浅谈煤矿数据的分析与应用

当今社会科技发展快、信息流通量大,人们之间的交流越来越密切,大数据这个高科技时代的产物也应运而生。煤炭作为工业发展的重要组成部分,其发展关系着整个工业的发展。如今,许多现代大型煤矿已能将井下设备信息上传到地面,在地面就可直观的看到设备当前运行的情况,从而更可靠的进行安全生产。通过结合实例将上传的设备信息数据进行整理和分析,从而预测设备的运行状况,提出建设性建议。同时对加强煤矿安全生产、促进煤炭行业现代化建设、提高煤矿的经济效益和社会效益具有重要的意义。     

综放高瓦斯矿井煤层瓦斯涌出量综合预测

为了成功预测竹林山煤矿综放高瓦斯矿井大采高工作面煤层瓦斯涌出量,以主采3号煤层为主要研究对象,针对3号煤层以往开采情况,通过布设测点测量其煤层瓦斯含量和了解相邻矿井瓦斯含量,采用分源预测法、回归法及统计法等预测方法得到了3号煤层瓦斯含量的分布规律,并绘制了3号煤层的瓦斯含量等值线图。对矿井不同生产时期的瓦斯含量进行预测,得到了生产前期、中期及后期采区的最大绝对瓦斯涌出量和最大相对瓦斯涌出量,说明了竹林山煤矿各个时期均属于高瓦斯矿井。     

Fatigue strength dependence on the ultimate tensile strength and hardness in magnesium alloys

The relationships between fatigue strength and ultimate tensile strength as well as hardness have been studied in high-strength NZK alloys (Mg–yNd–zZn–xZr) and other magnesium alloys. In the absence of casting defects, clear linear relationships have been found between the fatigue strength and the ultimate tensile strength and the hardness values in these magnesium alloys in both T4 (solutionized) and T6 (solutionized and aged) conditions. The fatigue strength models developed in this work alloys can be directly applied to other defect-free magnesium alloys.     

Structural modeling and docking studies of ribose 5-phosphate isomerase from Leishmania major and Homo sapiens: A comparative analysis for Leishmaniasis treatment

Leishmaniases are caused by protozoa of the genus Leishmania and are considered the second-highest cause of death worldwide by parasitic infection. The drugs available for treatment in humans are becoming ineffective mainly due to parasite resistance; therefore, it is extremely important to develop a new chemotherapy against these parasites. A crucial aspect of drug design development is the identification and characterization of novel molecular targets. In this work, through an in silico comparative analysis between the genomes of Leishmania major and Homo sapiens, the enzyme ribose 5-phosphate isomerase (R5PI) was indicated as a promising molecular target. R5PI is an important enzyme that acts in the pentose phosphate pathway and catalyzes the interconversion of d-ribose-5-phosphate (R5P) and d-ribulose-5-phosphate (5RP). R5PI activity is found in two analogous groups of enzymes called RpiA (found in H. sapiens) and RpiB (found in L. major). Here, we present the first report of the three-dimensional (3D) structures and active sites of RpiB from L. major (LmRpiB) and RpiA from H. sapiens (HsRpiA). Three-dimensional models were constructed by applying a hybrid methodology that combines comparative and ab initio modeling techniques, and the active site was characterized based on docking studies of the substrates R5P (furanose and ring-opened forms) and 5RP. Our comparative analyses show that these proteins are structural analogs and that distinct residues participate in the interconversion of R5P and 5RP. We propose two distinct reaction mechanisms for the reversible isomerization of R5P to 5RP, which is catalyzed by LmRpiB and HsRpiA. We expect that the present results will be important in guiding future molecular modeling studies to develop new drugs that are specially designed to inhibit the parasitic form of the enzyme without significant effects on the human analog.     

Simple Sequence Repeat Markers in Genetic Divergence and Marker-Assisted Selection of Rice Cultivars: A Review

Sequencing of rice genome has facilitated the understanding of rice evolution and has been utilized extensively for mining of DNA markers to facilitate marker-assisted breeding. Simple sequence repeat (SSR) markers that are tandemly repeated nucleotide sequence motifs flanked by unique sequences are presently the maker of choice in rice improvement due to their abundance, co-dominant inheritance, high levels of allelic diversity, and simple reproducible assay. The current level of genome coverage by SSR markers in rice is sufficient to employ them for genotype identification and marker-assisted selection in breeding for mapping of genes and quantitative trait loci analysis. This review provides comprehensive information on the mapping and applications of SSR markers in investigation of rice cultivars to study their genetic divergence and marker-assisted selection of important agronomic traits.     

On generic G-prevalent properties and a quantitative K-S theorem for Cr diffeomorphisms of the circle

We will consider a convex subset of a metric linear space and a certain group of actions G on this set, that allow us to define the notion of Haar zero measure on sets that have zero Haar measure for the translation (by adding) invariant HSY prevalence theory. In this way, we will be able to define the meaning of G-prevalent set according to the pioneering work of Christensen. Our setting considers problems which take into account the convex structure and this is quite different from the previous results on prevalence which consider basically the linear additive structure. In this setting, we will show a kind of quantitative Kupka–Smale theorem, and also we generalize a result about rotation numbers which was first considered by J.-C. Yoccoz (and, also by M. Tsujii). Among other things we present an estimation of the amount of hyperbolicity in a setting that we believe was not considered before.     

Adventitial Tertiary Lymphoid Organs as Potential Source of MicroRNA Biomarkers for Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is an inflammatory disease associated with marked changes in the cellular composition of the aortic wall. This study aims to identify microRNA (miRNA) expression in aneurysmal inflammatory cells isolated by laser microdissection from human tissue samples. The distribution of inflammatory cells (neutrophils, B and T lymphocytes, mast cells) was evaluated in human AAA biopsies. We observed in half of the samples that adventitial tertiary lymphoid organs (ATLOs) with a thickness from 0.5 to 2 mm were located exclusively in the adventitia. Out of the 850 miRNA that were screened by microarray in isolated ATLOs (n = 2), 164 miRNAs were detected in ATLOs. The three miRNAs (miR-15a-3p, miR-30a-5p and miR-489-3p) with the highest expression levels were chosen and their expression quantified by RT-PCR in isolated ATLOs (n = 4), M1 (n = 2) and M2 macrophages (n = 2) and entire aneurysmal biopsies (n = 3). Except for the miR-30a-5p, a similar modulation was found in ATLOs and the two subtypes of macrophages. The modulated miRNAs were then evaluated in the plasma of AAA patients for their potential as AAA biomarkers. Our data emphasize the potential of miR-15a-3p and miR-30a-5p as biomarkers of AAA but also as triggers of ATLO evolution. Further investigations will be required to evaluate their targets in order to better understand AAA pathophysiology.     

Human mobility synthesis using matrix and tensor factorizations

Human mobility prediction is of great advantage in route planning and schedule management. However, mobility data is a high-dimensional dataset in which multi-context prediction is difficult in a single model. Mobility data can usually be expressed as a home event, a work event, a shopping event and a traveling event. Previous works have only been able to learn and predict one type of mobility event and then integrate them. As the tensor model has a strong ability to describe high-dimensional information, we propose an algorithm to predict human mobility in tensors of location context data. Using the tensor decomposition method, we extract human mobility patterns with multiple expressions and then synthesize the future mobility event based on mobility patterns. The experiment is based on real-world location data and the results show that the tensor decomposition method has the highest accuracy in terms of prediction error among the three methods. The results also prove the feasibility of our multi-context prediction model.     

Improving visualisation and prediction performance of supervised self-organising map by modified contradiction resolution

We have previously proposed a new type of information-theoretic method where a neuron is evaluated by itself (self-evaluation) and by its surrounding neurons (outer-evaluation). If contradiction between different types of evaluation exists, it is reduced as much as possible. In the present paper, we try to separate self- and outer-evaluation more explicitly and introduce the importance of neurons. First, we separate self- and outer-evaluation to enhance the characteristics shared by the two types of evaluation. Second, we introduce the importance of neurons in evaluation. By using a limited number of important neurons in evaluation, we expect the main characteristics in input patterns to emerge. We applied this contradiction resolution to two types of data, namely, the Senate data and the Euro-yen exchange rates. In both data sets, experimental results confirmed that improved prediction performance was obtained. Prediction performance was better than that obtained by the conventional self-organising map (SOM) and radial basis function networks. In addition, final representations obtained by contradiction resolution were easier to interpret than those given by the conventional SOM. Experimental results confirmed that improved interpretation and visualisation were accompanied by improved prediction performance.