A study of internal heat transfer in nonuniform porous structures

The results of theoretical and experimental studies of heat transfer and pressure drop in nonuniform porous materials and systems are presented. In experiments, measurements were made of the air flow rate, inlet and outlet air pressures, and air and porous sample temperatures. Experimental determination of the heat transfer coefficient in porous structures is associated with certain difficulties. The problem of determining a temperature difference between coolant and porous skeleton is the most complex. As a rule, under laboratory conditions this difference is small and cannot be found with sufficient accuracy. In the present work, the method of determination of the internal heat transfer coefficient is based on solving the inverse unsteady heat transfer problem for porous structures. Using this approach, the heat transfer coefficient is calculated indirectly or on the basis of the porous material temperature variation over time.     

Intrinsic magnetism in Fe doped SnO2 nanoparticles

Iron doped semiconducting nanoparticles Sn_1−xFe_xO₂ with x=0, 0.001, 0.002, 0.003, 0.004, 0.01 and 0.03 were prepared by a sol-gel method. The X-ray diffraction, Transmission Electron Microscopy measurements confirm the rutile structure with no impurity phase. The three characteristic lines of electron spin resonance (ESR) are observed in the doped samples for all compositions, which is a clear evidence for rhombic Fe³⁺ in rutile phase. The line width of ESR increases with increase in Fe concentration due to induced disorder. The spin-pumping effect is observed at temperatures below 250 K for the samples with x=0.01 and 0.03. However, based on the Curie-Weiss susceptibility, iron is in paramagnetic state and is subject to weak antiferromagnetic interaction. Blue shift in the optical band gap is observed with increase in the Fe content.     

A comparative study of the leading machine learning techniques and two new optimization algorithms

We present here a computational study comparing the performance of leading machine learning techniques to that of recently developed graph-based combinatorial optimization algorithms (SNC and KSNC). The surprising result of this study is that SNC and KSNC consistently show the best or close to best performance in terms of their F₁-scores, accuracy, and recall. Furthermore, the performance of SNC and KSNC is considerably more robust than that of the other algorithms; the others may perform well on average but tend to vary greatly across data sets. This demonstrates that combinatorial optimization techniques can be competitive as compared to state-of-the-art machine learning techniques. The code developed for SNC and KSNC is publicly available.     

In-depth analysis of the fatigue mechanism induced by inclusions for high-strength bearing steels

A numerical study of stress distribution and fatigue behavior in terms of the effect of voids adjacent to inclusions was conducted with finite element modeling simulations under different assumptions.Fatigue mechanisms were also analyzed accordingly.The results showed that the effects of inclusions on fatigue life will distinctly decrease if the mechanical properties are close to those of the steel matrix.For the inclusions,which are tightly bonded with the steel matrix,when the Young’s modulus is larger than that of the steel matrix,the stress will concentrate inside the inclusion;otherwise,the stress will concentrate in the steel matrix.If voids exist on the interface between inclusions and the steel matrix,their effects on the fatigue process differ with their positions relative to the inclusions.The void on one side of an inclusion perpendicular to the fatigue loading direction will aggravate the effect of inclusions on fatigue behavior and lead to a sharp stress concentration.The void on the top of inclusion along the fatigue loading direction will accelerate the debonding between the inclusion and steel matrix.     

基于转录组学的绿豆改善肥胖小鼠肝脂肪变性的潜在机制

基于绿豆对高脂饲养肥胖小鼠肝脂肪变性的有效缓解作用,通过转录组学技术分析了其改善肝脂肪变性的潜在机制。结果表明,绿豆显著改善了肥胖小鼠的肝脏基因表达图谱。与模型组相比,全绿豆和去皮绿豆干预后的小鼠肝脏分别有306和461个表达量差异基因显著上调,596和1132个表达量差异基因显著下调。经KEGG功能注释分析显示,绿豆干预后引起的表达量差异基因显著注释到脂质代谢相关的通路上。KEGG通路富集分析结果表明,绿豆干预发生了以NOD样受体信号通路和Toll样受体信号通路激活为特征的功能转变,其中NOD样受体信号通路是最为显著富集的信号通路,涉及12个显著下调的表达量差异基因以反馈绿豆对小鼠肝脂肪变性的调控作用。绿豆干预后,小鼠血清中炎症因子TNF-α和IL-6水平的显著降低以及肝脏中TNF-α mRNA表达水平的显著下降也很好地支持了转录组学测序的结果。本研究旨在为阐释绿豆缓解肥胖小鼠肝脂肪变性的作用机制奠定数据基础,从而为绿豆基功能食品的开发和应用提供理论支撑。     

“修辞性阅读”与文学阐释

张江认为阐释是一种公共行为,文学阐释的目的是寻找文本的确定主旨与意义以得到人们的广泛认同,文学批评应该有完整系统的方法以提供普遍意义的指导。基于此原则,他对米勒的解构主义批评提出了质疑。米勒的回应是,解构批评根源于文学语言的比喻性,强调以特殊方法解释文学文本的意义,并不是否定文本意义的存在,它重视的不是理论范式与方法的指导,而是对于特定作品文本的阅读与体验。他将自己的工作称为“修辞性阅读”。本文认为,“修辞性阅读”和“公共阐释”的路径虽不相同,却存在着相似与相通,那就是它们都以语言问题为中心,重视文本细读,重视文学阐释参与文学实践的能力。其差异主要体现在对待文章与作者、读者关系的理解上。文章还将“修辞性阅读”纳入到现代阐释学与中国古代修辞批评的理论背景中,并通过张江对当代诗歌的“诵读”到“视读”现象解读的分析,论证了“修辞性阅读”作为文学阐释路径对于当代文学批评理论的重要性。     

人类学视野里的生存性智慧与生态文明

生态文明建设是当下国内各界的重要议题之一。本文通过阐释生存性智慧和生态文明这两个我国学者所创的概念,结合人类学的理论思考,提出生态文明建设成为当下的重要议题与对“发展”的反思有关。“发展”所带来消极影响已经引起了国际社会的广泛关注,而推动生态文明建设是人类文明积极发展日益完善所必不可少的,是文明过程的重要组成部分。非理性的生存性智慧对于我们理解文化多样性有所助益。生存性智慧是一个文化长年累月的生活实践经验的累积,不能因其非理性而忽视。狩猎采集社会千百年来的经验累积提供给社会成员许多有关所处环境的知识,他们对于其他物种的看法近些年来引起了所谓“本体论转向”的人类学家的高度关注。人类学者相信,许多狩猎采集社会和游耕社会对待各种动植物的态度是这些社会之所以能在整个生态系统里实现动态平衡的奥妙所在。他们对于其他物种的看法与态度是一种“美德”,值得珍视。     

Impact of Internal Factors on Information Technology Adoption: An Empirical Investigation of Chinese Firms

Organizations differ significantly in their inclination to deploy information technology (IT). The factors that determine the organizational inclination to deploy IT need to be classified to help firms formulate an appropriate e-strategy. This paper discusses a framework that explains the influence of internal factors on IT adoption. The framework is based on quantitative data on IT adoption from 95 firms in China. The results highlight that the internal factors of leadership, organizational learning, and IT resources positively impact IT adoption. The study also shows that these factors are correlated.