深埋矿体移动带三维圈定方法及应用

针对深埋矿山开采移动带二维圈定方法工作量大、精度低且难以满足日益增长的经济效益需求的问题，提出了一种深埋复杂矿体移动范围三维确定方法。结合沙岭金矿千米深井工程实例，在移动范围确定过程中，借助先进的3D建模技术获得三维矿山模型。该模型可以实现各类地质体的可视化，直观地展示其形态与产状，清晰地反映各构成因素间的相互关系。在3D模型中截取的特征剖面与经典移动带圈定岩移参数获取方法相结合，能轻松获得各特征剖面上的岩移参数值。通过给定的岩移参数值进而确定各特征剖面上的地表移动边界点，将各移动边界点连接即可实现矿山移动范围的圈定。研究结果表明，基于三维地质建模技术的移动带圈定方法合理可行，确定的纱岭金矿地表移动带能够兼顾安全生产与经济效益，为矿山生产开发奠定了有益基础，为类似矿山提供了有益借鉴。     

全电动注塑机研究进展及在汽配电子行业中的应用

介绍了全电动注塑机的特色，综述了国内外全电动注塑机在精密注塑、智能注塑、高效注塑和绿色注塑方面的研究进展，并对全电动注塑机在汽配电子行业中的应用作了简单介绍。对双电机同步控制技术的逐渐成熟为全电动注塑机实现大型化提供了助力，全电动注塑机高效、精密、智能、节能、环保的优势在汽配电子行业显示了很好的应用前景。     

Prediction of process parameters of water-assisted injection molding based on inverse radial basis function neural network

Because of the introduction of new processing parameters in water-assisted injection molding (WAIM), processes control has become more difficult. First, design of experiment (DOE) was carried out by using optimized Latin hypercubes (Opt LHS). On the basis of this, computational fluid dynamics (CFD) method was used to simulate and calculate hollowed core ratios and wall thickness differences of cooling water pipe at different positions. Then inverse radial basis function (RBF) neural network model reflecting the fitting relationship between processing parameters and molding quality was established, and accuracy of the model was detected by cross validation. Finally, expected molding quality was applied to predict processing parameters, and the obtained molding quality under the predicted processing parameters was verified by computer aided engineering (CAE) simulation and experimental methods. The results showed that mean relative precisions of processing parameters such as melt temperature, delay time, short shot size, water pressure, and mold temperature for inverse RBF model were 98.6%, 93.6%, 98.5%, 93.9%, and 97.9%, respectively, which met the accuracy requirements. Furthermore, compared with expected values of hollowed core ratios and wall thickness differences, the average errors of CAE and experiment were 2.3% and 4.9%, respectively.     

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.     

Elasto-Thermodiffusive Response in a Spherically Isotropic Hollow Sphere

The present work deals with the investigation of elasto-thermo diffusion interactions inside a spherically isotropic hollow sphere in the context of linear theory of generalized thermoelastic diffusion based on Green and Lindsay theory. The inner and outer boundaries of the body are free from stresses and are subjected to a time-dependent thermal shock and also the chemical shock. Laplace transform techniques are used to write the basic equations in the form of a vector matrix differential equations, which is then solved by the eigenvalue approach. The inversion of the transformed solution is carried out by applying the method of Bellman. The stress, temperature, mass concentration and chemical potential are computed and presented graphically. A comparative study of diffusive medium and thermoelastic medium is carried out, and it was seen that the effect of diffusion is significant on the stresses. A comparison of spherically isotropic body with isotropic body has also been presented, and a significant difference is observed.     

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.