A comprehensive indicator system for digital economy development was constructed, and provincial-level data from 2011 to 2021 were analyzed to explore the linear and nonlinear effects of digital economy on differently-skilled labor demand, with marketization level examined as a mediating variable in the linear pathway analysis and a random forest model was applied to investigate nonlinear relationships. The results show that the digital economy significantly increases high-skilled labor demand while reducing medium-and low-skilled labor requirements, and through marketization mechanisms, it primarily decreases medium-skilled labor demand and elevates high-skilled labor proportion, with nonlinear analysis revealing that high-skilled demand demonstrates initial marginal growth followed by stabilization, while medium-skilled and low-skilled demand undergoes marginal decline with subsequent low-level adjustments. Sectoral variations are also observed, as the industrial sector exhibits greater demand for high-skilled labor, contrasting with the construction sector. While medium-skilled labor shows higher affinity for service and construction industries, and low-skilled labor remains concentrated in agriculture-related sectors, highlighting the technology-driven skill restructuring effect of digital transformation across industries.

To improve the efficiency of unmanned ships in completing water quality monitoring in complex working environments, an improved A^* algorithm for global static path planning and an improved A * algorithm combined with artificial potential field method for local dynamic path planning were proposed. Firstly, the obstacles were inflated using a global algorithm, and the A^* algorithm was improved by expanding the node search neighborhood method, so that the search movement direction of the current path point was no longer limited to integer multiples of 45 °. To improve the ability of dynamic path planning, the path points planned by the A^* algorithm were used as local target points in the artificial potential field method. The artificial potential field method was improved by introducing distance factors and escape forces to solve the problem of unreachable targets and easy getting stuck in the minimum value. Finally, the effectiveness of the method was verified using Matlab. The results show that the unmanned ship could smoothly reach and pass through the water quality monitoring point. Compared with the traditional A^* algorithm, the obtained path is smoother and the distance is shorter, effectively improving the efficiency of water quality monitoring.

Medium-depth geothermal energy is one of the important clean heating energy sources because of its large heat storage capacity, good stability and wide distribution range. When using medium-depth geothermal energy for heating, considering that a certain amount of cold build-up will be generated at the bottom of the medium-depth buried pipe, the stratum heat supply capacity will continue to decay with time, i.e., the water supply temperature of the geothermal wells will be gradually reduced with the extension of time. Especially in the uninterrupted heating operation mode, the stratum heat recovery capacity is limited, how to maintain a constant heat load at the user's end under the variable temperature heating condition at the ground source side has become an urgent problem to be solved. A single heating strategy is difficult to meet the heat load demand under the variable temperature heating condition of geothermal wells, therefore, the optimisation strategy of gradient heating was proposed, which could maximize the extraction of stratum heat, convert low-grade heat source into high-grade heat source, improve the efficiency of heat extraction and reduce the operating cost at the same time compared with the former. Finally, the application and analysis of the heating strategy were combined with the pilot demonstration project of medium and deep geothermal energy building heating in CCTEG Xi’an Research Institute(Group) Co. Ltd.. The results show that the the average energy consumption of the heating system for the full heating season is 57.2 kW, and the average energy-efficiency Ratio is 21.16, which has certain guiding significance for the efficient heating application of medium and deep geothermal energy.

Aiming at the problem of information asymmetry among members of agricultural products supply chain, the Stackelberg game model of wholesale sales and agency sales was constructed by introducing brand building variables,and the pricing strategy and sales model selection in agricultural products supply chain were explored. The results show that under different market demands,the optimal pricing of green agricultural products is affected by the substitutability rate between the two agricultural products, and the commission rate and high market demand probability jointly affect the choice of the optimal sales model of cooperatives and e-commerce platforms. A suitable cooperative sales model is helpful for cooperatives and e-commerce platforms to achieve a win-win situation.

The policy of adding deduction for R&D expenses has a broad impact on high-tech enterprises, especially on their innovation activities.High-tech enterprises from 2014 to 2023 was taken as the research object to examine the impact of the R&D expense plus deduction policy on enterprise innovation. The results of the study show that enhancing the intensity of the policy has a more significant incentive effect on both R&D investment and innovation ability of high-tech enterprises. These effects are heterogeneous in terms of enterprise size, that is the incentive effect on innovation is better for large-scale enterprises. Based on the conclusions of the study, it is recommended to further increase the proportion of R&D expenses plus deduction, optimize the design of tax incentives to take into account enterprises of different sizes, and establish a perfect policy evaluation and feedback mechanism to provide a good platform for enterprise innovation.

Taking the Shanghai and Shenzhen A-share listed companies from 2012 to 2022 as an example, the relationship between the degree of enterprise digital strategic commitment and the risk of stock price crash was discussed. The results show that high-level digital strategic commitment can reduce the risk of stock price crash, and reveal the mechanism of information asymmetry in the influence between enterprise digital strategic commitment and the risk of stock price crash. By exploring the economic consequences of enterprise digital strategic commitment and the influencing factors of the risk of stock price crash, this study can fully realize the potential economic value of enterprise digital strategic commitment and promote the realization of high-quality development goals of enterprises and capital market.

Investment in new infrastructure facilitates green transformation of industries and promotes green economic and social development. Using panel data of provinces from 2013 to 2022, a comprehensive evaluation system of new infrastructure and green transformation of industries was constructed. Based on the coupling coordination degree model, the results indicate that the development levels of new infrastructure and green transformation of industries have steadily increased during the research period, with the coupling and coordination degree gradually evolving towards a coordinated state. The development of the new infrastructure and green transformation of industries exhibits significant regional differences, with outstanding performance in the east and lower comprehensive development in the central, western and northeastern regions. While the level of green transformation in most resource-based regions has improved, they are still lagging behind the national average level. Overall, the coupling coordination level displays a pattern of high in the east and low in the west.

With the continuous advancement of the digital transformation and upgrading of traditional railways, accurately obtaining information on railway basic components from massive railway line data is of great significance for railway maintenance, management, and safe operation. The difficulty lies in extracting key features of the data in the target area without distortion. The digital technology based on unmanned aerial vehicle (UAV) photogrammetry provides a new way to obtain extensive data on railway basic components. The UAV was equipped with a high-precision camera to acquire image data and graphic data of the basic components along the railway. Based on the comparison of the actual effects of two general methods for segmenting railway basic components from these two types of source data, the graphic data was selected as the segmentation data source, and the segmentation algorithm was improved. The aim is to automatically segment the rail and other railway basic components within the threshold range from the overall railway line data, and an engineering example is used to verify the effectiveness and feasibility of the algorithm.

Taking seven popular BYD models as research objects, 27 283 long-text reviews from AutoHome and DongCheDi were collected. Effective short texts were extracted using the DeepSeekV2 model, followed by BERTopic modeling to identify key consumer focus areas, including pure electric performance, blade battery and noise control. The experimental results reveal that consumers give positive feedback on battery technology and range capability but express concerns about comfort-related issues such as tire noise, wind noise and interior odors. The contributions of this study include proposing the use of the DeepSeekV2 model to split long texts, enhancing the adaptability of BERTopic in data analysis,and combining semantic embedding and hierarchical clustering techniques to uncover consumers’ multidimensional concerns and their structural relationships.

The development of advanced manufacturing clusters is an inevitable requirement for Shandong to build a strong manufacturing province, and it is also an important focus for overall development and security. In the context of the unstable global political, economic and trade environment, the resilient development of advanced manufacturing clusters will become the key to resisting risks and promoting growth. On the basis of combing the development effectiveness of advanced manufacturing clusters in Shandong Province, the shortcomings and bottlenecks faced by the development of clusters were analyzed, the mechanism framework for the formation of the resilience of advanced manufacturing clusters were studied and proposed. Countermeasures and suggestions are put forward for improving the resilience of advanced manufacturing clusters in Shandong Province from the three levels of promising government, effective market and strong society, in order to provide an effective reference for promoting the advanced manufacturing industry in Shandong to move towards the middle and high-end and improving the resilience and safety level of the industrial chain and supply chain.