Building a strong country in science and technology requires not only research outputs, but also the ability to move them into engineering systems, industrial settings and business organizations. As China’s university technology transfer reform shifts from institutional change and platform building toward capability building, the main bottleneck is increasingly the shortage of interdisciplinary talent and whole-process organizational capacity. Using literature analysis, functional comparison and typical-case analysis, this article defines Technology Business Schools as hybrid organizations integrating education with transformation platforms. Their central task is to train technology transformation managers through real projects, multi-mentor collaboration, platform embedding and case-based learning.

Large language models provide new technical support for smart policing with their capabilities in natural language understanding, text generation, semantic retrieval and task reasoning. They can improve policing efficiency in alarm summarization, document assistance, police knowledge question answering, anti-fraud warning and clue integration. However, their application may also cause risks such as hallucinated outputs, data security vulnerabilities, algorithmic opacity, unclear responsibility and technological dependence. To ensure standardized application, governance mechanisms should be improved in private deployment, data desensitization, police knowledge base construction, human review, hierarchical authorization, log retention and model evaluation.

In response to challenges in petroleum technology practice—including delays in data feedback, insufficient digital twin validation, and fragmented on-site collaborative decision-making—this study investigates an innovation model driven by the integration of artificial intelligence and digital twins. It outlines the foundational elements of full-chain oil and gas data, field and pipeline network mapping, and intelligent algorithm applications, and presents practical approaches for leveraging operational data from the field to drive decision-making, validating strategies through digital twin simulations, and enabling collaborative decision-making through intelligent reasoning.

Generative AI therapeutic landscape is an emerging interdisciplinary field. Based on a theoretical review and virtualization challenges , this article proposes an integration mechanism, analyzes three application scenarios, and offers policy recommendations on standardization, pilot testing, and data security. The findings show that generative AI transforms therapeutic landscapes from static, preset physical environments into intelligent, personalized, and affective dynamic systems, providing a technical path and policy reference for the digital wellness industry shifting from spatial provision to intelligent service.

Under the background of rural revitalization and the Digital China strategy, artificial intelligence brings business model innovation and efficiency improvement to rural cultural tourism, while also raising challenges such as data privacy, algorithmic bias, and technological unemployment. This study, from the perspective of artificial intelligence, systematically explores the sustainable development paths of rural cultural tourism. The research finds that although intelligent methods can improve operational efficiency and visitor experience, without regulation, they may erode personal privacy, solidify social injustice, and impact local employment. To address this, the paper constructs a multidimensional path system that includes technological optimization, talent cultivation, and policy coordination, aiming to achieve high-quality and inclusive development of rural cultural tourism in the digital era and empower rural revitalization.

In recent years, artificial intelligence has been deeply integrated into various business scenarios of libraries, bringing new data security risks that traditional protection systems are difficult to cope with. Focusing on the current situation from three aspects including institutional norms, technical deployment and operational management, this paper summarizes three major core risks in libraries: data fusion risks, algorithm black box risks and external dependency risks. Corresponding countermeasures are put forward, such as deploying privacy computing technology, implementing algorithm security auditing, and optimizing supply chain management. The research findings can provide practical references for libraries to establish a proactive defense-oriented data security system, and boost the high-quality development of smart libraries through the improvement of data security governance capability.

Industry-academy integration is a key mechanism connecting knowledge production and industrial practice, and its model evolution is profoundly influenced by changes in technological paradigms. As a general purpose technology, artificial intelligence is reshaping the operational logic of industry-academy integration from the ground up. Based on an analysis of traditional integration models, this paper examines the reconstructive effects of artificial intelligence on their coupling structure, operational mechanisms, and evolutionary paths. It proposes a model reconstruction framework based on the three dimensions of “knowledge-organization-value” and discusses the theoretical characteristics and enabling conditions of the new integration model. The study suggests that industry academy integration driven by artificial intelligence will move from linear collaboration to ecological symbiosis, from institutional coupling to algorithmic coordination, and from resource exchange to intelligent emergence.

With the continuous advancement of the industry-education integration strategy, universities face numerous challenges in coordinating student management and employment stability, while big data technology can effectively address these issues. Based on a three-dimensional framework of student development, industrial demand, and collaborative ecology, this paper explores its specific application approaches and proposes practical solutions including building an integrated big data platform, creating dynamic student profiles, strengthening industry-education data collaboration, and implementing a full-cycle tracking mechanism. A guarantee mechanism is constructed from four aspects: data security, sharing systems, faculty strength construction, and efficiency evaluation, to promote the synchronized resonance and collaborative improvement of student management and employment stabilization. This research provides theoretical basis and practical guidance for colleges and universities to optimize the level of talent cultivation and promote high-quality employment of graduates.

As AI rapidly integrates into corporate operations, more employees are experiencing AI anxiety, which may lead to negative consequences such as pro-organizational unethical behavior. Drawing on the cognitive appraisal theory of stress, this study examines the mechanism through which AI anxiety influences pro-organizational unethical behavior, using 320 two-wave survey responses. The paper also presents a case study of a smart manufacturing firm that implemented an “AI transformation psychological safety intervention program” to alleviate AI anxiety and its adverse effects, offering actionable management strategies.

While large e-commerce brands successfully use data-driven models to reduce costs, complex pricing algorithms remain too technical for small and medium-sized enterprises (SMEs), preventing them from leveraging AI. To bridge this gap, this paper develops an accessible agent-based pricing system tailored for SMEs. By combining machine learning and profit optimization models, it provides smaller merchants with robust, data-driven decision support.

In the era of digital intelligence, archives, propelled by DeepSeek, will undergo a brand-new transformation and upgrade. This article combines the full lifecycle business processes of archives to analyze the exploration and application of DeepSeek in archives, aiming to explore the realization value of the integrated development of archives and DeepSeek, and propose a top-level design plan, with the hope of promoting the high-quality development of archives.

Natural resources investigation and monitoring is a systematic, complex and comprehensive work, which puts forward higher requirements for the efficiency, accuracy and real-time performance of investigation and monitoring. This paper systematically expounds the specific applications of surveying and mapping geographic information technology in natural resources investigation and monitoring, and deeply discusses the core advantages of this technology in the links of spatial data management, storage, processing and analysis, aiming to provide technical support for the rational planning and sustainable utilization of natural resources.

China’s bio-manufacturing industry is rapidly emerging as a national strategic frontier and a core driver of the bioeconomy, serving as a critical leverage point for achieving leapfrog development. Supported by policy momentum, technological breakthroughs, and accelerating industrial expansion, the industry is entering a phase of high-speed growth. However, it continues to face a range of structural bottlenecks, including fragmented regulatory frameworks, lagging institutional supply, weaknesses in foundational and enabling technologies, insufficient synergy across innovation and industrial chains, reliance on imported key raw materials, and shortages in talent supply. These challenges collectively constrain the sector’s high-quality development and global competitiveness. To address these issues, the study proposes corresponding policy recommendations. The research aims to provide strategic insights and policy guidance to advance China’s bio-manufacturing industry toward scaled, systematic, and high-quality growth.

Against the dual background of the comprehensive advancement of industrial digitalization and the restructuring of the global electronic information industry chain, clustering serves as the core organizational form for the high-quality development of the electronic information industry. The co-evolution of the two has become a crucial approach to breaking through bottlenecks in industrial development. At present, China’s electronic information industrial clusters generally face problems such as homogeneous layout, insufficient independent innovation capacity, low efficiency of industrial chain collaboration, lagging digital transformation of small and medium-sized enterprises, and imperfect brand and public service systems, which restrict the process of high-quality development. Empowering cluster division of labor and collaboration, innovation transformation, resource allocation and brand building with digital technologies, promoting the dual-wheel drive of institutional innovation and technological innovation, strengthening the leadership of leading enterprises and the integration of large, medium and small enterprises, and improving cluster public services and digital governance platforms can effectively realize the in-depth synergy between cluster-based development and high-quality development. This will help the industry climb to the high end of the global value chain and enhance the resilience and international competitiveness of the industrial and supply chains.

As an advanced form of productivity led by technological innovation and breaking through the traditional mode of productivity development, the cultivation process of new quality productivity is deeply integrated with the development of the digital economy. The digital economy has become the core driving force for promoting industrial transformation and upgrading. This article analyzes the core concepts of new quality productivity and industrial transformation and upgrading, studies the mechanisms of technological innovation driven, factor allocation optimization, and industrial structure reshaping, and proposes optimization paths for core technology shortcomings, inefficient data factors, structural imbalances, and insufficient support. The aim is to construct a systematic framework for digital economy empowerment of industrial transformation and upgrading under the guidance of new quality productivity from the aspects of technological breakthroughs, market-oriented data factors, differentiated digital transformation, and improved support system.

This paper construct an indicator system by comprehensively utilizing AHP and entropy weight method to evaluate the security level of Liaoning’s high-tech industry chain including value chain, enterprise chain, supply and demand chain, and spatial chain. The results show that the security level has fluctuated and increased from 2010 to 2023, and the performance differs across sub-sectors. To promote safer development, Liaoning should leverage existing advantages, focus on shortcomings, strengthen independent innovation capabilities.

Driven by digital and intelligent technologies as its core forces, new-quality productivity is propelling the in-depth transformation of the automotive industry toward electrification, intelligence, and connectivity, placing brand-new demands on the cultivation of automotive professionals in higher vocational colleges. Taking digital-intelligent empowerment as the focus, integrating resources from colleges, enterprises and industries, and building a digital-intelligent driven industry-education integration community can effectively solve the disconnect between talent cultivation and industrial demand. This is achieved by constructing digital twin training platforms, developing intelligent teaching resource repositories, improving the dual-subject education mechanism of schools and enterprises, and establishing dynamically adaptive curriculum systems, so as to enhance the supply quality of technical and skilled talents and provide solid support for the high-quality development of the automotive industry.

This article, based on the development scenarios of cultural and tourism integration in Jiangxi Province, analyzes the transmission mechanism of digital technology empowering cultural and tourism integration from the perspective of terminology. On this basis, the study, based on terminology standardization and starting from multiple dimensions such as infrastructure, product innovation, and service consumption, proposes practical paths for the deep integration of cultural and tourism sectors empowered by digital technology in Jiangxi Province, aiming to provide theoretical references and practical guidance for comprehensively overcoming the digital bottlenecks of cultural and tourism integration and standardizing terminology application in Jiangxi Province.

Digital economy accelerates the intelligent transformation of regional industries. The design sector of Jiangxi’s digital industries has long been plagued by problems such as scattered knowledge, fragmented resources and inefficient collaboration. Taking the design knowledge system of Jiangxi’s digital industries as the research object, this paper constructs a technical framework of AI-enabled design knowledge graph, and implements the whole process including multimodal knowledge collection, ontology modeling, hybrid storage and dynamic update. The efficiency bottlenecks in semantic reasoning, industrial adaptation, knowledge updating and ecological collaboration are analyzed one by one. Systematic strategies are proposed, including graph neural network optimization, lightweight tool adaptation, knowledge security guarantee, incremental iteration mechanism and ecological collaboration. A path of intelligent organization and efficiency improvement of design knowledge suitable for Jiangxi’s regional characteristics is formed, which provides a feasible scheme for the intelligent upgrading of design in digital industries.

Virtual reality technology is a key driving force for the high-quality development of sports tourism, while accurate market analysis provides scientific support for the industry. Integrating Guizhou’s mountain resources and ethnic sports culture, this study proposes a VR–market analysis integrated framework covering scenario creation, product optimization, and industrial upgrading. The research shows that using virtual reality technology to enrich distinctive experience scenarios and employing market analysis to match resources with tourist demands can effectively solve issues like monotonous experience forms, supply-demand imbalance and weak brand influence in Guizhou sports tourism, further promoting industrial quality enhancement and business transformation. The findings offer theoretical support and practical references for innovating Guizhou’s sports tourism formats, applying VR technology locally and advancing high-quality industrial development.

The 15th Five-Year Plan fully deploys the “AI Plus” initiative, indicating that the relationship between artificial intelligence and industrial upgrading is evolving from simple technological superposition to profound in depth integration. Guided by the strategic orientation of the 15th Five-Year Plan, this paper systematically sorts out the theoretical logic, staged evolution and practical paths of industrial upgrading empowered by artificial intelligence, and constructs a coordinated promotion framework characterized by synchronous resonance. This paper holds that the core of collaborative advancement lies in properly handling the relationship between “substitution” and “integration”. It is essential to unleash the disruptive potential of artificial intelligence as a general-purpose technology, while anchoring its application in remedying industrial shortcomings and expanding comparative advantages, so as to find a dynamic equilibrium for coordinated evolution between transformative variables and quality increments.

As a critical category of advanced chemical materials, the localization substitution of lubricant additives and the enhancement of their supply chain resilience are vital to the security of high-end manufacturing industrial chains. This paper focuses on the improvement of supply chain resilience within the context of localization. It first analyzes the competitive landscape of the global market—where foreign capital dominates high-end segments while domestic enterprises compete in the mid-to-low-end range—as well as the development opportunities and shortcomings of China’s industry under policy support. Furthermore, grounded in supply chain resilience theory, the paper explores the interactive mechanisms between localization and resilience building, and provides a deep deconstruction of challenges such as external cost volatility, technological blockades, insufficient internal R&D capabilities, and low industry concentration. Finally, feasible paths to enhance supply chain resilience are proposed through technological innovation drivers, industrial synergy, and diversified supply chain layouts, aiming to facilitate the high-level localization of the lubricant additive industry.

Technology transfer and transformation, the core link bridging sci-tech innovation and industrial application, is undergoing profound changes amid high-quality development. This paper traces its evolutionary trajectory, reveals its development logic, and identifies future core directions and implementation pathways, offering theoretical and practical guidance for the industry to support sci-tech innovation and high-quality economic development. Using systematic review and dimensional decomposition, it retraces the evolution from the 1.0 to the 4.0 model, uncovering a logic from government-led to market-driven and intelligent collaboration. It analyzes pathways focusing on tools, capabilities, and resources, integrating innovation methods and digital technologies like AI and big data. By clarifying the characteristics and patterns of the four stages, the paper concludes that the future will center on precise matching and intelligent decision-making, thereby realizing intelligent, full-chain, and ecosystem-based collaboration. It elucidates that building a data-driven, multi-stakeholder collaborative ecosystem is an inevitable choice for the industry’s development.

Against the backdrop of rapid global AI iteration and deep industry integration, universities, as key carriers of AI basic research, have their technology transfer efficiency directly affecting the alignment between innovation and industrial chains. Technological powers such as the US, Europe, Japan, and South Korea, leveraging well-established systems, professional tech transfer offices, in-depth industry-university-research collaboration, and resource support, have developed a transformation model adapted to AI’s asset-light, fast iteration, and scenario-specific features, significantly improving industrialization rates. This paper takes leading universities such as Stanford University as research subjects, systematically reviewing their practical experiences in institutional design, organizational operations, and other aspects, to provide reference for Chinese universities in addressing pain points in AI technology transfer and building an efficient, compliant ecosystem for innovation transformation.

This article focuses on the scenario of school enterprise cooperation, analyzes the constraining factors in its development process, and proposes corresponding improvement strategies, aiming to provide some reference for improving the patent transformation ecology and enhancing the quality and efficiency of school enterprise cooperation.

Taking the 15th Five-Year Plan development stage of Nanyang City as the time framework, this paper focuses on the dual perspectives of high-tech development and industrialization implementation to explore the optimization paths of local scientific and technological system reform and governance capacity. Based on the current situation of Nanyang’s construction as a provincial sub-central city, it objectively sorts out the external environment of scientific and technological innovation development, and systematically summarizes practical bottlenecks including a weak innovation system, poor transformation of scientific and technological achievements, and imperfect governance mechanisms. Combined with the industrial endowments of Nanyang, it puts forward targeted practical countermeasures covering innovation platform construction, achievement transformation optimization and governance upgrading. The study aims to improve the local operation system of scientific and technological innovation, promote the in-depth integration of high and new technologies with local industries, and provide optimized ideas for the coordinated high-quality development of science, technology and economy in Nanyang City.

Using GraphRAG and PageRank, this study builds a knowledge graph of Shanghai’s S&T policies (1949~2025) and identifies key policy nodes across seven historical stages.Findings reveal three evolutionary patterns: actors expanded from few to many, coordination evolved from simple to complex, and policy targets broadened from narrow to wide. The study pushes the empirical timeline back to 1949 and introduces LLM-driven relation extraction with global centrality measurement to S&T policy research.

The 15th Five-Year Plan lays out systematic strategies for the integrated development of education, science, technology and talents. As a vital measure to implement relevant strategies, industry-education integration bridges the last mile between talent training and the transformation of scientific and technological achievements. This paper adopts CiteSpace to conduct a bibliometric analysis of existing literature, clarifying its research context and frontiers, analyzing predicaments in postgraduate training, and proposing targeted practical paths.

In the context of the integrated digital and intelligent transformation, the pharmaceutical and health industry faces an increasingly urgent demand for interdisciplinary digital and intelligent medical talents. Taking medical colleges and universities in Liaoning Province as the research subject, this paper analyzes the characteristics of talent supply and demand in the pharmaceutical and health industry of Liaoning Province under the digital and intelligent transformation, examines the adaptability contradictions in the industry-education integration cultivation mechanisms of medical colleges in the province, and constructs a cultivation mechanism characterized by “digital and intelligent leadership, industry-education symbiosis, and multi-stakeholder collaboration”. It further provides practical pathways for medical colleges in Liaoning Province to empower the high-quality development of the regional pharmaceutical and health industry.

Against the background of intensified global high-tech industry competition, overseas intellectual property infringement risks have become a core obstacle restricting the industrialization of achievements for China’s high-tech foreign trade enterprises. Combined with foreign-related dispute practices and foreign trade industry data, this paper sorts out the industrial characteristics and causes of risks, analyzes the practical shortcomings of market supervision, and proposes regulatory paths adapted to high-tech industrialization. The study finds that infringement risks of high-tech foreign trade enterprises show the characteristics of industrial agglomeration and technology targeting, with core causes being the disconnection between industrialization and intellectual property layout, and insufficient industrial-oriented supervision services. Market supervision departments should build an escort system of “early warning, collaborative disposal and closed-loop guarantee” to help high tech enterprises stabilize exports and promote industrialization, and ensure industrial chain security.

With its clean, low-carbon, high energy density and renewable characteristics, hydrogen energy has become a strategic energy carrier to promote the deep decarbonization and structural transformation of the global energy system. As a key hub connecting upstream hydrogen production and downstream hydrogen use in the hydrogen energy industry, liquid hydrogen storage and transportation is an important feasible path to support large scale, cross-regional and low-cost applications of hydrogen energy. Based on global patent data, this article specifically analyzes the patent application trend, geographical distribution, main applicants and technology efficacy in the field of liquid hydrogen storage and transportation technology, studies the innovation trend of liquid hydrogen storage and transportation technology, and further supports the hydrogen energy industry.

As artificial intelligence advances and proliferates, outputs generated via neural networks—text, music, and visual works—increasingly resemble human creations, challenging traditional copyright frameworks. Although formally work-like, such outputs depend on human intellectual input and technological guidance, and should be regarded as extensions of human labor. To address ambiguities in legal characterization, ownership, and authorship of AI-generated content, this paper proposes a sui generis copyright framework emphasizing clear criteria, user centered ownership, and refined attribution rules.

The rise of generative AI challenges the traditional copyright system centered on natural persons. Works created by natural persons through prompt adjustments and output selections often face difficulties in assessing human contribution due to algorithmic black boxes. Judicial practice recognizes the copyrightability of such AI-assisted outputs but fails to clarify the depth of human involvement via prompts. This paper focuses on the normative meaning of “substantial contribution,” correcting deviations in the sweat-of-the-brow doctrine and actual control theory. It emphasizes the role of human intellectual input in shaping original expression and advocates a process-oriented review approach. By analyzing creative nodes, causal chains, and contribution levels, it identifies human creativity beyond technical black boxes, balancing technological innovation with the anthropocentric values of copyright law.