With the deepening global concept of sustainable development, supply chain management has gradually shifted from a traditional cost-efficiency orientation to a comprehensive management model that balances environmental, social, and economic benefits. Focusing on innovation in supply chain management driven by sustainability, this study explores innovative approaches such as Green Supply Chain Management (GSCM), digital transformation and intelligent supply chains, and circular economy models from both theoretical and practical perspectives. By analyzing the impact of technology-driven advancements, policy support, and international cooperation on supply chain management, this paper proposes optimization strategies and future development trends for sustainable supply chains. The research reveals that green technologies, intelligent tools, and collaboration platforms will play a crucial role in the design and optimization of supply chains. To address future environmental and social challenges, enterprises must build more efficient and environmentally friendly supply chain systems through continuous innovation and cross-sector collaboration.

With the acceleration of global economic integration, the logistics industry, as an important pillar of the modern economy, has its operational efficiency directly affecting the competitiveness of the entire supply chain. Traditional logistics management models show obvious inadequacies when facing challenges such as massive data processing, complex route optimization, and real-time scheduling. Big data technology, with its powerful capabilities in data collection, storage, analysis, and mining, provides new technological pathways for the transformation and upgrading of the logistics industry. Through the application of machine learning algorithms, data mining technologies, and artificial intelligence algorithms, logistics enterprises can achieve precise demand forecasting, optimized transportation routes, and intelligent warehouse management, thereby significantly improving operational efficiency, reducing costs, and enhancing market competitiveness. 

As an important fractal unit of the global cyberspace, the smart education cyberspace is the core carrier of the value elements of national new quality productivity, and also the sovereign governance scope of national science, technology and culture. Governments of various countries attach great importance to it and elevate it to a national strategic proposition, actively exploring and constructing advanced governance patterns and value concepts to jointly address the security issues and risk challenges of global cyberspace development. In response to the current stage of AI integration and ecological reshaping in China's education development, the connotation system and value advocacy of building a smart education network space community with a shared future driven by deep technological openness and new economic growth. This article is based on the strategies of educational globalization and international space security development, proposing to adhere to the “community with a shared future for mankind” as the center, adhere to the two basic principles of “anti-monopoly and fair opening”, and adhere to the three point consensus of “strategic coordination, diversified governance, and new civilization” to construct a five level synchronized value system path for building a smart education network space community with a shared future.

The sensitive personal information of digitally vulnerable groups is highly susceptible to infringement. So this paper proposes targeted improvement suggestions, including constructing a safe and inclusive digital environment, regulating restrictive mechanisms for processing sensitive personal information, and improving rules for compensation for infringement of sensitive personal information. 

With the rapid development of the global economy and the rise of emerging industries, the demand for mineral resources such as cobalt, sulfur, and nickel has been continuously increasing, highlighting the growing importance of deep-sea mining in the field of resource extraction. The extensive application of automation technology has provided strong momentum for deep-sea mining, profoundly influencing technological innovation and efficiency enhancement within the industry. However, due to disparities in industrial development levels and technological capabilities across regions and countries, the introduction of automation technology is inevitably accompanied by a series of legal risks and challenges that urgently require attention and regulation.

County-level health spaces face challenges such as imbalanced medical resources, intensified ecological pressures, and fragmented services. This paper attempts to construct a four-dimensional collaborative framework of “institutional-space-technology-social” and proposes five core pathways.

Against the backdrop of rapid artificial intelligence development, the global employment landscape is undergoing profound transformation. As a vital segment of the labor market, college students are facing new challenges and a restructuring of both employment structure and quality. By systematically analyzing phenomena such as the reconstruction of vocational skill structures driven by AI, the dual compression of employment positions, and the increasing differentiation of employment paths, this study reveals deep-seated issues in university employment guidance services, supply-demand matching mechanisms,.It further proposes three strategic approaches: building interdisciplinary talent cultivation systems, optimizing employment guidance services.The aim is to provide theoretical support and practical insights for universities to adapt their talent development and employment services to the demands of the intelligent era.

The rapid development of artificial intelligence technology has opened up new possibilities for innovation in traditional calligraphy and painting. The integration of digital technology and traditional calligraphy and painting not only enables the digital preservation and inheritance of traditional art but also creates a new model for intelligent creation. By analyzing the application mechanisms of AI technology in the digitization of traditional calligraphy and painting, exploring strategies for building digital art creation platforms, and studying the paths to cultural industrialization driven by intelligent technology, we aim to provide theoretical support and practical guidance for the innovative development of traditional calligraphy and painting in the digital age, and promote the creative transformation and innovative development of China’s fine traditional culture.

The in-depth implementation of the rural revitalization strategy has raised higher demands for the construction of the rehabilitation medical service system. In this context, this article proposes an intelligent training model for rehabilitation talents (AI-RTS) based on big data and artificial intelligence technology. Experimental results indicate that the AI-RTS model provides a new technological approach for training rehabilitation talents in the context of rural revitalization.

Thanks to the vigorous development of artificial intelligence, correction technologies represented by affective computing have gradually been initiated and promoted. While improving the quality and efficiency of correction and facilitating correction institutions to better perform their functions, they have also triggered problems and challenges such as algorithm black boxes and data security. Therefore, this paper examines the topic from the perspectives of technological regulation and human-oriented optimization, with the aim of achieving a qualitative change in correction work from “tool innovation” to “governance model leap”.

Amid the rapid development of artificial intelligence and in-depth implementation of the digital education strategy, college ideological and political education, mainly in the form of online ideological and political education, is actively integrating this new intelligent information technology. This paper expounds on the value of artificial intelligence empowering college online ideological and political education from target accuracy, work efficiency, and interactive intelligence. It also identifies challenges in network information security, lack of educational subjects, and deficient intelligent systems. Finally, it explores solutions by improving rules, enhancing subject awareness, and building systematic platforms to give full play to artificial intelligence's empowering role and fulfill the fundamental task of fostering virtue through education.

Artificial Intelligence (AI)-assisted inventions pose significant challenges to patent novelty examination, primarily manifested in three dimensions: the scope of prior art, the principle of individual comparison, and examination criteria. Firstly, the application of AI has triggered an exponential growth in prior art volume, potentially distorting novelty examination into a tool for patent competition. Secondly, the principle of individual comparison reveals limitations when addressing cross-domain technological convergence, complicating the identification of innovative features in AI-assisted inventions. Thirdly, AI-generated technical documentation increases the complexity of examination processes. To address these challenges, this study proposes reconstructing the identification criteria for prior art through the introduction of a “substantive accessibility” standard. Concurrently, it advocates establishing a cross-domain comparison principle to clarify technical relevance assessments and predictability tests for prior art combinations. Furthermore, the principle of technical substantive equivalence and the integration of intelligent examination tools are recommended to strengthen disclosure obligations. These measures aim to ensure that AI technology fosters innovation while upholding the fairness and efficacy of the patent system.

In recent years, China has issued a series of policy documents related to the digital transformation of education. Based on the policy tool theory, this study constructs a two-dimensional analysis model of “tool type-synergy dimension”, and conducts coding and statistics on policy texts through content analysis. The figure reveals the characteristic features and structural contradictions of the content design related to school-enterprise collaboration in the process of formulating policies for the digital transformation of education by the policy subjects. At the same time, it puts forward future policymaking suggestions such as building a new model of collaborative governance for digital transformation, forging a power engine for school-enterprise collaboration, removing the bottlenecks in the practice of industry-education integration, and establishing an agile governance monitoring mechanism, to assist in the development of the school-enterprise collaborative ecosystem under the background of educational digital transformation.

As an innovation engine for economic and social development, artificial intelligence (AI) is reshaping the industrial landscape and social progress path. Globally, there has been a consensus on active layout in the AI field, aiming to lead future development trends and consolidate international competitive advantages. Taking Changzhou as an example, this paper systematically analyzes the existing foundation and potential for later development of the local AI industry. It proposes an innovative development strategic goal centered on “AI+”, aiming to promote the AIempowered upgrading of local characteristic industries through pathways such as enhancing industrial infrastructure, driving application scenarios, fostering a conducive development environment, and international cooperation. This will inject new impetus into high-quality economic development.

Based on the complex architecture, heterogeneous data, poor safety and stability, and insufficient talent support encountered in the integrated development of electrical systems in the petrochemical industry, this study focuses on the construction of system standards, intelligent platforms, strengthened security mechanisms, and talent systems. It explains the key role of a unified standard system in achieving interconnected transactions and mentions the relevant paths for intelligent control platforms to enhance collaborative operation capabilities. Systematic integration can effectively improve the intelligence and operational resilience of petrochemical electrical systems.

Against the backdrop of digital transformation and industry-education integration, higher vocational colleges are confronted with new development opportunities and challenges. This article analyzes the impact of digital transformation and industry-education integration on the talent cultivation model of higher vocational colleges, and explores the innovative paths of the talent cultivation model of higher vocational colleges to adapt to the development needs of the new era. The results of this discussion provide reference and inspiration for higher vocational colleges to build an industry-education integration teaching system that meets the needs of vocational education.

Based on patent data related to the aviation equipment industry in the Chengdu-Chongqing region from 2015 to 2024, this study adopts a patent bibliometric approach to construct a collaborative innovation network model grounded in patent co-application relationships. From the perspectives of patent cooperation networks, technological domain coupling, and actor interaction structures, the paper investigates the structural characteristics and evolutionary patterns of collaborative innovation in the Chengdu-Chongqing aviation equipment sector.

In the process of digital transformation of the logistics industry, data governance has become a core driving factor. Through reviewing the transformation practices of logistics enterprises, it is found that issues such as lagging standardization of data asset management and insufficient organizational structure and technical platform support are constraining the transformation process. Addressing these identified issues, governance strategies such as building a standardized data asset management system, strengthening data quality and security compliance, and improving organizational structure and technical platforms are proposed.

With the rapid advancement of urban renewal, the focus of China's modernization has gradually shifted to cultivating new quality productive forces, committed to promoting the transformation and upgrading of smart construction industrial parks toward “digitalization, efficiency, low-carbonization, and sharing.” The emergence of this new concept of new quality productive forces has injected fresh characteristics into shaping urban spatial quality. By employing a difference-in-differences model to conduct comparative analysis of relevant data between 25 smart construction pilot cities and 25 non-pilot cities in China from 2019 to 2024, the study found that the total factor productivity of the construction industry played a significant positive role in the application of smart construction. It further explored the profound impact of new quality productive forces on urban renewal under the context of smart construction, effectively fostering the vigorous development and comprehensive enhancement of new quality productive forces in the construction industry.

This manuscript investigates the global biopharmaceutical industrial landscape and development patterns, combining analytical insights into the characteristics of world-class life and health innovation hubs. The study aims to accelerate breakthroughs in critical life sciences technologies, establish an industry-collaborative innovation system, and deepen the convergence of innovation, industrial, financial, and talent chains. Ultimately, it seeks to expedite the creation of top-tier innovation hubs that leverage high-level scientific advancements to spearhead quality development and forge future-oriented competitive advantages. This approach charts a distinctive pathway for life sciences innovation that aligns with international standards, embodies Chinese characteristics, and addresses public health needs through science-driven solutions. 

Science and technology are the primary productive forces, and the transformation of scientific and technological achievements are a key process for turning science and technology into actual productive forces and promoting economic and social development. For a long time, Colleges and universities have had a large number of scientific and technological achievements, but the conversion rate has been relatively low. This study analyzed the current situation of the transformation of scientific and technological achievements in colleges in Ulanqab City. The main problems include a low match between university research and market demand, a weak talent team for the transformation of scientific and technological achievements, and an incomplete management system for the transformation of scientific and technological achievements. It is suggested that Colleges and universities enhance the conversion rate of scientific and technological achievements by adhering to the market demand orientation to achieve effective supply of scientific and technological achievements, building an information sharing platform to shorten the distance of the transformation of scientific and technological achievements, strengthening the professional title evaluation and appointment system to optimize the construction of scientific and technological talent teams, and establishing a multi-party collaboration system to promote the efficient transformation of scientific and technological achievements. At the same time, Colleges and universities should continuously increase investment in scientific and technological innovation, remove institutional and mechanism obstacles, and establish a fiscal investment mechanism oriented towards the industrialization of scientific and technological achievements to effectively solve the problems of difficult and low conversion rates of scientific and technological achievements, providing a reference for the efficient transformation of scientific and technological achievements in universities.

Artificial intelligence is profoundly reshaping the talent cultivation approach in universities, necessitating a transformation of the industry-education integration and collaborative education mechanism. In the context of artificial intelligence, collaborative education should focus on real job demands, enhancing students’ technical application and practical innovation abilities through joint teaching, project training, and other methods. Universities should proactively reconstruct course resources, teaching methods, and educational scenarios, making artificial intelligence an intrinsic driving force for high-quality educational development.

Recently approved by the State Council, the Master Plan for the China (Xinjiang) Pilot Free Trade Zone injects fresh momentum into graduate education in the region, while simultaneously exposing it to unprecedented challenges. This study first examines the long-standing constraints that shadow western China—modest economic output, scarce educational resources, and a fragile university–industry–government ecosystem—before narrowing its lens to the professional Master of Applied Statistics program at Xinjiang University. Fieldwork and in-depth interviews reveal specific gaps in talent cultivation, including outdated learning objectives, limited exposure to real-world data environments, and insufficient alignment with emerging market demands. In response, and with the Free Trade Zone’s evolving needs as a compass, the paper proposes a redesigned graduate training architecture: a forward-looking competency framework, pedagogical models that embed problem-solving in authentic trade-zone contexts, a re-engineered curriculum that interweaves statistical theory with frontier applications, deeper symbiosis between academia and industry partners, and a multi-dimensional evaluation system that rewards innovation, impact, and adaptability.

With the rapid development of technology, all fields are actively promoting the application of high technology, and the medical industry is no exception. The digital construction of hospitals is another significant manifestation of enhancing the efficiency of medical work, improving service and management models, and it also puts forward new requirements for the talent cultivation of medical staff. Based on the above analysis, it can be known that the current employment situation of medical and health care talents under the background of high technology is divided into the demand of the job market, the salary and benefits of the job market, the future development status of the job market, etc. At the same time, new requirements for medical and health care talents have also been put forward in response to the new situation, with the aim of providing a theoretical basis for promoting the employment and industrialization development of medical and health care talents.

Based on personal interviews and questionnaire surveys conducted among faculty and students in the Emergency Management School of N University, this paper systematically analyzes the current status of emergency management talent cultivation in the AI era. It delves into existing challenges,and on this basis, the study proposes countermeasures for emergency management talent cultivation in the context of artificial intelligence. The results indicate that AI can significantly narrow the gap between talent demand and cultivation while enhancing quality.

Against the backdrop of rapid development of the digital economy, the digital transformation process of the cultural and tourism industry is accelerating. The demand for digital cultural and tourism talents in the tourism industry is driving the continuous updating of talent training models for tourism majors in universities. As the main body of talent cultivation in the digital cultural and tourism industry, universities should actively match the industry’s development needs for talents and explore the training mode of digital cultural and tourism talents in universities under the guidance of the new liberal arts education concept. Based on the background of new liberal arts, this article explores the importance of cultivating high-quality digital cultural and tourism talents and the quality requirements for digital cultural and tourism talents in universities under the new development pattern, and proposes a path for cultivating digital cultural and tourism talents in universities.

Non-Fungibletokens (NFT) play the role of core assets. The work is transformed into a digital formthrough NFT, making it unique in the virtual world. This has become a key means forpeople to seize the lead in the field of digital collection, but also brings unprecedentedproblems to the current legal system. Based on existing NFT digital works and relevant literature, this paper takes the legal framework of Copyright Law of the People’s Reepublic of China as the starting point to analyze the basic conceptual characteristics and current situation of NFTs, aiming to explore the paths for the legal protection of copyright in NFT digital works.

The rapid development of artificial intelligence algorithms poses significant challenges to China’s patent protection system, primarily manifested in ambiguous patentability definitions, complex examination processes, and difficulties in infringement identification. This paper thoroughly examines these challenges and proposes multidimensional improvement pathways: clarifying patent standards for algorithmic technological contributions, optimizing examination procedures to enhance professionalism, strengthening judicial protection mechanisms for efficient rights enforcement, promoting international cooperation to align with global practices, and encouraging innovators to bolster their patent portfolios. These measures aim to establish a patent system better suited to the characteristics of the AI era, thereby effectively incentivizing algorithmic innovation and fostering the healthy development of China’s artificial intelligence industry.

9 月4日，第十七届中国生物产业大会在武汉开幕。本届大会以“生物科技赋能未来·生物制造重塑世界”为主题，举办生物制造高层论坛等26场活动，17位中外院士和700余家生物产业领域重点企业参加。南京师范大学副校长黄和在生物制造高层论坛做了题为《合成生物驱动生物制造产业革新》的报告。他指出，以合成生物学为基础的生物合成与生物制造，正在引发全方位的产业变革。

在近日举行的第十七届中国生物产业大会上，中国科学院天津工业生物技术研究所原所长、天津市人大常委会副主任马延和做了题为《生物制造与二氧化碳利用》的报告，以下为报告整理。

Information retrieval is one of the hot research topics in the field of computer science, and it has a wide range of application scenarios. However, it is mainly limited to specific domains or medium, so it’s unable meet the interaction needs of different user groups with different media. Aiming at the task of cross-domain information retrieval, this paper proposes a method based on a multimodal generative large model. Firstly, it analyzes the cross domain information retrieval technology in detail, summarizes the characteristics of information retrieval, and elaborates on the retrieval methods and processes. Then, a cross-domain information retrieval model based on multimodal generation is proposed. Finally, the effectiveness and reliability of the algorithm model are verified through experimental results. The results show that the proposed method achieves high accuracy in multimodal large models and achieves the best performance in cross-domain information retrieval tasks.

The social security system faces challenges in resource allocation, coverage, and efficiency. This study explores data integration methods, including behavior monitoring, fund tracking, and group identification, and proposes strategies such as classification, dynamic allocation, and policy adjustment. It also examines automated benefit calculation, service platform integration, and regional matching. The results improve data support and enhance system adaptability and efficiency.

During the 15th Five-Year Plan period, when digital-intelligence technologies permeate every domain, such libraries must take the triadic integration of smart resources, smart services, and smart spaces as their core mission, providing replicable institutional and technological models for digital-intelligence transformation. Research shows that, against this backdrop, the principal technological paradigms for building a future-oriented, vocation-type learning center are the graph-based organization of resources, personalized service delivery, and intelligent spatial interaction.

Under the background of “double carbon” strategy and transportation power, the intelligentization of new energy vehicles has become the core fulcrum of industrial transition. In this paper, the importance, main content, development status, innovation and future trend of intelligent technology for new energy vehicles are deeply discussed, and how intelligent technology for new energy vehicles can promote industrial transition and social sustainable development is comprehensively analyzed from multiple dimensions.

With the breakthroughs and development of technology, the application scenarios of artificial intelligence (AI) have been continuously expanding, and the application levels have been increasingly deepened, bringing new opportunities and challenges to nursing education in the new era. This study systematically reviews the specific applications of AI in multi-modal content generation, virtual simulation technology, personalized teaching, and teaching model innovation. It also analyzes the technical limitations, ethical dilemmas, and cost constraints existing in practical applications, and proposes relevant countermeasures such as macro planning, cross-disciplinary collaboration, systematic training, and the reconstruction of the teaching evaluation system. The aim is to promote the integration of AI and nursing education and provide references for cultivating high-quality nursing talents that can adapt to the development of the new era.