Flow and heat transfer behaviour of nanofluids in microchannels

Flow and heat transfer of aqueous based silica and alumina nanofluids in microchannels were experimentally investigated. The measured friction factors were higher than conventional model predictions at low Reynolds numbers particularly with high nanoparticle concentrations. A decrease in the friction factor was observed with increasing Reynolds number, possibly due to the augmentation of nanoparticle aggregate shape arising from fluid shear and alteration of local nanoparticle concentration and nanofluid viscosity. Augmentation of the silica nanoparticle morphology by fluid shear may also have affected the friction factor due to possible formation of a core/shell structure of the particles. Measured thermal conductivities of the silica nanofluids were in approximate agreement with the Maxwell-Crosser model, whereas the alumina nanofluids only showed slight enhancements. Enhanced convective heat transfer was observed for both nanofluids, relative to their base fluids (water), at low particle concentrations. Heat transfer enhancement increased with increasing Reynolds number and microchannel hydraulic diameter. However, the majority of experiments showed a larger increase in pumping power requirements relative to heat transfer enhancements, which may hinder the industrial uptake of the nanofluids, particularly in confined environments, such as Micro Electro-Mechanical Systems (MEMS).     

面向同源蛋白质探测的一种新型混合深度学习模型

根据蛋白质氨基酸链探测其同源蛋白质,进而预测蛋白质的功能,是生物信息学研究领域的一个重要挑战,也是众多生物医学研究领域的基础研究内容,有着重要的科研价值和广泛的应用需求。其研究难点在于:(1)如何学习对同源蛋白质预测有效、有用的蛋白质特征信息;(2)如何更好地运用蛋白质特征信息,实现同源蛋白质的探测与识别。为了解决同源蛋白质探测与识别研究中的关键难点,本文提出一种基于混合深度学习架构的同源蛋白质探测与识别模型(HDLM-PHP)。通过采用统一的"管道式"深度学习架构,将蛋白质特征学习和探测识别统一为一个整体,提高同源蛋白质探测与识别的效能。采用多组并行的深度卷积神经网络,学习蛋白质的各种属性信息,以期获得丰富的待检测蛋白质和靶蛋白质的高级相关性特征,并通过全连接方式使用多层RBM结构融合和精炼这些相关性特征为全局相关性特征。通过统一的深度网络连接方式,以探测和识别任务为导向,学习到对于同源蛋白质预测最有效、最全面的蛋白质特征信息。在标准数据集SCOPe上,对所提模型进行性能与效率评测,结果表明:本文提出的模型能有效地学习到符合任务导向的蛋白质特征数据,提升同源蛋白质探测与识别的准确度和召回率,优于现有的模型和算法。     

铝制沐浴水热回收器的初步设计

对一种新型的铝制沐浴水热回收器进行初步设计。该沐浴水热回收器具有成本低,回收效率高等优点。介绍其工作原理,并以某三口之家为例,计算该热回收器的节能效益。结合沐浴水余热使用情况不合理的现状,讨论其发展前景。     

PBNA： An Improved Probabilistic Biological Network Alignment Method

Biological network alignment is an important research topic in the field of bioinformatics. Nowadays almost every existing alignment method is designed to solve the deterministic biological network alignment problem.However, it is worth noting that interactions in biological networks, like many other processes in the biological realm,are probabilistic events. Therefore, more accurate and better results can be obtained if biological networks are characterized by probabilistic graphs. This probabilistic information, however, increases difficulties in analyzing networks and only few methods can handle the probabilistic information. Therefore, in this paper, an improved Probabilistic Biological Network Alignment（PBNA） is proposed. Based on Iso Rank, PBNA is able to use the probabilistic information. Furthermore, PBNA takes advantages of Contributor and Probability Generating Function（PGF） to improve the accuracy of node similarity value and reduce the computational complexity of random variables in similarity matrix. Experimental results on dataset of the Protein-Protein Interaction（PPI） networks provided by Todor demonstrate that PBNA can produce some alignment results that ignored by the deterministic methods, and produce more biologically meaningful alignment results than Iso Rank does in most of the cases based on the Gene Ontology Consistency（GOC） measure. Compared with Prob method, which is designed exactly to solve the probabilistic alignment problem, PBNA can obtain more biologically meaningful mappings in less time.     

爆炸冲击波在扁平大空间内的传播规律

为研究爆炸冲击波在地下停车场等扁平大空间内的传播规律，采用AUTODYN软件建立了二维轴对称分析模型，分析了8种质量的TNT在扁平大空间中间位置地面处引爆后冲击波的传播特性。通过结合爆炸冲击波传播云图和部分测点的压力时程曲线，分析发现冲击波在传播过程中会形成多个马赫波，首个马赫波的马赫杆高度可以达到空间净高，后续马赫波的马赫杆高度较小，但传播速率大，最终会追上首个马赫波，并与其汇合，在汇合处峰值超压较马赫杆其他位置有所增加，随着传播距离的增加后续马赫波对首个马赫波的影响越来越小。给出了根据比例净高确定马赫波阵面峰值超压恒定的临界点水平位置和对应最大峰值超压值的计算公式，给出了根据平面比例爆距确定最大峰值超压平均值的计算公式。     

基于全基因组测序的粘绿木霉Gv29-8中分泌蛋白预测

粘绿木霉Gv29-8作为木霉属中重要的生防菌之一,对该菌分泌蛋白进行预测及其特征进行明确具有重要的理论意义。利用SignalP、ProtComp等预测程序对该菌中12427条蛋白质序列进行分泌蛋白找寻,并对上述分泌蛋白的氨基酸分布、信号肽长度大小及切割位点等性质进行分析。粘绿木霉含有分泌蛋白为377个,其氨基酸长度、信号肽长度与植物病原菌不同;信号肽切割位点属于A-X-A类型,与其他已经报道的植物病原真菌、卵菌中分泌蛋白信号肽切割位点一致。     

钢包用透气砖的研究与发展方向

综述了透气砖的材质和结构对其抗热震稳定性和抗渣性的影响,以及透气砖在使用性能和损毁机理方面的研究进展,介绍了吹氩工艺对透气砖工作的影响,提出了钢包用透气砖耐火材料的可能的发展方向。     

A liquid helium temperature target with a 10 K vapor shield for shock compression experiment in the environment condition of 100 Pa

The shock compression experiment of liquid helium is an available way to gain properties of specimen at high temperatures and pressures.Based on Fluent,a thermal insulation analysis and design of a liquid helium temperature target in the environment condition of 100 Pa for shock compression experiment is performed.Then,a cryogenic target with a 10 K helium vapor shield and a separated vacuum interval is particularly developed.A lowest temperature of 3.63 K and a stable temperature of 3.70 K in the specimen cavity with an accuracy of 0.1 K are obtained by means of continuous flow and vacuum cooling.Both time-consuming and temperature stability are well-suited to the requirements of the shock compression experiment.The results show that the calculated and experimental data well-matched each other.The simulation method may be effective and feasible for the optimal design of the cryogenic target.     

植物分离蛋白功能特性研究综述

综述了植物分离蛋白主要功能特性的影响因素,包括蛋白质浓度、温度、离子强度、pH值和多糖等对植物分离蛋白的吸水性、起泡性、溶解性、乳化及乳化稳定性等的影响,为植物蛋白的相关研究提供一定的参考价值。     

蛋白质折叠过程模型

蛋白质折叠过程模型研究一直是蛋白质折叠研究领域的热点课题．就这个问题,提出描述蛋白质折叠过程的拟蛇模型．并且提出一个新的概念,那就是所有蛋白质空间结构都可以通过2种类型函数构造出来,此外,还从理论方面来证明该模型是可行和正确的：通过与其他蛋白质折叠过程模型的对比实验,结果表明,拟蛇模型所构造的空间结构能量值最小、相似度最好．进而说明拟蛇模型在描述蛋白质折叠过程方面具有明显优势,开辟了研究蛋白质的一种新的途径．