In order to investigate the characteristics of karst pipeline in Dongcun, Xinyu, Jiangxi Province, rationally develop and utilize Karst water resources and scientifically protect karst water environment, two kinds of fluorescence tracers, sodium fluorescein and Rhodamine, were selected for quantitative tracing test research on Karst pipeline. The distribution, morphology and hydraulic characteristics of the Karst pipeline through the penetration curve and clarifies the connectivity of groundwater recharge, runoff and discharge characteristics were analyzed. The test results show that Zhangmuqiao water-dissipation cave is connected to Niulang Zhinv cave underground river. The Karst development of the underground river is extremely developed, with large-scale Karst pipeline as the main Karst pipeline. The pipeline is single-like and the underground runoff path of the main Karst pipeline is short. Some parts of the groundwater has the characteristic of pressure-bearing. The direction of the underground runoff is from east to west. Its flow rate is fast, and so is the solute migration rate. There’s small possibility of other drainage outlets. However, there is no hydraulic connection between the Zhangmuqiao water-dissipation cave and Shenniu cave underground river outlet.

The research of landslide monitoring technology plays a key role in preventing landslide disasters, which is not only reflected in the pre-disaster early warning, but also provides a theoretical basis in the post-disaster reconstruction. A clear understanding of the history of landslide monitoring technology can not only understand the development situation of landslide monitoring, but also contribute to the improvement and update of the monitoring technology in the future. Through summarizing the work of a large number of domestic and foreign scholars, the research progress of landslide monitoring technology was expounded from three historical stages: manual monitoring stage, semi-automatic and manual monitoring stage, and semi-intelligent and automatic monitoring stage. The main instruments and methods of common monitoring technology in each period are reviewed. Combining the latest landslide monitoring technology research status, some problems necessary for further research and discussion were proposed from the four perspectives of data inversion, technology comprehensive, intelligent and low-cost technology of landslide monitoring technology.

Exploring the best method of regional landslide susceptibility assessment is of great importance for accomplishing regional hazard prevention and mitigation work.Taking Xishan mining area in Shanxi Province as the study area, nine assessment factors were selected including elevation, slope, aspect, relief, normalized vegetation index(NDVI), the engineering rock group, distance from faults, distance from roads, distance from drainages, the susceptibility of landslide hazard was evaluated and verified in certainty factor(CF) model, logistic regression model and CF-Logistic coupling model respectively, the location of landslide prone area in the study area is obtained, which provides reference for the prevention and control of geological disasters in this area.

Many types of defects are produced during the drilling of holes in carbon fiber reinforced composites, and of all the defects delamination has the most serious effect on the material. Therefore, it is crucial to develop an effective model that can accurately predict delamination in laminated materials. However, materials domain data is characterized by small samples, high latitude and complex relationships, which makes it necessary and feasible to use empirical knowledge to enhance the effectiveness of machine learning modeling. A knowledge-guided machine learning(KGML) model that integrates empirical knowledge and data-driven modeling is used to predict laminated material delamination, the fact that empirical knowledge is incorporated into the loss function as an adaptive weighting in order to enforce physical constraints during the training process. Finally, by comparing the prediction performance of the model without knowledge and the model with knowledge, the R² of the model with knowledge was improved from 0.79 to 0.91, which successfully demonstrated the advantages of empirical knowledge-based machine learning, and provide a generalized approach for delamination prediction to reduce the experimentation time and cost for researchers.

The prevailing techniques for seismic phase analysis encompass waveform classification, seismic attribute feature mapping, and seismic geomorphological delineation. The waveform classification method is a well-established and extensively utilized technique for lithological, sand body, and oil and gas reservoir prediction. Nevertheless, the conventional approach relies on equal-length time window waveform similarity, which is only pertinent to the stable zone of formation thickness. As a consequence of changes in formation thickness, equal-length seismic waveforms cannot reflect the complete lithological information, or conversely, may lead to the phenomenon of ‘time-warp’, which in turn affects the accurate revelation of the relationship between reservoirs and waveforms. A seismic waveform classification method for unequally thick layers, intending proposes to reduce complexity and enhance classification efficacy. In comparison to the traditional classification method, this approach transfers unequal seismic signals from the time domain to the Hilbert domain with constant bandwidth, thereby ensuring the completeness of the waveform extraction and simplifying the traditional two-dimensional self-organized feature mapping network into a structure with fewer neurons and a one-dimensional output layer. This adaptation is better suited to the resolution of the seismic data and the need for classification efficiency. The enhanced network retains the capacity to modify the field and value of weight correction by with the responsiveness of the output neurons to the input neurons, thereby facilitating effective control of the network size, reducing the complexity of classification calculations, and enhancing classification efficacy. The practical results confirm the effectiveness of the method and significantly improve the accuracy of waveform classification.

In response to the technical difficulties of the deep exploration and evaluation well FG119 in the Xujiahe Formation of the Sichuan Basin, an “S” shaped wellbore trajectory was designed, with limited ground conditions, resulting in increased difficulty in trajectory controlling and high safety risks of drilling tools. The implementation plan of the ϕ165.1 mm slimming well was adopted, and the development of fractures in the Xujiahe Formation and the high and low pressure interlayers led to high well controlling risks. Therefore, optimization technology for slimming well wellbore structure, complex trajectory optimization design, establishment of four pressure profiles in fractured formations, and supporting technologies such as pre bending dynamic drilling tool combination, fine pressure control, and friction reduction were carried out. This ensured the smooth completion of the first deep “S” shaped slim well in the work area, providing technical reference for the subsequent construction of complex wellbore track wells in the block.

A layout optimization model was constructed to address the issues of multiple material handling intersections, high handling costs, and low area utilization caused by the unreasonable layout of KF Company’s general valve workshop. The model considers the direction of material flow in both directions and aims to minimize material handling costs, maximize non logistics relationships, and workshop area utilization. The system layout planning (SLP) method was used to optimize the workshop layout and obtain a preliminary layout plan. Based on the traditional nondominated sorting genetic algorithm II(NSGA-II), the initial layout plan obtained by the SLP method was encoded as part of the initial population to improve the diversity of the algorithm. The adaptive control strategy was introduced into the crossover and mutation operations, and the simulated annealing algorithm was added. Finally, the analytic hierarchy process(AHP) was used to optimize the workshop layout. Process, AHP make optimization decisions on a set of Pareto optimal solutions obtained by the algorithm. The results show that this method can reduce material handling costs by 38.83%, increase non logistics relationships by 44.83%, and optimize workshop area utilization by 19.50%, demonstrating the effectiveness of the model in workshop layout optimization.

In order to reduce the floor area of ground equipment for sand control operations, meet the fast and flexible installation and disassembly of subsequent sand control operations, as well as the post-phase inspection, maintenance, inspection and repair, the layout of sand control equipment and process in deepwater gas field was studied. The modular adaptability analysis, modular equipment design, selection and module key connection design were carried out, the modular combination of surface process equipment was realized to ensure the safety and smooth completion of development Wells. Finally, the finite element analysis software SACS was used to model and simulate the module, and the load condition of the module was analyzed and calculated. The modular related design satisfies the design index and safety analysis of the operation, and has certain reference significance for the popularization of the relevant modular technology and scheme in the self-operated deepwater development projects.

Since feature point matching and optical flow estimation are closely related to the image texture, a standalone visual approach for video stabilization may not be suitable for all scenarios was used. A tightly coupled attitude-sensor-based video stabilization method was proposed. By adaptively adjusting weights, the optimal homography between images relies more on the attitude sensor in low-texture areas or more on feature matching in rich-texture areas. After obtaining the optimal transformation, a robust elastic warping method was applied to further align consecutive image frames. Experimental results demonstrate that the proposed video stabilization method achieves better performance and robustness.

Revealing the effect of particle size distribution (PSD) to the stiffness characteristics of the red stratum soil-rock mixture (RS S-RM) has significant implications for the subgrade construction, with Sichuan Basin as a representative. 20 large-scale triaxial tests with different PSDs were conducted. Introducing the concept of effective dominant skeleton size ( d_{\mathrm{e}\mathrm{d}}), digital image processing technology was utilized to collect the d_{\mathrm{e}\mathrm{d}}. The relative dominance ratio ( D_{\mathrm{d}}) describing the structural skeleton changes after the test was defined. The response of the stiffness characteristics of the RS S-RM regarding confining pressure ( {\sigma }_3) and D_{\mathrm{d}} were investigated. Validation experiment and related research verify the credibility of the formation mechanism of stiffness. The results indicate that as the shearing process, more and more particles near the shear plane transition from their initial interlocking state to sliding friction. Consequently, the soil-stone framework evolves from a suspended-dense structure to a skeleton-dense structure, and finally transforms into a skeleton-void structure; the initial deformation modulus ( E_0) relationship with {\sigma }_3 and D_{\mathrm{d}} follows: E_0 = 14.50 + ( 1 + 36.33 {{\sigma }_3}^{0.1} ) {\mathrm{e}}^{1.06D_{\mathrm{d}}}. The relationship between the tangent deformation modulus ( E_{\mathrm{t}}) of the specimen at failure {\epsilon }_1 = 15 \mathrm{\%} is E_{\mathrm{t}} = - 6.06 + ( 1 + 0.08 {\sigma }_3 ) {\mathrm{e}}^{-0.09D_{\mathrm{d}}}. Validation experiment and related research confirmed the response of E_0 and E_{\mathrm{t}} to {\sigma }_3 and D_{\mathrm{d}}. The stiffness characteristics of the RS S-RM can be predicted solely based on the PSD and {\sigma }_3.

Bedding slope is an easy-to-slide structure often encountered in mountain highway construction, and weak interlayer is a typical potential sliding surface. Taking the bedding slope of expansion project of Guangyuan-Mianyang section of G5 Beijing-Kunming highway as an example, the physical and mechanical parameters of the weak interlayer and the water content and strength parameters under different saturation time were obtained through laboratory tests. The continuous-discontinuous numerical simulation was carried out by using the finite element-smooth particle dynamics method to study the instability evolution and failure mode of the bedding slope. The results show that with the saturation softening of the weak interlayer, the water content increases and the strength decreases, and the plastic zone of the bedding slope continues to extend to the trailing edge of the slope. When the water content is higher than the liquid limit of the weak interlayer, the plastic zone range increases sharply to the first instability length, and the slope shows traction slip-crack failure. The horizontal displacement of the bedding slope has a displacement peak point at the foot of the slope at the slope line slope position, and there is a maximum displacement at the first-level slope platform ; with the increase of the water content of the weak interlayer, the horizontal displacement of the slope increases continuously, and the maximum point of the horizontal displacement appears after 1 h of saturation and begins to undergo large-scale instability deformation.

Icing on aircraft poses a serious threat to flight safety, and electric heating is an efficient method for anti-icing and de-icing. A three-dimensional mathematical model that considers water film flow and heat transfer for electric heating anti-icing was constructed. Additionally, a numerical calculation method for electric heating anti-icing was proposed. This method was applied to simulate the steady-state anti-icing process of the NACA0012 airfoil under continuous electric heating conditions. The accuracy of this calculation method was validated by comparison with existing experimental data and computational results. The results indicate that when the heating power is low, the water film flows out of the heated area and overflow ice forms downstream. Under the same inflow conditions, a higher heating power results in a higher anti-icing surface temperature and a smaller water film coverage area. Furthermore, the calculated anti-icing surface temperatures are within 5 ℃ error compared to experimental data, and for inflow temperatures no lower than 6.67 ℃, the error is less than 3 ℃.

The innovative development of core technologies in artificial intelligence field has become a competitive focus for major economies to seize the first-mover advantage. The analysis of the competitive landscape of artificial intelligence technology from the perspective of technical intelligence plays an important role to accelerate related technology innovation layout and decision-making of responding to challenges.With the help of analysis tools like Histcite, VOSviewer, and the “Science Headlines” big data collection tool of the Beijing Academy of Science and Technology, the development trend of artificial intelligence technology was identified based on data from the Web of Science database, global patent database. Combined with the analysis of the United States’ restrictive measures on China’s science and technology, the international competition situation, opportunities and challenges facing the development of China’s artificial intelligence technology were analyzed. The countermeasures and suggestions for the development of China’s artificial intelligence technology are proposed, which can provide reference for promoting the rapid iterative development of AI technology in China

To study the deformation patterns of wet-sinking loess widely distributed in the alluvial plains of the northern Tianshan Mountains in Xinjiang, experimental studies were carried out to differentiate the effects of soluble salts on the wet-sinking and dissolving effects of loess. Through the ‘three-line method’ compression test of original water content saturated with Na₂SO₄ salt solution and pure water on the original loess samples with five kinds of soluble salt contents, the influence of soluble salt content and its state of existence on the characteristics of loess wet subsidence and subsidence was obtained, and the calculation model of the amount of loess wet subsidence and subsidence deformation with different salt contents was constructed. The results show that there is a critical value for the salt content change to improve the skeleton effect between particles, and wet subsidence is the main mode of deformation when it is less than 8‰ and more than 23‰, while dissolution subsidence is the main mode of deformation when it is between 8‰~23‰; mathematical relationship between each salt content and deformation coefficients under the step-by-step pressure has been fitted by using the Giddings and Extreme model function. The FreundlichEXT regression model was used to construct the starting pressure function equation for different salt contents of soil samples in the study area. The research results can provide scientific basis for the study of the mechanism of joint action of wet subsidence and dissolution subsidence of eolian salt in the region, the design of structural loads and the calculation of deformation.

In response to the problem of insufficient accuracy of the traditional Sadovski model, based on vibration monitoring data from the soft rock tunnel blasting construction site of the West Chongqing high-speed railway, the variation trend of the model parameters of the traditional Sadovski model at different footage was explored, and the Sadovski model was improved accordingly. The fitting accuracy of the traditional model and the improved model was compared. The results show that the peak vibration velocity during blasting construction generally decreases exponentially with the increase of blasting center distance, and the traditional model has a large degree of data dispersion after fitting. In the traditional Sadovski model, the parameters k(coefficient of association)and α(attenuation index)exhibit linear and exponential functional relationships with the footage, respectively. The prediction accuracy of the modified model is improved by about 23% compared to the traditional model.

In response to the demand for reservoir protection during well maintenance of low-pressure gas wells in the South China Sea L gas field, the optimal evaluation of the system types and concentrations of foaming agents and foam stabilizers in the laboratory was carried out. A set of foam workover fluid system and preparation process suitable for L gas field were constructed. The system has a half-life of 60~72 h under reservoir conditions of 80~90 ℃ and a maximum temperature resistance of 100 ℃, demonstrating good temperature resistance and stability. The foam density can be as low as 0.5 g/cm³, matching with the pressure coefficient of the target reservoir, and effectively reducing the leakage. Through core damage test, the recovery rate of permeability of high permeability core after being polluted by foam workover fluid can reach 95.1%, indicating that the system has excellent reservoir protection performance.

The state of health(SOH) and remaining useful life(RUL) of a battery are core indicators for evaluating battery performance degradation and potential lifespan. Accurately predicting the SOH and RUL of batteries is crucial in practical applications. To capture changes in battery performance and make predictions, operational data of the battery is typically relied on to train machine learning algorithms, such as neural networks or deep learning methods. However, traditional machine learning models often adopt a single architecture to adapt to the entire dataset, which is insufficient when dealing with complex and highly heterogeneous big data. Such models generally have the risk of insufficient generalization ability and overfitting, and are inefficient in big data processing. Therefore, Hierarchical sparse mixture of experts(HS-MoE) and multi head mixture of experts(MH-MoE) models were used to construct predictive models for battery State of Health(SOH) and Remaining Useful Life(RUL), respectively. Comparative experiments were conducted on publicly available datasets from NASA and EIS, and the results showed that the MH-MoE model outperformed the HS-MoE model in predicting SOH and RUL on both datasets.

Thermoplastic resin is the main film-forming material of hot-melt marking coating, and it can guarantee the mechanical properties and service life of hot-melt marking. By changing the type and content of the resin, the influence of the resin on the mechanical properties of the hot-melt marking coating series was studied. The results show that the resin type has little influence on compressive property and wear property but has a significant impact on adhesion property, shear property, and adhesion property. At the same time, with the increase of resin content, the compressive strength increased first and then decreased, and the wear property, adhesion property, shear property, and adhesion property showed an overall increase trend. When the resin type is C5 petroleum resin and the content is not less than 20%, the hot-melt marking line has excellent mechanical properties.

Technological innovation serves as a significant driving force for economic growth. Taking the nine provinces in the Yangtze River Basin as the research object and based on panel data from 2011 to 2022, the impact of technological innovation factors on industrial economic development was studied. Empirical findings reveal that the level of technological innovation factors has an overall positive influence on regional industrial economic development. Technological innovation significantly impacts industrial economic development through various means, such as optimizing industrial structure, enhancing production efficiency, driving consumption structure upgrading, and creating new economic growth points. After conducting numerous robustness tests, this conclusion remains valid. Finally, based on the research findings, policy suggestions are proposed to promote the coordinated development of science, technology, and the economy in the region.

As the forefront of technological innovation, industry occupies a central position in promoting the development of productive forces. Accelerating new industrialization is an inevitable choice for generating new productivity, shaping new competitive advantages and stimulating new economic momentum. From the perspective of qualitative reconstruction, new industrialization leads the improvement of the efficiency of labor materials, promotes the expansion of the scope of labor objects, stimulates the ability of workers to leap, reshapes the basic elements of productivity, and promotes the leap and qualitative change of its optimized combination, giving birth to new quality productivity. From the perspective of base support, new industrialization builds a solid base for the development of new quality productivity in five dimensions, namely, market, industry, numerical intelligence, safety and greenness, and empowers the emergence of new quality productivity in an omni-directional way.The process of new industrialization can be pushed forward from the network layer, innovation layer, application layer and linkage layer to accelerate the formation and development of new productivity.

With the intensification of global climate change, low-carbon economy has become a key goal for economic transformation in various countries. Financial support is crucial for promoting low-carbon economic development. Based on provincial data of China from 2012 to 2021, a spatial Durbin model(SDM) was constructed to analyze the impact of financial structure, vitality, efficiency, and density on low-carbon economy. The results indicate that financial structure and density have a negative impact on the development of low-carbon economy, while financial vitality plays a positive role. In addition, the development level of low-carbon economy in various provinces shows spatial correlation. Based on this, it is proposed to strengthen regional policy coordination, enhance the vitality of financial markets, and promote coordinated development of low-carbon economy regions.

With the coordinated development of the Beijing-Tianjin-Hebei Region entering a new phase, the optimization and upgrading of the port logistics system have become critical factors in driving the economic vitality of the hinterland. The entropy weight method and a coupling coordination model were used to quantitatively analyze the interactive relationship between port logistics and hinterland economy in the four major port clusters of the Beijing-Tianjin-Hebei Region from 2017 to 2021. The results indicate that the efficiency and service capabilities of port logistics in the four major port clusters improved during the period from 2017 to 2021, with Tianjin Port showing the most significant performance. However, its direct driving effect on the hinterland economy remains limited. The coupling coordination level between port logistics and the hinterland economy in the Beijing-Tianjin-Hebei Region is still in a stage of mild imbalance, with uneven development within each port cluster, indicating that further potential needs to be unlocked. It is recommended to enhance the coordination between port logistics and the hinterland economy by optimizing port functional layouts, aligning with hinterland industries, deepening port collaboration mechanisms, and improving infrastructure construction, thereby promoting high-quality and sustainable regional economic development.

:In view of the existing problems of limited development and lack of experience of tourism electronic map products, based on the Kano model and Better-Worse four-quadrant analysis, in-depth interview method, questionnaire survey method and other research methods were comprehensively used to discuss the quality needs of users’ information. From the three dimensions of technical function, aesthetic emotion and utility value, user’s information quality demand type and satisfaction of tourism electronic map products were analyzed. In order to improve the design strategy of continuously optimizing technical function experience, some strategies are proposed, including deeply mining aesthetic emotional experience and focusing on utility value experience in the tourism electronic map experience, so as to improve tourists’ satisfaction and happiness experience index for the electronic map.

With the increasing penetration of new energy such as wind turbine(WT) and photovoltaic(PV) output in the energy system, the consumption of new energy in the energy system has become an urgent problem to be solved. At the same time, shared energy storage continues to participate in the grid connection, and the trading relationship between shared energy storage and other participants in the energy system is also the key to the optimization of power scheduling in the energy system. In this context, taking the energy system with micro-grids(MGs) and shared energy storage (SES) as the research object, and considering the uncertainty of new energy output, the energy system scheduling mechanism was designed based on Stackelberg game. The results of example analysis show that the actual energy capacity and power capacity of SESC have decreased by 11.83% and 31.89% respectively, and the new energy consumption rates of MGS has increased to more than 90%. The Stackelberg game scheduling strategy improves the overall operating income and stability of the energy system.

Scientifically estimating and analyzing the spatiotemporal pattern, influencing factors, and scenario predictions of carbon emissions in Yellow River Basin is of great significance for its high-quality development. Firstly, DMSP/OLS and NPP/VIIRS nighttime light data was used to simulate regional carbon emissions from 2000 to 2022 and their spatiotemporal patterns and agglomeration characteristics were analyzed. Secondly, the influencing factors of carbon emissions were analyzed through an extended STIRPAT(stochastic impacts by regression on population, affluence, and technology) model and ridge regression method. Finally, based on the extended STIRPAT model, the development trend of carbon emissions in this region under different scenarios is predicted. The results show that from 2000 to 2022, total carbon emissions in the Yellow River Basin showed an upward trend, with a significant positive global spatial autocorrelation at the prefecture-level city level. Among them, Shanxi, Shaanxi, Ningxia, and Inner Mongolia provinces exhibited “high-high” agglomeration of carbon emissions, while Qinghai, Sichuan, and Gansu provinces exhibited “low-low” agglomeration. Total population, per capita GDP, the proportion of secondary industry output value to GDP, urbanization level, energy structure, and energy intensity all contribute to increased carbon emissions in the Yellow River Basin, while government intervention has an inhibitory effect.Under different scenario predictions, the green development scenario predicts that carbon emissions will peak in 2035, while under the extensive scenario, the peaking time is delayed until 2045.

To explore the spatial-temporal coupling coordination relationship between land intensive use and regional high-quality development in Yijingjing metropolitan area, AHP(analytic hierarchy process) and entropy method were used to evaluate and measure the land intensive use and regional high-quality development from 2010 to 2022, and then the coupling coordination between the two was analyzed based on the coupling coordination degree model and the improved Tapio coupling index. The results show that the comprehensive index of land intensive use and regional high-quality development maintained positive growth, and the development trend of the latter was more stable and rapid than that of the former, showing a distribution pattern of “high in the central and eastern regions and low in the western regions”. The comprehensive index of land intensive use and regional high-quality development shows the status quo of coordination and discoordination, and the coordination degree is more and more dominant, especially in Jingzhou City, which has mainly shown the land-leading coupling and growth coupling since the “14th Five-Year Plan”. With the promotion of policies and the implementation of measures, the land economic system of Yijingjing metropolitan area is increasingly coordinated and reasonable, and the intensive use of land still needs to be promoted efficiently.

Taking 17 cities in Henan Province as the research object, the level and regional differences of digital economy development in Henan Province were analyzed by using the entropy weight method and Dagum Gini coefficient. The influencing factors of digital economy development in Henan Province were analyzed by using the fixed-effect panel model. The results show that the level of digital economy in Henan Province showed an upward trend from 2013 to 2020, and the overall level of digital economy development in 2021 and 2022 declined. There is a digital divide and Matthew effect in the development of digital economy in Henan Province. The level of economic development, government intervention, education, urbanisation rate and openness have a positive impact on the development of digital economy in Henan Province.

Drawing on the coupling theory in physics, the coupling and coordinative mechanism of higher education agglomeration and regional innovation was analyzed, an evaluation index system of the two was established. Using the coupling coordination model to measure the coupling coordination degrees of the 11 cities in Zhejiang Province from 2005 to 2019, the spatial-temporal evolution process was analyzed by using spatial statistical tools. The results show that from 2005 to 2019, the comprehensive development index of higher education agglomeration in Zhejiang Province presented a fluctuating upward trend, and the comprehensive development index of regional innovation showed a spiral upward trend, higher education and regional innovation ability in Zhejiang Province has undergone an overall development, but there is an imbalance in the 11 cities. The coupling coordination degree of higher education agglomeration and regional innovation in Zhejiang Province is generally on the rise, the overall coupling coordination types was “near maladjustment and decline” in 2005, while the types became “grudging coordinated development” in 2019. The coupling coordination development level of higher education agglomeration and regional innovation in Zhejiang Province presented the spatial pattern of “coexistence of polarization-balance” and “obvious gradient differentiation of center-periphery”, the single-polarization pattern with Hangzhou as the pole transferred to the multi-center pattern with Hangzhou, Ningbo, Jiaxing as the centers, presents a gradient difference between northeast Zhejiang and southwest Zhejiang. Based on this, some countermeasures and suggestions are put forward for the coordinated development of higher education agglomeration and regional innovation in Zhejiang Province.

Promoting design driven product innovation is currently an important measure for enterprises to enhance product competitiveness. Therefore, based on the theory of cue utilization, the intrinsic mechanism and boundary conditions of design driven product innovation on consumer purchase intention were explored. The research results indicate that aesthetics, functionality, and symbolism all have a significant positive impact on consumer purchase intention, and psychological ownership plays a mediating role between the aesthetics, functionality, and symbolism dimensions of design driven product innovation and purchase intention. In addition, brand trust can positively regulate the relationship between aesthetic and functional dimensions and psychological ownership.

Personal data is one of the most valuable segments of data and is also the most crucial resource for enterprises to create economic value. The circulation of personal data can unleash its immense potential. However, internet companies are prone to improper trading behaviors in personal data transactions, such as over-collecting personal data,inadequate data desensitization, deviation from the principles of fairness and integrity in contracts, and formalistic informed consent rules. To address these issues, regulatory measures should be implemented through the formulation of model user license agreements, the improvement of data desensitization rules, the clarification of protection obligations for internet companies, the establishment of industry self-regulatory mechanisms, and the enhancement of compliance with informed consent rules.

Under the background of global climate change and the “dual carbon” goal, the oil and gas field industry is facing a dual challenge of stabilizing oil and gas production and controlling emissions to reduce carbon emissions. In recent years, Zhongyuan Oilfield has vigorously developed new energy, with the Pusan Transfer Station as a pilot for new energy substitution. Combining the resources and energy consumption characteristics of the transfer station, the oilfield has fully utilized the waste heat resources and solar energy resources of the produced water in this area, forming a “waste heat+photovoltaic” multi energy comprehensive utilization technology, providing a clean, low-carbon and stable heat source for the transfer station. After the implementation of the project, the annual natural gas consumption has been reduced by 1.6 million cubic meters, saving 1 864 tons of standard coal annually and reducing 3 392 tons of carbon dioxide annually, achieving good economic and social benefits. It has been promoted and implemented at various transfer stations in the oilfield, laying the foundation for achieving green and low-carbon development of the oilfield.

To enhance the accuracy of customer churn prediction, an improved Stacking ensemble learning method with Bayesian optimization(BO) incorporated was introduced. First, base learners were selected based on their predictive performance and inter-model correlations. Noticing the fact that the performance variation among base learners was neglected in the traditional Stacking methods, the Bayesian optimization was introduced to fine-tune the weights of each base learner for minimizing prediction errors. Finally, the weighted predictions from the base learners were combined, and the Logistic Regression serves as the meta-learner for the final prediction. The results demonstrate that the proposed BO-Stacking model outperforms both the single models and the traditional Stacking methods in terms of recall rate, F1-score, and AUC(area under the curve) value, which validates the effectiveness of the proposed approach. This provides a reliable reference for enterprises to develop effective customer retention strategies.

To promote the digitization of standards in the field of construction engineering in China, the patterns of construction engineering standards and text structures were summarized, the process of knowledge graph construction was elaborated, and both manual and natural language processing techniques were applied to build a knowledge graph in the domain of construction engineering standards. Through practical case applications of the standards, it is verified that the knowledge graph in the field of construction engineering standards exhibits good usability in structured representation, extraction, and retrieval of relevant knowledge. The constructed knowledge graph can effectively structure and represent standard knowledge in the field of construction engineering.

China is in the stage of stock renewal and ecological civilization construction, and the renewal and optimization of urban waterfront space plays an important role. The CiteSpace metrology software was used to visually and quantitatively analyze 443 representative literatures in the research field of “waterfront space renewal”“waterfront redevelopment”“waterfront vitality” in Chinese National Knowledge Infrastructure(CNKI) database. The current research hotspot and trend of waterfront space were clarified. Based on this, the renewal path of urban waterfront space was briefly discussed from four aspects: “public”(serving the people), “garden”(conserving ecology), “city”(beautifying life), “municipality”(low-carbon and high-quality development).

With the rapid development of science and technology, the cooperation model in which multiple enterprises fund scientific research projects in the form of innovation alliances has gradually become normalized. Focusing on the problem of achievement rights and interests distribution encountered when multiple enterprises jointly fund a project portfolio, the contributions of funders were comprehensively considered in four aspects: funding amount, management contribution, research contribution, and transformation contribution. Using the fuzzy DEMATEL(decision-making trial and evaluation laboratory)-improved Shapley value method, a distribution strategy for achievement rights and interests is proposed. This provides a solution that is fair, scientific, and practical for the distribution of patent rights in multi-party jointly funded project portfolios. Through case analysis, it is confirmed that the distribution results obtained by this method are more reasonable, offering an effective approach to solving the problem of achievement distribution in multi-party funded project portfolios.

Policy oriented agricultural insurance is an important tool to reduce agricultural risks and protect farmers’ income. Since the establishment of the policy oriented agricultural insurance system in Beijing in 2007, through the policy of “raising the standard and expanding the coverage of additional products”, the full cost insurance of wheat and corn has been included in the uniform provisions, and premium subsidies have been implemented to effectively enhance the enthusiasm of farmers to participate in the insurance. At the same time, relying on satellite remote sensing, big data and other technologies, it has realized the informatization of the whole process of underwriting and claims settlement, and significantly improved the service efficiency. At present, Beijing’s policy oriented agricultural insurance has covered all agricultural administrative regions, forming a diversified risk protection system covering planting, forestry, animal husbandry and fishery, which provide strong support for agricultural modernization and Rural Revitalization.

In order to explore the relationship between education, science and technology and talent in China, the evaluation indicators of the development level of education, science and technology and talent were constructed respectively. Factor analysis method was used to calculate the development indexes of education, science and technology and talent in each province from 2018 to 2022, and the coupling coordination degree of the three systems was calculated based on the coupling coordination model. The results show that the coupling coordination degree of education, science and technology and talent systems has increased year by year, but the imbalance is still the main tone of the country. Further, the Tobit model was used to analyze the factors affecting the coupling coordination degree. It is found that the degree of opening up and industrial structure have a significant positive effect on the coupling coordination degree, and the government regulation has a significant negative effect. In order to improve the coordination level of education, science and technology and talent system, it is necessary to further expand foreign exchange and cooperation, vigorously support the development of strategic emerging industries, and enhance the systematicness of government regulation.

In order to explore the influence mechanism of digital trust on residents’ participation in community environmental governance behavior, and the mediating role of perceived value between the two, community residents in Fuzhou City were taken as the research object to conduct a field survey, and 616 sample data was analyzed by using STATA. The results of the study show that, first, the enhancement of digital trust helps to increase the enthusiasm of residents to participate in community environmental governance. Second, residents’ perceived value plays a mediating role between the two. Based on these conclusions, countermeasure suggestions are proposed, such as bridging the digital divide in old age, cultivating residents’ awareness and literacy in community environmental participation, and enhancing the transparency and responsiveness of digital government.

In order to solve the problems of weak internal motivation and insufficient resource capabilities in the ESG(environmental, social, and governance)development of Chinese enterprises, grounded theory was used to conduct a textual analysis of ESG reports from 102 A-share listed companies between 2020 and 2023. A dual-dimensional analysis model was constructed encompassing management attitude (“words”) and capital investment (“deeds”), with manual coding of the above ESG reports via Nvivo12 software, and statistical analysis of their patterns and trends. Key findings include from the perspective of management attitude, the sample companies currently focus on compliance ESG construction and institutional safeguards instead of strategic ESG development. From the viewpoint of capital investment, the sample firms’ inputs in the three ESG dimensions are significantly unbalanced, especially the environmental and governance dimensions that are under-invested. Through dual-dimensional cross-analysis, it is found that the “words” of enterprises do not match their “deeds” at this stage, but the current compliance management can be transformed into future strategic development. Industry comparative analysis shows significant differences between industries with high and low ESG ratings in both “Words” and “Deeds” dimensions, necessitating coordinated efforts to promote integrated collaboration between emerging and traditional industries. Accordingly, tripartite improvement pathways of corporate ESG construction are proposed for enterprises, government, and capital market.

In order to further explore the main research forces, knowledge base, evolution of knowledge structure and research front in the field of technology innovation management, the CiteSpace visual analysis software was used to analyze the paper data of the top 10 technology innovation management specialty journals in the Web of Science database during the year of 2000 and 2024. The results show that the main research force is concentrated in Europe, but are transferring to Asia.The knowledge base of this field includes two aspects, including theoretical perspective and research method. The evolution of knowledge structure in the field of technology innovation management is divided into four stages.The current research front in the field of technology innovation management include digital-intelligence technology innovation management and green technology innovation management.