Scaling in Electrical Conductivity Measurements and Rheological Measurements of Monarch 700 Dispersions Stabilized by Polymers

For making stable dispersions of graphitic carbon black (Monarch 700), the effectiveness of three dispersants/polymers (hypermer LP1, hypermer B246, and OLOA 11000) in xylene is investigated. Hypermer LP1 (polyhydroxystearic acid) is a homopolymer and hypermer B246 (PEG 30-dipolyhydroxystearate) is a polyhydroxystearic acid/polyethylene oxide/polyhydroxystearic acid ABA block copolymer, while OLOA 11000 (polyisobutylene succinimide) has a polar head group (polyamine) attached to a hydrocarbon chain (polyisobutylene). Well-dispersed graphitic carbon black dispersions were prepared using dispersants at optimum concentrations. Percolation threshold and rheological threshold were determined by analyzing the variations in electrical conductivity and elastic modulus with concentration of carbon black. Above threshold concentration, scaling law was applied to experimental data of rheology (dynamic measurements) and electrical conductivity measurements to evaluate quality of the system. Effectiveness of polymers was investigated on the basis of value of critical exponent (t and t′, respectively) in scaling power law. Hypermer LP1 was proved to be a poor dispersant for Monarch 700 dispersions while other two polymers were found to be effective stabilizers.     

Incompatibility networks as models of scale-free small-world graphs

We make a mapping from Sierpinski fractals to a new class of networks, the incompatibility networks, which are scale-free, small-world, disassortative, and maximal planar graphs. Some relevant characteristics of the networks such as degree distribution, clustering coefficient, average path length, and degree correlations are computed analytically and found to be peculiarly rich. The method of network representation can be applied to some real-life systems making it possible to study the complexity of real networked systems within the framework of complex network theory.     

非等熵气体动力学方程组大初值问题的放缩框架

非等熵气体动力学系统Cauchy问题弱解全局存在性有两个公开问题:一个是包含真空的小初值问题,另一个是任意大初值问题.本文通过引入一个放缩框架证明了上述两个问题的等价性,即对于粘性消失解,其包含真空小初值问题的一致BV估计蕴含着任意大初值问题弱解的全局存在性.该放缩框架对大多数具有物理背景的双曲守恒律系统亦成立.     

核磁共振代谢组学数据的尺度归一化新方法

在核磁共振代谢组学数据预处理中,尺度归一化主要目的是提高特征代谢物信息的权重,减小噪声及无关代谢物信息的影响,从而降低后续模式识别分析的难度. 本文提出一种新的尺度归一化方法,该方法不强调各变量在尺度上的归一,而是在原始数据的基础上,通过提高那些稳定性高、且在不同类别样本中具有显著差异性的变量的权重,以增强与特征代谢物相关的信息. 文中分别采用模拟数据和真实代谢组学数据对新归一化方法的性能进行评估,并与单位方差法(Unit Variance)、变量稳定性(Variable Stability)和尺度缩放法(Level Scaling)等常用的尺度归一化方法做比较. 研究结果表明：新归一化方法能够提高多变量统计模型的预测能力,较好地保留核磁共振谱的分子信息,有助于特征代谢物的识别,并使后续的数据分析结果具有更好的可解释性.     

应用近红外技术测定黄豆粕中水分、蛋白质和粗脂肪

应用近红外分析仪（NIR）快速测定黄豆粕中水分、蛋白质和粗脂肪的含量,通过光谱扫描统计分析,分别找出测量黄豆粕水分、蛋白质、粗脂肪的波长及校准常数值,经数理统计分析结果表明：近红外法与常规水分测定法经典凯氏定氮法、索氏浸提法所测定的结果呈密切的线性相关,检测结果令人满意。     

多层前馈模糊神经网络在儿童综合素质测评中的应用

运用对偶标度统计方法计算儿童发展调查问题中原始数据的变量权和样本得分,从而确定评价因素集.采用多层前馈模糊神经网络——FM LP实现对儿童个体综合素质的定量评价.     

任意矩阵伸缩的正交小波包

1 引言 Coifman和Meyer引入L~2(R)中正交小波包,可以用张量积形式构造L~2(R~2)上的二维正交小波包;Chui和Li研究单变量非正交小波包和对偶小波包;Shen给出矩阵伸缩为2I时L~2(R~s)上非张量积小波包的构造算法;程正兴给出矩阵小波包的构