Aiming to explore the influence of different dosages of SBS modifier on the indicators of modified asphalt, through testing the three major indicators, elastic recovery and post-aging indicators of SBS modified asphalt with different dosages, as well as the viscosity and rutting factor of SBS modified asphalt with different dosages at different temperatures, the impact of SBS modifier dosage on the indicators of modified asphalt was analyzed to provide a theoretical basis for the optimized design and application of modified asphalt. The experimental results show that with the increase of SBS dosage, the three major indicators, elastic recovery and ductility of modified asphalt exhibit different changing patterns. The viscosity of modified asphalt first increases significantly and then increases slowly, and the viscosity of modified asphalt reaches the optimum under an appropriate dosage. The rutting factor increases with the increase of SBS modifier dosage, but when the SBS dosage reaches a certain proportion, the rutting factor only increases slightly. This indicates that the pavement performance of modified asphalt does not continuously improve with the increase of modifier dosage. When the modifier dosage increases to a certain extent, the performance of some indicators may reach a peak or decline.

Traditional research on crew scheduling problem is difficult to directly measure the real fatigue of crew when working. Crew fatigue is affected by a variety of real-world factors. A quantitative model of crew fatigue was established to measure the fatigue of the crew’s task loop, and a crew scheduling model was further constructed. Then an algorithm was designed to solve the model based on the column generation framework combined with the dynamic constraint aggregation method. Finally, numerical experiments demonstrate that the algorithm is able to solve the larger-scale crew scheduling problem in a shorter time, and the model established in this paper is able to effectively reduce crew fatigue.

With high-quality development of economy, green innovation has emerged as a crucial driving force for fostering sustainable and healthy economic growth. Digital industry agglomeration can promote the agglomeration of factor resources and industrial transformation and upgrading, thereby enhancing regional green innovation efficiency. Based on the panel data of 30 provinces(due to the lack of data, the statistical data mentioned here do not include the Tibet Autonomous Region, the Hong Kong Special Administrative Region, the Macao Special Administrative Region and Taiwan Province)from 2012 to 2021, the Super-SBM model and location entropy were used to measure the evaluation indicators of green innovation efficiency and digital industry agglomeration, subsequently, the effects and mechanism of digital industry agglomeration on green innovation efficiency were examined. The results indicate that digital industry agglomeration contributes to the enhancement of regional green innovation efficiency. Due to the differences in geographical location and technology input level, the enhancement effect of digital industry agglomeration on regional green innovation efficiency is more significant in the eastern region and high-tech input provinces. Mechanism analysis shows that digital industry agglomeration can improve regional green innovation efficiency by promoting the upgrading of industrial structure. In view of this, each province should actively promote the development of digital industry clusters, scientifically formulate differentiated digital industry development strategies and promote the upgrading of industrial structure, so as to help the steady improvement of regional green innovation efficiency.

Under the background of a new development pattern, based on the five dimensions of innovation driven, digital economy, industrial transformation, green development and open development, select the relevant data of 41 urban agglomerations in the Yangtze River Delta from 2011 to 2020.Through cluster analysis and visualization, reflecting the development level of new economic drivers in urban agglomerations from different dimensions, and then a panel data model was constructed, taking per capital GDP as the explanatory variable and the level of new economic drivers as the explanatory variable, to explore the marginal impact of new economic momentum on economic growth in the Yangtze River Delta region. Finally, some constructive suggestions are put forward from the perspective of high-quality regional economic development.

Under the “dual carbon” target, the topic of corporate ESG information disclosure has become a hot research topic nationwide. As China is still in the initial stages of sustainable disclosure, most research solely concentrates on the rating of ESG information, overlooking the quality of ESG information disclosure. Therefore, from the perspective of sustainable disclosure standards for enterprises, taking the construction machinery industry as the research sample, a fuzzy comprehensive evaluation model was adopted to establish a quality evaluation system for enterprise ESG information disclosure, in order to assist the subsequent application of sustainable disclosure standards for enterprises and further standardize ESG information disclosure work in China’s industry.

To analyze the current situation and hotspots of the development of the Chinese herbal medicine industry in China, and provide reference for the research on high-quality development of the Chinese herbal medicine industry, using “Chinese herbal medicine industry” as the keyword, search for relevant literature on the Chinese herbal medicine industry included in the CNKI database of CNKI as a sample, and use CiteSpace visualization analysis to perform graph analysis on the paper. A total of 129 research articles were retrieved from CNKI from January 2000 to December 2023 for analysis. The keywords of the research articles mainly focused on traditional Chinese medicine, ecological planting, industrial agglomeration and informatization. The research hotspots mainly focused on the ecological planting, industrial agglomeration, informatization and traceability system of the traditional Chinese medicine industry. According to the knowledge spectrum and analysis of hot literature, the current research hotspots in the traditional Chinese medicine industry are related to the introduction, guidance and implementation of policies, and have stages. Scholars often use qualitative descriptive analysis as a research method; The ecological cultivation of traditional Chinese medicine, the agglomeration of the entire industry, and the traceability system should be an important research direction in the future.

Due to the lack of sufficient interaction support, the recommendation accuracy is poor. To address this, a sparse data collaborative filtering recommendation algorithm based on knowledge graph was proposed. Extract the interaction relationship between users and items, a knowledge graph was constructed, and the entity relationships in the knowledge graph was used to extend the representation of users and items. Combining CNN networks, interactive relationships was expanded into complex structures, contextual information was captured, and similarity using Euclidean distance was calculate. A set of similar neighbors was found for the target user, user collaboration filtering was used to predict ratings, the fusion time weighting strategy was dynamically adjusted, and a recommendation list was generated. Tests have shown that the algorithm has high NDCG values, low MAE and RMSE values, and ideal recommendation performance.

Air freight is an important part of modern transportation logistics system. In recent years, with the continuous development of air freight industry, the freight volume has continued to grow. Therefore, accurate prediction of air freight volume is very important for the development and operation of air transport industry. In order to scientifically predict the air cargo business volume between cities and comprehensively consider the influencing factors such as the level of urban economic development and airport facilities, the grey forecasting model was used to predict the total cargo business volume of airports, and then the comprehensive service capacity score of urban airports and the freight attraction intensity between urban nodes were determined by using principal component analysis and improved gravity model, so as to judge the trend of cargo flow. Finally, the freight volume between urban airports in 2026 was obtained by constructing a combined forecasting model. The results show that China’s air freight business market is in a period of rapid development, and the forecast of freight volume has certain reference value for setting the operating capacity of freight airports and improving the support capacity of logistics facilities.

The coordinated development of population and economy is one of the most basic starting points in the study of all population issues. Tuojiang Green Development Economic Belt carries distinct advantages and unique positioning in the construction of “Chengdu-Chongqing economic circle”. Based on regional economics and other theories, taking 6 municipal areas in the basin as the research object, and the effect of population and industry agglomeration from the structural characteristics and interaction mechanism of population and industry agglomeration was discussed. Scientific and reasonable suggestions are provided for the construction of Tuojiang green development economic Belt from the perspectives of industrial structure optimization, regional coordination and green development.

Based on the deep cutting landslide treatment project in Caixi Township, PLAXIS 3D was used to establish a slope model with complex cracks under rainfall conditions, and the existence of cracks and the slope deformation stability under different fissure depths were analyzed. The result shows that the sliding surface of the slope changes significantly with increasing fissure depth. When the crack depth is close to the potential sliding surface, the crack divides the landslide into two separate parts, one is the crack surface itself and the other is the original sliding surface below the crack. This segmentation effect leads in a significant reduction in the slope stability. It is further found that there is a threshold effect between the crack depth and the slope stability, that is, the slope stability does not change much before the crack depth reaches a certain critical value. When the crack depth exceeds this critical value, the slope stability will decrease sharply. It reveals the influence mechanism of fissure on slope stability, in order to provide a scientific basis for slope engineering design, disaster prevention and treatment.