As a new productivity tool, construction robots will help promote the development of new business forms and industrial upgrading in the construction industry. Aiming at the problems that the traditional building floor grinding equipment must be manually followed and controlled with low construction efficiency, an intelligent and automatic floor grinding construction robot was designed. The overall technical scheme framework and key technical principles of the robot was analyzed and explained. Then, through engineering application cases, the construction process of the floor grinding robot was described, and the comprehensive construction benefits of the robot and traditional equipment were compared and analyzed. The result shows that the comprehensive construction cost reduction rate of the robot is about 19.4%, which has a higher construction cost advantage. Finally, the social benefits of popularizing and applying the robot was elaborated as well.

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.

According to the challenge of monitoring the structural integrity of LNG storage tanks, persistent scatterer interferometric synthetic aperture radar (PS-InSAR) and small baseline subset InSAR (SBAS-InSAR) technologies were employed, sentinel-1A satellite imagery and digital elevation model (DEM) data were utilized to conduct deformation monitoring and stability assessment for an LNG terminal on an island in Guangxi, China. The results reveal three key findings. The maximum settlement occurrs in the LNG platform area in August, 2022, accompanied by slight uplift around the tanks. PS-InSAR detects annual deformation rates of -2.5 to 2 mm/year across 73% of the monitored area, while SBAS-InSAR indicats rates of -3.5 to 3 mm/year in 45% of the region, demonstrating overall deformation stability. Rainfall during the wet season shows a significant positive correlation with deformation magnitudes, where water infiltration increases soil pore pressure (reduced effective stress) and alters foundation bearing capacity, though no hazardous differential settlement is observed. The study demonstrates that radar interferometry enables millimeter-scale deformation monitoring across LNG storage facilities, providing critical technical support for operational safety in coastal areas with complex geological conditions.

Intellectual property protection and scientific research investment are important policy tools to promote scientific research in colleges and universities. Based on the perspective of policy mix, the relevant provincial data from 2008 to 2022 was used, and the propensity score matching method was applied to study the absolute effect and incentive effect of different policy mix on the scientific research output of universities, and heterogeneity test by region was conducted. The results show that the policy combination of high intellectual property protection and high scientific research investment has a significant role in promoting the scientific research output of universities. Compared with high IPR protection and low IPR protection and high IPR protection, high IPR protection and high IPR protection have a greater role in promoting the scientific research output of universities.

Coordinated development is the inevitable requirement and driving path for the three major industrial clusters of electronic information, automobiles, and equipment manufacturing to achieve high-quality development and cultivate world-class industrial clusters. An in-depth analysis of the current status of the coordinated development of electronic information, automobile and equipment manufacturing industrial clusters in the Chengdu-Chongqing region was conducted. The research finds that Chengdu-Chongqing region has achieved good results in regional linkage, industrial chain cooperation, collaborative innovation, talent training and shared cooperation. However, it still faces problems and challenges, such as homogeneous industrial structure, weak industrial chain, insufficient innovation resources, unbalanced talent finance and low digital collaboration. Therefore, corresponding countermeasures and suggestions are put forward from six aspects, such as industrial planning coordination, industrial chain cooperation, innovation resource aggregation, talent policy collaboration, financial integration and industrial digitalization.

With the increasingly widespread application of artificial intelligence (AI) technologies, more and more people are concerned about whether machine intelligence will replace traditional human labor. However, while there are concerns, the relationship between AI and traditional labor is not entirely mutually exclusive. They can cooperate under certain conditions. The BP neural network was applied to conduct a comprehensive evaluation of ChatGPT performance satisfaction, analyze the public's satisfaction with ChatGPT's performance, and provide references and suggestions for the future co-development of ChatGPT with humans. A satisfaction survey was conducted among 11 high-tech industrial parks and university students in Hangzhou, exploring the public's satisfaction with ChatGPT's generated language quality, knowledge accuracy, context understanding ability, model response speed, controllability and interpretability. In the prediction of public satisfaction, the BP neural network performs well in four indicators, such as accuracy, recall, harmonic mean and F1-score during model testing. The result shows that ChatGPT's context understanding ability, controllability and interpretability are important influencing factors of ChatGPT performance satisfaction. In the future, ChatGPT should further strengthen training and optimization in these three aspects.

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.

Aiming at the shortcomings of surface properties of CuW60 tungsten-copper alloy under extreme working conditions, laser modification technology was used to explore its influence on surface roughness and mechanical properties of the alloy. By finely adjusting the laser parameters, the microstructure, composition change of the modified layer and its correlation mechanism with the properties were analyzed. It is found that laser modification can significantly adjust the surface roughness of the alloy and enhance its mechanical properties such as hardness, which provides a new idea and method for improving the comprehensive properties of such materials. These rusults not only enriche the theoretical system of laser surface engineering technology, but also expand the application space of CuW60 tungsten copper alloy in the field of high-end manufacturing.

With the rapid development of mountain highway construction, frequent high-positioned collapse disasters have posed serious threats to road traffic safety. Based on a typical high-positioned collapse case along a highway in the western Sichuan Plateau, geological surveys and numerical simulation analysis were employed to reveal the formation mechanisms of high-positioned collapses, analyze collapse energy, and propose a hierarchical passive protection combined with monitoring prevention method. The results indicate that unfavorable topographic and geological conditions serve as fundamental factors, with long-term weathering exacerbating structural plane deterioration. Rainfall acts as a triggering factor, where rainwater infiltration induces creep deformation of unstable rock masses leading to collapse development. The prevention method utilizing passive nets, open-cut tunnels, and intelligent monitoring systems proves effective for collapse control. This protection scheme can be promoted for application in canyon geomorphological regions.

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.