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In mainland China, there are large surface areas covered with shallow overburden (Regolith thickness < 100 m). Geological mapping is difficult here as there is not enough exposed bedrock. In this paper, we transfer geochemical and geophysical data to characteristics, and use it in geological mapping to identify the underlying bedrock. Above all, we define the "represent area of one geochemical sample" as one "statistical unit". All geophysical data in each unit (hundreds of data) are analyzed generating statistical parameters, such as mode, interquartile range, frequency, skewness, and kurtosis, which are combined together to describe the characteristics of rocks in this area. As for the geochemical data in each unit, some rock-forming elements are screened to build new parameters, such as SiO2, Na2O + K2O, CaO, Al2O3, FeO + MgO. All geophysical and geochemical parameters are regarded as characteristics of one unit. The merged array is normalized so that all the parameters have uniform weight and the comparability between different parameters is improved. Then, K-means clustering method is used to classify all the samples in a research area. As the K-value is very difficult to estimate, it is necessary to conduct further experiments with different K-values, determine and explain the relationship between different classifications, and then identify the best classifications. Using the field information as a reference, one or more classifications are judged as one geological body. The method in this paper is practiced using the Tahe area, located within a typical shallow overburden area in Northeast China, as a case study. We used seven elements of 334 geochemical samples and 41.222 geological samples. K-values of 6, 7, 8, and 9 are calculated. We were successful in identifying geological bodies, and gained a new understanding on the scope of some rocks types. It is believed that the method proposed in this paper is highly efficient, easy to conduct, and can provide more detailed and comprehensive information than traditional methods. [ABSTRACT FROM AUTHOR]

Chinese Sign Language (CSL) offers the main means of communication for the hearing impaired in China. Sign Language Recognition (SLR) can shorten the distance between the hearing-impaired and healthy people and help them integrate into the society. Therefore, SLR has become the focus of sign language application research. Over the years, the continuous development of new technologies provides a source and motivation for SLR. This paper aims to cover the most recent approaches in Chinese Sign Language Recognition (CSLR). With a thorough review of superior methods from 2000 to 2019 in CSLR researches, various techniques and algorithms such as scale-invariant feature transform, histogram of oriented gradients, wavelet entropy, Hu moment invariant, Fourier descriptor, gray-level co-occurrence matrix, dynamic time warping, principal component analysis, autoencoder, hidden Markov model (HMM), support vector machine (SVM), random forest, skin color modeling method, k-NN, artificial neural network, convolutional neural network (CNN), and transfer learning are discussed in detail, which are based on several major stages, that is, data acquisition, preprocessing, feature extraction, and classification. CSLR was summarized from some aspect as follows: methods of classification and feature extraction, accuracy/performance evaluation, and sample size/datasets. The advantages and limitations of different CSLR approaches were compared. It was found that data acquisition is mainly through Kinect and camera, and the feature extraction focuses on hand's shape and spatiotemporal factors, but ignoring facial expressions. HMM and SVM are used most in the classification. CNN is becoming more and more popular, and a deep neural network-based recognition approach will be the future trend. However, due to the complexity of the contemporary Chinese language, CSLR generally has a lower accuracy than other SLR. It is necessary to establish an appropriate dataset to conduct comparable experiments. The issue of decreasing accuracy as the dataset increases needs to resolve. Overall, our study is hoped to give a comprehensive presentation for those people who are interested in CSLR and SLR and to further contribute to the future research. [ABSTRACT FROM AUTHOR]

Most prediction methods used to calculate mining-induced subsidence do not involve the formation of overburden, and therefore cannot explain the mechanism of fundamental rock strata movement. Due to the differences of the overburden's formation in different mining areas, to develop a feasible method for determining the movement of overburden is significant. This paper presents an original method for determining the movement of overburden, which is based on the key stratum theory and Mohr–Coulomb failure criteria. The mining-induced movement of overburden is described by two major theoretical models: the Analogous Funnel Model (AFM) and the Analogous Hyperbola Model (AHM). The theoretical predictions of movement boundary of overburden and surface subsidence are given in each model. The Distinct Element Method was used to assess the performance of the theoretical models using a case study of the Antaibao coal mine in Western China. The theoretical and numerical subsidence of the primary key stratum was validated by field measurements, most of which are in good agreement. The theoretical predictions of surface subsidence and the movement boundary of the overburden also match well with the numerical results during supercritical mining. The primary key stratum damages the least in the overlying strata in the Analogous Hyperbola Model. [ABSTRACT FROM AUTHOR]

A recent Chinese policy requires that all enterprises that store and use hazardous chemicals must become part of a chemical industry park. Although this reduces the environmental risk caused by the establishment of uncontrolled sites, it cannot eliminate the risk within the industrial park; on the contrary, it may exacerbate the risk. The storage and use of a wide range of hazardous chemicals in the industrial park increases both the complexity and the diversity of the environmental risk. Identification of the sources of risk will significantly affect the results of regional risk assessments. In this paper, we selected China's Nanjing Chemical Industry Park as a case study. Based on an environmental risk assessment for every enterprise within the park, we calculated the maximum environmental risk values of each individual risk source and obtained the overall regional environmental risk values by using information-diffusion theory. The regional environmental risk value can be clustered according to the classification criteria described in this paper and depicted using a spatial partitioning map. The result can help administrative managers optimize the distribution of industrial areas and support the development of risk-prevention and -management measures. [ABSTRACT FROM AUTHOR]

It is reported that there are hundreds of thousands of deaths caused by seasonal flu all around the world every year. More other diseases such as chickenpox, malaria, etc. are also serious threats to people's physical and mental health. There are 250,000-500,000 deaths every year around the world. Therefore proper techniques for disease surveillance are highly demanded. Recently, social media analysis is regarded as an efficient way to achieve this goal, which is feasible since growing number of people have been posting their health information on social media such as blogs, personal websites, etc. Previous work on social media analysis mainly focused on English materials but hardly considered Chinese materials, which hinders the application of such technique to Chinese people. In this paper, we proposed a new method of Chinese social media analysis for disease surveillance. More specifically, we compared different kinds of methods in the process of classification and then proposed a new way to process Chinese text data. The Chinese Sina micro-blog data collected from September to December 2013 are used to validate the effectiveness of the proposed method. The results show that a high classification precision of 87.49 % in average has been obtained. Comparing with the data from the authority, Chinese National Influenza Center, we can predict the outbreak time of flu 5 days earlier. [ABSTRACT FROM AUTHOR]

On April 20, 2013, a Mw 6.6 earthquake struck Lushan County of Sichuan Province, China, about 80 km southwest of the epicenter of the 12 May 2008 Wenchuan Mw 7.9 event. It triggered a large number of landslides in a broad area, causing causality and injuries and damages to roads, drains, dwellings, and infrastructures. Field investigations of coseismic landslides provide a basis for better understanding and illustrating the spatial distributions and hazards related to the Lushan earthquake-triggered landslides. Therefore, this paper presents results of field investigations of the Lushan earthquake-triggered landslides, which can be classified into two main categories of disrupted landslides and coherent landslides, and constitutes seven types. The disrupted landslides include five types: rock falls, rock slides, rock avalanches, soil falls, and soil slides; and the coherent landslides have two types: soil slumps and slow earth flows. All of the seven types of landslides can be observed in many field photos, aerial photographs, and/or satellite images. Among them, seven typical large-scale landslides, distributed in a northeast trending line consistent with the Shuangshi-Dachuan fault, which is presumably related with the earthquake, are described in detail. We prepared an original, emergency-based coseismic landslide inventory map based on visual interpretation of available post-earthquake aerial photographs and pre-earthquake satellite images, combined with results from emergency-based field investigations. The original inventory map registered 3884 landslides. Later, 11,761 more landslides were identified by much more careful and time-consuming visual interpretation based on the same aerial photographs and satellite images. Subsequently, all the 15,645 coseismic landslides were correlated with six common landslide impact factors, including elevation, slope angle, slope aspect, topographic position, stratum/lithology, and peak ground accumulation (PGA). These observational and compiled coseismic landslide data allow us to make subsequent compiling of a detailed and completed landslide inventory by visual interpretation of remote sensing images as well as further studies of landslides induced by the Lushan earthquake. [ABSTRACT FROM AUTHOR]

Background: Rhodiola plants are used as a natural remedy in the western world and as a traditional herbal medicine in China, and are valued for their ability to enhance human resistance to stress or fatigue and to promote longevity. Due to the morphological similarities among different species, the identification of the genus remains somewhat controversial, which may affect their safety and effectiveness in clinical use. Results: In this paper, 47 Rhodiola samples of seven species were collected from thirteen local provinces of China. They were identified by their morphological characteristics and genetic and phytochemical taxonomies. Eight bioactive chemotaxonomic markers from four chemical classes (phenylpropanoids, phenylethanol derivatives, flavonoids and phenolic acids) were determined to evaluate and distinguish the chemotaxonomy of Rhodiola samples using an HPLC-DAD/UV method. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied to compare the two classification methods between genetic and phytochemical taxonomy. Conclusions: The established chemotaxonomic classification could be effectively used for Rhodiola species identification. [ABSTRACT FROM AUTHOR]

Early Yanshanian (Jurassic) granitoids are widespread in the Nanling Range of South China, and are associated with numerous non-ferrous and rare metal mineral deposits. These granitoids consist mainly of slightly peraluminous biotite monzogranites and K-feldspar granites that are closely associated in time and space with subordinate amphibole-bearing granites and muscovite- and garnet-bearing granites. In most previous studies, the biotite-bearing granites were classified as crustal transformation-type (corresponding to the S-type) granites which were interpreted to be derived from the regional Paleoproterozoic meta-sedimentary rocks. In this paper, we re-analyze the geochemical characteristics of a number of representative Early Yanshanian Nanling granitoids. There exists a clear negative correlation between SiO2 and P2O5 for the studied granitoids. The Early Yanshanian Nanling granitoid suites (including amphibole-bearing granodiorites→biotite monzogranites→K-feldspar granites→two-mica (muscovite) granites) are metaluminous to slightly peraluminous I-type or fractionated I-type granites. They were derived predominantly from Proterozoic igneous protoliths. The juvenile crust and/or newly mantle-derived materials might also have been involved in some of these granites. In addition, the I- and fractionated I-type granites are closely associated in time and space with minor amount of A-type felsic and mafic volcanic and intrusive rocks as well as alkaline rocks. All these rocks constitute a typical assemblage of anorogenic, intraplate magmatism, suggesting a dominant lithospheric extensional regime for the Nanling Range and neighboring region during the Early Yanshanian period. [ABSTRACT FROM AUTHOR]