Low-temperature synthesis of SiC nanowires with Ni catalyst

SiC nano wires were fabricated on the silicon substrate dipped with a layer of Ni catalyst at 900 ℃ by gas pressure annealing processing. The morphologies and crystal structures were determined by scanning electron microscopy(SEM), transmission electron microscopy(TEM)and X-ray diffraction(XRD). The results show that the assynthesized nanowires are β-SiC single crystalline with diameter range of 50-100 nm, and length of tens of micron by directly annealing at 900 ℃. The SiC nano wires grow along the [111] direction with highly uniform morphology. And the possible growth mechanism of SiC nano wires is proposed.The present work provides an efficient strategy for the production of high-quality SiC nano wires.     

Semantic word shifts in a scientific domain

Understanding semantic word shifts in scientific domains is essential for facilitating interdisciplinary communication. Using a data set of published papers in the field of information retrieval (IR), this paper studies the semantic shifts of words in IR based on mining per-word topic distribution over time. We propose that semantic word shifts not only occur over time, but also over topics. The shifts are examined from two perspectives, the topic-level and the context-level. According to the over-time word-topic distribution, stable words and unstable words are recognized. The diverging and converging trends in the unstable type reveal characteristics of the topic evolution process. The context-level shifts are further detected by similarities between word vectors. Our work associates semantic word shifts with the evolving of topics, which facilitates a better understanding of semantic word shifts from both topics and contexts.     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

8e6科技走校园路线--校园网行为管理解决方案最受青睐

8e6科技公司近日发布的一项校园网安全状况和网络行为管理调查报告显示:目前校园网关注的主要问题是安全威胁和网络带宽浪费。校园网络遇到的安全问题主要集中在防病毒和网络行为管理上,为此,网络行为管理解决方案成为改善校园网安全和应用状况的优选解决方案。大部分受访人表示,他们很愿意采用网络行为管理解决方案,用以解决目前遇到的网络行为管理问题。而选择网络行为管理解决方案时,他们比较关心的是设备的稳定性、安全性和性价比,通过网络行为管理解决方案来分析、记录网络行为以及阻断不当的上网行为,提高网络的安全性和网络带宽利用…