Breaking the resource curse: The impact of green finance on the energy transition of resource-based cities

The modernization of traditional fermented foods is often constrained by a limited understanding of the complex microbial ecosystems underpinning their quality. Guizhou sour soup, a representative Chinese fermented food, exemplifies this challenge. This review systematically reveals that its distinctive characteristics stem from a raw material-driven fermentation ecology. Red sour soup and rice sour soup cultivate specific functional microbial communities centered on lactic acid bacteria and yeasts, exhibiting clear dynamic succession patterns. This gives rise to markedly different flavor profiles-the former dominated by alcohols and terpenes, the latter characterized by esters and organic acids-with microbial metabolism serving as the primary mechanism for flavor formation. Concurrently, sour soup is rich in bioactive compounds, demonstrating health potential including antioxidant effects and regulation of the gut microbiota. However, current research lacks systematic analysis of microbial interaction networks, specific flavor metabolic pathways, and structure-activity relationships of bioactive components, which severely hinders process standardization and industrial upgrading. To address this, this paper establishes an integrated associative framework linking "raw materials-process-microbes-quality." This not only provides a critical theoretical basis for standardized production and targeted flavor regulation of Guizhou sour soup but also offers a scientific framework for modernizing similar traditional fermented foods worldwide.

Driving digital innovation through quality incentives: Evidence from Chinese cities in the digital transformation era

Against the backdrop of global climate change and sustainable development, cities, as major sources of carbon emissions, play a pivotal role in achieving carbon neutrality goals. This study examines the synergistic impact of innovative city and low-carbon city pilots on carbon intensity, using panel data from 272 Chinese cities. The findings reveal that low-carbon and innovative city construction (LCICC) significantly reduces carbon intensity, primarily through technological advances, industrial upgrading, and green finance. However, the carbon intensity reduction is only significant in central regions and resource-based cities. Conversely, LCICC significantly increases carbon intensity in cities characterized by lower administrative status and non-resource-dependent economic structures. This study not only enriches the theory of urban transformation and provides new perspectives for carbon reduction research but also offers the first empirical evidence of synergistic emission reduction effects from the simultaneous implementation of innovation and low-carbon city pilots. These findings provide a replicable analytical framework for other developing economies pursuing dual policy pathways toward carbon neutrality.

Neo-chemical industry: a new perspective for understanding biomanufacturing industry

Advances in glutathione biosynthesis and industrialization

Advantages and prospects of developing microalgal industry in hot-dry valley regions of China

Promoting the upgrading of the value chain in the equipment manufacturing industry is a crucial strategy for China to address the current challenge of being "big but not strong" in this sector, and to establish itself as a manufacturing powerhouse. As a general-purpose technology, artificial intelligence (AI) has emerged as a new engine driving value chain upgrades in equipment manufacturing industry. However, the mechanisms through which AI influences this upgrade remain unclear. Utilizing panel data from 30 Chinese provinces spanning 2010 to 2022, the paper investigates AI's impact on value chain upgrading in the equipment manufacturing industry and its underlying mechanisms. The findings indicate that: (1) AI promotes value chain upgrading in the equipment manufacturing industry, the conclusion that remains robust after a series of stability tests and discussions on endogeneity. (2) AI exerts a significant positive impact on value chain upgrading in both eastern and western regions, while its effect on central regions is insignificant. AI significantly enhances value chain upgrading in capital-intensive and technology-intensive equipment manufacturing industry, yet it has a significant negative influence on labor-intensive equipment manufacturing industries. (3) AI facilitates value chain upgrading in the equipment manufacturing industry through two channels: enhancing human capital levels and driving product research and development (R&D). Production scale positively moderates both the human capital mechanism and the product R&D mechanism of AI. This paper elucidates the mechanisms by which AI facilitates value chain upgrading in the equipment manufacturing industry, uncovers new evidence of AI's heterogeneous impact on this upgrading, and provides policy implications for formulating measures to promote value chain upgrading in China's equipment manufacturing industry.

ABSTRACT Europe’s persistent slowdown in labor productivity growth has widened the gap with global peers, largely due to an innovation lag that only recently spurred targeted policy responses. This slowdown, however, has unfolded unevenly across regions, reinforcing existing territorial disparities. To address this dual challenge, this paper applies an augmented Kaldor–Verdoorn framework to test for increasing returns beyond manufacturing. Using a regional-sectoral panel of 237 European NUTS-2 regions (2004–2022), we examine how sectoral output growth drives productivity gains and shapes regional disparities. Results reveal strong core–periphery heterogeneity: while manufacturing remains the main productivity engine, ICT and other knowledge-intensive services play a growing role. Accounting for fiscal and institutional diversity, findings support a twin-track strategy – industrial upgrading and digital adoption – embedded in place-based, two-tier policies to revitalize productivity and foster long-term regional convergence.

ABSTRACT High-quality entrepreneurship plays a crucial role in technological innovation, industrial upgrading, and economic resilience. Drawing on institutional complementarity theory, this study investigates how government, market, and societal institutions jointly shape entrepreneurial quality under different macroeconomic conditions. Using a panel fuzzy-set qualitative comparative analysis (fsQCA) of 81 countries from 2007 to 2017, the study identifies six institutional configurations that lead to high-quality entrepreneurship. From these, it derives three distinct context-sensitive models of institutional complementarity. These models reflect how institutional domains interact functionally rather than additively, with different configurations prevailing under economic recession, moderate prosperity, and general growth. By integrating economic cycles into the logic of institutional complementarity, this study advances a temporally contingent, configurational understanding of institutional effectiveness. The findings contribute to institutional and entrepreneurship theory and provide actionable insights for policymakers seeking to foster entrepreneurship through adaptive institutional design.

The silkworm, Bombyx mori, is an economically important insect resource in China. With the transformation and upgrading of the sericulture industry, genetically engineered silkworms have emerged as efficient animal bioreactors for producing bioactive proteins and functional compounds. However, the diversity of available transgenic silkworm bioreactor resources remains limited and requires further expansion. Herein, we focused on human lactoferrin (hLF), which exhibits potent antibacterial activity due to its strong iron-chelating capacity, and established an efficient recombinant hLF (rhLF) expression system in the posterior silk glands (PSGs) of transgenic silkworms using piggyBac technology. The rhLF production reached 45.13 ± 2.46 mg/g cocoon shell weight, with N-glycosylation modifications consistent with those of native hLF. Functionally, rhLF exhibited robust antibacterial activity, achieving inhibition rates of 31.64% ± 4.66% against Escherichia coli and 74.35% ± 0.87% against Staphylococcus aureus. Additionally, rhLF significantly promoted cell migration and accelerated wound healing, with a migration rate of 17.06% ± 4.05%. The resulting chimeric fibroin fibers containing rhLF demonstrated enhanced antibacterial activity while maintaining cytocompatibility. Collectively, we constructed a novel transgenic silkworm strain enabling high-yield rhLF production and achieved the biomanufacturing of functional silk fibers. These findings provide a cost-effective strategy for generating high-value products within conventional agricultural systems.

ABSTRACT This study examines how China’s Green Finance Reform and Innovation Pilot Zones affect urban biodiversity using city-level bird observation data from 2012 to 2020. Adopting a quasi-natural experiment and difference-in-differences method, we assess the policy’s impacts. The results show that green finance policies notably raise overall bird species richness. Such ecological gains mainly stem from sustainable agriculture development, industrial green upgrading and rising public environmental awareness.Policy effects differ across bird species: common and migratory birds benefit greatly, whereas endangered species see no significant changes. This reveals general green finance policies have limited effects on protecting vulnerable wildlife, calling for targeted financial tools. Overall, the study proves financial policies incorporating biodiversity goals bring tangible ecological benefits, offering references for balancing economic growth and biodiversity conservation.

Under global pressure to reduce carbon emissions, understanding how the level of artificial intelligence (AI) use affects corporate carbon emissions (CCE) is crucial for achieving a green transition. This study, based on provincial panel data from China, employs a combination of two-way fixed effects (TWFE) empirical analysis and structural equation modeling (SEM) to identify the nonlinear effects of AI use levels on corporate carbon emission intensity and their transmission pathways, and conducts robustness and regional heterogeneity tests. The empirical results show that: first, the relationship between AI use levels and corporate carbon emissions exhibits a significant inverted U-shaped curve-in the early stages of development, due to high energy consumption in computing and deployment, AI adoption may temporarily increase carbon emissions; however, after exceeding a critical point, further deepening of use significantly reduces carbon emissions. Second, SEM analysis reveals several key mediating channels: improving green innovation efficiency (GIE), enhancing energy utilization efficiency (EUE), promoting Scientific innovation (SI), and driving industrial structure upgrading (ISU). These pathways collectively amplify the emission reduction effect of AI. Third, regional heterogeneity analysis shows that the AI emission reduction effect is significantly stronger in the eastern region than in the central and western regions. Finally, this study emphasizes the policy implications: while promoting the use of AI, energy structure and incentive mechanisms should be optimized, and differentiated policies should be formulated according to regional characteristics to achieve an AI-driven sustainable low-carbon transformation.

Enhancing agricultural economic resilience (AER) is essential for global food security. As a key policy tool for stabilizing agricultural production, policy-based agricultural insurance lacks rigorous causal evidence on its impact on resilience. In this study, AER is operationalized as a composite index capturing resistance and recovery capacities across pressure, state, and response dimensions. Using 2012–2023 provincial panel data from China (31 provinces × 12 years = 372 observations), we measure AER via the entropy method and identify policy effects using a staggered multi-timepoint difference-in-differences (DID) model. We find that policy-based staple crop insurance significantly increases AER by approximately 2.5 percentage points, primarily by promoting agricultural technological innovation (ATI) and regional industrial structure upgrading (RIS). The improvement effects are more pronounced in central and western regions, non-major staple-crop producing areas, and regions with higher natural risks. Robustness is confirmed via event study, alternative weighting schemes (PCA and equal weighting), and placebo tests. This study provides reliable causal evidence for the resilience-enhancing effect of agricultural insurance and clarifies its internal transmission mechanisms, offering empirical support for the optimization of agricultural risk governance policies. Limitations include the use of provincial-level aggregate data and the lack of analysis of spatial spillover effects between regions. Our findings suggest that differentiated policy implementation can support more sustainable and targeted agricultural risk governance.

For precision assembly tasks, the accuracy and efficiency of robotic arm trajectory planning directly impact product quality and production efficiency in manufacturing, making it a core technology driving industrial automation upgrades. This research endeavors to establish a sophisticated multi-objective trajectory planning model, specifically engineered to cater to the intricate demands of precision assembly scenarios. The model optimizes for "maximum efficiency, minimum energy consumption, and minimal impact," quantifying time costs, energy expenditure, and the influence of mechanical impact on assembly precision during the process. To enhance the performance of traditional multi-objective particle swarm optimization (MOPSO), this study proposes an improved CEMOPSO algorithm. This approach enhances initial population diversity by incorporating Chebyshev mapping strategies, dynamically adjusts particle search directions through evolutionary elimination mechanisms, and optimizes constraint handling capabilities via a designed infeasibility evaluation function. Engineering experiments using pyrotechnic grain assembly as a typical scenario validate CEMOPSO's practical application value. Implementing this algorithm increased robotic arm assembly efficiency by 15.2%, reduced energy consumption by 20.4%, and decreased impact by 26.4%. This demonstrates the effectiveness and engineering applicability of the theoretical methods developed in this study for complex precision assembly tasks.

Study on spatiotemporal evolution and regional control of financial risks in the Yangtze river delta based on SDM-GWR

Multi-scale social metabolism of China: An extended MuSIASEM analysis of energy, economy, and human activity

Toward a sustainable energy future: Can green data center construction promote energy efficiency?

This study explores the association between district vitality and industrial structure in historic districts through a quantitative analysis of the Xuanen Xinglong Historic District. In this study, on the basis of multisource data, we constructed the framework of a quantitative analysis system for the association between historic district vitality and industrial structure to explore the reasons for the decline in historic district vitality and propose strategies and recommendations for creating vitality in historic districts. The findings reveal that (1) the vitality of the Xuanen Xinglong Historic District showed a higher middle area than the surrounding area and more rest days than working days; (2) in terms of functionality, the degree of aggregation of POIs in catering, shopping and consumption, living services, and recreation and sports in the Xuanen Xinglong Historic District is high; and (3) the impact of POI data on district vitality is more significant for shopping and consumption and catering, followed by company and enterprise, hotel and accommodation, and recreation and sports, with other types of POIs having a weaker impact. The results can guide strategies for industrial upgrading and cultural tourism development for Xuanen Xinglong and other historic districts facing similar challenges.

Industrial park planning from the perspective of productive service industries: based on the mechanism of “form-flow synthesis”