Liaoning Province, as a paradigmatic region with the highest concentration of shrinking cities in China, enhancing the development of resilience-related networks is essential for improving urban risk management capabilities. This study utilized the TOPSIS entropy weight method, an adjusted gravity model, social network analysis, and disruption simulation to investigate the correlation strength and structural characteristics of urban resilient spatial networks in Liaoning Province from 2012 to 2022. We simulated changes in network structure under various attack scenarios and subsequently identified key influencing factors using the QAP analysis method. The findings are summarized as follows: 1) The spatial correlation network of urban resilience in Liaoning Province exhibits a distinct “core-periphery” structure, with overall correlation intensity remaining relatively low. Over time, the network has transitioned from a “dual-core independent leadership” pattern to one of “dual-core coordinated development.” At the subsystem level, networks related to economic, engineering, and innovation resilience demonstrate steady improvement, whereas the social resilience network undergoes a significant decline, adversely affecting overall network stability. 2) The overall network structure has steadily strengthened, with core cities exerting significant influence and maintaining substantial control over resources. Meanwhile, peripheral regions have leveraged their geographical advantages to generate notable inter-provincial spillover effects. 3) Under random attack scenarios, the resilient interconnected network displays marked structural vulnerability, evidenced by rapid declines in key indicators such as network efficiency and clustering coefficient. In contrast, the network demonstrates greater structural robustness under targeted attacks, with these indicators declining at a more gradual pace. 4) Economic development, population size, industrial structure, and infrastructure investment exhibit positive correlations with resilient connectivity, whereas geographical proximity and ecological environment quality show negative associations. Specifically, spatial adjacency intensifies competition for resources and environmental stress, while uneven distribution of ecological assets further constrains regional resilience enhancement.

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.

As the “bridge” and “medium” of urban-rural factor flow, rural innovation and en-trepreneurship breaks through the boundaries of rural physical space and gradually becomes an emerging driving force to promote the transformation of agricultural modernization in China in the new period. Rural innovation and entrepreneurship has led to the integration of primary, secondary and tertiary industries, but its productive projects are still centered on modern agri-culture. The mechanism of rural innovation and entrepreneurship's impact on agricultural mod-ernization has not been fully explored in the research field. This study uses county panel data of Zhejiang Province from 2014 to 2021 to identify the spatial and temporal evolution characterist-ics of rural innovation and entrepreneurship, and constructs a mechanism framework and empir-ical model based on the background of urban-rural integration and the dialectical relationship between innovation and entrepreneurship, to explore the effects and the mechanisms of rural in-novation and entrepreneurship on the Agricultural Modernization. The results show that: 1) Rural innovation and entrepreneurship in Zhejiang Province is characterized by obvious spatio-temporal heterogeneity. In terms of temporal characteristics, the level of rural innovation and entrepreneurship is on an upward trend. The level of rural innovation also shows an upward trend, but the level of rural entrepreneurship is more stable. Regarding spatial characteristics, there are concentrated and continuous high-value areas of rural innovation and entrepreneur-ship in northeast Zhejiang. Southwest Zhejiang is developing rapidly in rural entrepreneurship. 2) Rural innovation and entrepreneurship effectively drive the development of agricultural mod-ernization, and the narrowing of the urban-rural income gap strengthens the driving effect of rural innovation and entrepreneurship on agricultural modernization. 3) Rural innovation and rural entrepreneurship are closely related, but essential differences exist. Rural innovation can promote the development of agricultural productive services to accelerate the process of agri-cultural modernization. Rural entrepreneurship can promote the growth of regional consump-tion level on the demand side to drive the development of agricultural modernization. 4) On the geospatial scale, rural innovation and entrepreneurship in northeast Zhejiang have a more signi-ficant effect on agricultural modernization than that in southwest Zhejiang. On the administrat-ive scale, the driving effect of rural innovation and entrepreneurship on agricultural moderniza-tion at the county level is more significant than that of county-level cities. In the future, the rur-al innovation and entrepreneurship system should be improved according to local conditions, giving full play to the role of rural innovation and entrepreneurship as a medium in integrating urban and rural factors, and guiding the coordinated development of rural innovation and entre-preneurship.

As an important spatial carrier for regulating social health, urban green space plays a crucial role in promoting resident's physical and mental well-being and enhancing social cohe-sion. However, the academic community has not yet reached a consensus on which characterist-ics of green space are most closely related to resident's individual social health levels. Based on the survey data on green spaces and health collected in Guangzhou in 2021, this study first clas-sifies resident's individual social health using the latent profile analysis (LPA) method. Sub-sequently, it estimates the association between the characteristics of nearby green spaces in the residential areas and resident's individual social health through unordered multinomial Logistic regression. The results reveal that socio-demographic attributes such as age, work status, per capita monthly household income, and whether the household with a car can explain the differ-ences in individual social health among residents. Relevant planning and policy formulation should consider the diverse needs of groups with different socio-demographic characteristics for urban green spaces to fully leverage their social health benefits. In addition to resident's socio-demographic attributes, nearby green spaces in the residential areas have a significant impact on their individual social health. Specifically, there is a significant positive correlation between resident's subjective perception of green space accessibility and their individual social health. Quality characteristics of green spaces, including cleanliness, the number of recreational ser-vice facilities, safety, and aesthetics, are key factors influencing resident's individual social health. Therefore, constructing a complete and continuous urban green space system and im-proving the walking environment and walkability in neighborhoods and surrounding areas to enhance resident's subjective perception of green space accessibility are effective ways to pro-mote individual social health. Meanwhile, enhancing green space cleanliness, aesthetics, and safety can be achieved through regular cleaning and maintenance, strengthening green space management, and organizing volunteer activities. On the basis of balancing community needs and resource investment, appropriately increasing and diversifying recreational facilities in green spaces can further encourage residents to engage in physical activities and strengthen so-cial interactions. The conclusions can provide a scientific basis for improving the spatial qual-ity of urban green spaces, enhancing the interactive connection between residents and neighbor-hood green spaces, and fully leveraging the health effects of green spaces.

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.