Traditional patent classification is carried out manually by experts. With the development of big data, artificial intelligence and natural language processing technology, automatic classification of patents is becoming one of the important research directions in both academia and industry. The text classification technology can be applied to determine whether a patent application can be granted, aiding in the automation of processing and analyzing a large number of patent documents, thereby improving work efficiency. This paper focuses on the English texts from a vast number of patents, and proposes an automatic patent text classification method based on the graph neural network model, which is used to assess whether patent applications can obtain authorization. This article utilizes the deep learning algorithm TextGCN to learn on patents’ abstracts, leveraging the neighbor information and node features of graph-structured data. Through the neural network, it generates representation vectors for patents, facilitating the forecasting of patent authorization results. The experimental findings demonstrate that the deep learning approach applied in this study achieves commendable classification results. Compared to the Doc2vec and TFIDF methods, the TextGCN model shows improvements in terms of precision, recall, accuracy, and F1 score. This method can offer a dependable research foundation for automatic prediction of the grant status of patents.

Artificial intelligence (AI) , as a key technology driving global digital development, has become a focal point of attention for countries around the world in the latest round of technological competition and intellectual rivalry. Interpreting the strategies of major developed countries in promoting the AI industry can provide a cutting-edge perspective and reference for our country's policy framework in the field of AI in the intelligent era. This article selects the United States, Singapore, and the United Kingdom as case studies, starting from the interpretation of AI policies and initiatives to promote AI development, focusing on the efforts of major developed countries in advancing the AI industry, and comparatively analyzing the characteristics of their AI industry strategies. The study reveals that the United States is committed to maintaining its global leadership position, encouraging technological innovation, and emphasizing ethical issues in AI; Singapore strives to become a global center for AI solutions; while the United Kingdom highlights its status as a global scientific powerhouse, focusing on building a vibrant AI ecosystem as the core of its policy.

New quality productivity is the core engine for enhancing international competitiveness and securing future growth. This paper references internationally recognized rankings and combines industry trends to conduct a comparative analysis of the development of new quality productivity in China and the United States from three dimensions: innovation, creativity, and transformative power. The study shows that the United States holds significant advantages in its technological innovation system and industrial ecosystem, particularly in cuttingedge technologies. Through high-intensity R&D investment and the rise of unicorn companies, the U.S. has established a leading global industrial layout. In contrast, China demonstrates potential in catching up in certain
advanced manufacturing sectors, but still lags behind in achieving major innovative breakthroughs and in the completeness of its innovation ecosystem.

As Japan’s industrial technology innovation accelerator, new energy industrial technology development organization gathers officials, industries and universities, with the main task of “strengthening industrial technology” and “solving energy and earth environmental problems”, and is committed to exploring the seeds of future industrial core technologies, strengthening the foundation of medium and long-term industrial competitiveness, and the practical application of research results. On the basis of introducing the background information of the institution, such as its history, function positioning, research and development fields, organizational structure and operation, this paper attempts to sort out and analyze the characteristic operation mode and cases of the institution. Based on this, the successful experience of the institute is summarized from the aspects of scientific research management, government-industry-academic coordination, international cooperation, etc., which provides reference and reference for China to further improve its own science and technology innovation system and realize industrial upgrading and transformation and sustainable development.

As a “star player” in biological manufacturing, synthetic biology is reshaping many industries at an unprecedented rate, including biopharmaceutical, biological agriculture, personal care, high-performance materials, chemical energy and food health. Through further analysis of various links of synthetic biology industry chain, including upstream enabling technology, midstream enabling platform and downstream innovative application, we can find that this emerging field has vigorous vitality and great potential; by looking into the future development trend of this field, we can discover new industrial track, guide the future development of life and health, and stimulate the potential of new quality productivity.

Integrating resource transmission, collaborative filtering, and link prediction theories to systematically and innovatively express the “enterprise patent” relationship, and then accurately and effectively identify potential cooperative relationships between enterprises, helps enterprises enrich their technological dimensions and promote the process of industrial innovation. Based on competitive intelligence thinking and data from 7 415 technical patents in the field of perovskite solar cells, a dynamic transfer recommendation based on patent resource transmission, a heterogeneous network recommendation based on link prediction method, and a collaborative filtering recommendation based on patent text are constructed. By introducing adjustable parameters, the three are integrated into a recommendation system, enable enterprises to select patent resources and partners that require attention based on real-life scenarios. Research shows that the fusion perspective of hybrid recommendation systems provides a new research method for predicting potential relationships in disruptive technology enterprises. The constructed recommendation system achieves multi-dimensional expression of recommendation results that are “accurate, novel, and comprehensive”, providing decision-making and reference for future cooperation between enterprises.

This article fully utilizes the information of patent applications and rights holders contained in patent literature, and constructs an effective method for identifying technological opportunities from the perspective of patent applicants/patent holders, providing decision-making support for innovative entities to carry out technological innovation activities. Firstly, using invention applications and authorized inventions as data sources and based on the LDA model to explore potential technical topics, by cross judging the attention of patent applicants from enterprises and research institutes in recent years, identify technology opportunities with great development potential, and classify them into subject focused, market transformation, and R&D potential types. Secondly, using valid patents as the data source, by introducing patent strength indicators based on patent portfolio analysis methods, the primary driving entities of various types of technological opportunities are identified, and the technical competition elements of representative primary driving entities are analyzed in detail. In the empirical part, taking intelligent connected vehicles as an example, a total of 9 technological opportunities were identified, including 3 main focus, 3 market transformation, and 3 research and development potential each, with enterprises as the primary driving force.The results indicate that based on the cross trend of the number of invention applications by the “patent applicant/patentee” subject and the patent intensity of the two types of subjects, different types of technological opportunities with great development potential can be identified, and their market competition intensity can be judged, providing a new perspective for identifying technological opportunities.

Artificial intelligence (AI) technology, with its powerful data processing capabilities and deep learning algorithms, is driving unprecedented changes in the pharmaceutical industry. These changes span from the initial discovery and refined design of drugs, to the accelerated launch and intelligent production of pharmaceuticals, and even to the precision marketing of strategies and personalized medical services. Through the literature search method, this article systematically explores AI’s impact on various aspects of the pharmaceutical industry, including drug discovery and design, clinical trials, product launch and production management, marketing strategies. It highlights how AI has driven profound changes in the industry and summarizes the challenges faced by AI technology in the pharmaceutical field, providing a forward-looking outlook on future development trends. The global market value of AI in drug discovery is expected to continue growing, and its role in biopharmaceutical research and manufacturing is gradually emerging. AI is anticipated to bring sustained momentum to the development of the pharmaceutical industry.

近年来，我国科技情报界对于情报支持科学决策和战略决策的功能与作用的认识与实践在不断提升与深化。相对而言，对于情报支撑服务科技创新的思考研究与实践探索是不充分的。前者是“对上的服务”，为政产学研的中高层决策者服务，这基本属于“智库建设”范畴，这里暂且称之为情报决策服务；后者是“对下的服务”，直面科学研究、技术创新的一线与主体，为科学家和工程师服务，这里暂且称其为情报专业服务。在信息化的进程中，数字化一直在赋能图情行业，不断尝试提升支撑科技创新的情报服务的效率和效能，但当下的智慧化正在颠覆情报专业服务。

With the development of the industrial internet, the manufacturing industry is gradually transitioning from traditional product manufacturing models to emerging service-oriented models. This article selects 60 manufacturing enterprises from the panel of A-share listed manufacturing enterprises in Shanghai and Shenzhen as the research objects, and uses the fuzzy set qualitative comparative analysis (fsQCA) method to deeply explore the service-oriented transformation paths under different conditions from the perspective of “R&D manufacturing supply chain” in the manufacturing value chain. Research has found that: the level of digitalization is a  necessary condition for the service-oriented transformation of manufacturing enterprises; The service-oriented

The prediction of emerging technologies based on patent text data is of great significance for managers, who must focus on the direction of technology development, adjust technology research and development routes, and take the initiative in technology competitions. Taking the AI technology as an example, firstly, use grammatical analysis technology to identify noun phrases in English sentences and construct a noun phrase co-occurrence graph through the network word co-occurrence method. Secondly, a graph neural network model is built to implement co-occurrence graph link prediction and regression. Finally, link prediction and link regression results are combined to make technical predictions for artificial intelligence technology. The experimental results show that using the graph neural network to fuse the noun phrase co-occurrence graph method is more suitable for the prediction of emerging technologies in complex semantic situations and can obtain smaller prediction recognition granularity; in addition, the prediction results show that artificial intelligence technology is forward to application development in electronic meetings, computer vision, medical health, interactive interfaces, measurement and monitoring, machine learning algorithms, sensors, data channels, and intelligent manufacturing.

为贯彻落实国家科技创新大会精神，服务“创新驱动、转型发展”的重大战略，推动华东地区科技情报界适应经济全球化和重大科技变革的新时期、新形势要求，鼓励调动华东地区科技情报人员的积极性，提高自主创新能力，促进科技情报成果的开发利用，推进华东地区六省一市科技情报学会沟通与合作，2024年8月，华东六省一市科学技术情报学会组织评审2024年度“华东地区科技情报成果奖”，共授予“华东地区科技情报成果奖”142项，其中一等奖21项，二等奖50项，三等奖71项。

The development and governance balance of artificial intelligence technology is crucial for maintaining social security, improving the transformation efficiency and industrialization level of current AI technological achievements, and promoting high-quality development. At present, the two mainstream development views of artificial intelligence: “effective acceleration” and “super alignment” fail to reach a consensus, and also limit effective decision-making in the development and governance process. Based on the law of technological development of artificial intelligence, this paper proposes a trinity development concept of “alignment-acceleration-co-governance” , explores ways to transcend the theoretical boundaries of “effective acceleration” and “super alignment” , and provides a new development perspective for artificial intelligence.

Cell and gene therapy (CGT) refers to the process of transferring genetic material or cells into the patient’s body for disease treatment. As an advanced treatment, it involves a wide range of technologies and product categories, and broad clinical application. This article systematically reviews the key technologies and equipment and consumables involved in the upstream of the CGT industry, the drug production in the midstream of the industry, the market terminals and application scenarios in the downstream of the industry, and the contract research organization (CRO), contract development and manufacturing organization (CDMO) and inspection and test in the industry. According to the correlation and logical relationship between important technologies, we draw the CGT industry knowledge graph. Based on the knowledge graph, we analyzed key technologies such as target development, gene delivery strategies, new gene editing tools, and CAR molecular structure design. We further analyzed the development progress of chimeric antigen receptor T-cell immunotherapy (CAR-T therapy) , induced pluripotent stem cell (iPSC) therapy and nucleic acid drugs, and analyzed the function of CRO and CDMO in improving the development efficiency of the CGT industry. It can be foreseen that more technologies will be developed in the CGT industry, and the process of drug launch will be faster.

2024年适逢《竞争情报》杂志创刊20周年，借此契机，本刊邀请《竞争情报》杂志前执行主编张左之回望中国竞争情报近70年发展之路。自1956年《科学技术发展远景规划纲要》首次提出建立科技情报机构以来，中国竞争情报经历了启蒙探索、孕育研究、成长突破至转型创新四个阶段。从科技情报向经济领域延伸，对标西方学习先进，再到IT公司推动系统普及，竞争情报日益融入市场经济。未来，面对国际形势新变化，中国竞争情报要寻求新途径、新方法，以应对更加激烈的全球竞争。

With the rapid development of information technology, open-source intelligence (OSINT) has become an indispensable resource in the corporate decision-making process. Based on the Hall three-dimensional structure, this paper establishes a framework for the application of OSINT in corporate competitive decision-making and proposes a system of capabilities and services that should be constructed under this framework. Through an analysis of the competition in the offshore wind power industry, this paper preliminarily presents methods for collecting and producing OSINT products in the field of power grids.

Disinformation governance requires comprehensive measures, combining government supervision, platform governance, and media self-regulation into a co-governing force. Using evolutionary game theory, a tripartite model involving government, media platforms, and bloggers reveals the mutual strategic influence in disinformation governance. Results show that strict government supervision and process supervision can prevent platform inaction; excessive crackdown increases governance costs and causes platform slackness, hindering co-governance; strict government crackdowns, improved platform governance, and enhanced public resistance reduce disinformation benefits and creation. Currently, high-cost government governance requires long-term strategies to engage social forces in reducing disinformation benefits to lower governance costs.

With the increasing frequency of cross-border data flow, the security of enterprise data exit has become an issue that cannot be ignored. With the latest revision of the Anti-espionage Law of China, it is of great theoretical and practical significance to carry out anti-competitive intelligence research on enterprise data exit security. Starting from the legislative background and revision focus on the Anti-espionage Law of China, this paper analyzes the possible scenarios and security risks of enterprise data exit, discusses the feasibility and necessity of anti-competitive intelligence to ensure the security of enterprise data exit, and puts forward the anti-competitive intelligence working mechanism for enterprise data exit security under the framework of the Anti-espionage Law of China. Under the framework of the new Anti-espionage Law of China, enterprises should integrate the data outbound work and anti-competitive intelligence activities from three dimensions: organizational system, institutional system and technical system, and explore the construction of an active anti-competitive intelligence working mechanism with internal and external linkage, both offense and defense.

Institut des Hautes Études Scientifiques (IHÉS) is dedicated to mathematics, theoretical physics and to sciences at the interface of those disciplines. It is also the top research institution in Europe, comparable to the Institute for Advanced Study (IAS) . This article analyzes the development history, management structure, funding sources, and operation model of IHÉS, and summarizes its characteristics. The study found small and elite academic community, free and open academic atmosphere, academic influence of top talents, stable and efficient scientific research management are the important reasons, why IHÉS has become the top research hall of the world.

At present, China is in a complex environment of the technological revolution, industrial transformationt and “following, parallel, and leading”, which will be a great opportunity for the development of China’s scientific and technical intelligence work. Exploring and practicing the working mechanism of scientific and technological intelligence is of great significance to improve the ability of scientific and technological intelligence service and promote the development of China’s scientific and technological innovation. The development process of China’s scientific and technical intelligence work is reviewed in this paper, the key factors that lead to the prosperity and development of intelligence work are summarized, and the opportunities and challenges under the new situation are sorted out. The working mechanism of scientific and technological intelligence under the new situation are explored and practiced, that is, the construction concept and framework of scientific and technological intelligence consortium are putting forward. In order to provide replicable experience for the establishment of scientific and technological intelligence working system at the national or provincial level under the new situation, the aspects of clarifying the construction mode, establishing the  operation mechanism, and carrying out the pilot construction are described in detail.