High catalytic activity of PdOx/MnO2 for CO oxidation and importance of oxidation state of Mn

PdO_x/MnO₂ has been examined as a catalyst for CO oxidation using a conventional flow reactor at reaction temperatures between 50 and 150°C. In the reaction conditions of GHSV (gashourlyspacevelocity) of 1.22 × 10⁵/h and CO concentration of 2000 ppm, PdO_x/MnO₂ showed higher catalytic activity compared with PdO_x/Mn₂O₃, which had been previously reported as an effective catalyst due to the cooperative action of Pd and Mn₂O₃ for this reaction. The reason for higher activity of PdO_x/MnO₂ than PdO_x/Mn₂O₃ has been investigated using TPR (temperatureprogrammed reduction) and XPS studies. TPR showed that PdO_x/MnO₂ could be reduced by CO at much lower temperature than PdO_x/Mn₂O₃. During the experiment of reduction and oxidation, XPS showed that the valence of Mn in the PdO_x/MnO₂ was between 4+ and 3+, which is higher than that of Mn in the PdO_x/Mn₂O₃ catalyst of which the valence has been reported to be between 3+ and 2+. It is known that in this catalyst system the support supplies oxygen onto Pd, where the oxidation occurs with adsorbed CO, and the ability of the support to provide oxygen improves the performance of the catalyst. Therefore, it was concluded that the readiness of MnO₂ to be reduced with maintaining a higher oxidation state showed higher CO oxidation activity than Mn₂O₃ as support for PdO_x.     

Nanocrystalline CeO2 in SBA-15: Performance of Pt/CeO2/SBA-15 Catalyst for Water-gas-shift Reaction

CeO₂ particles confined within the pores of an SBA-15 mesoporous silica host were prepared by incipient wetness impregnation (IMP) and deposition precipitation (DP) methods. The materials were characterized by XRD, N₂-adsorption and temperature programmed reduction (TPR) to evaluate the structure, texture, and redox properties. The preparation procedure had significant impact on the assembling mode of CeO₂ inside the SBA-15 mesopores. A high dispersion of CeO₂ particles was achieved via DP, whereas the dispersion of CeO₂ prepared by IMP was found to be inhomogeneous and CeO₂ partially blocked the pores. The CO conversion in the water-gas-shift reaction was enhanced over 1 wt% Pt supported on CeO₂-modified SBA-15 obtained by DP.     

企业信息安全管理现状与管理对策探讨

随着互联网技术的快速发展,企业的信息化建设步伐在不断的加快,企业的信息安全问题也逐步显现,信息安全所面临的危险已渗透到企业生产经营管理的各个方面,加强企业信息安全管理刻不容缓。文章对企业的信息安全现状和管理对策进行了分析探讨。     

Non‐fragile H ∞ control for switched stochastic delay systems with application to water quality process

In this paper, the problem of non‐fragile observer‐based H _∞ control for discrete‐time switched delay systems is investigated. Both data missing and time delays are taken into account in the links from sensors to observers and from controllers to actuators. Because data missing satisfies the Bernoulli distribution, such problem is transformed into an H _∞ control problem for stochastic switched delay systems. Average dwell time approach is used to obtain sufficient conditions on the solvability of such problems. A numerical example and a real example for water quality control are provided to illustrate the effectiveness and potential applications of the proposed techniques. Copyright © 2013 John Wiley & Sons, Ltd.     

浅谈互助教学在高校信息技术教学中的运用

现在的社会是信息社会,大范围的信息交流需要借助信息技术技术的运用。现在的高校学习越来越重视了信息技术的学习,信息技术教学是高校为社会输送信息技术人才的重要的方式,在现在的高校信息技术教学中,互助教学是信息技术课堂上常用的教学方式。本文将从信息技术课堂上互助教学的必要性出发,分析互助教学运用中应注意的问题,以及互助教学在高校信息技术教学如何运用。     

火焰原子吸收光谱法测定硅粉中的铜

介绍了用火焰原子吸收法测定工业硅粉中微量铜的具体方法和过程，同时也给出了最佳实验条件。实验中采用新的样品处理方法，得到了令人满意的结果。其中样品回收率为99．8％—104．0%，相对标准偏差为0．31％—0.38％。本方法在实际应用过程中，简单、快速、     

钛酸铝材料性能及合成工艺

着重介绍了钛酸铝（Al2TiO3）陶瓷的结构、性能和合成工艺，并对今后发展趋势提出了基本观点。     

城域网应用层流量异常检测与分析*

首先对流量数据按应用层协议进行分类分析,采用小波分析对原始流量数据进行去噪处理,建立流量数据矩阵;然后采用主元分析（PCA）方法进行流量建模;在此基础上,通过SPE统计量的控制图能快速检测出流量异常,结合SPE统计量的贡献图可以分析出导致异常的主要原因。实验结果表明,小波去噪能降低异常检测的误警率,SPE贡献图可有效分析流量异常的原因。     

扩充编码符号的EZW改进算法

为了提高EZW算法的性能,分析发现EZW算法主扫描编码对最高频子带中不重要系数的编码存在冗余,且当重要系数的所有子孙系数都是不重要系数时的编码存在冗余.据此提出了扩充编码符号的EZW改进算法,用最高频子带的坐标作为限制条件来减少不重要系数的编码冗余;通过扩充编码符号和赋予原始EZW算法的4个编码符号新的适用范围的方案来减小第二种编码冗余.实验结果表明,本文算法使峰值信噪比提高0.9～2.3dB,从而证实了本文改进算法的有效性.     

Effective prediction of DEA model by neural network

In this paper,a fast neural network model for the forecasting of effective points by DEA model is proposed,which is based on the SPDS training algorithm.The SPDS training algorithm overcomes the drawbacks of slow convergent speed and partially minimum result for BP algorithm.Its training speed is much faster and its forecasting precision is much better than those of BP algorithm.By numeric examples,it is showed that adopting the neural network model in the forecasting of effective points by DEA model is valid.