Yuan Wang

To address the sustainability challenges faced by the machinery manufacturing industry, this study establishes an emergy-based evaluation framework that integrates four dimensions—economic, social, ecological, and sustainability—to comprehensively assess the sustainability of mechanical manufacturing systems. An empirical study was conducted on the balance shaft housing manufacturing system of AH Axle Co., Ltd. Results reveal that the system exhibits a relatively low net emergy yield ratio (NEYR), with an emergy investment ratio (EIR) of 2.27 and an improved emergy sustainable index (IESI) of 0.44, indicating poor social benefits and weak long-term sustainability. However, through the optimization of finishing and casting processes, the emergy waste rate (EWR) decreased from 12.96% to 9.86%, substantially enhancing overall sustainability. This study not only provides a novel perspective and practical tool for sustainability assessment in mechanical manufacturing systems but also offers significant theoretical and practical implications for promoting green transformation and sustainable development across the industry.

Evaluating the regional ecological carrying capacity (ECC) is the key to promoting regional ecological civilization construction and high-quality development. However, the ECC is a dynamic and complex system with substantial regional differences. Therefore, it is necessary to consider the data and relationships of the regional economy, society, and resource environment according to local conditions. We have proposed a data-driven method to evaluate the spatiotemporal evolution of regional ECC. Based on the application of economic, social, resource, and environmental data reflecting ECC, a regional ECC evaluation index system was constructed. The entropy weight TOPSIS model was applied to measure and evaluate the regional ECC and the three subsystems of economy, society, resources, and the environment. Their spatiotemporal evolution trends were analyzed, and targeted policy recommendations for data application have been proposed. This study examined the ECC in the Yangtze River Delta region from 2011 to 2020 to demonstrate the implementation of datadriven methods. The findings have verified the feasibility of the research method, providing theoretical and methodological support for the study and management of ECC. This has also provided a basis for the construction of a regional ecological civilization, sustainable development, prevention of ecological degradation, and formulation of environmental protection-related policies.

Licorice flavonoids (LCFs) have been widely used in food care and medical treatment due to their significant antioxidant activities. However, the molecular mechanism of their antioxidant activity remains unclear. Therefore, network pharmacology, ADMET, density functional theory (DFT), molecular docking, and molecular dynamics (MD) simulation were employed to explore the molecular mechanism of the antioxidant effects of LCF. The network pharmacology and ADMET studies showed that the active molecules of kumatakenin (pK_a = 6.18), licoflavonol (pK_a = 6.86), and topazolin (pK_a = 6.21) in LCF are key antioxidant components and have good biosafety. Molecular docking and MD simulation studies demonstrated that active molecules interacted with amino acid residues in target proteins to form stable protein–ligand complexes and exert their antioxidant effects. DFT studies showed that the antioxidant activity of LCF could be significantly modulated under the solvent‐mediated effect. In addition, based on the derivation of the Henderson–Hasselbalch and van't Hoff formulas, the functional relationships between the reaction‐free energy (ΔG) of LCF and the pH and pK_a values were established. The results showed that active molecules with larger pK_a values will be more conducive to the improvement of their antioxidant activity under solvent‐mediated effects. In conclusion, this study found that increasing the pK_a value of LCF would be an effective strategy to improve their antioxidant activity under the effect of solvent mediation. The pK_a value of an LCF will be a direct standard to evaluate its solvent‐mediated antioxidant activity. This study will provide theoretical guidance for the development of natural antioxidants.

Green development is an important connotation of high-quality development and is one of the goals of scientific and technological innovation. This study constructs a data-driven measurement model of the green development efficiency of regional sci-tech finance, measures the green development efficiency of sci-tech finance by using the super-slack-based measure model, and deeply analyses and evaluates the changes in green development efficiency of regional sci-tech finance by calculating Malmquist index. This study calculates the green development efficiency of sci-tech finance in the Yangtze River Delta. Results show that the green development efficiency of sci-tech finance in the Yangtze River Delta is on the rise as a whole and maintains an efficient state, but differences are observed between provinces and cities. This study provides theoretical and methodological support for the evaluation of the green development efficiency of regional sci-tech finance and serves as reference for policy makers and researchers of sci-tech finance.

This study develops a data-driven, comprehensive evaluation method to improve the science and technology innovative efficiency of industrial enterprises above designated size (hereinafter “industrial enterprises”). Based on an innovation value chain perspective, a two-stage evaluation index system is constructed. Thereafter, the Pearson correlation coefficient method was used to analyze correlations in the constructed index system. A two-stage network data envelopment analysis model with additional intermediate input was constructed to measure and evaluate industrial enterprises’ science and technology innovative efficiency from three aspects—research and development (R&D), commercialization, and comprehensive efficiencies—to reveal the temporal and spatial evolution. The feasibility and effectiveness of the method was verified using the statistical data of industrial enterprises in 16 cities in Anhui Province, China, from 2011 to 2020. The results show that the comprehensive efficiency of the scientific and technological innovation of industrial enterprises in these cities is at a medium level, and the efficiency development of the two stages is uncoordinated; the two-stage efficiency distribution tends to be “high R&D–high commercialization” and “low R&D–low commercialization”, and targeted countermeasures and suggestions are proffered. This study provides a reference for the sustainable development of industrial enterprises in relevant regions.

To promote coupling coordination development for regional innovation environment-resource-output-benefit (EROB) composite systems, we propose a data-driven integrated model method for measurement, evaluation, and identification. First, we construct an evaluation indicator system of coupling coordination development of regional innovation EROB composite systems. Second, we apply the entropy method to measure indicator weights and comprehensive development indices of regional innovation composite systems. The coupling coordination degree model is used to calculate and evaluate four subsystems’ coupling coordination development levels. The obstacle degree model is used to identify the main obstacle factors affecting coupling coordination development. Finally, using panel data of the Yangtze River Delta region (three provinces and one city) between 2014–2019 as a case study, we test the integrated model method. The results show that the comprehensive development level of the regional innovation EROB composite system in the Yangtze River Delta region maintained a stable growth trend; the coupling coordination development level among four subsystems continuously improved, with the main obstacle being the innovation resource subsystem. Accordingly, targeted policy suggestions are put forward. This study not only provides theoretical and methodological support for evaluating and optimizing regional innovation composite systems but also provides decision-making support for sustainable and high-quality development of regional economies.