Search

Based on the theory of regional innovation niches, this study calculates the resilience of regional innovation ecosystems and constructs a comprehensive evaluation index system for regional artificial intelligence development, resulting in a panel dataset for 30 provinces in China from 2009 to 2021 (excluding Tibet, Hong Kong, Macao, and Taiwan). Within the framework of the construction of innovative provinces, regional artificial intelligence, and the resilience of regional innovation ecosystems, spatial double-difference and double machine learning models are employed for a quasi-natural experiment. The main research conclusions are as follows: (1) Both the construction of innovative provinces and artificial intelligence have a significant positive impact on the resilience of regional innovation ecosystems. (2) However, regional artificial intelligence exhibits a negative spatial spillover effect on the resilience of regional innovation ecosystems. (3) The construction of innovative provinces can positively moderate the effect of artificial intelligence on the resilience of regional innovation ecosystems. (4) Through the promotion of regional artificial intelligence, the construction of innovative provinces can indirectly enhance the diversity, evolutionary potential, buffering capacity, fluidity, and coordination of regional innovation ecosystems, thereby driving a leap in resilience. (5) The mechanisms by which the construction of innovative provinces stimulates regional intelligent input, application, innovation, and market dynamics to further enhance the resilience of regional innovation ecosystems are effective not only in the treatment group but also in the control group. [ABSTRACT FROM AUTHOR]

In recent years, propelled by societal transformations and technological advancements, emerging technologies founded upon diverse disciplines such as financial and information technology have rapidly evolved. Identifying the trends associated with these emerging technologies and extracting their salient topics is crucial in order to accurately grasp the developmental trajectory of these tools and for their efficient utilization. In this study, we chronologically categorize information derived from five types of multi-source data, including journal articles, patent inventions, and industry reports, into distinct periods. We employ the LDA (Latent Dirichlet Allocation) topic model to identify emerging technological themes within these periods and utilize a dual-index theme lifecycle analysis method to construct a hotspot theme distribution map, thereby facilitating the extraction of significant themes. Through empirical research on blockchain financial technology, we ultimately identify 22 thematic areas of blockchain finance and extracted eight prominent themes, including financial technology, cross-border payments, digital invoices, supply chain finance, and decentralization. By analyzing these themes alongside their respective popularity levels, we validate that the methods above can be used to effectively identify emerging technological hotspots and illuminate their developmental directions. [ABSTRACT FROM AUTHOR]

During the mining process of coal mines, coal pillars are often formed in the goaf on three sides, and the stress behavior of coal seams has a significant impact on the safety of coal mines. The upper part of panel 3104 of Xinwang Coal Mine is the room-pillar goaf of the 2# coal seam, and the lower part is the goaf of the 7# coal seam. The same coal seam is adjacent to the goaf of panel 3102. Therefore, there are hidden dangers for safe mining in panel 3104 affected by the goaf on three sides. Through FLAC3D numerical simulation, on-site Pasat-M detection, microseismic monitoring, and support resistance measurement, the stress distribution law of surrounding rock in the working face is analyzed. The following conclusions are obtained. There are several high wave velocity stress concentration areas in the coal body of 3104 working face. During the mining of the working face, the mining influence 90m in front of the working face began to spread to the area of the left coal pillar, and the vertical stress at the left coal pillar began to increase. Stress concentration appears in 0–20m strata at the top of 3# coal seams. At the top of a 3# coal seam, the vertical stress concentration coefficient can reach 2 in the range of 4–12m. The influence range of 3104 working face mining advance can reach 200m. Under the influence of mining, a large number of microseismic events occurred at 160m above and 150m below 3# coal seam. This law has reference value for the mining strata behaviors of coal seams under similar conditions.

Against the backdrop of an ongoing energy revolution, this study measured the regional green energy efficiency and ecological niche suitability of high-tech industry innovation ecosystems using the Super-SBM and entropy methods. We employed panel data from 30 mainland provinces (excluding Tibet) from 2009 to 2021 to conduct a quasi-natural experiment using spatial difference-in-differences models and double machine learning models. This was performed in order to investigate the impact mechanisms of the transformation of ecological niche suitability within the innovation ecosystems of high-tech industries driven by regional breakthrough innovation change strategies on green energy efficiency. The findings of this study revealed the following: (1) Driven by regional breakthrough innovation strategies, the transformation of the ecological niche suitability of high-tech industry innovation ecosystems has significant and positive local effects and spillover effects on green energy efficiency. (2) Regional breakthrough innovation strategies have a significant and positive mediating transmission effect on green energy efficiency through the development and optimization of internal factors within the ecological niche suitability of high-tech industry innovation ecosystems, including innovation entities, support, vitality, resources, and environment. (3) The transformation of the ecological niche suitability of high-tech industry innovation ecosystems driven by regional breakthrough innovation strategies promotes the advancement and rationalization of the industrial structure, thus indirectly enhancing regional green energy efficiency. These findings are of paramount importance for propelling the next wave of regional disruptive innovation reform strategies, ensuring that the outcomes of these reforms drive the ecological niche suitability of high-tech industry innovation ecosystems toward the advancement and realization of clean and efficient energy utilization. [ABSTRACT FROM AUTHOR]