empowerment effect with pronounced spatial spillovers. Further heterogeneity analysis reveals marked regional and urban–rural disparities: the estimated effects are substantially stronger in eastern China than in the central and western regions, and cities located within urban agglomerations experience more pronounced resilience gains than those outside such clusters. In addition, threshold analyses indicate that agricultural technological progress and industrial structure upgrading act as positive moderating factors, implying a nonlinear and stage-dependent relationship between the digital economy and agricultural product supply chain resilience. Overall, these findings underscore the role of digital development in fostering resilient and sustainable agricultural supply chains and provide insights relevant to coordinated regional development under the broader agenda of high-quality agricultural transformation. Full article

The grading of beef appearance quality is crucial for standardizing market circulation and promoting the upgrading of the beef cattle industry. China’s current beef quality grading system, which relies primarily on human sensory-based visual assessment with marbling and meat color as core parameters, suffers from strong subjectivity, low efficiency, and large errors. This study proposes a rapid grading method for beef rib eye muscle using smartphone imaging combined with ImageJ software. Standardized images were acquired, and ImageJ was employed for grayscale conversion, threshold segmentation, and morphological processing to extract length, width, area, and marbling proportion. The R, G, B color channels were separated to calculate the R/(R + G + B) color ratio. Pearson correlation analysis showed that the ImageJ results were highly consistent with manual measurements (correlation coefficients > 0.97), indicating good reliability. A five-level grading standard (A1–A5) was established, characterized by low cost, simple operation, and objective results. It provides an economical technical solution for beef quality grading and facilitates the intelligent development of the industry. It should be noted that this experimental grading model has only been validated under the specific experimental conditions of this study, and further verification is required for broader application. Full article

High-efficiency electric motors represent a core enabling technology for sustainable industrial systems, providing substantial opportunities to reduce electricity consumption, operating costs, and associated greenhouse gas emissions across motor-driven processes. This paper presents a structured synthesis of recent progress in high-efficiency motor technologies within the IE3–IE5 efficiency classes, with emphasis on design innovations in electromagnetic optimization, advanced materials, and thermal management that collectively improve efficiency retention, reliability, and service lifetime under practical duty cycle conditions. Beyond component-level advances, the review analyses how high-efficiency motor–drive systems are being embedded within Industry 5.0 manufacturing environments, where human-centric automation and data-driven intelligence extend motor functionality toward adaptive, condition-aware operation. In this context, the integration of IoT-enabled sensing, AI-based analytics, and digital twin models supports predictive maintenance, real-time condition assessment, fault diagnostics, adaptive control, and duty cycle-responsive energy optimization, thereby improving both energy management and operational resilience. The paper also discusses implementation considerations that commonly constrain industrial adoption, including interoperability with legacy infrastructure, control architecture compatibility, data quality and model robustness, cybersecurity concerns, and lifecycle-oriented sustainability requirements such as material criticality and end-of-life pathways. Representative industrial case studies are synthesized to illustrate typical deployment architectures, observed implementation effects, and recurring technical challenges, together with practical mitigation strategies. This article advances the viewpoint that, under the Industry 5.0 paradigm, the value of high-efficiency motors is evolving from a component-level efficiency upgrade to a cyber-physical enabling asset that shapes lifecycle carbon performance and manufacturing resilience; realizing this shift requires integrated co-design spanning electromagnetics, thermodynamics, information science, and control. Full article

Milk tea is a globally popular new-style tea beverage product. In recent years, the industry has achieved rapid development in terms of scale expansion and quality iteration and upgrading. The flavor quality and product stability have become the focus of attention and research hotspots in this field. The chemical foundation of milk tea flavor, processing methods, and flavor quality evaluation approaches are thoroughly elaborated. The chemical basis of tea-based, milk-based, and milk tea flavors is systematically summarized, primarily including the analysis of key flavor compounds and the interactions between tea-based and milk-based substances. Subsequently, the tea-based production methods, mixed processing techniques, and factors influencing storage and preservation of milk tea are discussed. Furthermore, evaluation methods for milk tea flavor quality, including traditional sensory evaluation and intelligent assessment techniques are systematically outlined. This review not only summarizes the recent research progress but also looks forward to the interdisciplinary work that needs to be carried out in the future. These efforts aim to provide information on the transformation from the research stage of tea milk product formulas to the development of solutions with controllable quality. Thus, they offer valuable theoretical guidance for the formation and regulation of tea milk flavor and quality as well as the development of new products. This work aims to provide theoretical insights and technical support for the translation from laboratory formulations to quality-controlled industrial solutions. Full article

Considering consumer health, consistency in processes, and developing trust among the public, food manufacturing facilities are expected to adhere to strict regulatory policies. Along with these expectations, machinery capabilities, especially considering reliability, maintainability, and hygienic designs, would play a significant role in delivering quality products and developing efficient processes. This paper focuses on a belt-style depositor machine, whose primary purpose is to deposit product pieces onto product passing below it. First, the key issues with the current machine are pinpointed. Next, alternative designs are provided aimed at testing, evaluating, and building belt-driven depositing machines. The original design experienced persistent belt tracking issues, frequent maintenance interruptions, and sanitation concerns due to its complex, heavy components. The project applied the Define, Measure, Analyze, Design, and Verify (DMADV) framework to test alternative belt configurations and implement improvements that significantly reduced maintenance time, improved tracking reliability, and enhanced hygienic design. Lab and real-world tests compared three prototypes, namely the V-Rib, Crowned Roller, and Pin Drive. The prototypes were compared against defined performance targets. The final system, built around a self-tracking V-Rib belt with modular components and reduced tool disassembly, demonstrated a 75% reduction in belt change time, and improved product consistency and compliance with sanitation standards. This redesign offers a replicable model for upgrading depositor systems across production lines. Full article

Against the backdrop of comprehensively promoting a green economy to drive high-quality development, curbing corporate greenwashing is pivotal to advancing this agenda. Consequently, leveraging the quasi-natural experiment presented by the gradual regional rollout of intermediate environmental courts, this study employs A-share data from Chinese listed companies between 2012 and 2024, utilizing a difference-in-differences approach. It empirically examines the impact of environmental judicial systems on corporate greenwashing practices. The findings reveal that the policy of establishing intermediate environmental courts exerts a restraining effect on corporate greenwashing. This conclusion remains robust across a series of stability and endogeneity tests. Mechanism analysis indicates that this policy reduces greenwashing by enhancing judicial efficiency, upgrading green strategies, and strengthening rights protection oversight. Further analysis indicates that the negative effect of intermediate environmental courts on corporate greenwashing is more pronounced among state-owned enterprises, heavily polluting industries, and regions with stringent environmental regulations. This provides substantial evidence that specialized environmental adjudication effectively curbs corporate greenwashing. Consequently, leveraging environmental judicial mechanisms to curb corporate greenwashing and promote green innovation holds significant implications for advancing high-quality socio-economic development. Full article

Efficient treatment of aquaculture effluent is a crucial measure for ensuring the green and sustainable development of fisheries and alleviating pressure on aquatic ecosystems. However, traditional treatment technologies face bottlenecks of low efficiency and poor adaptability, making it difficult to meet the pollution control demands of large-scale aquaculture development. This is a systematic review focusing on artificial intelligence (AI) applications in aquaculture effluent treatment, aiming to clarify the technical framework, core application scenarios, industry trends, challenges, and future directions of AI-driven aquaculture effluent treatment. It first outlines core machine learning technologies, compares model adaptability, and analyzes AI synergies with IoT and digital twins. It then details AI implementation pathways across four core scenarios: precision feeding for pollution reduction, water quality monitoring and prediction, development of denitrifying and phosphorus-removing engineering bacteria, and system module control. Finally, it validates technical effectiveness through case studies, identifies industry trends toward integrated models and predictive monitoring, highlights existing challenges, such as data quality bottlenecks, system coupling complexity, and insufficient implementation economics, and proposes future research directions. This study provides theoretical foundations and practical references for the intelligent upgrading of aquaculture effluent treatment and the high-quality development of the fisheries industry. Full article

The rational allocation of talent resources is significant to regional transformation and upgrading high-quality development. Focusing on urban agglomerations in China, this study examines the spatial patterns and underlying mechanisms of graduate talent mobility using employment data from the Ministry of Education Graduate Employment Quality Reports. We utilized the social network analysis method, stickiness rate, external attractiveness index, and directed migration model. The results reveal the following. (1) Spatial Stratification and Typology: A significant “Matthew Effect” characterizes China’s talent landscape. While the Yangtze River Delta and Pearl River Delta exhibit a “high stickiness–high attractiveness” dual-drive pattern, emerging inland agglomerations like Chengdu–Chongqing rely on high internal stickiness as a critical “stabilizer,” maintaining regional resilience through local stock retention despite limited external pull. (2) Complexity of Driving Mechanisms: Ridge regression indicates that while economic development (GDP per capita) and innovation capacity remain core drivers of external attractiveness, public services and institutional costs exert stronger constraints on mobility. (3) Policy Implications: In contrast, monetary talent policies show limited marginal utility. The study concludes that talent governance in urban agglomerations must shift from homogenous “talent wars” to differentiated sustainable strategies. Advanced regions should foster polycentric networks to mitigate overcrowding, while emerging regions should prioritize “soft infrastructure” to lower social costs, leveraging endogenous stickiness for long-term human capital accumulation and spatial equity. Full article

Analyzing the evolution of cultivated land quality protection policy in China is crucial for refining its frameworks and constructing a “trinity” system integrating quantity, quality, and ecological sustainability. This study employs content analysis to systematically trace the evolutionary patterns of such policies, based on a review of 200 national and local policy documents issued between 1986 and 2014. The results reveal the following: (1) Policy development has occurred in five distinct stages: embryonic, practical exploration, system construction, in-depth transformation, and comprehensive upgrading. The policy system is now maturing toward an integrated “trinity” protection mechanism. Accordingly, governmental priorities have shifted from emphasizing subsistence benefits to prioritizing ecological benefits. (2) Despite a multifaceted policy framework, effectiveness is hindered by the absence of binding national legislation, which remains in the drafting phase. This gap has resulted in fragmented implementation, inconsistent regional standards, and limited policy efficacy. (3) To strengthen the system, we propose three optimization pathways: elevating the legislative hierarchy for robust legal safeguards, implementing zoning-based control mechanisms for targeted governance, and refining interest linkage policies to enhance stakeholder coordination. Furthermore, by constructing a policy orientation index, we quantify the distinct shift from quantity control towards quality and ecological priorities. The study links this discursive evolution to land governance challenges, arguing that policy fragmentation and weak legal binding may undermine land value stability and long-term investment. Our findings extend beyond descriptive policy history, offering a framework for assessing how policy discourse translates into tangible land system outcomes. Full article

The purpose of this study is to investigate the impact of new-type urbanization on land use efficiency and its spatial spillover effects, aiming to provide theoretical support and practical references for improving land resource allocation and optimizing regional development strategies. Using panel data from 61 counties in Zhejiang Province between 2010 and 2022, this research applies a two-way fixed effects model, supplemented by mediation effect analysis and spatial econometric models, to empirically examine these relationships. The results indicate that: (1) both the level of new-type urbanization and land use efficiency show an overall upward trend, exhibiting a spatial pattern characterized by “coastal regions outperforming inland areas, and northern Zhejiang surpassing the south”; (2) new-type urbanization exerts a significantly positive impact on land use efficiency, with industrial structure upgrading serving as a partial mediator in this relationship; (3) significant spatial spillover effects are observed—new-type urbanization not only enhances local land use efficiency but also generates positive spillovers to neighboring regions through spatial diffusion mechanisms; (4) the influence of new-type urbanization on land use efficiency displays regional heterogeneity, with stronger promoting effects observed in coastal and low-efficiency areas, whereas marginal effects diminish in non-coastal and high-efficiency regions. In conclusion, strategic priorities should be established to enhance the quality of new-type urbanization, foster green and intensive development, optimize the industrial structure, and strengthen land conservation practices. Furthermore, region-specific policies are essential to improve land use efficiency across diverse areas, which will ultimately contribute to coordinated regional development. Full article