第四周期过渡金属钨磷杂多酸盐催化过氧化氢氧化正己醇成正己醛

以Keggin型杂多酸盐 (Na5PW11Z(H2 O)O3 9,Z =Mn ,Fe ,Co,Ni,Cu ,Zn ,以下简称为PW11Z)为催化剂 ,过氧化氢为氧化剂 ,在水—正己醇两相体系中进行了正己醇到正己醛的选择氧化反应 .在此选择氧化反应中同时伴随着过氧化氢分解的竞争反应 ,两种反应间存在着明显的对应关系 .在 70℃时 ,生成正己醛的催化剂活性序列为PW11Co>PW11Fe≈PW11Ni≈PW11Mn >PW11Cu≈PW11Zn ,其中PW11Co的正己醛收率为 3.3% ,当把过氧化氢稀释 ,向反应体系中滴入时 ,则正己醛的收率将大幅度提高 .对于PW11Co来说 ,正己醛的收率提高为 7.12 % ,选择性为 89.4% .还利用ICP ,IR ,UV等手段对催化剂进行了表征     

LDPC码概述及若干理论和应用问题

低密度奇偶校验码（LDPC码）被普遍认为是当今最先进的一种纠错码（信道编码）。LDPC码，图模型，迭代译码的研究热潮已在全球流行有10年以上。这篇论文高度概括的简述了LDPC码的背景和基本知识，从一些独特的视角并联系多个领域提出一些对LDPC码相关知识的理解方法和见解主张，总结了LDPC码当今最新的研究进展。从理论和应用两方面提出作者认为非常有意义的研究问题。     

天然黄酮芦丁的化学改性及抑菌作用

通过对芦丁的化学改性,合成了芦丁的第一过渡系生命元素的配合物。对芦丁配合物的抑菌作用进行了比较研究。研究结果表明,芦丁配合物在水中的溶解性优于芦丁;芦丁配合物的抑菌活性能力强弱为:Ru-Cu>Ru-Zn>Ru-Co>Ru-Ni>Ru-Mn>Ru-Cr>Ru-Fe>Ru,且芦丁配合物抑菌活性的稳定性明显优于芦丁,芦丁经化学改性的产物比芦丁有更好的生物活性。     

Language clusters based on linguistic complex networks

To investigate the feasibility of using complex networks in the study of linguistic typology, this paper builds and explores 15 lin-guistic complex networks based on the dependency syntactic treebanks of 15 languages. The results show that it is possible to classify human languages by means of the following main parameters of complex networks: (a) average degree of the node, (b) cluster coefficients, (c) average path length, (d) network centralization, (e) diameter, (f) power exponent of degree distribution, and (g) the determination coefficient of power law distributions. The precision of this method is similar to the results achieved by means of modern word order typology. This paper tries to solve two problems of current linguistic typology. First, the language sample of a typological study is not real text; second, typological studies pay too much attention to local language structures in the course of choosing typological parameters. This study performs better in global typological features of language and not only enhances typological methods, but it is also valuable for developing the applications of complex networks in the humanities, social, and life sciences.     

基于标签传播识别网络中的关键节点

基于标签传播动力学提出了一种识别网络关键节点的算法,主要思想是把每个节点接收到不同标签的数量作为判断节点重要性的指标。应用两种不同的传播模型,在不同网络上与其它中心性指标作比较。结果表明:基于标签传播的中心性指标比其它的中心性方法可以更好地识别网络中的关键节点。基于标签传播的中心性指标还具有以下优势:不需要利用网络的结构信息,因此可以推广到大规模网络上;揭示了一种现象——好的接收者往往也是好的传播者。     

基于复杂行为响应的传染病爆发问题的研究

在小世界网络拓扑结构上,研究信息影响力、接种比例和个体间信息传播概率的变化,对传染病传播的影响。研究发现小世界强度减弱时,信息影响力对传染病爆发概率和爆发规模的影响作用发生了逆转;在个体间信息传播速率增加的过程中,传染病的爆发概率和爆发规模呈现上升的趋势。     

钌配合物[Ru(phen)2(7-R-dppz)]2+( R=-CH3,-F,-CF3)的合成、表征及DNA键合性质

合成并表征了三个钌(II)多吡啶配合物[Ru(phen)2(7-CH3-dppz)]2+ (i)、[Ru(phen)2(7-F-dppz)]2+ (ii)和 [Ru(phen)2(7-CF3-dppz)]2+ (iii).利用光谱法和粘度实验研究了配合物与DNA的结合行为.结果表明3个配合物均以插入方式与DNA结合,其与DNA的亲和力顺序为(ii) > (i) > (iii).同时采用密度泛函(DFT)理论计算合理解释了3个配合物与DNA结合行为的差异.     

Satellite Image Adaptive Restoration Using Periodic Plus Smooth Image Decomposition and Complex Wavelet Packet Transforms

A satellite image adaptive restoration method was developed that avoids ringing artifacts at the image boundary and retains oriented features. The method combines periodic plus smooth image decomposition with complex wavelet packet transforms. The framework first decomposes a degraded satellite image into the sum of a "periodic component" and a "smooth component". The Bayesian method is then used to estimate the modulation transfer function degradation parameters and the noise. The periodic component is deconvoluted using complex wavelet packet transforms with the deconvolution result of the periodic component then combined with the smooth component to get the final recovered result. Tests show that this strategy effectively avoids ringing artifacts while preserving local image details (especially directional textures) without amplifying the noise. Quantitative comparisons illustrate that the results are comparable with previous methods. Another benefit is that this approach can process large satellite images with parallel processing, which is important for practical use.     

Power law and small world properties in a comparison of traffic city networks

We analyze the statistical properties of the urban public bus networks of two cities (Beijing and Chengdu) in China. To this end, we present a comprehensive survey of the degree distribution, average path length, and clustering of both networks. It is shown that both networks exhibit small world behavior and are hierarchically organized. We also discuss the differences between the statistical properties displayed by the two networks. In addition, we propose a weight distribution approach to study the passenger flow through the public bus networks we considered. A hierarchical structure is observed here also.     

动态过程的复频域分析

从建立复频域电路定律和电路模型入手,把时域电路通过拉普拉斯变换为复频域电路模型,建立简单的代数方程,利用拉普拉斯反演,求得动态过程中的电路响应.这一方法免除了经典的解微分方程,求初始值的复杂过程,更重要的是解决了换路定律和基尔霍夫定律之间的矛盾,从而使电路动态过程的分析和解决变得简单快捷.