Search Results (1,009)

High-technology supply chains are increasingly concentrated in advanced economies, limiting the industrial upgrading potential of emerging regions. At the same time, growing sustainability pressures require the integration of circular economy principles into production systems. However, existing research rarely integrates supply chain localization, circular value creation, and regional capability within a unified framework. This study addresses the following research question: how can circular supply chain design be structurally integrated into high-technology localization strategies to support sustainable industrial development in emerging economies? To answer this question, the study develops an integrative conceptual framework through the synthesis of localization theory, circular supply chain design, and capability accumulation literature. The framework is structured around three interdependent structural dimensions (SDs): (1) core technological supply chain processes, (2) circular value creation mechanisms, and (3) regional capability accumulation pathways. The framework embeds circular mechanisms—such as modularity, repairability, remanufacturing, and lifecycle management—within the supply chain architecture, enabling the transition from linear acquisition models to lifecycle-oriented systems. It provides an analytical basis for understanding circular localization and offers practical insights for policymakers and firms seeking to develop sustainable high-technology supply chains in emerging economies. This contribution advances the integration of circular economy and localization strategies and supports sustainable industrial transformation. Full article

This study presents a structural and geotechnical assessment of an onshore wind turbine foundation that has been in service for approximately 15 years. It aimed to evaluate its suitability for service life extension under the current operational conditions, within the broader context of decision-making in aging wind farms. The investigation integrated original design documentation, detailed field inspections, in situ and laboratory geotechnical testing, and advanced 3D numerical modeling incorporating soil–structure interaction effects. Verification procedures followed international standards and current guidelines for the design and reassessment of wind turbine foundations. Critical structural and geotechnical aspects, including internal forces and reinforcement demand, stiffness, bearing resistance, settlement, and global stability, are examined to verify performance under the current operational loading conditions. The results provide a sound technical basis for strategic decision-making regarding service life extension or decommissioning of wind turbines in established wind farms, and constitute an essential baseline for any future structural upgrading associated with repowering strategies. Full article

To address the strong nonlinearity, coupling, and time-delay characteristics in greenhouse environmental regulation, as well as the large overshoot and limited robustness of conventional proportional–integral–derivative (PID) control, while considering the practical constraint that complex intelligent control methods are difficult to deploy directly on low-cost industrial controllers, this study proposes a predictive fuzzy PID control method for greenhouse environments under programmable logic controller (PLC)-based edge deployment. An integrated remote monitoring and control system with a “PLC–human–machine interface (HMI)–cloud–mobile” architecture was also developed. Based on the intelligent greenhouse experimental platform of Yunnan Agricultural University, the proposed method was validated for greenhouse temperature and air humidity regulation through MATLAB simulations, PLC deployment, and on-site operation tests. The results showed that all four control strategies were able to effectively track the setpoints of greenhouse temperature and humidity, while predictive PID and predictive fuzzy PID achieved better overall performance than conventional PID and fuzzy PID. Predictive fuzzy PID performed best in the humidity channel, whereas its performance in the temperature channel was close to that of predictive PID but with more stable disturbance recovery and better overall balance. On-site operation results further showed that, under typical operating conditions, the tracking error of the actual greenhouse temperature relative to the target temperature could be maintained within approximately ±1 °C, while the error of the actual air humidity relative to the target humidity remained within approximately −2% to 3% RH. These results verify the engineering feasibility of the proposed method on resource-constrained industrial PLC platforms. The proposed method can provide a useful reference for the lightweight and intelligent upgrading of small- and medium-sized greenhouse environmental control systems. Full article

Examining the effect of digital village construction (DVC) on agriculture–culture–tourism integration (ACTI) is important for understanding sustainable rural development. Using panel data from 30 Chinese provinces from 2012 to 2022, this study employs a two-way fixed-effects model to examine the impact of DVC on ACTI, along with its mediating mechanisms and heterogeneous effects. Results show a significant inverted-U-shaped relationship between DVC and ACTI. This finding remains robust across a series of tests. Mechanism analysis reveals that industrial structure upgrading and urbanization play partially mediating roles with the same inverted-U-shaped characteristics. Heterogeneity analysis indicates that DVC presents a linear positive effect in central and western regions and in areas with low DVC levels, while an inverted-U-shaped pattern is observed in eastern regions and in areas with high DVC levels. These findings suggest that DVC strategies should account for both regional differences and development stages. Full article

Improving energy efficiency is critical for tackling environmental issues and achieving sustainable development. Understanding how digital technology affects energy efficiency and its underlying mechanisms can deepen our comprehension of the economic consequences of digital innovation. This study adopts a dictionary-based method to identify digital technology patents from a large-scale patent dataset and employs a comprehensive evaluation approach incorporating both subjective and objective weights to measure digital technology advancement. Building on this framework, the research uses city-level data from China and applies panel data models alongside mediation effect models as core analytical tools to investigate the impact mechanisms and effects of digital technology on energy efficiency. Key findings reveal that digital technology has developed rapidly, exhibiting distinct phase-specific characteristics, especially after 2010, though notable regional disparities remain. Robust tests confirm that digital technology significantly enhances energy efficiency. Nonlinear regression results indicate that the marginal effect of digital technology changes dynamically across different stages of energy efficiency development. Heterogeneity tests demonstrate that the impact of digital technology on energy efficiency exhibits typical heterogeneous characteristics. Mechanism analysis shows that digital technology enhances energy efficiency primarily through two pathways: green technology innovation and industrial structure upgrading. Further analysis suggests that regional convergence in energy efficiency is objectively present, and digital technology actively accelerates this convergence process. These findings offer practical insights to guide policymakers in designing and implementing digital technology-driven strategies aimed at enhancing energy efficiency. Full article

Background/Objectives: An accurate preoperative assessment of prostate cancer malignancy is crucial for risk stratification and selection of the optimal treatment strategy. This study assessed the concordance of Gleason scores between MRI–TRUS fusion biopsy and radical prostatectomy specimens, and identified clinical and histopathological factors associated with post-procedural Gleason score upgrading. Methods: This retrospective analysis involved patients who underwent transperineal MRI–TRUS fusion biopsy followed by radical prostatectomy from 2020 to 2025. Concordance, upgrading, and downgrading of the Gleason score were assessed by comparing biopsy results with the final histopathological examination. Clinical parameters (age, PSA level, prostate volume, and PSA density) and histopathological features of biopsies (Gleason score and percentage of prostate lobes affected by cancer) were analyzed. Multivariate logistic regression models were stratified by PSA level (<10 ng/mL and >10 ng/mL). Results: Gleason score concordance was found in 53.1% of the 603 patients analyzed, upgrading in 29.9%, and downgrading in 17.1%. Higher Gleason scores on biopsy were independently associated with a lower risk of upgrading in the entire cohort and in both PSA subgroups. Larger tumor extent on biopsy was associated with a lower risk of upgrading, with heterogeneous dependencies between prostate lobes. The other clinical parameters showed no independent association with upgrading. Conclusions: Gleason score upgrading remains common after radical prostatectomy. The risk of this progression is primarily related to the histopathological features of the biopsy rather than to baseline clinical parameters, reflecting the limitations of biopsy as a sampling method and the biological heterogeneity of prostate cancer. Full article

In the context of global efforts to achieve carbon neutrality, understanding how digital–intelligent integration influences carbon emissions is crucial for advancing the ecological transition. Using panel data from 30 provincial-level regions in China (2014–2023), a digital–intelligent integration index was constructed via entropy weighting and a coupling coordination model. Employing fixed-effects, mediation, and spatial Durbin models, the analysis shows that digital–intelligent integration is significantly associated with lower carbon intensity, a result that is robust to endogeneity concerns and alternative specifications. Industrial structure upgrading and green technology innovation were identified as mediating pathways. Furthermore, digital–intelligent integration generates positive spatial spillovers, reducing carbon intensity in neighboring provinces. Notably, these spillovers are geographically constrained and vary significantly across the regions. These findings indicate the need to formulate regionally differentiated strategies to harness the specific mechanisms through which digital–intelligent integration operates in different contexts. Full article

In the context of the global dual-carbon goals and China’s DP strategy, strengthening the coupling between digital productivity (DP) and the high-quality development of the energy industry (HQDEI) is essential for resource-based regions. Doing so can help these regions overcome transition constraints and advance green, low-carbon development. Using panel data for nine prefecture-level cities in Guizhou Province from 2014 to 2023, we construct composite indices for DP and HQDEI with an improved entropy-weight TOPSIS approach. We then characterize their spatiotemporal evolution using a coupling coordination degree (CCD) model and kernel density estimation. Finally, we examine the determinants of coupling coordination through panel regression and threshold models. The results show that: (1) The CCD between DP and HQDEI efficiency continues to increase, with regional differences displaying a periodic convergence–divergence pattern and a spatial structure characterized by core agglomeration and outward diffusion. Gradient disparities in coordinated development are evident between central and peripheral areas. (2) Consumption upgrading and fiscal self-sufficiency significantly promote CC, whereas a traditional resource-dependent growth model significantly suppresses it. Constrained by short-term adaptation and integration costs, digital innovation currently exerts a negative effect, and its enabling potential has not yet been fully realized. (3) Nonlinear tests identify a single digital-infrastructure threshold: the enabling effect of digital innovation turns positive only once infrastructure surpasses a critical level, revealing pronounced interval heterogeneity. This study advances the theoretical understanding of the bidirectional coupling between DP and HQDEI, provides empirical guidance for energy digital transformation and high-quality development in resource-based regions of western China, and offers transferable insights for green, low-carbon transitions in traditional energy regions worldwide. Full article

Utilizing panel data from prefecture-level and above cities in China, this study conceptualizes the “Made in China 2025” pilot policy as a quasi-natural experiment and applies a multi-period difference-in-differences (DID) methodology to assess the policy’s impact on carbon emission efficiency. The findings reveal several key insights: (1) The “Made in China 2025” pilot policy significantly enhances carbon emission efficiency, a result robust to various checks, including placebo tests. (2) Heterogeneity analysis indicates that the policy markedly improves carbon emission efficiency in resource-based and larger cities, with less pronounced effects in non-resource-based and smaller cities. (3) Non-linear regression analysis suggests that the policy’s benefits are more substantial in cities with higher initial levels of carbon emission efficiency, whereas its positive impacts are less evident in cities with lower efficiency levels. (4) Spatial effect analysis demonstrates that the policy not only boosts local carbon emission efficiency but also exerts a significant demonstrative effect on neighboring cities. (5) Mechanism analysis reveals that the policy primarily enhances carbon emission efficiency through the promotion of green technological innovation and the facilitation of industrial upgrading, without invoking a reinforced environmental regulation mechanism during the study period. (6) Extension analysis indicates the presence of regional convergence in carbon emission efficiency. While the “Made in China 2025” pilot policy aids in elevating efficiency levels, it does not actively foster convergence. The outcomes of this study offer substantial theoretical underpinnings for the implementation of industrial policies and the formulation of urban low-carbon development strategies. Full article

This study explores a circular bioeconomy strategy for microbrewery waste by characterizing and valorizing its primary waste streams: sugar mash water (A), spent yeast with hops (B), spent yeast without hops (C), and alkaline cleaning wastewater (D). The biochemical methane potential of the acidic organic blend (E, from A-C) was assessed under mesophilic (38 °C) and thermophilic (55 °C) conditions, revealing significant substrate-specific temperature sensitivity. The highly acidic blend E (pH 4.16) was effectively neutralized to pH 7.0 using the on-site alkaline wash water (D, pH 12.03). Mesophilic anaerobic digestion of the neutralized blend achieved a high methane yield of approximately 500 mL/g VS. Furthermore, the alkaline wash water successfully served as an in situ CO₂ scrubber, upgrading biogas to ~100% methane content. This integrated approach demonstrates a viable, closed-loop pathway for microbreweries to achieve simultaneous energy recovery from organic wastes and chemical-free treatment of acidic and alkaline effluents. The findings also highlight the importance of substrate-specific thermal management and provide a robust framework for microbreweries to achieve energy independence and internal CO₂ neutralization–wastewater treatment. Full article

Integration of informatization and industrialization (IoII) is a pivotal sustainable strategy in China, aimed at industrial modernization and high-quality economic development, which accelerates enterprise digitalization. This paper explores the economic impacts of China’s integration of informatization and industrialization (IoII) policy on enterprises’ environmental, social, and governance (ESG) performance, a core indicator of corporate sustainability. Employing the quasi-natural experiment setting offered by the pilot policy of “Integration of Informatization and Industrialization (IoII)” in China, this paper explores the effects of the IoII on corporate ESG performance through effect analysis, mechanism identification, and heterogeneity test, utilizing the data from A-share listed companies in China. Using the difference-in-differences (DID) analysis, the results suggest that the IoII significantly contributes to improving corporate ESG performance, primarily driven by improvements in the environmental (E) and governance (G) dimensions, while the social (S) dimension is not significantly affected, thereby enhancing long-term sustainability competitiveness. The findings from the mechanism identification indicate that the IoII can promote corporate ESG performance through the three mechanisms: green innovation, corporate governance, and information transparency, all of which underpin sustainable operational practices. The heterogeneity tests reveal that the IoII promotes corporate ESG performance more effectively in high-tech enterprises, non-SOEs, and enterprises with low growth rates, implying differentiated paths for sustainability-driven digital upgrading. By linking industrial digital integration with corporate sustainability, this study enriches the understanding of ESG determinants and provides meaningful implications for sustainability-oriented digital transformation. Full article

The accelerating integration of electric vehicles (EVs) presents considerable operational challenges for distribution networks, particularly through aggravated voltage deviations and compromised protection coordination during periods of simultaneous charging. In response, this study introduces a novel protection-constrained Binary Evolutionary Algorithm (BEA) designed for expedited electric vehicle-oriented Distribution Network Reconfiguration (DNR) to enhance EV hosting capacity without necessitating costly infrastructure upgrades. The proposed framework uniquely embeds the inverse time–current characteristics of protective fuses—termed Protection Curve Consideration (PCC)—within the optimization process. By explicitly accounting for the thermal inertia of protection devices, the algorithm identifies reconfiguration strategies that uphold voltage stability under elevated EV transportation loading, including configurations typically deemed infeasible by conventional voltage-driven approaches. This selective coordination precludes unnecessary fuse operations, thereby preserving the continuity of electric vehicle charging services. Simulation results on a 16-bus radial distribution system, evaluated under four high-demand scenarios reflective of concentrated EV transportation charging, validate the efficacy of the BEA-PCC methodology. The approach achieves a maximum voltage deviation reduction of up to 15.2%, thereby enhancing power quality for all consumers. Moreover, compared to standard metaheuristic techniques, it reduces Energy Not Supplied (ENS) by 8% and switching operations by 20%, contributing to improved grid resilience and operational efficiency. These outcomes underscore the potential of BEA-PCC as an effective real-time control strategy for distribution system operators seeking to accommodate increasing electric vehicle penetration while safeguarding protection coordination and minimizing customer disruptions. Full article

Microplastics have become a ubiquitous environmental contaminant in natural waters, raising significant concerns regarding aquatic ecosystem health and potential human exposure. A comprehensive synthesis of current knowledge on microplastic pollution in freshwater and marine systems is presented, focusing on sources, distribution patterns, environmental behavior, and associated risks. In freshwater environments, microplastic inputs are closely linked to human activities and land use, with wastewater treatment plant effluent, urban runoff, and agricultural drainage serving as major pathways. In marine systems, microplastics undergo dynamic transport influenced by particle properties, hydrodynamic conditions, and biological interactions such as biofouling and aggregation, leading to widespread distribution from coastal zones to deep sea sediments. Importantly, the role of the freshwater–estuarine–marine continuum is emphasized, highlighting the coupled processes of transport, retention, and remobilisation that govern the spatiotemporal distribution and ultimate fate of microplastics across interconnected aquatic systems. Toxicological effects on aquatic organisms are further examined, particularly immunotoxicity and neurotoxicity, alongside potential human health risks via ingestion, inhalation, and dermal exposure. Attention is drawn to the discrepancy between experimental exposure conditions and environmentally relevant concentrations, which constrains robust risk assessment. Current mitigation strategies, including source reduction, wastewater treatment upgrades, transport interception, and degradation technologies, are critically evaluated in terms of effectiveness and limitations. A clear distinction is made between apparent removal and actual degradation, with further consideration of the environmental implications associated with sludge retention and degradation byproducts. Finally, key research priorities are identified, including the need for standardized detection methods, improved exposure assessment, development of environmentally benign alternatives, and strengthened policy-driven source control. These insights provide a basis for advancing sustainable management strategies for microplastic pollution in natural waters. Full article

Hot-air drying is widely adopted for herbs because it is robust and easy to control, yet it is often energy-intensive and may operate far from optimal conditions when industrial dryers rely on fixed airflow paths and large air recirculation rates. This work investigates a conventional basket-type, adiabatic hot-air dryer through an instrumented 30 h drying campaign and a psychrometric energy analysis. The hot-air drier is designed to reduce the relative humidity of herbs from the environmental value (highly variable as a function of the species, the weather conditions, and, mostly, the seasonality) to 20%. Temperature and relative humidity were measured at four positions to characterize the shelf-by-shelf drying sequence and to identify process phases. A mass balance indicated that approximately 3.8 t of water was removed during the trial. Based on the measured thermodynamic states of the moist air and estimated airflow rates (35,000–53,000 m³/h), the baseline configuration was analyzed and an upgrade strategy was proposed to improve dehumidification and overall efficiency while preserving the conventional hot-air-drying concept. The alternative solution integrates a refrigeration-based dehumidification loop (heat pump) to decouple moisture removal from sensible heating; three plant layouts and seasonal boundary conditions (summer/winter) were simulated. For the most favorable configurations, the specific final–primary energy demand and the associated CO₂-equivalent emissions were reduced by about 70–85% compared with the baseline, depending on the airflow rate and recirculation strategy. The results highlight practical retrofit options for existing herb dryers and provide a transparent framework for translating measured psychrometric states into energy and emission indicators. The results, achieved and discussed in this study, were used to optimize the utilization of an already existing and operative hot-air dryer. Based on the proposed working configuration, the dryer now allows achieving the fixed target for herb mixtures of the previous configuration and, at the same time, reducing the energy consumption and associated equivalent CO₂ emitted, as well as achieving process completion in less time. Full article

Membrane technology demonstrates broad prospects in the field of methane capture and purification due to its high efficiency and low energy consumption characteristics. This paper systematically reviews the research progress in membrane technology for methane separation in recent years, focusing on the design and optimization of membrane material systems, in-depth analysis of mass transfer mechanisms, and practical applications in areas such as biogas upgrading and natural gas decarbonization. Researchers have significantly enhanced membrane separation performance for CO₂/CH₄, CH₄/N₂, and other systems by developing novel material systems such as polymer membranes, inorganic membranes, and mixed matrix membranes (MMMs), combined with strategies like pore structure regulation, interface optimization, and functionalization. Although membrane technology has shown good economic feasibility and application potential in some scenarios, challenges such as long-term material stability, anti-plasticization capability, and large-scale manufacturing remain the main current obstacles. Future research should further focus on the development of novel membrane materials, process integration optimization, and intelligent process control to promote a greater role for membrane technology in the efficient utilization of methane resources and energy structure transformation. Full article