Under the context of China's energy powerhouse strategy and the development of characteristic new-type think tanks, focusing on the talent mechanisms of central SOE think tanks in the energy sector, a systematic analysis of their current status was conducted. The research reveals that these institutes have established a five-dimensional influence system encompassing policy, enterprises, academia, international cooperation, and society, demonstrating notable achievements in strategic support, professional capacity, and institutional innovation. However, challenges persist, including delayed pilot implementations, talent structure imbalances, and rigid incentive mechanisms. Based on comparative case studies, a three-dimensional optimization framework was proposed: structuring strategic-level collaborations through “government-industry-academia-research-application”integration to establish four-dimensional talent development objectives, designing operational mechanisms including differentiated training, market-oriented incentives, and digital governance platforms, and instituting institutional reforms such as dual-track evaluation systems and intellectual property sharing arrangements. The conclusions provide theoretical foundations and practical pathways for advancing the modernization of talent teams in energy SOE think tanks and supporting national energy security strategies.

Based on the data of Shanghai and Shenzhen A-share listed companies from 2011 to 2022, a two-way fixed effect model was used to study the impact of digital transformation of enterprises in the Guangdong-Hong Kong-Macao Greater Bay Area on new quality productivity. The results show that the digital transformation of enterprises has significantly improved the level of new quality productivity. Mechanism-wise, the digital transformation of enterprises further promotes the development of new quality productivity by optimizing human capital, enhancing innovation quality, overcoming financing constraints, and broadening international perspectives. Heterogeneity analysis indicates that non-state-owned enterprises and high-tech enterprises perform more outstandingly in terms of improving new quality productivity in Guangzhou and Shenzhen.

The deep integration of the digital economy and real economy(DRI) serves as a pivotal strategy for driving China's high-quality economic development. Leveraging social network analysis (SNA), a DRI network was constructed using patent data from listed construction enterprises, their DRI levels were measured, and its impact mechanisms on corporate performance were investigated. Key findings include DRI significantly enhances corporate performance through dual pathways of knowledge breadth expansion and product competitiveness enhancement, with results remaining robust after addressing endogeneity concerns and rigorous robustness checks. Heterogeneity analysis reveals stronger performance improvements in high-tech enterprises, private-owned enterprises, and firms in growth/maturity stages, while stronger intellectual property protection and advanced digital infrastructure amplify these effects. Building on these insights, targeted policy recommendations are proposed to deepen DRI adoption in the construction sector.

Artificial intelligence is a new driving force for promoting the high-quality development of the economy. The mechanism of artificial intelligence promoting economic development through the optimization and upgrading of the industrial structure, technological innovation, and human capital was analyzed. Based on the panel data of 12 major cities in Hubei Province from 2013 to 2022, a fixed-effects model was constructed for empirical testing. The research found that artificial intelligence can significantly promote economic development. Artificial intelligence can drive economic development through three paths: the optimization and upgrading of the industrial structure, technological innovation, and human capital. The impact of artificial intelligence on economic development has regional heterogeneity. Finally, countermeasures and suggestions are provided to better promote economic development with the help of artificial intelligence.

Taking the research hotspot of “science and technology boosting rural revitalization” as the research object, the research hotspots and development trends in this field were explored through bibliometric analysis and CiteSpace software. The results show that in recent years, the research enthusiasm for “science and technology boosting rural revitalization” has continued to rise, mainly focusing on four aspects: industrial prosperity, talent revitalization, rural governance, and common prosperity. The research content mainly includes digital countryside, smart agriculture, green agriculture, modern agriculture, rural governance, vocational education, and so on. Meanwhile, emerging fields such as science and technology courtyard, digital economy, and green finance will become the key directions for future research.

Based on panel data from nine cities in Fujian Province, how trade between Fujian Province and ASEAN promotes industrial structure upgrading was analyzed. The empirical results indicate that increasing imports and exports to ASEAN can promote the upgrading and rationalization of Fujian Province's industrial structure. In regions with higher levels of economic development in Fujian Province, expanding trade has a greater positive impact on industrial structure upgrading. Financial support plays a positive regulatory role in the chain of expanding imports and exports to promote industrial structure upgrading. In the process of increasing exports and expanding imports in Fujian Province and ASEAN, innovation or boosting consumption are both beneficial for promoting industrial structure upgrading.

Green economic development has become a key path to achieve high-quality regional economic development and achieve the strategic goal of “carbon peak and carbon neutrality”. Based on the panel data of 268 prefecture-level cities in China from 2015 to 2022, a fixed-effect model was used to test the impact of government attention allocation intensity on the level of regional green economic development. It is found that the intensity of government attention allocation has a significant positive effect on the improvement of the level of urban green economic development, and the effect is more significant in areas with high public environmental attention and strong government environmental execution, and the upgrading of industrial structure is one of the important intermediary paths of the main effect. After the robustness test, this conclusion still holds.

The study of “production, living and ecological space” plays a significant role in optimizing national land layout, advancing ecological construction, and achieving sustainable development. Taking the central city of Lanzhou as the research object, based on POI(point of interest) data, grid division, sample square statistics, AHP(analytic hierarchy process) hierarchical analysis and GIS(geographic information system) spatial analysis techniques were used to identify and characterize the production, living and ecological spaces. The results show that the production space is concentrated in the periphery, the living space is clustered in the core area, and the ecological space is distributed in a decentralized manner.The quantity is dominated by the production and living space, the ecological space accounts for the smallest proportion, and there are very few mixed-function zones,and the four types of space all show obvious clustering characteristics. The study shows that POI data are scientific and practical in spatial identification and can provide reference for urban territorial spatial planning.

Using the logistics index from 2010 to 2022 and the DEA-BCC (data envelopment analysis and Banker-Charnes-Cooper) model, it is found that the static comprehensive logistics efficiency in China is 0.668, which is at a low level. Using DEA-Malmquist index method to analyze dynamic logistics efficiency, the total factor productivity is 0.981, and the overall productivity is slightly reduced. Tobit regression model was used to explore the factors affecting logistics industry efficiency, among which economic development level had a significant and weak negative impact on logistics efficiency. The degree of industrial agglomeration and the level of innovation have significant positive effects on logistics efficiency. The degree of government intervention, informatization level and opening to the outside world have no significant influence on logistics efficiency. According to the research results, some countermeasures and suggestions are puts forward to improve the efficiency of logistics industry in China, that is, to improve the level of logistics service, optimize the level of resource allocation and improve the capability of technology research and development.

To obtain accurate temperature and pressure data during downhole fracturing processes, a novel dissolvable fracturing ball is developed for collecting temperature and pressure data during downhole fracturing stages. This method utilizes the fracturing ball as the external structure, with pressure and temperature sensors as the core components for data acquisition. Based on a single-chip integrated circuit, data transmission was achieved through RS-485 communication, and data storage was accomplished via SPI communication. In accordance with the operational conditions of the novel dissolvable fracturing ball, experiments on pressure, temperature, and signal storage ball escape were conducted. The experimental results demonstrate that the design structure of the novel dissolvable fracturing ball meets the requirements of operational conditions, with excellent sensor acquisition accuracy. Its capability to read and store pressure and temperature data during downhole fracturing stages provides new insights for the digital transformation of oil and gas field exploration and development technologies.