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.

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.

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. 

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.

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.

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. 

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.

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.

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.

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.

This research solves the problems of information island and insufficient data analysis in traditional policing work by constructing a new intelligent policing model based on big data and knowledge graph as the core framework. The research expounds in detail how big data provides rich and comprehensive data sources for public security work, and how knowledge graph uses its powerful semantic correlation ability to realize deep integration, efficient retrieval and intelligent reasoning of these data. At the practical application level, the paper analyzes the practical cases and applications of big data and knowledge atlas fusion in case detection, crime prediction, social security prevention and control, resource optimization allocation and other police scenarios. On this basis, it looks forward to the future challenges and development trends of intelligent policing, and provides valuable thinking and suggestions for the digital transformation and intelligent upgrading of public security field.

Cryo-electron microscopy is a pivotal technique for resolving biological ultrastructure, where high-quality sample preparation, particularly cryo-thinning for thick samples, is essential. Traditional cryo-thinning techniques, such as cryo-ultramicrotomy, face challenges including sample compression artifacts, operational complexity, low efficiency, and insufficient positioning accuracy, which constrain in situ structural biology research. Driven by the increasing demand for high-fidelity, high-precision in situ observation, correlative light and electron microscopy has become the core development direction. The Chinese Academy of Sciences Scientific Instruments High-End Instrument Research Institute（Beijing） and the Institute of Biophysics，Chinese Academy of Sciences team have successfully commercialized an innovative achievement—the ELI-Triscope System. This system realizes groundbreaking “three beam co-focusing,” integrating an inverted fluorescence imaging system. By monitoring the actual fluorescence signals of target molecules, it achieves “cutting while seeing,” resolving the traditional “blind cutting” dilemma. With positioning accuracy better than 200 nanometers, it enhances the capability for targeted thinning of subcellular structures. Simultaneously, by eliminating ice contamination risks associated with sample transfer, it drastically reduces sample preparation time to approximately 45 minutes per sample. This provides robust support from a domestically developed tool for the precise analysis of organelle-scale in situ three-dimensional structures.

Traditional Automated Guided Vehicles (AGVs) typically rely on predefined paths to complele sorting and delivery tasks, lacking flexibility. In recent years, the explosion of ecommerce, sustained growth in order volume, and the demand for flexible manufacturing with high-mix, low-volume production have posed new challenges to the logistics industry. Autonomous Mobile Robots (AMRs), with their capability for flexible route planning and intelligent environmental interaction, are gradually replacing AGVs as a focal point in smart logistics. This paper reviews the technological evolution from AGVs to AMRs, encompassing both intrinsic and extrinsic driving factors. By conparing performance differences in various scenarios, it proposes optimization solutions for key challenges such as path planning and multi-robot collaboration. In the future, further iterations of AMRs can be achieved through integration with 5G/6G, high-precision navigation, and human-robot interaction technologies.

With the implementation of the national cultural digitalization strategy, vigorously promoting the integration of culture and technology has become an imperative choice for inheriting and promoting China’s excellent traditional culture. In the context of digital transformation in vocational colleges, vocational college libraries serve as key vehicles for advancing the integration of culture and technology. This paper summarizes four core values of promoting the integration of culture and technology in vocational college libraries, analyzes five challenges in its advancement, and proposes five pathways for its implementation, providing theoretical reference and insights for the service transformation of vocational college libraries.

With the continuous expansion of transportation infrastructure construction, traditional highway maintenance decision making models face challenges such as data silos, decision-making lag, and uneven resource allocation. This paper deeply analyzes the value connotation of big data technology in highway maintenance decision-making, and examines key issues in current integration applications, including uneven data quality, lack of technical standards, insufficient talent teams, and difficulties in input output evaluation. On this basis, the paper constructs a precision decision-making implementation path based on optimization of data collection at the perception layer, enhancement of intelligent analysis at the platform layer, improvement of decision support at the application layer, and establishment of sound institutional mechanisms at the guarantee layer. This research provides theoretical guidance and practical references for enhancing the scientific nature and effectiveness of highway maintenance decision-making.

Against the backdrop of the commercial deployment of 5G technology promoting a new round of industrial transformation and the deep integration of computer technology and high-speed communication networks becoming a key driving force for industrial innovation, this article focuses on the innovative application and impact analysis of computer technology in the industrial field in the 5G era. Based on the high bandwidth, low latency and high reliability of 5G, this paper discusses its empowerment of the optimization and upgrading of computer technologies such as edge computing, cloud computing and artificial intelligence. It selects two typical scenarios of intelligent manufacturing and smart healthcare to analyze and explain the actual implementation paths of innovative application models such as real time quality control and remote surgery. Research has found that although the application of computer technology driven by 5G has significantly improved the operational efficiency of industries and given rise to new business forms, it still faces challenges such as the integration of technologies like cyber security and privacy protection. Therefore, in the future, it is necessary to strengthen cross-domain collaboration and standard construction to release the potential of technological innovation and provide continuous impetus for the digital transformation of industries.

To tackle issues like scattered storage, varied formats, and outdated data in traditional geological data management, this study developed the Xiamen Geological Data Collection (XGDC) system. It uses a distributed, unified, and centralized framework to integrate multi-source geological data. The system has successfully integrated over 130,000 borehole records in Xiamen, creating an electronic archive that supports public queries, professional analysis, and decision-making.

Based on the WSR (Wuli - Shili - Renli) methodology, this paper analyzes the constituent elements, operational mechanisms, existing problems and optimization strategies of the discipline coordination and scientific research output system in local universities. It proposes the following research optimization strategies for such a system. The strategies include: (1) Strengthen top-level design and optimize the layout of disciplines; (2) Srengthen scientific research connection and serve regional needs; (3) Enhance the efficiency of resource allocation; (4) Build an interdisciplinary cooperation ecosystem; (5) Improv the evaluation system to stimulate research vitality; (6) Create a collaborative innovation culture.

Guided by China’s agricultural modernization strategy, agriculture and animal husbandry on the Qinghai Plateau are rapidly moving toward mechanization, digitization, and intelligence, yet the region’s unique ecological and socio-economic conditions pose distinct challenges for intelligent agro-pastoral robots. This paper reviews relevant policies and current developments, analyzes the drivers of agro-pastoral intelligence in Qinghai, and summarizes domestic and international progress in agricultural and pastoral robots, highlighting differences in typical applications. It identifies key bottlenecks in plateau environments, technology adaptation, talent, and infrastructure, and proposes a plateau-oriented technology system integrating environmental perception, intelligent computing, autonomous learning, and human–robot interaction, together with a framework for embodied, learnable robots that adapt through continuous human–environment interaction. Comparative cases from the United States, Germany, and Japan inform strategies in policy support, industry–academia–research collaboration, talent training, and shared service models, providing guidance for smart agriculture and ecological animal husbandry in plateau regions.

Based on the requirements of the “Realistic 3D China” initiative and the construction of a new fundamental surveying and mapping system, this paper clarifies the connotation and components of terrain-level geographic entity conversion by integrating the characteristics of Guizhou’s multi-source heterogeneous geographic information data. Furthermore, it systematically outlines the conversion production process and technical methods, providing a valuable reference for geographic entity conversion in Guizhou Province and other complex terrain regions across Southwest China.

New-type productivity, driven by technological innovation, serves as the core catalyst for technological advancement in smart archives. This paper examines the pivotal role of new-type productivity within the context of smart archives development, addressing critical challenges including technological compatibility, data governance, talent development, and cost-effectiveness. It proposes implementation strategies such as scenario-driven technology integration, end-to-end data governance, cultivation of interdisciplinary professionals, and cost-benefit optimization. These approaches provide actionable pathways for smart archives to achieve technological upgrades and enhance service quality through the application of new-type productivity.

Cosmic dust is a key material connecting stellar evolution, planetary formation, and the evolution of the interstellar medium. Benefiting from the motion of the solar system relative to the local interstellar cloud, several deep-space exploration missions have achieved in-situ detection of interstellar dust. Impact ionization detectors such as those on Helios, Ulysses, Galileo, and Cassini, along with the Stardust sample return mission, have made significant progress in analyzing the dynamical characteristics and composition of particles, initially revealing the mass distribution, radiation pressure response, and material composition of interstellar dust. However, due to limitations in orbital configuration, detection geometry, instrument performance, and dynamic filtering effects, significant uncertainties remain in existing observations regarding the particle size range, compositional completeness, and understanding of internal structure, requiring further breakthroughs.

With the rapid development of information technology, big data is increasingly being applied in the healthcare sector. As a key tool for integrating medical resources and enhancing service quality, healthcare information platforms have encountered new opportunities and challenges in the era of big data. This paper explores the importance of building healthcare information platforms in the context of big data, analyzes existing issues in current construction processes, and proposes corresponding solutions. The aim is to provide guidance for advancing the informatization of healthcare and improving public health levels.

Against the backdrop of accelerated digital and intelligent transformation, small and medium-sized retail enterprises are confronted with prominent contradictions in human resource management due to the industry characteristics of “scattered stores, frequent personnel turnover, and high labor costs”. This paper adopts a hybrid research method of “questionnaire + interview + multi-case analysis”, based on 296 valid questionnaires, in depth interviews with 23 stores and 12-month tracking data of 3 typical enterprises, systematically analyzes the current application status of digital tools and the bottleneck of efficiency transformation, and constructs a three in-one optimization strategy system of “precise empowerment by modules + full-process collaboration + efficiency transformation”. Empirical verification shows that this system can effectively solve core problems such as data silos and help enterprises improve the quality and efficiency of human resource management.

Domestic large-scale models represented by DeepSeek, with their powerful capabilities in semantic understanding, knowledge generation, and logical reasoning, are reshaping the innovative pathways and methodological systems of academic research. To systematically reveal the research hotspots and development trends in this field, this study conducted a quantitative analysis of 236 core DeepSeek-related articles from CNKI)using the LDA topic model. By refining the topic terms, four key research themes were identified: intelligent information management and cultural service transformation; education and social change in the intelligent era; the digital economy and technology industry ecosystem; and technological risks and global governance. Based on the refined themes, a visual analysis was performed, followed by future prospects.

In the digital age, libraries, archives, and museums house vast amounts of high-quality information resources, yet they face challenges such as heterogeneous fragmentation, weak connections, and inefficient utilization. As a core technology of semantic networks, knowledge graphs possess strong semantic expression and association-mining capabilities. This paper addresses the practical difficulties in integrating information resources from libraries, archives, and museums, explains the characteristics of knowledge graph technology, analyzes its application value, and proposes a comprehensive integration strategy that includes ontology construction, data fusion, platform establishment, and collaborative management. This strategy aims to provide a technical path and practical reference for achieving semantic interconnection of resources and intelligent upgrading of services.

Integrating ECOSTRESS and Urban Functional Zones identified via POI and road network data, this study uses an XGBoost-SHAP framework to analyze spatial differentiation and non-linear drivers of nighttime Land Surface Temperature (LST) in Fuzhou’s main urban area. Results indicate: (1) Residential zones are heat sources whereas industrial zones are cold spots. (2) Socio-economic factors of Nighttime Light Intensity(NTL) and Population Density (POP), plus the 3D morphology factor Average Building Height (BH), dominate warming over 2D factors. (3) NTL saturates near 40; POP and BH thresholds are approximately 150 people/ha and 20 m. Findings support zone-specific regulation.

With the rapid development of information technology and the increasing diversification of medical service needs, Internet electronic health records have gradually become an important starting point for hospital management reform and innovation. Through the deep integration of online platforms and patient health data, this model can realize cross-departmental and cross-institutional sharing of medical information, providing key support for hospitals to optimize resource allocation, improve the quality of medical services, and promote health management. Integrate scattered information resources, systematically process and update patients’ multi-dimensional data in real time, so as to make the medical process more transparent and efficient.

Spatial intelligence represents the cutting-edge of artificial intelligence development. It is not only the product of the evolution of multiple digital technology paradigms but also an algorithmic tool that drives multiple changes in social governance. At present, public security organs have not yet fully integrated spatial intelligence into their practical work. Grassroots police officers mostly adopt traditional models to handle police situations, which are cumbersome and inefficient.Studies have shown that spatial intelligence can play a good auxiliary role for public security organs in reproducing crime scenes, constructing evidence chains, and daily patrols. However, problems such as privacy leakage, technical black boxes, and over-reliance may arise during its use. Therefore, methods such as strengthening privacy protection, optimizing technology, and formulating corresponding laws have been proposed to solve these problems.Spatial intelligence empowers traditional policing to move towards a new era of smart policing characterized by digitalization, networking, and intelligence. It promotes the intelligent transformation of policing activities from being “people-oriented” to “technology-led”, and accelerates the modernization of policing activities.

The Nianligou mining area in Inner Mongolia features a complex geological structure, with long-term coal extraction causing significant ground subsidence and deformation, impacting safety and ecosystems. This study employed Small Baseline Subset InSAR (SBAS-InSAR) technology to analyze ground deformation using 54 Sentinel-1A images from January 21, 2021, to April 6, 2025. Results revealed the spatial and temporal patterns of subsidence over the past five years, indicating overall stability but notable ongoing subsidence in certain areas, primarily linked to coal mining. The findings provide valuable insights for monitoring ground subsidence and guiding future resource extraction and ecological restoration.

In the context of global green transition, the technological upgrading of test equipment compressor units is confronted with the dual challenges of core technology breakthroughs and market competition, and the intellectual property strategy has become the core driving force for their technological innovation. The core argument of this paper is that constructing an intellectual property strategy that is both precise and forward-looking can effectively coordinate and integrate the processes of technological R&D, achievement protection and transformation of test equipment compressor units, helping to break through the bottlenecks in green and low-carbon technologies. Based on this understanding, from the three dimensions of patent layout optimization, intellectual property risk prevention and control, and achievement transformation mechanism construction, this paper analyzes the collaborative logic between intellectual property strategy and technological innovation,clarifies the innovation direction and implementation path of test equipment compressor units under the guidance of green technology, and provides solid intellectual property support for improving the green performance of equipment and enhancing the core competitiveness of the industry.

Under the wave of digital government construction, the scientific adaptation and deep application of information technology is expected to provide critical support for the coordinated development of public. Therefore, this article deeply analyzes the core value of promoting the coordinated development of public management by information technology, proposes a method to promote the coordinated development of public management by information, realizes data integration and sharing through the construction of data sharing platform, and aggregates data among departments; Reasonable use of intelligent technology to strengthen the basis and effectiveness of collaboration, establish and improve the intelligent technology standard system to ensure the coordinated development of public management, and then provide more practical theoretical references and practical guidance for the coordinated development of public management in government construction.

This study focuses on the Facial Expression Recognition and Sentiment Analysis System V1.0 for learning situation analysis. It unfolds around the research of technical feasibility demonstration, expression classification extraction, and practical application verification. By improving the deep neural network model to enhance the accuracy of expression recognition, collecting procedural expression data to support learning situation analysis, and ultimately optimizing the system through teacher recognition surveys and student experience feedback, the study achieves the integration of technical research and teaching application.

Fishing ban policies are vital for biodiversity conservation, yet traditional manual patrols are limited by low efficiency and coverage. With advances in artificial intelligence and video surveillance, a collaborative “human defense + technological defense” model has emerged. This study examines its theoretical basis, key mechanisms, and promotion pathways. The findings show that the model improves supervisory precision and coordination, supporting biodiversity protection and ecological governance modernization.