Ozonation of CI Reactive Black 5 using rotating packed bed and stirred tank reactor

This study investigates the ozonation of CI Reactive Black 5 (RB5) by using the rotating packed bed (RPB) and completely stirred tank reactor (CSTR) as ozone contactors. The RPB, which provides high gravitational force by adjusting the rotational speed, was employed as a novel ozone contactor. The same ozone dosage was separately introduced into either the RPB or the CSTR for the investigation, while the experimental solution was continuously circulated within the apparatus consisting of the RPB and CSTR. The decolorization and mineralization efficiencies of RB5 in the course of ozonation are compared for these two methods. Moreover, the dissolved and off‐gas ozone concentrations were simultaneously monitored for the further analysis. As a result, the ozone mass transfer rate per unit volume of the RPB was significantly higher because of its higher mass transfer coefficient and gas–liquid concentration driving force. Furthermore, ozonation kinetics was found to be independent of the gravitational magnitude of an ozone gas–liquid contactor. Therefore, the results suggest employing RPBs as ozone‐contacting devices with the advantage of volume reduction. The experimental results, which can be used for further modeling of the ozonation process in the RPB, also show the requirement of correct design for the RPB. Consequently, the present study is useful for the understanding of practical application of RPBs. Copyright © 2004 Society of Chemical Industry     

Perceived risk and trust associated with purchasing at electronic marketplaces

Understanding consumer behaviour is of vital importance to consumer-oriented e-business models today. In this paper, we study the relationships between consumer perceptions of risk and trust and the attitude towards purchasing at a consumer-to-consumer electronic marketplace (EM). Typical for EM settings is that consumer behaviour is subject to perceptions of the selling party as well as of the institutional structures of the intermediary that is operating the EM. Building upon the well-established literature of trust, we consider the concepts of intermediary trust and seller trust. We extend this categorisation by introducing the concepts of intermediary risk and seller risk. We developed measurement instruments for intermediary risk and seller risk. All measurement scales have acceptable alphas and are unidimensional. An empirical study is conducted to explore the relationships between the risk and trust types and consumer purchase attitude. The results reveal significant, direct effects of seller trust and seller risk. Second-order effects of intermediary trust and intermediary risk are investigated and reported. The paper concludes with general observations and recommendations for research and practice.     

新型超微晶软磁合金FePCCuMoSi微观结构缺陷的正电子湮没研究

用正电子湮没方法研究了新型超微晶软磁合金的微观结构缺陷，样品选用的是在不同温度下退火的Ｆｅ８１Ｐ１２Ｃ３Ｃｕ１Ｍｏ０．５Ｓｉ２．５合金，结果表明，合金的微观结构构陷大小，密度随退火温度有规律地变化，这种现象可能与非晶的晶化过程有关。     

用保形样条方法求解非定常对流扩散方程

在欧拉-拉格朗日分裂方法的基础上,本文发展了一种固定网格上的欧拉-拉格朗日分裂方法.保形样条方法(SPSM)被用来解决倒特征线插值问题.通过求解几个有精确解的例子,说明SPSM方法的解是单调无振荡的,并且数值耗散也是比较小的.     

反应离化团束（RICB）法生长CN硬质薄膜

用反应离化团束（ＲＩＣＢ）法，以低分子量聚乙烯为蒸发材料，氨气为反应气体，在ＮａＣｌ（１００）和Ｓｉ（１００）衬底上淀积Ｃ－Ｎ薄膜，透射电子衍射（ＴＥＭ）分析表明薄膜中含有β－Ｃ３Ｎ４晶粒，Ｘ射线光电子谱（ＸＰＳ）和红外吸收谱（ＩＲ）表明存在Ｃ，Ｎ原子的化学键合。     

以CGA卡为基础的智能显示系统

本文介绍了以微处理器与ＩＢＭ－ＰＣ上的彩色／图形适配器相结合构成的一种智能显示系统。本系统主要解决数控系统中主ＣＰＵ与６８４５ＣＲＴＣ争夺显示缓存的矛盾。保证了６８４５ＣＲＴＣ对显示缓存操作的时间要求；并且保证了数控系统中主ＣＰＵ对显示缓存操作的随意性。     

薄Si膜对基底表面粗糙度的影响

利用ＺＹＧＯ光学干涉测量仪，散射积分测量法观测了光学元件表面均方根粗糙度．详细分析了薄Ｓｉ膜对基底均方根粗糙度的影响，由此认为薄膜并不总是复制基底表面的粗糙度，结果出现了薄膜降低表面粗糙度的现象．提出了一定厚度范围的薄Ｓｉ膜的表面粗糙度存在着一个稳定值的新设想．     

重馏分油加氢脱氮反应动力学模型的研究

简要地介绍了一些典型的模型氮化物的ＨＤＮ反应规律。根据胜利ＶＧＯ在３７２２Ｂ催化剂上的大量ＨＤＮ实验数据，提出了如下的ＨＤＮ基本反应动力学方程：ｄＣＮｄｔ＝－ｋ１＋Ｋ＊ＣＮＣＮＰＨ２为了扩大上式的应用范围，详细分析了各种因素（如原料油种类和馏程及Ｈ２Ｓ等）对ＨＤＮ的影响，并开发了相应的经验关联式，从而得到了一个较完整的馏分油ＨＤＮ反应动力学模型。验证实验表明，该模型是成功的。     

高性能各向异性Sm2Fe17Nx磁粉的制备

本文研究了高性能各向异性Ｓｍ２Ｆｅ１７Ｎｘ磁粉的制备工艺路线与工艺参数。优化了制备与工艺参数。已制备出磁性能达到：Ｂｒ＝１．３９Ｔ，Ｈｃｉ＝８５０ＫＡ／ｍ和（ＢＨ）ｍ＝２３６ＫＪ／ｍ＾３的各向异性Ｓｍ２Ｆｅ１７Ｎ２．８８磁粉，该磁粉的各向异性场ＨＡ达到２０Ｔ。     

Packed hyper-ellipsoid classifiers

Pattern classification is frequently performed using the k-nn algorithm or a neural network. The choice of parameters for the former is often difficult and the amount of data which has to be stored in the classifier can be high. Neural network classifiers can overcome some of these problems but learning is often unreliable and slow. An alternative which combines some of the best features of the k-nn and neural network classifier is described by the authors. The classifier is called a packed hyper-ellipsoid classifier