Boundary quantitative characterization of the top-coal limit equilibrium zone in fully mechanized top-coal caving stope along the strike direction of working face.

In the process of fully mechanized top-coal caving mining, the top-coal is affected by mining-induced stress, and the stress varies along the strike direction of working face, so the boundary position of its entering the limit equilibrium state changes accordingly. The determination of the boundary along the strike direction of working face can provide scientific guidance for the stability control of support-surrounding rock in fully mechanized top-coal caving face. Using the research methods of theoretical analysis, physical similarity simulation experiment and numerical simulation experiment, the stress state analysis model of the boundary position of the top-coal limit equilibrium zone under macro-scale conditions was established, the stress state characterization method of the boundary of the top-coal limit equilibrium zone along the strike direction of working face was given, and the quantitative characterization of the boundary of the top-coal limit equilibrium zone along the strike direction of working face was realized by combining with the mining-induced stress path, and the distance relationship between the boundary of the top-coal limit equilibrium zone and the langwall face along the strike direction of working face was revealed. The results show that after critical mining in fully mechanized top-coal caving face, the distance between the boundary of top-coal limit equilibrium zone and the langwall face along the strike direction of working face presents a relationship of increasing from top to bottom. The distance between the top-coal upper boundary and the langwall face was 2.85 m and the distance between the top-coal lower boundary and the langwall face was 5.39 m. The boundary of top-coal limit equilibrium zone along the strike direction of working face was verified by the top-coal elastic-plastic zone boundary and the boundary of the peak position of front abutment pressure in different layers of top-coal. The results show that the quantitative characterization of the top-coal limit equilibrium zone boundary along the strike direction of working face was reasonable. In order to improve mine production efficiency, optimization measures were put forward for hard coal seam and soft coal seam respectively.

Internal stress transfer characteristics of coal-rock medium under concentrated force based on particle flow method.

To solve the problem that the macroscopic deformation and failure of coal-rock medium under external loads are easy to be observed while the internal stress transfer mode and path are unclear. Based on the discrete element idea, the numerical models for pure coal or rock samples and coal-rock combination samples with different lithologies and combination methods under concentrated force are established by PFC2D software. Then the influence of coal or rock strength and combination methods on the internal stress transfer law and distribution evolution characteristics of coal-rock medium are discussed from the perspectives of macroscopic stress and mesoscopic force chain, respectively. The results showed that under concentrated load, the macroscopic stress transfer paths within pure coal or rock samples and coal-rock combination samples are primarily in the form of 'point source radiation'. However, when transferring between coal-rock interfaces, there is a certain interface effect. For pure coal or rock samples, differences in lithology does not change the transfer rules and macro distribution patterns of internal stress, but it can cause changes in internal unit transfer stress value and local area transfer direction. For coal-rock combination samples, the greater the difference in lithology between the two sides of the interface, the more likely the interface effect will occur. In addition, the internal stress transfer is also influenced by the relative stratigraphic relationships of coal and rock. When the stress is transferred from a higher-strength rock to a lower-strength coal mass, the interface effect will be more significant. However, regardless of the combination pattern, the locations where significant stress surges occur are always within the higher strength rock mass near the interface. The findings are helpful to understand the mechanical properties and failure mechanism of mining coal and rock mass, and provide a theoretical basis for the study of the mining-induced mechanical behavior of the floor under the action of the coal pillar.

Intelligent crowd sensing pickpocketing group identification using remote sensing data for secure smart cities.

As a public infrastructure service, remote sensing data provided by smart cities will go deep into the safety field and realize the comprehensive improvement of urban management and services. However, it is challenging to detect criminal individuals with abnormal features from massive sensing data and identify groups composed of criminal individuals with similar behavioral characteristics. To address this issue, we study two research aspects: pickpocketing individual detection and pickpocketing group identification. First, we propose an IForest-FD pickpocketing individual detection algorithm. The IForest algorithm filters the abnormal individuals of each feature extracted from ticketing and geographic information data. Through the filtered results, the factorization machines (FM) and deep neural network (DNN) (FD) algorithm learns the combination relationship between low-order and high-order features to improve the accuracy of identifying pickpockets composed of factorization machines and deep neural networks. Second, we propose a community relationship strength (CRS)-Louvain pickpocketing group identification algorithm. Based on crowdsensing, we measure the similarity of temporal, spatial, social and identity features among pickpocketing individuals. We then use the weighted combination similarity as an edge weight to construct the pickpocketing association graph. Furthermore, the CRS-Louvain algorithm improves the modularity of the Louvain algorithm to overcome the limitation that small-scale communities cannot be identified. The experimental results indicate that the IForest-FD algorithm has better detection results in Precision, Recall and F1score than similar algorithms. In addition, the normalized mutual information results of the group division effect obtained by the CRS-Louvain pickpocketing group identification algorithm are better than those of other representative methods.

Research on user recruitment algorithms based on user trajectory prediction with sparse mobile crowd sensing.

Sparse mobile crowd sensing saves perception cost by recruiting a small number of users to perceive data from a small number of sub-regions, and then inferring data from the remaining sub-regions. The data collected by different people on their respective trajectories have different values, and we can select participants who can collect high-value data based on their trajectory predictions. In this paper, we study two aspects of user trajectory prediction and user recruitment. First, we propose an STGCN-GRU user trajectory prediction algorithm, which uses the STGCN algorithm to extract features related to temporal and spatial information from the trajectory map, and then inputs the feature sequences into GRU for trajectory prediction, and this algorithm improves the accuracy of user trajectory prediction. Second, an ADQN (action DQN) user recruitment algorithm is proposed.The ADQN algorithm improves the objective function in DQN on the idea of reinforcement learning. The action with the maximum input value is found from the Q network, and then the output value of the objective function of the corresponding action Q network is found. This reduces the overestimation problem that occurs in Q networks and improves the accuracy of user recruitment. The experimental results show that the evaluation metrics FDE and ADE of the STGCN-GRU algorithm proposed in this paper are better than other representative algorithms. And the experiments on two real datasets verify the effectiveness of the ADQN user selection algorithm, which can effectively improve the accuracy of data inference under budget constraints.

Research on rainy day traffic sign recognition algorithm based on PMRNet.

The recognition of traffic signs is of great significance to intelligent driving and traffic systems. Most current traffic sign recognition algorithms do not consider the impact of rainy weather. The rain marks will obscure the recognition target in the image, which will lead to the performance degradation of the algorithm, a problem that has yet to be solved. In order to improve the accuracy of traffic sign recognition in rainy weather, we propose a rainy traffic sign recognition algorithm. The algorithm in this paper includes two modules. First, we propose an image deraining algorithm based on the Progressive multi-scale residual network (PMRNet), which uses a multi-scale residual structure to extract features of different scales, so as to improve the utilization rate of the algorithm for information, combined with the Convolutional long-short term memory (ConvLSTM) network to enhance the algorithm's ability to extract rain mark features. Second, we use the CoT-YOLOv5 algorithm to recognize traffic signs on the recovered images. In this paper, in order to improve the performance of YOLOv5 (You-Only-Look-Once, YOLO), the 3 × 3 convolution in the feature extraction module is replaced by the Contextual Transformer (CoT) module to make up for the lack of global modeling capability of Convolutional Neural Network (CNN), thus improving the recognition accuracy. The experimental results show that the deraining algorithm based on PMRNet can effectively remove rain marks, and the evaluation indicators Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) are better than the other representative algorithms. The mean Average Precision (mAP) of the CoT-YOLOv5 algorithm on the TT100k datasets reaches 92.1%, which is 5% higher than the original YOLOv5.

Expressions of interleukin-17 and interleukin-8 in the prostatic tissue of the patients with BPH or BPH with inflammation / 中华男科学杂志

Objective@#To investigate the expressions of interleukin-17 (IL-17) and interleukin-8 (IL-8) in benign prostatic hyperplasia (BPH) and BPH complicated with histological inflammation and their significance.@*METHODS@#According to the results of HE staining, we divided 60 cases of BPH treated by transurethral resection of the prostate (TURP) into a BPH group (n = 23) and a BPH with inflammation group (n = 37). We analyzed the clinical data of the patients and determined the mRNA and protein expressions of IL-17 and IL-8 by immunohistochemistry, real-time fluorescence quantitative PCR, and Western blot, respectively.@*RESULTS@#Compared with the BPH patients complicated with inflammation, the BPH group showed significantly lower International Prostate Symptom Score (IPSS) (29.1 ± 6.2 vs 21.6 ± 3.7), quality of life score (QoL) (5.4 ± 1.3 vs 4.4 ± 1.6), postvoid residual urine volume (RUV) (［198.6 ± 15.5］ vs ［98.2 ± 19.3］ ml), prostate volume (［69.2 ± 24.1］ vs ［49.8 ± 16.5］ ml), PSA level (［7.4 ± 1.9］ vs ［2.8 ± 0.8］ μg/L) and serum c-reactive protein content (CRP) (［5.1±2.0］ vs ［1.5±0.6］ mg/L), but a higher maximum urine flow rate (Qmax) (［4.7 ± 2.1］ vs ［8.2 ± 1.8］ ml/s) (all P<0.05). The former group had a significantly higher incidence rate of urinary retention than the latter (32.4% ［12/37］ vs 8.69% ［2/23］), mRNA expressions of IL-17 (0.303 ± 0.076 vs 0.042 ± 0.019) and IL-8 (0.536 ± 0.059 vs 0.108 ± 0.025), and protein expressions of IL-17 (0.88 ± 0.10 vs 0.34 ± 0.05) and IL-8 (1.07 ± 0.08 vs 0.43 ± 0.04) (all P<0.05).@*CONCLUSIONS@#The expressions of IL-17 and IL-8 are upregulated in the prostatic tissue of the BPH patients with inflammation, which may play a significant role in the development and progression of BPH.

The damage of rat brain mitochondria induced by endotoxin and its relation to oxygen free radical metabolism / 中国病理生理杂志

The study was undertaken to determine whether low dose of endotoxin could induce rat brain damage, and its relation to the metabolism of oxygen free radicals. Male Wistar rats were treated with E. Coli endotoxin intraperitoneally (2 mg/kg body wt). Fourteen hours later, the lipoperoxide level was markedly elevated in animals given endotoxin compared with that in the controls (5.0?1.0 vs 3.9?0.7, P