The layout of the distribution path of urban logistics terminals is the key to controlling transportation costs. In order to solve the path planning problem of urban low-carbon logistics, a brainstorming-adaptive large neighborhood search algorithm (BSO_ALNS) was proposed. Firstly, a low-carbon vehicle path model with capacity and time window constraints based on vehicle fuel consumption (CVRPTW) was established with the optimization goal of minimum total vehicle transportation cost. Secondly, the brainstorming algorithm (BSO) was used to improve the quality of the initial solution, and the heuristic crossover strategy was introduced to improve the quality of the global search. Using the adaptive large neighborhood search (ALNS) local search, ten kinds of damage and repair operators were designed, and the adaptive weighting mechanism was introduced, combined with the simulated annealing criterion to avoid falling into the local optimum. The performance of the BSO_ALNS algorithm was tested by selecting C, R, CR and other types of instances of different scales in Solomon. Taking the shortest path distance as the goal, the error between the BSO_ALNS algorithm solution and the historical optimal solution is within 1.5%. With the goal of minimizing the total cost of vehicle transportation, the optimal solution is obtained BSO_ALNS compared with BSO and ALNS. It is proved that the proposed algorithm can effectively solve the problem of urban low-carbon logistics path optimization.

Composite material is widely used in aerospace field. It is important to research the damage process of composite and its failure mode. Composite damage is a complex progressive process. In order to predict the strength and damage propagation of reinforced composite wall panels under compression conditions, taking the cap shaped single rib panel under compression load as an example, one instantaneous stiffness degradation model and three continuous stiffness degradation models were used for analysis and comparison. By reducing the stiffness of material points in the element, the damage evolution process of composite materials was simulated, and the experimental results were compared with the analysis results. The comparison results show that all four damage degradation models can accurately predict the bearing capacity and damage range of reinforced wall panels under compression conditions. Compared with other models, the constant type model in the continuous damage degradation model has the highest accuracy. The research results provide theoretical guidance for the study of mechanical properties of composite reinforced wall panels.

In order to solve the problem of poor forecasting effect due to the large number of influencing factors of aviation material consumption and small amount of sample data. A prediction model for aircraft spare parts demand based on principal component analysis (PCA), improved particle swarm optimization (IPSO), and least squares support vector machine (LSSVM) was proposed. Firstly, the principal component analysis method was used to screen the main influencing factors of aviation spare parts, and then the improved particle swarm optimization algorithm was used to optimize the least square support vector machine parameter combination, and finally the selection results and optimization parameter combination were used to complete the PCA-IPSO-LSSVM aviation spare parts demand prediction model training. The results show that compared with the other four prediction models, the PCA-IPSO-LSSVM model has the highest prediction accuracy, and the RMSE and MRE of the test set are 3.24 and 4.23%, respectively, indicating that the model has good prediction precision and fitting effect.

In order to obtain the location of erosion gullies in Bayan County, understand the spatial relations between multi-features and erosion gullies, assessing the occurrence risk, and provide information and method reference to erosion gully management and precaution, high-resolution satellite imagery, digital elevation model, soil, and precipitation data were used to acquire erosion gully locations and topographical, soil, hydrological, meteorological features. Subsequently, the spatial relations between erosion gullies and multi-feature were analyzed, and erosion gully occurrence risk was assessed using the random forest method. As results, towns like Waxing, Dexiang, and Xinglong could be paid more attention on the erosion gully management. Elevation relief, slope, slope factor, slope length factor, water flow density, and distance to water flow tend to show more spatial relations with erosion gullies, and erosion gully would participate in the redistribution of soil nutrition. On the other hand, for natural or data spatial resolution reasons, slope aspect, terrain curvature, catchment quantity, rainfall erosivity factor, soil bulk density, and soil erodibility factor show little spatial relations with erosion gullies. Assessment indicates that the erosion gully risks are mainly in arable lands with slopes between 1.5°~6°. Results indicates that topographical and hydrological features are closely related to erosion gullies, and diagonal ridge is an economical and effective measure.

In order to meet the large number of future unmanned aerial vehicle (UAV) operation requirements, the safe takeoff interval for UAVs was formulated on the basis of conforming to the safety target level and aiming at the highest efficiency. According to the operating speed error characteristics of UAVs, taking into account the operating characteristics of the climb phase and cruise phase, the takeoff safety problems in three scenarios of same route operation, cross route operation and route network operation were analyzed, a collision risk assessment model was established respectively, and a calibration method for the takeoff interval was proposed in combination with Monte Carlo simulation. Finally, taking the actual operation of logistics UAVs as an example, the 10^-7 maximum collision probability was taken as the target safety level for verification, and the minimum safe takeoff interval in the three operation scenarios was analyzed and determined. The results show that the safe takeoff interval of the same route T is 122 s, the safe takeoff interval T of the cross route is related to the difference D between the distance of two takeoff points from the intersection point and satisfies T = (D±1 199.97)/14(T≥0), and the safe takeoff intervals between the four takeoff points of the airway network system are 158, 86, 0, and 0 s, respectively. The method can provide a reference for the UAV operation enterprises to carry out takeoff interval management.

The pathogenesis of diabetic nephropathy is complex and can ultimately progress to end-stage renal disease, imposing a heavy burden on patients. Current treatment methods show limited efficacy. The protein kinase RNA-like endoplasmic reticulum kinase (PERK)-eukaryotic initiation factor-2$\alpha$(elF2$\alpha$) -activating transcription factor 4 (ATF4)-C/EBP homologous protein (CHOP) signaling pathway serves as a critical pathway in endoplasmic reticulum stress, with downstream regulation of pathological processes such as apoptosis and autophagy closely related to the progression of diabetic nephropathy. Traditional Chinese medicine regulates the PERK-eIF2$\alpha$-ATF4-CHOP pathway through methods that tonify$\mathrm{{Qi}}$and nourish$\mathrm{{Yi}}$, strengthen the spleen and benefit the kidneys, promote diuresis and reduce edema, clear heat and detoxify, as well as invigorate blood and eliminate stasis. These interventions protect the glomerular filtration barrier, reduce capillary basement membrane thickening, enhance protein reabsorption in urine, and delay renal interstitial fibrosis. The mechanistic role of the PERK-eIF2$\alpha$-ATF4-CHOP signaling pathway in diabetic nephropathy was elucidated, the theoretical basis for traditional Chinese medicine interventions in this pathway was summarized, and recent advances were reviewed in the mechanisms of action of effective components of traditional Chinese medicine targeting this pathway, aiming to provide new ideas and methods for the prevention and treatment of diabetic nephropathy through traditional Chinese medicine.

With the increasing number and aging of in-service oil and gas pipelines in China, issues such as corrosion, aging, and geometric deformation have become increasingly apparent. Due to the limitations of manual inspections, such as complex spatial environments and narrow pipe diameters, the use of pipeline robots for inspection and maintenance has emerged as a dominant trend in both domestic and international research. To address the risks of pipeline failure after prolonged service, understanding the latest advancements in pipeline robotics is crucial for setting forward-looking development goals and minimizing redundant research efforts. A comprehensive review of recent developments in in-service pipeline robotics was provided, these robots were divides into two main types based on their movement mechanisms and working environments: internal (passive and active) and external pipeline robots. By examining specific examples of each type, their overall performance were compared and highlighted key considerations for field applicability. Furthermore, the future directions were explored for pipeline robotics, emphasizing the importance of multi-parameter integration in ensuring the safe operation of oil and gas pipelines in the future.

As a widely distributed and abundant clean energy source, geothermal energy may lead to inefficient resource utilization and a series of ecological environmental issues when improperly developed. The typical geothermal distribution area in Linqing, Liaocheng City, Shandong Province was selects as the research object. Based on detailed geothermal geological survey data, the construction of a "multi-well coordination system" geothermal heating model was explored and the feasibility analysis with operational benefit was conducted. The results demonstrate that the proposed coordinated multi-well geothermal heating mode can reduce geothermal resource extraction by 41.46% while maintaining equivalent heating coverage and quality standards, significantly enhancing maximum utilization efficiency of geothermal resources. The system simultaneously achieves geothermal tailwater reinjection with favorable economic returns. The static investment payback period approximates 3 years, and the total revenue over 20 heating seasons reaches 25.742 million yuan. Through zoning division implementation in key operational areas, this model effectively addresses challenges including dense well distribution, uneven development patterns, and difficulties in reinjection well construction. The findings provide technical references and application demonstrations for geothermal heating development in other regions.

In order to study the formation mechanism, paleoenvironment, paleoclimate, tectonic background, and source of black shale in the Shengping Formation of the Middle Ordovician in northern Guangxi, sixteen samples of black shale and black siliceous shale were collected from the Shengping Formation at Xishuiyuan section in Quanzhou County, Guilin City, Guangxi Zhuang Autonomous Region, and element geochemistry testing and analysis were conducted on them. The results show that the content of the main element${\mathrm{{SiO}}}_{2}$in the black shale of the Shengping Formation at Xishuiyuan section is the highest (${62.37}\%\sim {91.65}\%$, average${78.04}\%$), followed by${\mathrm{{Al}}}_{2}{\mathrm{O}}_{3}({2.88}\%\sim$16.92%, average 9.15%). Compared with the North American shale (NASC), the content of trace elements in the study area shows a loss for all elements. The value of the sample${\left(\mathrm{{La}}/\mathrm{{Yb}}\right)}_{\mathrm{N}}$is${7.185}\sim {15.858}$, with an average of 10.678. The light rare earth elements (LREE)/ heavy rare earth elements (HREE) values are${8.165}\sim {15.440}$, with an average of 11.029. It indicates that the differentiation phenomenon of light and heavy rare earth elements is more obvious, and LREE are relatively enriched compared to HREE. The δEu value exhibits negative anomalies$\left({{0.589}\sim {0.950}}\right)$, with an average value of 0.758 ; The$\delta \mathrm{{Ce}}$value exhibits positive anomalies$\left({{1.165}\sim {1.412}}\right.$, with an average of 1.259). The geochemical characteristics show that the structural background of the black shale source area in the Shengping Formation of the Xishuiyuan profile is passive continental margin, and the source rock type is sedimentary rock. The source area has undergone moderate to strong chemical weathering, which is greatly affected by chemical weathering, with a predominantly warm and humid climate. The sedimentary environment is mainly a deoxidizing environment with oxygen deficiency.

To explore the impact of the spatial distribution of material sources within a watershed on the susceptibility to debris flows. The nearest neighbor index was adopted, based on the principles of mathematical statistics, to quantify the spatial clustering of material sources. Using 2243 small watersheds as evaluation units, the longitudinal gradient, area-elevation integral, topographic wetness index, peak ground acceleration of earthquakes, and rock hardness were taken as disaster-prone indicators, and the aggregation index of material sources, connectivity index, and material reserves were taken as the core material source indicators. The LightGBM model was relied on to investigate the susceptibility to debris flows in the Shigu-Gangtuo section of the upper reaches of the Jinsha River. The research process calculated the index system of material source factors and the index system without material source factors. Both results indicate that the high and very high susceptibility areas are mainly concentrated in the Benzilan-Batang section. The receiver operating characteristic curve (ROC) curve analysis shows that after incorporating the material source characteristic indicators, the area under the curve (AUC) value increases by 6% compared to the AUC value without material source characteristics, indicating that the model performs well and has high predictive accuracy after the inclusion of material source indicators. It also proves that the material source characteristic indicators are highly correlated with the probability of debris flow occurrence.