Study on In Situ Stress Measurement and Surrounding Rock Control Technology in Deep Mine

In situ stress is the direct cause of roadway deformation and failure in the process of deep mining activities. The measured data of in situ stress in the Shuanghe coal mine show that the maximum principal stress is 44.94~50.61 MPa, and the maximum principal stress direction is near horizontal direction, which belongs to tectonic stress field. The maximum horizontal principal stress is 1.66~1.86 of the vertical stress. The horizontal principal stress controls the deep stress field. According to the measured data of in situ stress, the high-strength prestress bolt and cable collaborative support form is designed in the Shuanghe coal mine. Based on the stress field research of bolt and cable, the optimal prestress ratio of bolt and cable is proposed as 3. When the prestress ratio of bolt and cable is constant, the smaller the length ratio of bolt and cable is, the better the effect of prestressed field formed by cooperative support is. The results are applied to the support design of the mining roadway in the Shuanghe coal mine. Through the field monitoring test results, it is found that the maximum roof subsidence is 86 mm, the maximum floor deformation is 52 mm, and the maximum deformation of two sides is 125 mm. The surrounding rock control effect of the roadway is good, and the surrounding rock deformation conforms to the engineering technology standard requirements. The research results of this paper can provide some reference for the surrounding rock support of high ground stress mining roadway under similar conditions

Combined Early Warning Method for Rock Burst and Its Engineering Application

Rock burst is a common mine disaster often accompanied with casualties and property damage. In order to effectively predict and prevent the rock burst occurrence, an effective and accurate method for predicting rock burst is necessary. This paper first establishes the relationship between the drilling cuttings and the releasable elastic deformation energy. However, the traditional drilling cutting method has the defect that the drilling depth cannot reach the stress concentration area and the drilling cuttings cannot accurately reflect the internal stress variation in the deep part of coal body. So, an improved drill cutting method is presented to make up for these defects. Finally, the combined monitoring method based on the improved drilling cutting method and the microseismic monitoring method is established. It not only overcomes the limitations of a single prediction method but also effectively utilizes the advantages of improved drilling cutting method and the microseismic monitoring method. And this combined monitoring method is applied to the No. 3302 coalface of Xingcun Coal Mine. The obtained results indicate that the combined monitoring method can improve the prediction capabilities of the rock burst and provide novel insights for preventing the rock burst occurrence

Comprehensive Experimental Study of Affecting Factors on Rectangular Roadway Stability

In this paper, two methods of orthogonal numerical simulation test and similar material simulation test are used to study the influence of five factors on the stability of rectangular roadway: roadway width, roadway height, roadway buried depth, lateral pressure coefficient of surrounding rock, and comprehensive strength of surrounding rock. The results show that five factors have influence on the stability of roadway, but the degree of influence is different. The depth of the tunnel and the coefficient of the side pressure of the surrounding rock are positively correlated with the stability of the tunnel; the comprehensive strength of the surrounding rock is negatively correlated with the stability of the tunnel, but the correlation between the width and height of the tunnel and the stability of the tunnel is not obvious. The results of orthogonal numerical simulation test and similar material simulation test verify each other. The results of the field practice of the Fucun coal mine are basically consistent with the results of the two test methods, which shows that the research results have a certain guiding effect on the field roadway support

Developmental expression patterns and correlation analysis of TLR4 and its downstream genes in the intestinal and immune tissues of Meishan pigs

We aimed to evaluate the impact of milking management practices on milk quality though somatic cell count (SCC) and total bacterial count (TBC). By means of a survey that included farmers associated to two cooperatives, namely Cosulati in the state of Rio Grande do Sul and Castrolanda in the state of Paraná, the hypothesis that milking handling practices impact SCC and TBC levels negatively, regardless of the technological development level of the farm, was analyzed. For such, the quantile regression method was used to estimate models for the 10th, 50th, and 90th quantiles. The results confirmed that SCC and TBC levels decrease as the number of practices increases. However, only three practices impact SCC and TBC levels significantly, and their impact is not related to the farm technological level, according to tests performed by quantile regression. Finally, the study showed that some milk quality and management practices affect somatic cell count and total bacterial count more than others, which consists of using the correct active principle during dry cattle, post-dip, and the water temperature control period

3D Layout encoding network for spatial‐aware 3D saliency modelling

Three‐dimensional (3D) [red, green and blue (RGB) + depth] saliency modelling can help with popular 3D multimedia applications. However, depth images produced from existing 3D devices are often with low quality, e.g. containing noises and holes. In this study, rather than relying on features or predictions directly derived from single depth images, the authors propose to encode deep layout features to facilitate the spatial‐aware saliency prediction. Specifically, they first generate coarse depth‐induced saliency cues which are careless of depth details. Then, to leverage the information of the high‐quality RGB image, they embed both low‐level and high‐level RGB deep features to refine the final prediction. In this way, they take both bottom‐up and top‐down cues together with spatial layout into account and achieve better saliency modelling results. Experiments on five public datasets show the superiority of the proposed method

Spatial variations and influencing factors analysis of heavy metals in the soil of typical rocky desertification peak cluster depression

Karst peak cluster depression areas are characterized by a special double-layer hydrogeological structure, and under the influence of human activities, there are many environmental problems, such as soil erosion, rocky desertification, dryness and wetness, and heavy metal pollution. How to clarify the spatial variations and influencing factor analysis of heavy metals in the soil of typical rocky desertification peak cluster depressions has become an important content to promote the prevention and control of heavy metal pollution in soil and the comprehensive management of rocky desertification. The typical rocky desertification peak cluster depression soil in Pingguo City, Guangxi, was selected as the research object in this study.Spatial variations, associated mechanisms and pollution risk assessments of eight heavy metals (e.g., As, Hg, Cr, Ni, Cu, Zn, Cd, and Pb) in soil were carried out by using the geo-statistical, geological accumulation index, potential ecological danger index and geographical detector methods. These results show that the spatial distribution of heavy metals in the study area generally shows a downward trend from northeast to southwest. Cr and Cd show medium spatial correlation, and the other six heavy metals show strong spatial correlation, which was analyzed by semivariogram. The study area is affected by different pollution levels of Cd, As, Cr, Cu and Zn, and the impact of Cd is the most important. The geological accumulation index and potential ecological hazard index of Cd are 1.34 and 107.73, respectively, but the average geological accumulation index of other heavy metals is less than 0, and the potential ecological hazard index is less than 16.The main factors affecting the spatial differentiation of eight heavy metals in the soil of the study area are pH, stratum, Fe2O3, land use, phosphorus, CaO, Mn, distance to fault and rocky desertification degree. Moreover, the interaction types of different factor groups on the spatial differentiation of heavy metals in soil were mainly two factors enhanced and nonlinear enhanced. Therefore, it is considered that different factors have different effects on the spatial differentiation characteristics of various heavy metals in the soil of rocky desertification peak cluster depression. Cd is the most serious heavy metal element in the soil pollution degree and potential ecological harm degree of rocky desertification peak cluster depression. Strata, Mn, CaO, lithology, distance to fault and phosphorus are the key factors affecting the spatial differentiation of Cd