The Xiong'an New Area is established to relieve Beijing's non-capital functions. The promotion of Beijing's international science and technology innovation center construction is driven by it. The development of the Beijing-Tianjin-Hebei regional innovation system is also driven by it. It is of great significance to analyze the current situation and problems of the construction of the Science and Technology Innovation Center in Xiong'an New Area and propose corresponding countermeasures. Based on relevant policies, the strategic positioning of the construction of the Science and Technology Innovation Center in Xiong'an New Area was clarified. Based on the current situation, the problems and deficiencies in the construction of the Science and Technology Innovation Center in the new area were analyzed. Several countermeasures and suggestions were put forward to improve the construction of the scientific and technological innovation system in Xiong'an New Area and enhance the capabilities of scientific and technological innovation and industrial innovation.

The construction of an important carrier for high-end and high-tech industries in Xiong'an New Area is a crucial engine for the relocation of non-capital functions from Beijing and the coordinated development of the Beijing-Tianjin-Hebei region. Through an analysis of the current situation of the construction of the high-end and high-tech industry carrier in Xiong'an New Area, it is found that the carrier has already possessed a certain carrying capacity, but there are deficiencies in policy guidance, industrial agglomeration, local support, talent reserves, and industrial collaboration. Based on this, the following policies are proposed to provide an innovative environment for the development of high-end and high-tech industries in the new area: introduction of leading enterprises in the supply chain, construction of platform and carrier, improvement of policy support measures, optimization of the innovation and development ecosystem of the host area.

Disruptive technology is strategic technology that could overturn mainstream technology and reshape competitive landscape, characterized by complex evolution process and typical “non-consensus” attributes. Traditional research project evaluation methods, which rely on “one-time evaluation determines the lifetime outcome”, are unsuitable for disruptive technology projects. Instead, an evaluation-cultivation integrated approach should be adopted for their identification. Thus, the connotation of disruptive technology was analyzed, the typical practices and experiences of foreign institutions were drawn on, and three basic principles: “Logical Consensus, Inclusive Standards”, “Recognizing Strengths and Offseting Weaknesses, Sifting out the gold from the sand”, and “Tiered Planning, Dynamic Optimization” were proposed. It explores the construction of an evaluation-cultivation integrated mechanism aligned with the evolutionary traits of disruptive technologies, centered on “high-consensus logical reasoning”. The results provide methodological reference for accurately identifying disruptive technology.

Coordinating the relocation of Beijing's non-essential capital city functions with Xiong'an New Area's own development is the key for achieving Xiong'an's strategic target of “national project of millennial significance,” and it provides the fundamental guideline for building a high-quality and modern socialist city. The progress of non-capital-function relocation to Xiong'an was reviewed, the emerging situation and challenges were analyzed, and the urban development momentum theory to examine domestic and international new-city experiences was drawn on. It delineates three stages for the development of Xiong'an, identifies the core drivers and priorities for each stage, and offers recommendations for the next phase on how to advance both functional relocation and local development in tandem.

In order to solve the influence of bolt length on roadway support under different geological and mining conditions, using FLAC3D numerical simulation software, the numerical simulation research of tunnel support effect of 1.6, 1.8, 2.0, 2.2 and 2.4 m different bolt lengths was carried out. Through five bolt-length support schemes, the stress change and displacement deformation rule of roadway under each scheme were analyzed, and the optimal bolt-length was obtained. The results show that the change of bolt length affects the displacement and deformation of roadway after excavation. When the diameter of the bolt is constant and the length is 2.2 m, the deformation of the roadway surrounding rock is small, and the shear failure in the plastic zone is minimal. Through the comparison of several schemes, it is found that the roadway support effect is best when the length of bolt is 2.2 m.

15111 working face of Huangyanhui Coal Mine in Shanxi Province was selected as the support of the actual project, and the stress distribution state and roadway deformation characteristics of coal pillar and solid coal under different coal pillar widths were analyzed in depth, aiming to realize the optimal design of the parameters of coal pillar excavation along the gob of the track channel in this working face. The lateral stress distribution law of goaf was deeply discussed, and the stress distribution of small coal pillar after goaf excavation was studied. At the same time, the distribution characteristics of vertical stress and horizontal stress during mining are comprehensively analyzed, and the specific values of vertical displacement and horizontal displacement in mining stage are precisely measured. The research results show that with the continuous increase of the width of coal pillar, the stress carried by coal pillar and solid coal increases correspondingly. At the same time, the increase of the width of coal pillar causes the deformation of the two sides of the tunnel to expand first and then shrink, and the deformation decreases further when the tunnel reaches a stable state. However, the deformation of the top plate and the bottom plate showed a gradually decreasing trend. Through research and analysis, the optimal design size of coal pillar in goaf excavation is optimized and determined. The research result will provide a key and reliable reference standard for the coal pillar maintenance of Huangyanhui Coal Mine and other similar projects, and effectively promote the improvement of the safety, stability and economy of the project, which has important value for promoting the technological progress in related fields.

The strong heterogeneity of the Lower Permian gas reservoir in the Hechuan Gas Field and the significant differences in gas well productivity, along with the unclear characteristics of high-efficiency wells, have constrained the profitable development of the gas reservoir. To identify the controlling factors of high-yield wells, research was conducted from both geological and engineering perspectives, focusing on the relationships between paleogeomorphology, dolomitization degree, reservoir thickness, fracture and vug development, acid treatment volume, and gas test productivity. The results indicate that wells located in high paleogeomorphological positions, with high dolomite content and large reservoir thickness, exhibit well-developed fractures and vugs, achieving productivity of up to a million cubic meters. Large-scale acid treatments can modify the surrounding reservoir of the wells, enhancing their productivity.

Aiming at challenge about the limited reforestation effect of conventional fracturing operating type on tight sandstone reservoir in Linxing block of Ordos Basin, using core data, experimental analysis data, well logging data and production dynamic data, parameter normalization and weight analysis methods were used to conduct a friability evaluation for volume fracturing in tight sandstone reservoirs. For the first time in this region, a multi-parameter comprehensive evaluation formula and parameter criteria were established and a set of volumetric fracturing design scheme and supporting process method suitable for this area were formed. After field application in Linxing Area, the productivity of volumetric fracturing is increased by 1.3 times compared with that of conventional fracturing. With exceptionally abundant tight sandstone gas reserves in Linxing, the friability evaluation-guided volume fracturing technology represents a significant innovation in hydrocarbon development. This approach has shown growing advantages in unconventional resource exploitation and holds broad prospects for industrial applications.

To obtain accurate temperature and pressure data during downhole fracturing processes, a novel dissolvable fracturing ball is developed for collecting temperature and pressure data during downhole fracturing stages. This method utilizes the fracturing ball as the external structure, with pressure and temperature sensors as the core components for data acquisition. Based on a single-chip integrated circuit, data transmission was achieved through RS-485 communication, and data storage was accomplished via SPI communication. In accordance with the operational conditions of the novel dissolvable fracturing ball, experiments on pressure, temperature, and signal storage ball escape were conducted. The experimental results demonstrate that the design structure of the novel dissolvable fracturing ball meets the requirements of operational conditions, with excellent sensor acquisition accuracy. Its capability to read and store pressure and temperature data during downhole fracturing stages provides new insights for the digital transformation of oil and gas field exploration and development technologies.

To address the limitations of traditional gas consumption prediction methods in dealing with complex time series data, a combined model (CNN-BiLSTM-Attention) integrating convolutional neural networks, bidirectional long short-term memory networks, and attention mechanisms is proposed for urban gas consumption prediction. An empirical analysis was conducted on the actual gas consumption situation of a city in the western region. The results show that the root mean square error, mean absolute error, and coefficient of determination of this model are 19.14, 17.53 and 0.966 6 respectively, and its prediction effect is significantly better than that of other models. The research indicates that the CNN-BiLSTM-Attention network model provides an effective solution for urban gas consumption prediction and offers a scientific basis for urban energy management and decision-making.

In order to address the issues of arbitrariness and blindness in emergency rescue force allocation for mountainous highway tunnels, the principles of emergency response resource allocation was studied, and an optimized resource allocation model specifically tailored for mountainous highway tunnel networks was proposed. By abstracting and modeling the road network, this model effectively positions emergency response points and introduces a phased collaboration strategy to optimize the deployment of emergency rescue forces, which not only focuses on efficiently utilizing limited rescue resources but also emphasizes the feasibility and effectiveness of practical operations. Through case study validation, this model demonstrates robust practicality and operability, it can provide a scientific basis and effective tool for emergency rescue efforts in mountainous highway tunnels.

The layout design of an assembly line has a significant impact on a company's production and logistics efficiency.Taking the layout design of the D4 engine assembly line as the research object, the assembly process was analyzed,an assembly line balancing model was constructed with the goal of minimizing the number of workstations. Based on the balancing results, the task division for each workstation was determined. On the basis of analyzing the capacity requirements of the workstations, the design of the workstation layout was formed. Utilizing the systematic layout planning(SLP) method, and considering the constraints of workstation positions as well as the need for flexibility in assembly line production, the layout of the assembly line was determined based on the analysis of inter-station logistics after balancing. The layout is arranged to fulfill the rhythm demands, satisfy the assembly process, and support the efficient functioning of the assembly line.

For the convenience of installation, the bolt hole diameter in the transmission tower is generally required to be 1.5 mm larger than the diameter of the bolt, and there is sliding phenomenon after the bolt is subjected to force. The current tower design software generally uses a spatial truss model for analysis, without considering the influence of bolt slip, which cannot accurately reflect the actual deformation of transmission towers. As a result, the calculated deformation values are generally much lower than the measured values, which affects the accuracy and safety of structural internal force analysis. At present, the analysis of the impact of bolt slip on deformation is mainly carried out through finite element software combined with spring elements. Due to the large number of transmission tower members and complex structure, this processing method has low efficiency and is generally only used for verification analysis of tests. Based on the principle of virtual work, considering bolt slip and residual deformation, the calculation formula for tower deformation is improved, and fast identification methods for various joint models are proposed. At the same time, a full-scale real type experimental study was conducted for the deformation of the yak shaped landscape tower for the first time, and the experimental results, theoretical calculation values, and improved formula calculation values were compared and analyzed to verify the effectiveness of the improved formula. In addition, the measures to reduce bolt slip deformation are proposed. The research results have certain reference value for the optimization design of transmission tower, deformation control, and evaluation of bearing capacity under foundation deformation conditions such as landslides and settlements.

Accurate prediction of lithium-ion battery state of health (SOH) is crucial for battery management systems. Existing deep learning-based prediction methods primarily focus on single temporal scale features, making it challenging to simultaneously capture multi-scale dynamic characteristics during battery degradation processes. To address this issue, a SOH prediction model based on multi-scale attention mechanism (MSANet) is proposed. The model employs three parallel attention modules - short-term, medium-term, and long-term - to capture features at different temporal scales, achieving comprehensive battery state modeling through an adaptive feature fusion strategy. Additionally, bidirectional LSTM (long short-term memory) and low-rank adaptation (LoRA) techniques are incorporated to enhance the model's feature extraction capability and parameter efficiency. Experiments on the NASA (National Aeronautics and Space Administration) battery dataset demonstrate that this method achieves superior prediction accuracy and efficiency compared to LSTM-based prediction methods, providing a novel solution for battery health state assessment.

Static pressure densification piles exhibit significant technical and economic advantages in addressing the collapsibility of loess. However, during construction, there is a widespread issue of severe shrinkage after static pressure hole formation. To address this, specialized field tests were conducted using the volume conversion method to compare and analyze the shrinkage conditions of static pressure densification piles after the first and fourth hole formations. It is found that shrinkage occurred to varying degrees after both hole formations, with the overall shrinkage rate after the fourth hole formation reaching as high as 26.54%, an increase of 101.40% compared to the first hole formation. To effectively tackle this challenge and ensure the quality of pile construction, the importance of the tamping and filling process stands out. Given the limitations of traditional heavy hammer tamping methods in terms of construction efficiency, quality control, and environmental protection, an innovative fill-tamp integrated device has been developed. This device not only improves the quality and efficiency of densification pile construction but also advances tamping and filling technology, achieving dual improvements in economic and social benefits, and it has value for promotion and application.

Green economic development has become a key path to achieve high-quality regional economic development and achieve the strategic goal of “carbon peak and carbon neutrality”. Based on the panel data of 268 prefecture-level cities in China from 2015 to 2022, a fixed-effect model was used to test the impact of government attention allocation intensity on the level of regional green economic development. It is found that the intensity of government attention allocation has a significant positive effect on the improvement of the level of urban green economic development, and the effect is more significant in areas with high public environmental attention and strong government environmental execution, and the upgrading of industrial structure is one of the important intermediary paths of the main effect. After the robustness test, this conclusion still holds.

Based on the analysis of Sichuan liquor invention patent application trend, distribution of patent application types, patent grant rate and patent regional distribution from 2010 to 2024, it is found that Sichuan liquor industry has some problems, such as low patent application quality, low invention patent grant rate, insufficient patent application motivation and lack of reasonable patent strategy layout.In order to improve the patent licensing rate and innovation ability of Sichuan liquor industry and promote its sustainable development, it is suggested Sichuan liquor enterprises choose high-quality agencies to improve the patent authorization rate, pay attention to the quality of application documents and the quality of reply to the review opinions, improve the enterprise's attention to patents and application awareness, and flexibly formulate patent strategic layout according to the changes in the product market.

With China's economic development entering a new normal, improving the quality of economic development has become the core task of transformation and development in various regions. As an important economic sector in central China, Jiangxi Province plays a leading role in optimizing and upgrading its industrial structure through the use of new quality productive forces, which is of great significance for promoting high-quality economic development in Jiangxi Province. The promotion of new quality productive forces in optimizing and upgrading the industrial structure of Jiangxi Province was studied from both theoretical logic and path perspectives, providing theoretical guidance and practical references for the development of Jiangxi Province's industries in the new era.

Using the logistics index from 2010 to 2022 and the DEA-BCC (data envelopment analysis and Banker-Charnes-Cooper) model, it is found that the static comprehensive logistics efficiency in China is 0.668, which is at a low level. Using DEA-Malmquist index method to analyze dynamic logistics efficiency, the total factor productivity is 0.981, and the overall productivity is slightly reduced. Tobit regression model was used to explore the factors affecting logistics industry efficiency, among which economic development level had a significant and weak negative impact on logistics efficiency. The degree of industrial agglomeration and the level of innovation have significant positive effects on logistics efficiency. The degree of government intervention, informatization level and opening to the outside world have no significant influence on logistics efficiency. According to the research results, some countermeasures and suggestions are puts forward to improve the efficiency of logistics industry in China, that is, to improve the level of logistics service, optimize the level of resource allocation and improve the capability of technology research and development.

Based on panel data from nine cities in Fujian Province, how trade between Fujian Province and ASEAN promotes industrial structure upgrading was analyzed. The empirical results indicate that increasing imports and exports to ASEAN can promote the upgrading and rationalization of Fujian Province's industrial structure. In regions with higher levels of economic development in Fujian Province, expanding trade has a greater positive impact on industrial structure upgrading. Financial support plays a positive regulatory role in the chain of expanding imports and exports to promote industrial structure upgrading. In the process of increasing exports and expanding imports in Fujian Province and ASEAN, innovation or boosting consumption are both beneficial for promoting industrial structure upgrading.

General purpose technologies (GPTs) exhibit strong externalities and innovational complementarities. Their diffusion within supply chains and impact on the technology ecosystem are of significant interest to both industry and academia. Based on the resource dependence theory and absorptive capacity theory, the nonlinear effects of leader firms' GPT innovation on the technological complementarity between leader firm and its supply chain partners was examined. It also explores the boundary conditions of these effects. Analyzing panel data from 1,405 firm-year observations of 145 biopharmaceutical firms from 2010 to 2019, the findings reveal that an inverted U-shaped effect of GPT innovation performance on the technological complementarity between leader firm and its supply chain partners.Within the supply chain, partners' capability in GPT innovation positively moderates this inverted U-shaped relationship.

Data factor allocation is an important driving force of enterprise digital technology innovation, and is gradually regarded as the core production factor of new quality productivity because of its significant multiplier effect and innovation engine. Taking enterprise data factor allocation as the starting point, listed manufacturing enterprises from 2011 to 2022 were selected as samples to empirically study the relationship between data factor allocation and enterprise new quality productivity, and the intermediary mechanism effect was studied from the two dimensions of digital technology innovation quantity and quality. It is found that data factor allocation of manufacturing enterprises can effectively promote the improvement of new quality productivity of enterprises, especially for state-owned enterprises, high-tech enterprises and the eastern region. The mechanism effect test shows that data element allocation can improve the new quality productivity of enterprises through the “incremental quality improvement” effect of digital technology innovation. In order to promote the formation of new quality productivity, it is suggested that manufacturing enterprises actively integrate the “data factor x” action, improve the level of data factor allocation, promote the synergy between data and technology factors, and promote the double improvement of the quantity and quality of digital technology output.

Artificial intelligence is a new driving force for promoting the high-quality development of the economy. The mechanism of artificial intelligence promoting economic development through the optimization and upgrading of the industrial structure, technological innovation, and human capital was analyzed. Based on the panel data of 12 major cities in Hubei Province from 2013 to 2022, a fixed-effects model was constructed for empirical testing. The research found that artificial intelligence can significantly promote economic development. Artificial intelligence can drive economic development through three paths: the optimization and upgrading of the industrial structure, technological innovation, and human capital. The impact of artificial intelligence on economic development has regional heterogeneity. Finally, countermeasures and suggestions are provided to better promote economic development with the help of artificial intelligence.

Methods such as literature review, logical analysis, and SWOT (strengths, weaknesses, opportunities, threats) analysis were used to conduct a systematic examination of the development of sports tourism in Guiping City, aiming to explore its strengths and weaknesses while proposing feasible countermeasures. Through SWOT analysis, it is found that Guiping's advantages including strategic transportation positioning, abundant tourism resources, and rich historical heritage. However, challenges persist in inadequate understanding of sports tourism and insufficient market development expertise. Opportunities arise from contemporary demands for integrated development, supportive policies, and digital-intelligent empowerment, while threats include ecological-environmental conflicts and homogeneous competition from neighboring cities. Development strategies for Guiping's sports tourism are proposed, including the rational integration and development of sports tourism resources, adopting a “sports + tourism” oriented approach citywide, cultivating interdisciplinary management professionals, creating an eco-sports tourism brand with local characteristics, and enhancing governmental support and policy reinforcement.

The high-quality development of the sports goods manufacturing industry serves as a significant driver for building a sports powerhouse. Based on the summarization and interpretation of the connotation of high-quality development in sports goods manufacturing, an evaluation system was constructed using the entropy method. The evaluation system encompasses five dimensions, industry scale, industrial quality, innovation level, structural optimization, and green development along with 12 measurement indicators. Utilizing these indicators, the high-quality development level of the sports goods manufacturing industry in Henan Province was measured, and it is compared with that of 14 other provinces, including Fujian, Jiangsu, Zhejiang, and Guangdong. Building on this analysis, recommendations are proposed to enhance the high-quality development of the sports goods manufacturing industry in Henan Province.

In recent years, the rapid development of digital new quality productivity has given rise to the smart transportation industry chain. Taking the resilience of the smart transportation industry chain as the research object, its resilience connotation and influencing factors were defined. The OSM(objective-strategy-measurement) model was employed to construct a diagnostic index system for industry chain resilience from three dimensions: resistance, transformation, and recovery capabilities. “G1+CRITIC”(order relation+CRITeria importance through intercriteria correlation) information entropy diagnostic model was proposed for diagnosing industry chain resilience. Data from 2015 to 2024 of Jiangsu Province was selected for empirical analysis. The results indicate that the level of resilience in the smart transportation industry chain mainly depends on the recovery capability of the industry chain. The diagnostic model can effectively evaluate the resilience level of the industry chain and identify weaknesses. Based on the diagnostic results, precise measures to solidify and strengthen the industry chain can be proposed.

Taking the national advanced manufacturing clusters in the Yangtze River Delta region as a sample, the mechanism of knowledge collaboration networks on collaborative innovation performance was explored. Findings reveal that knowledge network characteristics (knowledge diversity, knowledge network density, knowledge recombination opportunities) have a positive impact on collaborative innovation performance, with knowledge absorption capacity playing a mediating role and cooperative network structural features exerting moderating effects. Specifically, network centralization and average shortest path inhibit the positive influence of knowledge network structure on collaborative innovation performance, while connectivity strengthens this positive effect. The research can provide theoretical references for enhancing collaborative innovation performance in advanced manufacturing clusters from the perspective of knowledge collaboration networks.

Exploring the coupled coordination between regional economic high-quality development and ecological environmental protection is the basis for integrating the promotion of high-quality development and high-level ecological protection. Based on the data of Heilongjiang Province from 2010 to 2022, the coupling coordination model and decoupling model were used to measure the coupling coordination degree and decoupling index between the two systems. The results show that the index of high-quality economic development in Heilongjiang province shows a fluctuating upward trend, and the index of ecological environmental protection steadily recovers after experiencing a significant decline. The degree of coupling and coordination between the two systems generally shows a rising trend, but there is still a gap with the state of high-quality coupling and coordination. Heilongjiang Province has experienced the decoupling state transition of “strong negative decoupling-expansive negative decoupling-weak decoupling” at various stages, and the decoupling state is great, while only a few years of each prefectural-level city have reached the ideal decoupling state. Based on the conclusions, countermeasures are proposed to promote the synergistic development of regional economic quality and ecological environment.

Based on data from 13 cities in the Beijing-Tianjin-Hebei Region from 2015 to 2022, an integrated evaluation system was constructed to assess urban development comprehensively across subsystems such as environmental quality, economic scale, social progress, and scientific and technological innovation. The coupling coordination degree model was then employed to measure the coordination of urban development, while the LMDI(logarithmic mean Didier index)model is used to quantitatively assess the contributions of these subsystems to overall coordination. The research results indicate that from 2015 to 2022, the overall development level of the Beijing-Tianjin-Hebei Urban Agglomeration has shown a steady upward trend, reflecting continued progress in economic, social, and technological aspects across cities in the region. However, significant spatial gradients persist in the development levels among these cities. Core cities like Beijing and Tianjin maintain a leading position in overall development, while cities farther from the core area lag behind, leading to a relatively differentiated development landscape within the region. In addition, the degree of coordination of urban development has improved, but the differences in the coordination of development among various cities are still significant. Among them, scientific and technological innovation is the main driving force for the coordinated development and changes of the Beijing-Tianjin-Hebei Urban Agglomeration, while environmental quality is still a key bottleneck restricting coordinated development and has the lowest contribution to coordinated development and changes. Finally, recommendations for optimizing the coordinated development of cities are proposed, including enhancing the radiative influence of core cities, promoting cross-regional interconnectivity, prioritizing innovation resource allocation, and strengthening cooperation in environmental protection and governance.

Based on the data of Shanghai and Shenzhen A-share listed companies from 2011 to 2022, a two-way fixed effect model was used to study the impact of digital transformation of enterprises in the Guangdong-Hong Kong-Macao Greater Bay Area on new quality productivity. The results show that the digital transformation of enterprises has significantly improved the level of new quality productivity. Mechanism-wise, the digital transformation of enterprises further promotes the development of new quality productivity by optimizing human capital, enhancing innovation quality, overcoming financing constraints, and broadening international perspectives. Heterogeneity analysis indicates that non-state-owned enterprises and high-tech enterprises perform more outstandingly in terms of improving new quality productivity in Guangzhou and Shenzhen.

In the realm of digital development, the proliferation and permeation of digital technologies into rural regions have exerted a profound influence on the political, economic, cultural, and organizational frameworks of these areas, which has catalyzed a transformative reconstruction of the rural spatial configuration in turn. Taking Lianzhang Village, a quintessential poverty alleviation site in Guangdong Province as an example, the underlying mechanisms of digitalization and its impact on the reshaping of public spaces was meticulously dissected. Findings indicate that the digital edifice can significantly facilitate the metamorphosis of rural spatial structures through the agency of digital forces, including the digital economy, digital technology, and digital infrastructure. This is realized through the application of digital operational paradigms within the realms of economic, cultural, and social spaces.The trajectory of reconstructing rural public spaces primarily involves leveraging the productive potential of these spaces to drive the digital transformation of the rural economic sector. This is achieved by enhancing the cultural gravitas and governance efficacy of these spaces, endowing rural culture with enhanced spiritual resonance and improving the convenience and openness of the inhabitants' daily lives, thereby synergistically advancing the transformation of the rural spatial structure.

The study of “production, living and ecological space” plays a significant role in optimizing national land layout, advancing ecological construction, and achieving sustainable development. Taking the central city of Lanzhou as the research object, based on POI(point of interest) data, grid division, sample square statistics, AHP(analytic hierarchy process) hierarchical analysis and GIS(geographic information system) spatial analysis techniques were used to identify and characterize the production, living and ecological spaces. The results show that the production space is concentrated in the periphery, the living space is clustered in the core area, and the ecological space is distributed in a decentralized manner.The quantity is dominated by the production and living space, the ecological space accounts for the smallest proportion, and there are very few mixed-function zones,and the four types of space all show obvious clustering characteristics. The study shows that POI data are scientific and practical in spatial identification and can provide reference for urban territorial spatial planning.

In order to realize of the Poyang Lake Eco-economic Region's “dual-carbon” goal, carbon emissions was analyzed on energy consumption, and carbon emissions from 2024 to 2035 was predicted using the logistic model. The results showed the the maximum inaccuracies between the carbon emissions predicted by the Logistic model and the actual value from 2011 to 2022 was 9.0%, and the average inaccuracies was 2.43%, which is able to fit the trend of carbon emissions in Poyang Lake Eco-economic Region. The logistic model predicts that carbon emissions in 2035 will reach 23 345.38×10⁴ t. The growth rate of carbon emissions is in a decreasing trend, from 0.85% in 2024 to 0.04% in 2035, and the carbon peak would be basically realized in 2035. The research results are of great significance in promoting the scientific development of carbon emission reduction pathway in Poyang Lake Ecological and Economic Zone.

Digital-enabled green transformation is an important path and inevitable choice to achieve high-quality development. Based on the data of Shanghai and Shenzhen A-share specialized and new “small giants” enterprises from 2013 to 2023, the impact of the digital transformation of specialized and sophisticated small and medium-sized enterprises on green technological innovation and the intrinsic mechanism of its effect were empirically examined. It is found that the digital transformation of specialized and sophisticated SMEs significantly promotes green technological innovation. This effect is more pronounced among firms in the eastern and central regions, high-level digital infrastructure firms, and high-tech firms. The mechanism analysis shows that digital transformation can promote green technology innovation by optimizing human capital structure and increasing analysts' attention. Finally, specific policy recommendations are put forward from the level of government and enterprises themselves to provide insights into the digital transformation of enterprises and the high-quality development of the economy.

The deep integration of the digital economy and real economy(DRI) serves as a pivotal strategy for driving China's high-quality economic development. Leveraging social network analysis (SNA), a DRI network was constructed using patent data from listed construction enterprises, their DRI levels were measured, and its impact mechanisms on corporate performance were investigated. Key findings include DRI significantly enhances corporate performance through dual pathways of knowledge breadth expansion and product competitiveness enhancement, with results remaining robust after addressing endogeneity concerns and rigorous robustness checks. Heterogeneity analysis reveals stronger performance improvements in high-tech enterprises, private-owned enterprises, and firms in growth/maturity stages, while stronger intellectual property protection and advanced digital infrastructure amplify these effects. Building on these insights, targeted policy recommendations are proposed to deepen DRI adoption in the construction sector.

Based on the resource-based view and dynamic capability theory, using large sample survey data from high-tech manufacturing enterprises, the mechanism and boundary conditions of the impact of digital orientation on new product development(NPD) performance was empirically analyzed. The results show that digital orientation has a positive impact on NPD performance.Organizational agility partially mediates the relationship between digital orientation and NPD performance.Top management team heterogeneity not only enhances the positive impact of digital orientation on organizational agility, but also strengthens the mediating path of organizational agility between digital orientation and NPD performance, that is, top management team heterogeneity plays a moderated mediating role. The research conclusion can provide theoretical and practical guidance for enterprises to effectively improve NPD performance under the drive of digitalization.

In recent years, high-tech enterprises have shown good performance in innovation output. Using a total of 5 418 sample data from 2021 to 2023, a regression model for empirical analysis was established to explore the impact of R&D expenses and R&D personnel on the innovation performance of enterprises. The research results show that both R&D expenses and R&D personnel have a positive impact on the innovation performance of enterprises. Heterogeneity analysis reveals that R&D expenses positively promote the innovation performance of large, medium, and small enterprises, but have no significant impact on the innovation performance of micro enterprises.

At present, the environmental costs of a large number of enterprises in China remain high. Exploring can the introduction of artificial intelligence effectively control the environmental costs of enterprises has significant importance. The financial data of Shanghai and Shenzhen A-share listed companies from 2013 to 2023 was collected to empirically test the relationship between the artificial intelligence level of enterprises and environmental costs. The research findings are as follows there is a significantly negative correlation between the introduction of artificial intelligence technology and the environmental costs of enterprises. The mechanism of action shows that the development of artificial intelligence by enterprises reduces their environmental costs through the mediating effects of alleviating financing constraints, improving the quality of internal control, and enhancing the quality of innovation. The heterogeneity analysis indicates that the impact of artificial intelligence on environmental costs varies under different enterprise scales and industry attributes.

Quantitatively assessing the incentive effect of tax incentives is of practical significance for playing the regulatory role of tax policy and promoting the development of enterprises. Taking the implementation of accelerated depreciation policy of fixed assets as a quasi-natural experiment, selecting the data of A-share listed companies in Shanghai and Shenzhen from 2010 to 2022 as samples, a multi-period double difference model was constructed to empirically test the incentive effect of tax preferential policies on enterprise growth. It is found that the policy of accelerated depreciation of fixed assets can significantly promote the growth of enterprises, and the incentive effect of this policy is heterogeneous, subject to the nature of the enterprise's equity, the nature of the industry and the size of the constraints, the growth incentive effect on non-state-owned enterprises, high-tech industry enterprises and large-scale enterprises is better. On the basis of empirical research, suggestions are proposed to further improve the tax preference policy and promote the growth of enterprises.

Under the context of China's energy powerhouse strategy and the development of characteristic new-type think tanks, focusing on the talent mechanisms of central SOE think tanks in the energy sector, a systematic analysis of their current status was conducted. The research reveals that these institutes have established a five-dimensional influence system encompassing policy, enterprises, academia, international cooperation, and society, demonstrating notable achievements in strategic support, professional capacity, and institutional innovation. However, challenges persist, including delayed pilot implementations, talent structure imbalances, and rigid incentive mechanisms. Based on comparative case studies, a three-dimensional optimization framework was proposed: structuring strategic-level collaborations through “government-industry-academia-research-application”integration to establish four-dimensional talent development objectives, designing operational mechanisms including differentiated training, market-oriented incentives, and digital governance platforms, and instituting institutional reforms such as dual-track evaluation systems and intellectual property sharing arrangements. The conclusions provide theoretical foundations and practical pathways for advancing the modernization of talent teams in energy SOE think tanks and supporting national energy security strategies.

Guangxi, as an important province in southwest China, has had an increasing demand for young scientific and technological talents in recent years driven by policy support and industrial transformation and upgrading. From the perspective of matching policy support and industrial needs, the optimization strategies for cultivating young scientific and technological talents in Guangxi were explored. The current situation of Guangxi's science and technology policies, industrial structure characteristics, and the current situation and dilemma of cultivating young scientific and technological talents were analyzed. Some ways are proposed to achieve talent training, including improving the policy system, optimizing the allocation of educational resources, deepening the integration of industry and education, improving practical ability training, and strengthening incentive mechanisms, in order to realize the effective docking with industrial needs. It is verified the correlation between policy support and talent training effectiveness, and can provided theoretical basis and practical reference for the training of young scientific and technological talents in Guangxi.

Taking the research hotspot of “science and technology boosting rural revitalization” as the research object, the research hotspots and development trends in this field were explored through bibliometric analysis and CiteSpace software. The results show that in recent years, the research enthusiasm for “science and technology boosting rural revitalization” has continued to rise, mainly focusing on four aspects: industrial prosperity, talent revitalization, rural governance, and common prosperity. The research content mainly includes digital countryside, smart agriculture, green agriculture, modern agriculture, rural governance, vocational education, and so on. Meanwhile, emerging fields such as science and technology courtyard, digital economy, and green finance will become the key directions for future research.

Under the background of rapid urbanization and industrialization, the risk of environmental damage to architectural heritage was increasingly exposed. Taking Tianjin as the research area, the advantages of macro and micro scale architectural heritage risk were comprehensively evaluated based on the environmental perspective of urban resilience. The construction heritage vulnerability environmental risk assessment system should be established with flood risk, comprehensive terrain and geological risk, atmospheric environment risk, fire risk, traffic facility risk and architectural heritage value risk as evaluation factors. Based on the past research, the quantitative factors were selected, and the spatial quantitative evaluation of geographic information system was used to screen 18 indicators and carry out correlation analysis. The research results show that the vulnerability areas of architectural heritage are highly concentrated in urban areas, and the influence of human factors is higher than that of natural factors. Generally speaking, the high vulnerability area is mainly concentrated in the peace area, which is distributed nuclear to the six districts in the city. Most of the architectural heritage is located in the six districts of the city, which has a high risk from the perspective of urban resilient environment.

Based on the qualitative research methodology of rootedness theory, 71 typical cases of rural governance were selected as the research basis, and the “subject-institution-technology-industry” practice framework for effective rural governance was extracted. It is found that grassroots organizations have positively driven the construction of rural revitalization by stimulating the vitality of the main body, establishing a sound system, introducing advanced technology and promoting industrial development. The realization of the overall goal of rural revitalization will be influenced by different subjective and objective factors, which will form the process of “reverse shaping” for the realization of effective rural governance in localities. In the practice of rural governance, the “top-down coordination” among multiple governance subjects and the “complementary coordination” among different institutional forms serve as internal driving forces, effectively empowering the implementation of the rural revitalization strategy. The “matching of supply and demand” of talents and technology, and the “internal and external” of the collective economy and social capital, as effective external driving forces for rural governance, have strongly contributed to the realization of rural revitalization.