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Coal bump, a common dynamic disaster in mining of deep coal resources, its assessing and predicting is an important component in safety management. This paper presents a model to assess and predict coal bump risk based on multiparameter indices. A new energy accumulation index S was proposed by considering acoustic emission and electromagnetic emission signal characteristics in mine shocks. Combined with indices E (energy of microseisms) and N (frequency of microseisms) of microseismic monitoring, a static and dynamic coal bump risk assessment and prediction model was established. We studied coal bump events that occurred during extraction in 311305 working face of Bayangale coal mine in Inner Mongolia, China. We obtained the acoustic emission and electromagnetic emission signal distribution and change law, using principal component analysis method and density ellipse to establish the index S. A typical precursory of coal bumps is that AE and EME strength has obvious fluctuation period of 3-4 days, index S showing an obvious decreasing trend, while the time-series curve of the microseismic energy is relatively stable, and the vibration frequency curve has a significant upward trend. After predict the potential coal bump risk and its area of occurrence, large diameter drilling (Φ150 mm) on-site was used to relief pressure concertation in coal seam and roof. The results demonstrate that this model based on multiparameter indices is capable of quantitatively prewarning rock burst risk. [ABSTRACT FROM AUTHOR]

The Kubuqi Desert is the seventh-largest desert in China. Under the leadership of the central, autonomous region and local governments, the ecological situation has undergone historic changes. In this paper, we select Hangjin Banner and Dalate Banner, which have the most widely distributed deserts and use 347 households as the research perspective to construct the evaluation index system of the government's ecological environment governance effect. The entropy method is used to evaluate the governance effect, and the ordinary least squares and quantile regression are used to compare the evaluation differences of different publics. The research found the following. (1) The public believes that the government's ecological governance measures have achieved good results in the third-level index analysis. The ecological environment in the desert area has been significantly improved; that is, the survival rate of trees has increased, the area of vegetation coverage and vegetation types have increased, and the frequency of sandstorms has decreased. However, the intensity of sandstorms and the flow of water sources did not change significantly. The various types of public income have increased significantly compared to before the governance. The public takes the ecological priority as the concept and actively participates in the government's governance implementation, which means that the ecological awareness and behavior are higher. (2) Among the second-level index, the weights and scores in descending order are public economic characteristics: 45.53% and 0.4840, public ecological behavior: 25.62% and 0.1682, public ecological effect perception: 18.35% and 0.1240, and public ecological awareness: 10.51% and 0.0291. The comprehensive evaluation result is 0.8054, which is in the first grade, and the effect is excellent. (3) The public comprehensive evaluation results of the two regions are similar. Hangjin Banner is 0.8209 and Dalate Banner is 0.8557, both in the first grade. The effect is excellent. (4) In the OLS regression results, gender has a significant positive impact on evaluating the government's ecological environment governance effect. Age, ethnicity, and occupation have a significant negative impact. As the quintile increases, the influence of gender, age, and ethnicity first increases and then decreases. The maximum regression coefficient of gender at the 50% quantile is 0.714, which has a significant positive effect. Age has a significant negative impact at each quantile. The regression coefficient of ethnicity at the 50% quantile is the highest -0.357, which has a significant negative impact. Occupation only has a significant negative impact at the low quintile. [ABSTRACT FROM AUTHOR]

Great efforts have been made to curb soil erosion and restore the natural environment to Inner Mongolia in China. The purpose of this study is to evaluate the impact of returning farmland to the forest on soil erosion on a regional scale. Considering that rainfall erosivity also has an important impact on soil erosion, the effect of land use and land cover change (LUCC) on soil erosion was evaluated through scenario construction. Firstly, the universal soil loss equation (USLE) model was used to evaluate the actual soil erosion (2001 and 2010). Secondly, two scenarios (scenario 1 and scenario 2) were constructed by assuming that the land cover and rainfall-runoff erosivity are fixed, respectively, and soil erosion under different scenarios was estimated. Finally, the effect of LUCC on soil erosion was evaluated by comparing the soil erosion under actual situations with the hypothetical scenarios. The results show that both land use/cover change and rainfall-runoff erosivity change have significant effects on soil erosion. The land use and land cover change initiated by the ecological restoration projects have obviously reduced the soil erosion in this area. The results also reveal that the method proposed in this paper is helpful to clarify the influencing factors of soil erosion. [ABSTRACT FROM AUTHOR]

Earlier studies on the innovation process in the high-tech manufacturing industry failed to take environmental pollution into account, making it difficult to estimate green innovation efficiency in the industry. From a perspective of innovation value chain, this paper decomposes green innovation process in the high-tech manufacturing industry into two stages: R&D stage and achievement transformation stage; a network DEA approach considering undesirable outputs is utilized to estimate the green innovation efficiency in China's high-tech manufacturing industry. Compared with the method of conventional innovation efficiency without considering environmental pollution, the estimation method for green innovation efficiency can not only avoid bias of estimation results of provinces producing low pollution emissions like Inner Mongolia and Hainan but also reflect the volatility in efficiency of the high-tech manufacturing industry before and after the implementation of the environmental law. [ABSTRACT FROM AUTHOR]

Potholes are the most common form of distress on cement concrete pavements, which can compromise pavement safety and ridability. Thus, timely and accurate pothole detection is an important task in developing proper maintenance strategies and ensuring driving safety. This paper proposes a method of integrating the processing of grayscale and texture features. This method mainly combines industrial camera to realize rapid and accurate detection of pothole. Image processing techniques including texture filters, image grayscale, morphology, and extraction of the maximum connected domain are used synergistically to extract useful features from digital images. A machine learning model based on the library for support vector machine (LIBSVM) is constructed to distinguish potholes from longitudinal cracks, transverse cracks, and complex cracks. The method is validated using data collected from agricultural and pastoral areas of Inner Mongolia, China. The comprehensive experiments for recognition of potholes show that the recall, precision, and F1-Score achieved are 100%, 97.4%, and 98.7%, respectively. In addition, the overlap rate between the extracted pothole region and the original image is estimated. Images with an overlap rate greater than 90% accounted for 76.8% of the total image, and images with an overlap rate greater than 80% accounted for 94% of the total image. A comparison discloses that the proposed approach is superior to the existing method not only from the perspective of the accuracy of pothole detection but also from the perspective of the segmentation effect and processing efficiency. [ABSTRACT FROM AUTHOR]