To explore the effects of weak mineralized water and straw separation treatment on soil water and salt transport, through indoor soil column infiltration and evaporation test, the distribution of water and salt in soil under the irrigation condition of fresh water and slightly mineralized water with different salinity (1, 2, 3 g/L) at the buried depth of 0, 10 and 20 cm of straw interlayer was studied. The results show that there is a power function relationship between the wetting front and the infiltration time at the infiltration stage. The water infiltration rate increases with the increase of salinity, and the cumulative infiltration decreases with the increase of salinity. Kostiakov model and Philip model are used to fit the cumulative infiltration amount and infiltration time respectively, and the fitting results are good. During the evaporation stage, the straw interlayer has a significant water retention effect on the soil below the buried depth, and the vertical distribution of soil salinity shows a significant low desalination effect, and salt accumulates in the straw interlayer. When the salinity of irrigation water is 2 g/L and the depth of straw layer is 10 cm, it is conducive to soil bottom desalting, and has a better effect of promoting soil water infiltration and water retention. The research can provide basis and reference for weak mineralized water irrigation and the exploitation and utilization of straw resources.

In order to study the effect of basalt fiber on the porosity of recycled concrete under salt erosion, the internal variation of concrete was analyzed by scanning electron microscopy, and a linear regression model was established between the porosity of concrete and the number of dry and wet cycles, the height of penetration, the compressive strength and the splitting tensile strength. A fully connected neural network (FCNN) model was established for the penetration height under different soaking ages and fiber content for predicting the corrosion resistance life of basalt fiber regenerated concrete under salt erosion conditions. The results show that the porosity of concrete increases gradually with the erosion age increasing, and the appropriate addition of basalt fiber can significantly reduce the porosity of concrete, and the improvement effect is most significant when the fiber content is 1.0%. With fiber content increasing, the salt permeability resistance of recycled concrete increases, and permeability height decreases. When the fiber content is 1.0%, the best compressive strength and splitting tensile strength are obtained. The fully connected neural network model has a good effect and provides a reliable reference for the life prediction of basalt fiber recycled concrete.

The Box-Behnken experimental design and response surface methodology were employed to optimize the preparation of the aspirin micro-porous osmotic pump tablets. The core of the tablet was prepared with aspirin and β-CD inclusion, then osmotic pump tablets were obtained by coating a layer of cellulose acetate containing PEG 4000 as porogenic agent. The in vitro release test shows that the aspirin inclusion complex microporous osmotic pump tablets prepared by this process has a cumulative release rate of 1.5% and 1.6% within 0~2 h in artificial gastric juice compared to commercially available aspirin enteric coated tablets. After adjusting the release medium to pH 6.8, there is no significant difference in the cumulative drug release between the two formulations at 10 h. And the inclusion complex microporous osmotic pump tablet shows zero order release and complete release within 12 h(cumulative release rate > 90%), indicating the possibility of reducing drug damage to the gastric mucosa.

The Loess Plateau, as a natural ecological barrier in the western region of China, has made positive contributions to the sustainable development of the nation. The governance and restoration of the ecological environment on the Loess Plateau (Gansu region) plays a critical role in the implementation of China’s ecological civilization construction strategy. To monitor the changes in forest resources on the Loess Plateau (Gansu region) from 2008 to 2018, based on cloud platform, Landsat, PALSAR, and terrain data were integrated to explore the advantages of spectral index, backscatter, texture, and terrain features in obtaining forest resource information. The random forest feature selection algorithm was utilized to obtain the spatiotemporal distribution of forest cover in the study area for 10 years, and factor detection was conducted using geographic detectors. The results indicate that the random forest feature selection algorithm can effectively screen important feature information, with an overall accuracy of 91.88% and a Kappa coefficient of 0.91. The experimental scheme that integrates Landsat, PALSAR, and terrain data presents significantly higher accuracy compared to the forest classification results using a single data source. The overall accuracy of the four classification results is 86.65%, 88.23%, 90.15%, and 89.86% respectively. Over the past 10 years, the net increase in forest area in the study area is 0.60×10⁴ km². The areas with increased forests are primarily distributed in the central and eastern parts of Qingyang City, Pingliang City, Tianshui City, and the western region of Linxia Hui Autonomous Prefecture, while forest degradation primarily occurs in the southwestern part of Dingxi City and the central and eastern areas of Linxia Hui Autonomous Prefecture. In single-factor detection, land use type is the dominant factor in forest cover change, and the spatial distribution of suitable soil type and the auxiliary effect of rainfall provide favorable natural conditions for the survival rate of afforestation and the healthy growth of forests.

With the transition from traditional centralized power systems to distributed energy systems, harmonics are produced due to the penetration of renewable energy, resulting in additional losses. Distribution network loss accounts for more than half of the total system loss and is the focus of network loss reduction. A network reconstruction method based on improved binary particle swarm optimization algorithm was proposed to reduce distribution network loss. Firstly, considering the influence of harmonic wave on network loss and the harmonic effect of the line under high frequency current, the line impedance was modified. Then, the total loss of the network was calculated using the corrected impedance, and a probabilistic reverse learning approach suitable for binary algorithms was creatively proposed, integrating the theory of the good point set to obtain uniform and diverse initial particles. Finally, taking the modified 33 node power system as an example, the optimization objective was to minimize the total loss and obtain the optimal topology structure of the distribution network. The experimental results show that the distribution network reconstruction considering harmonic factors has played a good role in reducing the loss of distribution network.

Primary cracks and new cracks develop within the engineering rock mass, leading to the formation of macroscopic cracks. The hollow cylindrical discrete element simulation test enables the emulation of complex stress paths. In order to solve the problems existing in the simulation test of hollow cylindrical discrete element, such as numerous influencing factors and lengthy meso-parameter calibration, a method of mesoscale parameter calibration of hollow cylindrical sandstone discrete element based on machine learning algorithm was proposed. Through variations in input variables within the discrete element model, 210 sets of simulation data were obtained. A mesoscopic parameter calibration model based on random forest algorithm and extreme gradient boosting(XGBoost) algorithm was established, the prediction accuracy of the model was compared, the parameter sensitivity was analyzed, and the contribution of input parameters to the overall mechanical properties of the rock was quantified. Combined with the indoor triaxial test of hollow cylinder, the calibration results show that the XGBoost algorithm has the advantages of computing speed, and can quickly locate the range of discrete element mesoscopic parameters, which provides a new idea for the calibration of discrete element mesoscopic parameters of hollow cylinder, and has the value of engineering application.

In order to improve the recognition accuracy of high-altitude nuts and reduce the false detection rate of bolts and nuts, a high-altitude nut recognition model based on improved YOLOv5 was proposed. Firstly, a new attention mechanism efficient multi-scale attention(EMA) was added to the backbone network to integrate more information. Secondly, in order to enhance the network’s feature extraction capability, bidirectional feature pyramid network(BiFPN) was used to replace the PANet of the neck network. Finally, structured intersection over union(SIoU) was used to replace the original loss function complete intersection-over-union(CIoU) to accelerate the convergence of the model and improve its classification accuracy. The results show that the improved model has better performance than the original YOLOv5 model. The accuracy of the improved model increases by 0.92%. The recall increases by 0.16%. The average precision 1 (mAP_0.5:0.5) increases by 0.53%. And the average precision 2 (mAP:0.95) increases by 2.26%. An actual recognition comparison experiment between the improved model and the original YOLOv5 model was carried out. The experimental results show that the improved model has better recognition performance, which reduces the missed detection rate and the false detection rate, and improves the actual recognition rate. The improved model can well meet the recognition and image data acquisition of high-altitude nuts. And it also provide a data foundation for subsequent nut maintenance.

In order to solve the influence of intermittent and fluctuating wind energy on the economy and reliability of the system, a day-ahead and real-time energy management strategy for islanded wind power hydrogen production system with energy storage battery was proposed. In the day-ahead energy management stage, the energy management strategy of alkaline electrolytic cell power classification was adopted, and the economic energy management model of isolated wind power hydrogen production system was established with the maximum daily profit of the system as the objective function. An improved grey wolf optimization algorithm was proposed to solve the system energy management model, optimize the system energy flow and improve the system economy. In the real-time energy management stage, in order to ensure that the system can maintain stable operation when unplanned power fluctuations occur, a real-time energy management strategy for island wind power hydrogen production system based on condition identification was designed, which can adjust the system operation status in time according to the real-time operating conditions of the system. The experimental results show that the day-ahead energy management based on the improved grey wolf optimization algorithm effectively increases the daily revenue of the system and improves the economy of the system. The real-time stage energy management based on condition identification can maintain the system power balance when the wind power fluctuates under the day-ahead plan, and realize the stable hydrogen production of the electrolytic cell throughout the day.

Henan Province has abundant geothermal resources, with the northern and central regions having undergone extensive exploration and large-scale development. However, the southern region of Henan has been subject to limited exploration efforts, resulting in a scarcity of drilling data. Consequently, research on its structural characteristics, stratigraphic distribution, geothermal geological characteristics and resource potential is relatively underdeveloped. This knowledge gap poses challenges in meeting the demands for industrialization and large-scale development. Based on regional geological characteristics and two-dimensional seismic interpretation results, the research on geothermal geological characteristics, resource evaluation and favorable area prediction in Zhumadian area were carried out on the basis of previous studies. The results show that Zhumadian structure is located in five secondary structural units: Wuyang Depression, Zhumadian-Huaibin Depression, Pingyu Uplift and Changshan uplift in the southwest of Zhoukou Depression and Biyang Depression in the east of Nanxiang Basin. In Zhumadian area, the geothermal geological conditions are poor in Zhengyang and Chishan, which are located in the uplift area of Changshan Mountain. There are three sets of stratified heat reservoirs in Neogene, Paleogene sandstone and Cambrian-Ordovician carbonate rocks in this area, and the total static resources are about 115×10¹⁵ kJ. It is predicted that Biyang County urban area, Xincai County urban area and the west of Yicheng District are the most favorable areas for geothermal resources development, with moderate depth of heat storage, large water inflow and high temperature.

1g shaking table test refers to the shaking table test carried out under conventional gravity conditions, which is the mainstream type of shaking table test at present. A distinction was made between strict similarity models and strain distortion models, primarily utilizing the control equation method with supplementary dimensional analysis. The similarity relationships between these models and the prototype during different deformation stages in rock slope 1g shaking table tests were theoretically derived, and the key parameters required to achieve similarity between the model and the prototype were established. Numerical tests were conducted to verify and evaluate the established similarity relationships for different deformation stages, considering the inherent vibration characteristics and dynamic response characteristics of rock slopes. The results indicate that both strict similarity models and strain distortion models can accurately calculate the natural vibration characteristics of the prototype slope and the dynamic response characteristics during the elastic deformation stage under seismic loads. However, for large deformation issues, it is recommended that the strain similarity ratio be close to or equal to 1. These research findings provide valuable references for the design of similarity relationships and the selection of similarity models in 1g shaking table tests for rock slopes.