Studies of structure and cycleability of LiMn2O4 and LiNd0.01Mn1.99O4 as cathode for Li-ion batteries

Lithium manganese oxides LiMn₂O₄ and rare earth elements doped LiNd_0.01Mn_1.99O₄ were synthesized by microwave method. The structure and the electrochemical performances of the samples were characterized. XRD data shows both samples exhibit the same pure spinel phase. But due to the introduction of Nd³⁺ ion into the unit cell, the lattice parameter of the Nd-doped spinel was larger than that of the undoped one. The two samples had a similar morphology including small particle size and homogeneous particle distribution as tested by SEM. The cyclic voltammmetry and constant-current charge-discharge tested that Nd-doped spinel displayed a better reversibility and cycleability.     

Effect of fretting amplitudes on fretting wear behavior of steel wires in coal mines

Given that fretting wear causes failure in steel wires, we carried out tangential fretting wear tests of steel wires on a self-made fretting wear test rig under contact loads of 9 and 29 N and fretting amplitudes ranging from 5 to 180 μm. We observed morphologies of fretted steel wire surfaces on an S-3000N scanning electron microscope in order to analyze fretting wear mecha-nisms. The results show that the fretting regime of steel wires transforms from partial slip regime into mixed fretting regime and gross slip regime with an increase in fretting amplitudes under a given contact load. In partial slip regime, the friction coefficient has a relatively low value. Four stages can be defined in mixed fretting and gross slip regimes. The fretting wear of steel wires in-creases obviously with increases in fretting amplitudes. Fretting scars present a typical morphology of annularity, showing slight damage in partial slip regime. However, wear clearly increases in mixed fretting regime where wear mechanism is a combination of plastic deformation, abrasive wear and oxidative wear. In gross slip regime, more severe degradation is present than in the other regimes. The main fretting wear mechanisms of steel wires are abrasive wear, surface fatigue and friction oxidation.     

Application of structural curvature of coalbed floor on CBM development in the Zaoyuan block of the southern Qinshui Basin

Based on controls of structural style and the position in coalbed methane(CBM)development,we used a method of curvatures to study its relations with CBM development parameters.We calculated structural curvatures of contours of the No.3coal seam floor of the Shanxi Formation in the Zaoyuan block of the Qinshui Basin and analyzed its relations with development parameters of coalbed methane wells.The results show that structural curvature is negatively related to coal reservoir pressure,while positively related to permeability.With an increase in structural curvature,the average production of coalbed methane wells increases at first and then decreases,reaching the highest production at 0.02 m-1 of structural curvature.Therefore,structural curvature can be an important index for potential evaluation of coalbed methane development and provide a basis for siting coalbed methane wells.     

基于模块化模型的自适应预失真技术

系统地比较和分析了OFDM传输系统里高功率放大器（HPA）预失真方法的优缺点,提出一种基于模块化模型的有记忆高功率放大器自适应数字预失真方法,该方法分别基于Wiener、Hammerstein和Wiener-Hammerstein模型各自构成一个有记忆HPA的自适应预失真器。从而避免了因分别估计Wiener-Hammerstein模型各个环节特性参数所带来的复杂性。使得有记忆高功率放大器的预失真设计变得简单了。     

让设计成为科学、艺术、时尚融合的载体——记北京服装学院教师作品展

本文结合北京服装学院2008年在中国美术馆举办的首届教师作品展,就学校的办学理念、办学特色、创新教育、优势互补和理论研讨等方面展开论述。不仅彰显了北京服装学院的学科优势,而且突出了学校在“奥运”和“神七”设计中贡献社会的浓重一笔。同时,也强调了学校对传统与时尚、艺术与科学、民族与世界融为一炉的设计理念的高度重视。     

交通运输业节能减排国际管理手段及启示

交通运输业的能源消费在许多国家中都占有较高比例,经济发展较快的国家更是如此。介绍了能源消费大国英国、美国、欧盟以及日本交通运输业节能减排采取的主要管理手段,包括健全的法律体系、节能技术创新、有效的税费政策等。借鉴其先进经验,为我国交通运输业节能减排管理工作提供启示。     

因子分析法和熵值法在高校科技创新评价中的应用

在已有研究的基础上总结出了一套科学合理并具有可行性的高校科技创新评价指标体系,并把因子分析法和熵值法应用于高校科技创新评价.首先对高校科技创新评价体系的5个一级指标分别进行因子分析,然后运用熵值法对其确定权重.分析结果表明两种方法的结合使用能够简化分析对象的结构,使评价结果更具科学性、客观性.     

燃煤发电机组锅炉节油技术

介绍浙能长兴发电有限公司300MW燃煤机组锅炉在节约燃油方面所采取的措施.     

A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition

Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.