Vegetation fires may lead to tripping and shutdown of overhead transmission lines, thus endangering the safe and stable operation of power grids. In order to study the change of flame inclination of vegetation under the influence of ambient wind, a square fir crib with the size of 1 m×1 m×0.6 m was used as the research object, and a 5 m×5 m×5 m outdoor site with ventilation was set up by Pyrosim software, and simulation research was carried out on 10 free burning cases with the wind speed of 1~10 m/s, and the change of the flame pattern with the size of the wind was analysed. The formula for calculating the flame inclination applicable to this wind speed range was fit. The flame inclination calculation formula was based on the flame inclination of this range, and the flame inclination calculation formula was based on the flame inclination of this range. The change of flame shape with the wind speed was analyzed. The formula for calculating the flame inclination angle applicable to the wind speed range was fitted. And the horizontal offset distance of the flame was obtained according to the change of the flame inclination angle. The results show that the larger the wind speed is, the smaller the change of flame inclination and flame horizontal offset distance are. The results of this study can be used as a reference for the prevention of tripping accidents on transmission lines and the cutting distance of vegetation on both sides of transmission line corridors.

In order to predict perforation velocity of SCS (steel-concrete-steel) slab against missile impact and obtain influence sequence of structural factors of SCS slab on the perforation velocity, a dimensionless equation of the perforation velocity was established and a prediction model was obtained based on dimensional analysis and artificial neural network. Orthogonal experiment design was used to determine finite element calculation, and the influence degree of 7 factors of SCS slab on perforation velocity was quantitatively evaluated by variance analysis. The deviation between the predicted perforation velocity and the actual value is less than 12%, and the quantitative evaluation results of variance analysis show that the thickness of steel plate has a largest effect, followed by the distance of tie bar and the thickness of concrete, the yield strength of steel plate, the yield strength of tie bar and the diameter of tie bar have a smaller effect, and the concrete compressive strength has a smallest effect. The established model solves the prediction problem of perforation velocity from a new perspective with a good prediction effect, which can effectively evaluate the ability of SCS slab against perforation failure of missile impact, and the order of the factors is beneficial to the optimal design of SCS slab resisting perforation from missile impact.

As an important aluminum industrial base in China, the bauxite concentration area in central Guizhou Province is hosted within the Lower Carboniferous Jiujialu Formation, and the deposit type belongs to the sedimentary bauxite. The Caijiaba bauxite deposit is a newly discovered bauxite deposit during the fine investigation of bauxite in central Guizhou Province in recent years. The paleoclimatic conditions, sedimentary environment and metallogenic provenance related to this bauxite deposit in the metallogenic process were studied. The results show that the upper bauxitic claystone of the Al-bearing rock series is mainly pelitomorphic texture and is mainly composed of kaolinite and illite. The middle bauxite ore is mainly clastic and cryptocrystalline textures, followed by a small number of ooidal texture, which is mainly composed of diaspore and illite. The lower ferruginous rock is mainly cryptocrystalline texture and is mainly composed of hematite. The Al-bearing rock series of the Caijiaba bauxite deposit is mainly formed in the continental environment, and the upper bauxitic claystone and middle bauxite ore layers are mainly formed in a relatively oxidized environment, while the lower ferruginous rock layer mainly shows a relatively reduced environment. Meanwhile, the lower ferruginous rock and middle bauxite ore layers are mainly formed in hot and humid paleoclimatic conditions, while the upper bauxitic claystone layer is the product of warm and humid climatic conditions. Research on the sources of ore-forming materials indicates that the Al-bearing rock series of the Caijiaba bauxite deposit is mainly derived from the dolomite and interbedded gray-green claystone of the Lower Cambrian Qingxudong Formation.The results are of great significance in guiding the exploration and prospecting of bauxite deposits in this area.

In order to reveal the association patterns between ferroptosis-related diseases and genes and predict potential Disease-Gene associations, ferroptosis-related research literature was analyzed to extract disease and gene entities, and a disease-gene complex network was constructed. The network's basic characteristics were further analyzed, and the Apriori algorithm was applied to extract strong disease-gene association rules. Link prediction technology was used to identify potential disease-gene associations. The results show as follows. ferroptosis plays a critical role in lethal diseases such as hepatocellular carcinoma, adenocarcinoma, breast cancer, and colorectal cancer. The genes such as GPX4 and ROS play key roles in cell survival or death through the regulation of iron homeostasis, oxidative stress, and lipid peroxidation. GPX4 and ROS are significantly associated with various diseases. The link prediction method revealed potential target genes for adenocarcinoma, lung cancer, colorectal cancer, and breast cancer, and preliminary validation of some predicted results was conducted through literature review.It is concluded that the research methodology employed in this study is both feasible and effective. The findings offer valuable references and suggest future directions for research on the prevention and treatment of ferroptosis-related diseases.

To solve the problem of bearing fault and complex sound field environment, taking H7009C full ceramic angular contact ball bearing as the research object, the dynamic analysis model of full ceramic angular contact ball bearing was established, and the error of theoretical calculation and simulation of rolling body was compared to verify the validity of the model. Based on the transient dynamic analysis of the influence of inner ring fault on the bearing dynamic characteristics, the surface SPL (sound pressure level) of bearings caused by different faults was calculated, and the SPL characteristics of high-speed bearings were compared under the action of variable speed and variable load. The results show that the sound pressure level of the faulty inner ring bearing increases with the increase of speed, and increases first and then decreases with the increase of load. When the ratio of the lowest sound pressure level frequency to the vibration frequency is close to 0.75 or the ratio of the highest sound pressure level frequency to the vibration frequency is close to 4, it can be identified as an inner ring fault.

In order to analyze the effect of maximum window area and multi-resolution DEM (digital elevation model) on the extraction of optimal area for relief amplitude, explore feasible solutions to quantitatively analyze the optimal area, and classify landforms based on the best results of various types data. Based on three DEM data obtained, including ALOS (advanced land observing satellite), ASTER GDEM.V2 (Version 2 of the advanced spaceborne thermal emission and reflection radiometer global digital elevation model) and SRTM3 (3 arc-seconds shuttle radar topography mission), the influence mechanism was statistically analyzed by calling the Arcpy module and using the mean variation point method, respectively, with the maximum window area and the resolution of the DEM as a single variable. In order to determine the appropriate maximum window area, the traversal method to correlate the relief amplitude classification results with the DEM data were proposed, to determine the optimal area for different data according to the maximum correlation coefficient, and to arbitrate the elevation classification data to obtain the geomorphic distribution map. The results show as follows. The optimal area increases in a stepwise manner with the increase of the maximum window area. There is a negative correlation between the DEM resolution and the optimal area in the same area range, that is, the corresponding area decreases sequentially with the increase of resolution. Based on the correlation analysis, the maximum correlation coefficient of ALOS DEM is 0.785 0, which corresponds to the optimal area of 0.21 km². ASTER GDEM.V2 DEM is 0.764, with an area of 0.32 km², and SRTM3 DEM is 0.782, with an area of 0.40 km². The geomorphological classification maps corresponding to the optimal areas of the three data were obtained, and by comparing them with the spatial distribution of China's 1∶1 million geomorphological types, it is concluded that the distribution of geomorphological features of the experimental data is more reasonable, and the boundaries are more clear. It is concluded that the maximum window area has a greater influence on the optimal area compared to the DEM resolution, and in order to solve the influence of the maximum window area, the correlation analysis can provide a theoretical basis for quantitatively determining the optimal area of relief amplitude.

With the rapid development of the Internet and social platforms, the problem of spammer detection has become a major technical challenge in building a harmonious Internet environment. However, user data collected from social platforms are often subject to issues such as missing information and data noise. Therefore, in graph-based learning models for bot army detection, methods that use point estimation as weights fail to express uncertainty in regions with sparse or missing data. A graph neural network model for bot army detection, VRGAT, integrating variational inference, was proposed. It introduces a probability distribution for the weights and derives a variational approximation of the true posterior. By applying different convolution operations to the mean and variance, the model more accurately captures the variability in the data. Simulations based on the Twibot-20 dataset show that, compared to the best existing benchmark for bot army detection (F₁ = 88.12), VRGAT achieved an improved performance with an F₁ score of 89.64.In robustness experiments, when random noise was added at varying levels, the accuracy drop for VRGAT is significantly slower than for other baseline models, demonstrating its superior noise resistance. The experimental results demonstrate that the introduction of variational inference can enhance the effectiveness of spammer detection and improve the model's robustness against noise.

To study the influence of dense floor openings on existing main structures of subway stations, based on the reconstruction and expansion project of Dongsi Shitiao Station on Line 3 of Beijing Subway, finite element analysis method was used to simulate the dense openings on the bottom plate and the construction of vertical shafts. The stress and deformation characteristics of the station main structure were analyzed, and the impact of different phased opening schemes on the structural deformation of the station floor was discussed. Finally, verification was conducted in conjunction with on-site monitoring. The results show as follows. During the excavation and support process of shafts after floor opening, staggered excavation of adjacent shafts can effectively reduce the deformation of the station main structure, with the deformation being related to the depths of the two shafts and the distance between them. When the number of floor openings is large and dense, the opening order needs to be reasonably allocated. Through comparison and optimization of different phased opening schemes, it is found that compared to the three-phase opening scheme, the two-phase opening scheme increases the settlement by an average of 0.3 mm. However, the former shortens the construction period, improves construction efficiency, and is therefore recommended under the condition of meeting deformation control requirements.

To compare and analyze the differences in pore structure characteristics of coal from Huainan and Huaibei, this study focuses on No. 13 coal from Liuzhuang Mine in Huainan mining area and No. 7 coal from Qidong Mine in Huaibei mining area. Using mercury intrusion porosimetry and low-temperature nitrogen adsorption methods, the pore structures were analyzed, and fractal theory was applied to study the fractal characteristics of the pore structures. The differences in pore structures between Huainan and Huaibei coals were compared and analyzed. The mercury intrusion results show that the total pore volume and specific surface area of No.13 coal from Liuzhuang are 3.488 mL/g and 0.02 m²/g, respectively, while those of No.7 coal from Qidong was 4.926 mL/g and 0.027 m²/g, respectively, with Qidong coal having a larger pore volume. Both coals show the largest pore volume in macropores and the smallest in mesopores. Low-temperature nitrogen adsorption results indicate that the specific surface area ratio of micropores in No.13 coal from Liuzhuang is 76.25%, showing the most developed micropores. The specific surface area ratio of small pores in No.7 coal from Qidong is 79.79%, showing the most developed small pores. Fractal analysis demonstrate that both coals exhibited fractal characteristics. From mercury intrusion data, the fractal dimensions of pores larger than 100 nm for No.13 coal from Liuzhuang and No.7 coal from Qidong are 2.805 6 and 2.756 7, respectively. From low-temperature nitrogen adsorption data, the fractal dimensions of pores smaller than 100 nm for No.13 coal from Liuzhuang and No.7 coal from Qidong are 2.727 5 and 2.037 2, respectively, all within the range of 2 to 3. This indicates that the pore structure of No.13 coal from Liuzhuang is more complex and heterogeneous, especially in the range of small pores and micropores, where the fractal dimension differences are more significant. This may be related to differences in maceral composition and mineral content, where vitrinite is the main component for pore development in coal and shows a positive correlation with pore fractal dimensions. Exinite and inertinite are not primary components for pore development and show a negative correlation with pore fractal dimensions. Uneven mineral distribution may increase the heterogeneity and complexity of the coal pore structure, thus showing a positive correlation between mineral content and fractal dimensions in the two types of Huainan and Huaibei coal samples.

With the rapid development of industry and agriculture, the situation of Cd pollution in farmland soil is severe. Cd pollution in farmland will directly or indirectly have adverse effects on soil ecological security, crop growth and human health development. Cd has received extensive attention due to its strong biological toxicity and easy migration and accumulation, and effective management and control of Cd pollution in farmland is urgently needed. At present, the remediation technology of Cd pollution in farmland soil has been gradually developed and enriched, but the summary analysis of the remediation technology is relatively lacking. The characteristics and hazards of farmland soil Cd contamination were analyzed, focusing on the current status and sources of farmland Cd pollution. Based on this analysis, the principles, characteristics, and applicable scopes of remediation technologies for Cd-contaminated farmland soil were summarized. Case studies were used to compare the practical application effects of these remediation technologies. Additionally, the advantages, disadvantages, and limitations of various remediation approaches were examined, providing theoretical references for the prevention and remediation of farmland soil Cd pollution and promoting high-quality development of agriculture.