[Objective/Significance] The deep integration of technological innovation and industrial innovation, as the core path to cultivate new-quality productivity, has long been a critical topic in theoretical research and practical exploration regarding its implementation mechanisms and promotion models. China boasts abundant context resources, and relying on context-driven integration of technological and industrial innovation (technology-industry integration) is a scientific choice aligned with China's development reality, serving as a key path to advance the upgrading of innovation ecosystems. [Method/Process] Based on an interdisciplinary perspective integrating context-driven innovation theory, innovation diffusion theory, and innovation ecosystem theory, this paper systematically analyzes the internal logic and practical approaches of context driven technology-industry integration. [Results/Conclusions] By sorting out typical domestic and international practical cases, it explores the theoretical logic of context in promoting the transformation of scientific and technological achievements and the upgrading of industrial formats, and further refines the practical paradigms and future evolution trends of context-driven technology-industry integration. The study aims to provide a theoretical basis and analytical framework for deepening the reform of the scientific and technological system, optimizing the allocation of innovation resources, and accelerating the cultivation of new-quality productivity, thereby facilitating the construction of an innovation ecosystem featuring positive interaction between science & technology and industry.

[Objective/Significance] Organoid technology, which enables the in vitro three-dimensional culture of adult stem cells or pluripotent stem cells to mimic the structure and function of human tissues, has brought about a transformative advancement in biotechnology. Analyzing the developmental trends of organoid research can provide valuable insights for the strategic planning and advancement of this field in China. [Method/Process] A total of 16971 research articles related to organoids were retrieved from the Web of Science Core Collection. Scientometric methods, BERTopic-based topic modeling, and text clustering techniques were employed to conduct a comprehensive analysis of publication trends, research countries, institutions, and authors. Comparative analysis was also conducted to examine thematic focuses and research frontiers globally and across leading countries. [Results/Conclusions] Organoid research is currently experiencing a phase of rapid development, with a steady increase in scholarly output. The United States, China, and Germany are the leading contributors to the field. Research efforts are predominantly concentrated in academic institutions, with a high degree of centralization. Current research in the organoid field primarily focuses on several key areas: organoid culture techniques, the establishment of organoid models for normal tissues and disease states, their application in drug screening and toxicity testing, and their potential in precision medicine.

[Objective/Significance] The rapid development of generative artificial intelligence(GenAI) is profoundly restructuring the global technology competition landscape. By analyzing the patent texts of leading GenAI companies, it provides experience and reference for the ecological construction and strategic layout of China's GenAI industry. [Method/Process] Based on the text data of 1059 patents from 19 American GenAI companies, keyword co-occurrence network analysis, LDA topic modeling and K-means clustering algorithm are comprehensively used to reveal the technological innovation characteristics and internal differentiation of American GenAI industry from the aspects of network structure, technical topic distribution and technical content attention. [Results/Conclusions] GenAI leading companies generally develop their layout in the three core areas of “algorithms, computing power, and data”. Based on core common AI technologies, they focus on their core businesses and resources, and conduct differentiated competition based on commercial application value. With the implementation of technology, an innovative ecosystem composed of four types of entities: emerging explorers, ecological layouts, integrated collaborators, and core drivers is formed. Based on the research findings, the paper discusses the development status of leading companies in the early stage of GenAI in the United States, and combines the development characteristics of China's GenAI industry to propose policy implications from three levels: enterprise, industry and policy.

[Objective/Significance] Rural revitalization plays a vital role in addressing issues related to agriculture, rural areas, and farmers (the “three rural” issues) and in promoting the modernization of agriculture and rural areas. This study aims to systematically review the current status, research hotspots, and evolution of rural revitalization studies in China, explore future research directions, and provide theoretical references for rural development practices. [Method/Process] Based on CiteSpace, this study conducts a bibliometric analysis of literature indexed in the CNKI CSSCI database since 2016, using rural revitalization (strategy) as the research keyword. The analysis employs author-institution collaboration network graphs, keyword clustering graphs, and temporal evolution graphs. [Results/Conclusions] The results reveal five major research hotspots: the concept and connotation of rural revitalization, rural governance and institutional reform, urban-rural integration and spatial coordination, poverty alleviation outcomes and common prosperity, and cultural construction and livable environments. The research on rural revitalization in China shows a clear disciplinary bias toward agricultural economics. Coupling practices involving policy evaluation, digital technologies, urban-rural integration, and common prosperity require further exploration. Additionally, interdisciplinary integration across different academic fields needs to be strengthened.

[Objective/Significance] With the rapid development of China's new energy automobile industry, enterprises urgently need to accurately capture user demand characteristics to drive continuous optimization and innovation of products and services. However, given the rapid updates and frequent hotspot shifts of Weibo topics, traditional demand analysis methods exhibit significant limitations in topic recognition comprehensiveness, demand hierarchy relevance mining, and dynamic evolution tracking. [Method/Process] By analysing the interaction data under the topic of new energy vehicle “BYD Han” in Sina Weibo, firstly the study employs the BERTopic model for topic modeling to identify and analyze hotspot topics. Secondly, it combines Maslow's Hierarchy of Needs Theory to analyze topic relevance, revealing the distribution characteristics of demand hierarchies. Finally, the Dynamic Topic Model (DTM) is used for time-series modeling of topics to uncover the evolution trends of user demands. [Results/Conclusions] The results show that hotspot analysis reveals user discussions mainly focus on new car releases, Chinese-style design, and product sales. Relevance analysis combined with Maslow's theory demonstrates that highly relevant topics are mostly concentrated in adjacent or the same hierarchy, verifying the hierarchical characteristics of user demands. Theme evolution analysis indicates that industry hotspot events significantly guide public attention, intensified market competition drives rationalization of consumption decisions, and brand marketing strategies profoundly influence user behavior. Due to its high consistency, the BERTopic model can identify and track changes in user demand more accurately than the LDA model.

[Objective/Significance] Emerging pollutants threaten ecology and health. Exploring their research hotspots and trends is of great significance for optimizing management and promoting innovation. This study combines bibliometrics and patent analysis to reveal knowledge evolution and technology direction from the perspective of scientific and technological innovation, and provides a basis for policy and scientific research. [Method/Process] Using bibliometrics and patent analysis, combined with information visualization technology, this paper systematically analyzes 37503 SCI papers and 3304 patents in the core collection of Web of Science and incoPat database, and excavates key information to sort out research hotspots, technological context and regional innovation trend. [Results/Conclusions] China and the United States, China and Republic of Korea are respectively in the forefront of the world in academic papers and patent applications. Personal care products, refractory organics, etc. are key research areas, and microplastic processing patents have grown rapidly in the past five years. The research divides the microbial treatment technology of emerging pollutants into four categories, and points out that the future will focus on the optimization of treatment technology, targeted monitoring and early warning system development.

[Objective/Significance] The nurturing and development of outstanding young scientists played a significant role in promoting the coordinated development of education-S&T-talent integration, as well as achieving breakthroughs in key core technologies and advancing new quality productive forces.[Method/Process] By conducting a combined quantitative and qualitative analysis of the resumes of 68 recipients of the “DAMO Academy Young Orange Award” from 2018 to 2023, this paper reveals common characteristics of these exceptional young scientific talents during their growth process across four dimensions: individual basic attributes, higher education background, professional experience, and growth cycle.[Results/Conclusions] The findings of this paper indicate that the shared characteristics of successful young scientific talents include: possessing an undergraduate degree and doctorate from top domestic and international universities; obtaining senior professional titles; and holding positions in first-rate scientific research institutions, especially high-level research universities. Additionally, experiences such as studying abroad or being a visiting scholar, along with overseas postdoctoral experience and moderate career mobility, contribute to accelerating the growth rate of young scientific talents; the average growth cycle for outstanding young scientific talents is 5.43 years. Finally, several recommendations are proposed to foster the emergence of more outstanding young talents in science and technology.