This paper explores the critical role of research assessment system reform in fostering a healthy research ecosystem and proposes a researchecologyoriented path for reforming the research assessment system. The article first analyzes the urgent need for a robust research ecosystem in building a science and technology power, emphasizing that reforming the research assessment system is a key prerequisite for creating such an ecosystem. Research assessment reform should return to the essence of scientific research, constructing a modern assessment system that aligns with research norms, stimulates innovation, and serves national strategic goals. Subsequently, the article delves into the deepseated issues within China’s research assessment system, including the indicator distortion during process of shifting from “breaking the four sole criteria” to “establishing new benchmarks”, systemic flaws in the underlying logic of assessment, and the inadequacy of assessment systems in meeting international competition demands. Building on this analysis, the article proposes four pathways for reforming the research assessment system: strengthening the theoretical and methodological foundations of research assessment, clarifying the internal logic of the assessment system, exploring a contributionoriented assessment system that focuses on the impact on the innovation system, and establishing a robust data infrastructure and institutional framework.

This paper examines the historical origins, practices, and insights of State-Organized Research (SOR) from the perspective of the shifts in global scientific centers. The paper focuses on analyzing the expansion of scientific utility, changes in the modes of scientific knowledge production, the perfection of higher education systems, and how these factors collectively contribute to the formation of SOR. Through historical examination, this study locates SOR within the dynamic process of the shift of global scientific centers, reveals its long-term correlation with the enhancement of national competitiveness, traces the developmental trajectory of China’s SOR, and examines its key innovative practices. On this basis, it puts forward several strategic initiatives for China to strengthen SOR and build a world scientific center, including improving the new system for mobilizing resources nationwide, strengthening national strategic science and technology forces, and establishing a global open innovation ecosystem.

The ongoing new round of scientific and technological revolution and industrial transformation is profoundly reshaping the global economic landscape. Future industries, exemplified by artificial intelligence, quantum information, and bio-manufacturing, have become strategic commanding heights in the competition among major powers. Focusing on the United States and India as primary case studies, this paper systematically examines and compares the strategic approaches, policy frameworks, and specific measures of the two nations in developing future industries amidst this technological revolution. Employing literature analysis and case study, the paper first traces the theoretical underpinnings and historical logic of statedriven future industry development. It then analyzes the current strategic deployments of the US and India within key technological domains. The analysis reveals that the US strategy is primarily driven by the imperatives of maintaining technological hegemony and national security, exhibiting “explicit” and “systematized” industrial policy characteristics. Conversely, India pursues economic ascendancy and technological self-reliance, adopting a leapfrogging development path that combines a “smart follower” strategy with leveraging “asymmetric advantages”.The paper concludes by summarizing the differences between the US and Indian development models, alongside their underlying drivers. Finally, it provides strategically relevant reference points and policy insights for China. These insights, spanning the dimensions of top-level design, innovation ecosystems, and international cooperation, aim to assist China in cultivating future industries and enhancing its comprehensive national competitiveness within a complex international environment.

By analyzing the connotation of technological power and establishing an analytical framework for technological leadership, this paper explores the competitive situation of the United States in Artificial Intelligence(AI) leadership from three dimensions: innovation capability, industrial capability, and innovation ecological competitiveness, and provides targeted suggestions for China. Adopting processtracking research to analyze AI competition of the United States, and using the data of AI research and industry from European and American universities and think tanks to support relevant competitiveness comparison and analysis. The paper considers that ,the AI strategy of the United States presents practicality ,efficiency and competition oriented. With the upgrading of competition in AI technological leadership, the United States recognized that a single export control on AI chips was ineffective. It began to shift its focus to innovative research, industrial development, and ecological construction as a whole. Through a series of measures such as R&D decoupling, security verification, chip deterrence, supply dismantling, standard dominance, and narrative confrontation, the United States aimed to gain technological leadership by competition. China can actively respond by jointly building highlevel domestic innovation system, AI+independent industry system and global AI governance system.

The rapid development of artificial intelligence (AI) technology holds immense potential to drive sustainable development. However, it simultaneously creates unpredictable risks, which intensify challenges in AI governance. In recent years, with the adoption of a peoplecentered governance philosophy, the United Nations (UN) and its specialized agencies have actively promoted global AI governance through rulemaking, standard development, capacity building and international cooperation, aiming to help developing countries bridge the AI gap and achieve fair, inclusive, and sustainable development of AI. These efforts seek to enhance the interoperability in AI governance and advance the formulation of coherent global rules. This paper provides a systematic overview of the key initiatives undertaken by the UN system in advancing global AI governance. It analyzes the internal and external drivers, enabling conditions, and constraints of UN participation in this field, and summarizes the practical experience gained by the UN. Based on four dimensions—philosophy implementation, model construction, pathway selection, and action demonstration—the paper proposes recommendations for China’s participation in global AI governance and the development of a diverse, collaborative, agile, flexible, and inclusive global AI governance system within the UN framework.

Brain-computer interface and artificial intelligence are key research fields that countries are competing to lay out, and to a certain extent, they represent a country’s scientific and technological innovation and comprehensive strength. To explore the impact of the application of artificial intelligence in the field of brain-computer interface, this paper conducts patent retrieval and analysis based on the IncoPat patent database, and conducts a comparative study on brain-computer interface patents (BCI patents) and artificial intelligence + brain-computer interface fusion patents (AI + BCI patents).Research shows that BCI patents as a whole are developing in an intelligent direction. The integration of artificial intelligence has injected vitality into the development of brain-computer interfaces and is conducive to the future development of the industry. China leads the industry in both BCI patents and AI+BCI patents, but there is still a considerable gap compared with the United States in terms of international market layout, technological influence and some specific technical fields. Research in our country is more concentrated in universities and research institutes, with relatively low participation of technology companies. In contrast, many foreign technology companies rank among the top in terms of the number of patents. India’s rapid development in AI+BCI patents deserves attention. Therefore, China should deepen the integrated development of artificial intelligence and brain-computer interfaces, strengthen patent monitoring and early warning in key regions and directions of brain-computer interface, increase support for key and weak technologies such as implantable electrodes, and further improve the quality and international influence of BCI patents.

With the widespread application of large language models (LLMs) across various fields, issues related to privacy governance and their own risks have become increasingly prominent. This paper systematically explores the dual nature of LLMs in privacy protection: on one hand, LLMs, as intelligent tools, can enhance data security capabilities, such as improving the accuracy of code vulnerability detection tasks; on the other hand, they face typical privacy attacks, including gradient leakage, membership inference, and personal identity information disclosure, posing significant privacy risks. Based on China’s legal framework for cyberspace governance, this paper reviews the compliance applications of LLMs in privacy protection according to the structure of preventive obligations, processing rules, rights protection, and incident response. It also analyses typical privacy attacks and defense methods targeting LLMs, and discusses measures to enhance LLM security from a full lifecycle perspective of “data-training-inference”, highlighting the fundamental conflict between model scale expansion and privacy protection needs that must be addressed in the future.

In the global strategic layout of artificial intelligence, countries generally regard the establishment of new artificial intelligence talent training institutions as a key measure, and such institutions are also important carriers for countries to promote the coordinated development of education, science and technology, and talent. From the perspective of international practices, these new institutions show four major development trends: government-led co-construction with industry, academia, and research, cultivation of a pyramid-shaped talent team, project-driven coordinated development of education, science and technology, and talent, and establishment of a full-factor-supported guarantee system. In view of this, to promote the high-quality construction of China’s artificial intelligence talent training institutions, this paper analyzes the current domestic situation and challenges from the perspective of the integration of education, science and technology, and talents, and puts forward countermeasures and suggestions: 1) strengthen government coordination to establish a regular and systematic promotion mechanism; 2) refine training objectives to build a multi-level talent education system; 3) enhance project-driven mechanisms to integrate education, science and technology, and talent development; 4) promote inclusive AI education to improve AI literacy across society. These measures aim to build an artificial intelligence talent training network with Chinese characteristics to provide solid support for China’s strategic development of artificial intelligence.

Promoting the assetization and value realization of public data is a key issue of concern for major global economies. Through qualitative research methods such as literature review and comparative analysis, this paper summarizes the rule construction and models of public data assetization in China, the United States, and the European Union. It concludes that China has established a system for the development and utilization of public data through authorized operation, the United States promotes the development and utilization of public data through open access and the cultivation of data brokers, while the European Union emphasizes the reuse of public data to accelerate its development and utilization. Through a comparative study in three aspects，such as property rights delineation, pricing formation, and circulation and trading, it is found that, compared with the U.S. and the EU, China’s pricing rules for public data assets are more operational. However, there is room for optimization in terms of property rights and circulation and trading. To accelerate the assetization of public data in China, it is advisable to continue encouraging judicial practices for data rights protection, promote legislation on data property rights, accelerate the construction of a national unified open platform for public data, and strengthen the cultivation of data brokers in China.

In the context of global digital transformation, data policy has an important impact on national and regional economic development, social governance, and international competitiveness. Through the comparative analysis of data policies of China and Europe, it could provide reference for the further development and improvement of China’s data policies. For this reason, this research selects 10 representative data policies from China and the European Union, analyzes them by text mining such as LDA topic model and highfrequency words, and constructs a PMC index model to quantitatively evaluate and compare the data policies. Research has found that most of the data policies in China and the EU are in a good grade, and the gap between the scores is small, but the EU data policies are more balanced, the system is coordinated, the legal effect is high, and the protection of personal data rights is emphasized. China has built a multi-dimensional governance system with multiple policies, and its Data Security Law has become the only policy in all samples to achieve an excellent level, but it still needs to be improved in terms of legal construction, clear rights of subjects, and data sharing norms.

Bottleneck issues such as the decentralized structure of the technological innovation network in the industrial chain and insufficient collaborative efficiency between upstream and downstream segments of the industrial chain have constrained the overall competitiveness of China’s new energy vehicle industry. This paper, from the perspective of technological innovation networks, systematically explores the collaborative optimization mechanisms and implementation paths of the new energy vehicle industrial chain. First, social network analysis methods are employed to measure the structural indicators of the patent cooperation network, in order to understand the evolutionary characteristics of the technological innovation network; secondly, a coupling coordination degree model is used to evaluate the level of synergy between technological innovation and industrial development; furthermore, an obstacle degree model is introduced to identify major limiting factors, and a Tobit regression model is applied to explore their impact mechanisms. The study finds that: the inter-level coupling coordination degree of the new energy vehicle industrial chain in Shandong Province shows a “high-decline-fluctuation” trend, with the degree of synergy between technological innovation and industrial development continuously improving. After 2021, the “inflection point effect” is significantly released, gradually forming a virtuous interactive mechanism; the focus of obstacles shifts from “quantitative” to “qualitative” indicators, with infrastructure and market demand obstacles becoming the main bottlenecks; Tobit regression results further confirm the critical impact of innovation capability, supply pressure, and market demand on the collaborative development of the industrial chain.

This paper examines the Flanders Institute for Biotechnology (VIB) in Belgium as a case study, systematically analyzing its institutional context and developmental trajectory to elucidate the origins and implications of its distinctive “virtual institute” model. The study reveals that throughout VIB’s transformation from a regional innovation platform to an internationally recognized biotechnology hub, it has functioned as the designer, operator, and catalyst of a specialized innovation microsystem, demonstrating three core capabilities: rule design, resource integration, and project incubation. Drawing on empirical data and illustrative cases, this paper further investigates the structure and impact of these capabilities, demonstrating that VIB has evolved from a passive participant into a proactive leader within the innovation ecosystem by establishing and managing an efficient innovation value cycle. These insights offer valuable lessons for advancing reforms in China’s industry-university-research cooperation mechanism. Based on these findings, this paper recommends institutional and governance reforms in China’s research and development (R&D) sector, with a focus on strengthening institutional supply, innovating R&D organizational models, and expanding channels for capital integration. It further calls for the strategic rebuilding of the innovation ecosystem’s capacity to enhance the integration efficiency of industry, academia, and research, thereby supporting high-level self-reliance in science and technology and advancing the construction of a modern industrial system.