China’s higher education has entered the stage of a universal system, enrolling over 50% of students, and the Chinese government takes its high-quality oriented development as its educational goal. However, as the largest developing country in the world, the regional inequality is still a major obstacle to the equitable development of higher education in China. With the 1270 higher education institutions listed by the Chinese Ministry of Education in 2021 as the research objects, the degree of regional inequality of higher education development (HED), and its influencing factors, was visualized after being calculated by geo-statistical methods, such as geographical detectors. The results show that, first, HED in China shows regional linkage and hierarchical connection in high-value regions in the input and outcome dimensions. Second, the input dimension is still the leading factor restricting current HED in China. At the local scale, the geographical stratification characteristics of the four dimensions are evident. The restriction of the educational process covers a wide range and is concentrated in areas with the high-value regions of HED. The innovation of the research is the analysis of the geographical stratification of mechanisms, which identifies regional differences in the factors affecting HED in China.

The relationship between traditional village landscape genes and the geographical environment is closely intertwined, exhibiting notable spatial differences and cultural characteristics during scale transformations. To effectively elucidate the formation mechanisms of these landscape genes, it is essential to construct a multi-scale analytical framework that integrates multiple dimensions. This paper address these challenges by expanding the sample selection range and combining both qualitative and quantitative analyses of landscape genes across various scales. Subjective judgments reveal that macro conditions influence microscopic responses, which, in turn impact outcomes at the micro level. Similarly, quantitative analyses underscore the significant role of geographic factors in shaping architectural patterns, illustrating the interplay of geographic, cultural, and economic factors across different dimensions. Convergence analysis challenges the simplistic correspondence between subjective judgment and quantitative findings, indicating that macro-level geographic environmental features may not exert as substantial an influence on micro-level architectural clusters as previously assumed. Instead, there are instances where the internal spatial structure of clusters may transcends geographic constraints. The research paradigm centered on landscape genes offers a valuable approach to identifying the factors contributing to spatial disparities in traditional villages and advancing our understanding of the processes and mechanisms governing landscape gene inheritance, expression, and variation.

Enhancing rural resilience is crucial due to the significant vulnerabilities faced by rural areas, such as weak economic foundations, scarce resources, and deficient infrastructure. This paper aims to provide a comprehensive review of rural network resilience (RNR) to underscore its importance in understanding the mechanisms and pathways of rural sustainable development. To establish the theoretical foundations of RNR, we trace the evolution of resilience concepts and their applications across disciplines. The proposed analytical framework integrates evaluation methods from network science to assess RNR’s structural characteristics and outlines simulation techniques for predicting resilience under various risk scenarios. Furthermore, the paper examines the key influencing factors that shape RNR within complex rural regional systems, exploring the intricate evolutionary mechanisms involved. To bridge existing research gaps, a synergistic development perspective is introduced, emphasizing the interconnected, multi-layered nature of rural networks across societal, economic, and ecological domains. Additionally, a county-level analytical framework tailored for county-level rural resilience analysis is presented to offer strategic guidance for enhancing RNR and driving sustainable rural revitalization. This transdisciplinary synthesis propels RNR as an emerging field with significant policy implications.

Self-rated health status (SRHS) reflects individuals’ social environment, and the difference between urban and rural areas in China further highlights the impact of social environment on health. This paper aimed to systematically analyze and compare the impact mechanism of the SRHS of urban and rural residents from multiple dimensions, i.e., time, space, and scale. Drawing on data from the Chinese General Social Survey (CGSS) and China Statistical Yearbook, we used spatial, cross, and HLM analyses. Results indicate that: (1) From 2010 to 2017, the overall SRHS level of Chinese residents gradually declined; the gradient pattern of east, middle, and west became more marked, and the health level in rural areas generally fell behind that of urban areas. (2) The focus of SRHS moved toward mental health, and people’s perceptions of the social environment gradually became a key factor affecting health. (3) In the long term, the gradient allocation of medical service resources could narrow the gap between urban and rural areas to comprehensively improve regional health levels.