Universities and specialized, refined, distinctive and innovative (SRDI) enterprises are key supply and demand actors in regional innovation systems. Their coordinated spatial distribution is crucial for optimizing the allocation of innovation resources and building efficient regional innovation networks. Focusing on Beijing-Tianjin-Hebei, the Yangtze River Delta and the Pearl River Delta urban agglomerations, this study develops a theoretical framework to analyze the spatial mismatch between universities and SRDI enterprises. Methods including the spatial mismatch index, the optimal parameter-based geographical detector, and partial least squares (PLS) regression are employed to examine their spatial distribution patterns, mismatch characteristics, and influencing factors. The results indicate the following key findings. 1) Both universities and SRDI enterprises in the three major urban agglomerations exhibit significant spatial agglomeration characteristics. These can be broadly categorized into three typical patterns: a ‘single-center agglomeration’ model, a ‘multi-core networked’ model, and a ‘deep specialization broad higher education’ model. The latter is exemplified by the Pearl River Delta region, where SRDI enterprises are highly concentrated in Shenzhen, while higher education resources are clustered in Guangzhou. Bivariate spatial analysis further shows that the spatial distributions of universities and SRDI enterprises demonstrate a relatively weak positive spatial autocorrelation overall. Among the three urban agglomerations, the Beijing-Tianjin-Hebei region displays the strongest spatial association between the two, followed by the Yangtze River Delta, while the Pearl River Delta shows comparatively weaker spatial linkage. 2) A widespread spatial mismatch exists between universities and SRDI enterprises, with notable variations in both the degree and types of mismatch within each urban agglomeration. These mismatches exhibit multi-level structural differences across cities. Specifically, the Pearl River Delta demonstrates a relatively high overall level of matching between universities and enterprises. In contrast, the Yangtze River Delta exhibits more pronounced spatial mismatch phenomena, characterized by a higher prevalence of ‘dual-low positive mismatch’ types, where both universities and enterprises are relatively underrepresented but maintain a positive spatial relationship. Meanwhile, ‘enterprise-dominated negative mismatch’ and ‘dual-high negative mismatch’ types—indicating imbalances where either enterprises or both entities are disproportionately concentrated—are less common. 3) The spatial mismatch between universities and SRDI enterprises is jointly driven by multiple dimensions of factors. Among these, road network density and elevation provide fundamental geographical and infrastructural conditions. Economic development levels and the scale of talent cultivation in higher education institutions create structural tensions that shape spatial alignment. In addition, public cultural resources and the quality of the business environment play important moderating roles, influencing how effectively universities and enterprises can colocate and interact within the urban innovation system. Overall, these findings contribute to a deeper understanding of the spatial organization and interaction mechanisms of innovation actors, offering valuable insights for policy-making aimed at enhancing regional innovation efficiency.

Establishing off-site R&D centers in innovation-rich regions is crucial for enterprises in peripheral areas to overcome the constraints of the “agglomeration shadow” and construct a regional collaborative innovation system. Based on the data of high-tech enterprises and their associated enterprises in Hebei Province, this study systematically examines the layout characteristics, industrial correlations, and internal and external driving factors of enterprises' off-site R&D centers. The findings are as follows: 1) In terms of the layout characteristics of departure locations, there are significant disparities in the number of off-site R&D centers among prefecture-level cities. Shijiazhuang leads significantly with a 24.91% share, forming the first echelon. Leveraging their locational advantages, Langfang, Baoding, and Tangshan have prioritized setting up off-site R&D centers in Beijing and Tianjin, thus forming the second echelon. In contrast, Xingtai, Hengshui, and Chengde are relatively underdeveloped with sluggish growth in the later period. 2) In terms of the layout characteristics of destination locations, offsite R&D centers have gradually expanded from the initial local agglomeration adjacent to central areas to distant innovation-rich regions, forming a multi-tiered spatial layout that covers megacities with high innovation levels, regionally innovative provincial capitals, and coastal cities with a high degree of trade liberalization. 3) The driving factors for the layout of enterprises' off-site R&D centers exhibit the characteristics of internal and external coordination: at the enterprise level, capital reserves, locational attributes, and innovation cooperation levels are the main internal driving factors for their layout; at the urban level, talent cultivation, population density, and digital infrastructure play a facilitating role in the layout, while the lag in the business environment exerts a significant crowding-out effect.

The intensification of climate change and human activities has exposed the world to highly complex ecological risks. Identifying ecological security patterns based on ecological security early warning constitutes the theoretical foundation and practical support for ecological risk management. Taking the Poyang Lake Basin as the study area, this paper conducts an ecological security early warning assessment using a CNN-LSTM model. By integrating the early warning results with the MSPA method and circuit theory, a basin-scale ecological security pattern was constructed, and targeted protection measures were proposed for the identified ecological restoration areas. The results indicate that: 1) The CNN-LSTM model demonstrates strong predictive capability and high accuracy in ecological security early warning assessment. The ecological security early warning in the study area exhibits a spatial pattern of high in the surrounding areas and low in the central region. 2) Ecological source area 26 405 km2, 29 ecological corridors, 149 ecological pinch points, 968 ecological barrier points, and 96 ecological break points were identified, leading to the construction of an ecological security pattern with a “five zones and three belts” configuration. Based on an “early warning-pattern” coupled framework, this study organically integrates ecological security early warning with ecological security patterns to achieve comprehensive spatiotemporal ecological risk management. This research provides theoretical and methodological support for watershed ecological protection, restoration, and the enhancement of ecosystem functions.

The wine industry, as a representative sector combining both cultural attributes and consumption-oriented characteristics, serves as a crucial vehicle for promoting high-quality regional economic development and meeting the growing needs for a better life. However, in recent years, China's wine industry has fallen into a dilemma of simultaneous declines in both output and consumption. Existing studies have predominantly focused on the supply side, while insufficient attention has been paid to the spatial mechanisms of demand. This paper argues that inadequate market demand constitutes the core constraint underlying the current downturn, primarily due to the absence of the “home market effect” and the “price index effect,” which together result in weak consumption performance and limited market expansion. To address this issue, this study builds upon the theoretical framework of New Economic Geography and integrates an agent-based modeling (ABM) approach to dynamically simulate the evolution of China's wine industry under multiple counterfactual scenarios. By incorporating both supply-side and demand-side interactions into a unified analytical framework, the paper aims to uncover the endogenous mechanisms shaping industrial spatial dynamics and market outcomes, as well as their policy implications under different development paths. The results yield 3 main findings. First, the relaxation of cost constraints can fundamentally reshape spatial equilibrium. A reduction in production costs enhances the competitiveness of domestic wine by amplifying both the price index effect and the home market effect, thereby expanding market size and improving the relative position of domestic producers. Second, spatial product differentiation strategies play a critical role in fostering competitive advantages. By increasing product heterogeneity, domestic wine producers can attract more consumers, which in turn leads to a rise in the number of firms and an expansion of market share. Third, the coordinated interaction between demand and supply across space is essential for breaking the current impasse. When domestic wine gains a cost advantage, the expansion of demand significantly strengthens the home market effect, effectively reversing the import-dominated market structure. Meanwhile, the price index effect facilitates a mutually beneficial outcome for both producers and consumers and promotes a more balanced spatial distribution of production and consumption. These findings suggest that the development of the wine industry in China should not rely solely on supply-side improvements, but must also place greater emphasis on demand-side cultivation. In particular, fostering a wineoriented lifestyle and enhancing consumer engagement are critical to unlocking market potential and sustaining long-term growth. By integrating New Economic Geography with computational experimental methods, this study constructs a comprehensive analytical framework that jointly considers supply and demand dynamics. It not only contributes to the theoretical understanding of spatial economic processes in cultural consumption industries, but also provides methodological insights and policy implications for promoting the high-quality development of regionally distinctive industries.

Cultural empowerment has emerged as a critical strategic pathway to promote rural revitalization and modernization. This paper constructs a logical framework of cultural em-powerment for rural revitalization, and analyzes the multi-dimensional value coupling mechan-isms and cultural IP construction pathways. The results show that: 1) Cultural empowerment for rural revitalization follows the logic of “value identification and coupling-resource capitaliza-tion and IP reconstruction-spatial restructuring and industrial operation”. The essence is to achieve innovative transformation with characteristic IPs through exploration and integration of cultural resources and value coupling, thereby promoting spatial restructuring and industrial op-eration to empower rural revitalization. 2) The multi-dimensional value attributes of cultural empowerment interact and transform with each other, and each value dimension forms a two-way coupling with the goal of rural revitalization. By fully activating the economic, spiritual, governance, ecological, and life well-being values of rural cultural resources, it promotes the construction of rural civilization, industrial integration, governance innovation, ecological liv-ability, and prosperous life in a coordinated manner. 3) Cultural IP construction constitutes a key path for cultural empowerment of rural revitalization. Through resource exploration and IP design, IP spatial structure and scene construction, as well as IP brand promotion and industrial integration, the industrialization of cultural resources and the comprehensive rural revitaliza-tion can be achieved, forming the logic of “value coupling- value embedding-value transforma-tion”. In the future, cultural empowered for rural revitalization should focus on the research of basic theories, spatial structures, path models and guarantee mechanisms for cultural resource industrialization, cultural IP construction, regional public brand cultivation, county-town-vil-lage cultural IP system construction, and gradually establishs a research system of cultural em-powerment to support comprehensive rural revitalization and urban-rural integrated develop-ment.

To explore the variations of aeration zone soil specific yield under the condition of deep buried groundwater, The southern edge of Gurbantunggut Desert was taken as the research area by field in-situ observation.The complete specific yield under the condition of zero surface flux, the average releasing specific yield under the condition of evapotranspiration and the average charging specific yield under the condition of lateral leakage recharge were determined, and the effects of groundwater depth, infiltration and evapotranspiration on specific yield were discussed. Results showed that: 1) It is feasible to determine the soil specific yield under the condition of deep buried groundwater by the zone of aeration section water content method. 2) Under the condition of zero surface flux, the complete specific yield μ increases with the increase of groundwater depth H. When the groundwater depth exceeds the maximum rising height of capillary water, the change of complete specific yield is small and can be approximately regarded as a constant. 3) The average groundwater depth of interdune land in the southern edge of Gurbantunggut Desert is 8.80 m. The complete specific yield under the condition of zero surface flux is 0.36, the average releasing specific yield under the condition of deep buried groundwater evaporation is 0.13, and the average charging specific yield under the condition of lateral leakage recharge is 0.17. The results of this study can provide a new idea for the determination of soil specific yield under the condition of deep buried groundwater.

Return migration has become a notable socio-economic trend in the new stage of China's urbanization, and the analysis of its driving mechanism has received extensive academic attention. As a micro behavior, the return of migrants is not only affected by personal and family factors, but also closely related to external environment. However, existing studies have focused on the role of individual factors, but not enough research has been conducted on the relationship between regional contexts and return migration. We introduce a gradient boosting decision tree model in the field of machine learning, based on the data from the 2017 China Migrants Dynamic Survey, with the return intention as the response variable and the regional contexts—Both in the place of origin and destination—As well as migrants' personal and household factors as the explanatory variables, focusing on the non-linear influence of the regional contexts on the return migration intentions and the threshold effect. The results show that: 1) The total contribution of the local contexts of the place of place of the origin and destination to the intentions of the migrants to return is 44.1%, which is an important factor influencing the return intentions, and the contributions of the two places is roughly equal. Among these, medical and health resources and air pollution are extremely important in both places. In addition, economic growth in the place of origin is also important for the return intention of migrants, while the climatic condition in the place of destination is more important; 2) There are both non-linear and linear relationships between local contextual factors and migrants' intention to return. Among them, medical and health resources, basic education resources, air pollution have obvious non-linear effects on the return intention, while economic growth and temperature conditions have mainly linear effects; 3) The influence of individual factors on return intention is mainly nonlinear effect. There is an irregular U-shaped relationship between age, migration duration and return intention, and the non-linear influence of household income is more complex. There is an obvious threshold effect between household housing expenditure and return intention, and a negative correlation between migrant's education level and return intention. This study incorporates the local contexts of the place of origin and destination into the analytical framework for the mechanism of return migration, identifies the relative importance of the local context and individual characteristics of the two places on the return intention of the migrants, and reveals the specificity and complexity of internal return migration in China, which contributes to deepening the research on migration in the new era and provides scientific reference for policy makers.