NMR Reveals Non‐Distributed and Uniform Character of Network Chain Dynamics

Results of different NMR investigations of elastomers are reviewed with respect to their significance for statistical models of rubber elasticity. In contrast to earlier work based on lineshape analysis and relaxometry, results of recent multiple‐quantum experiments indicate that the NMR‐detected dynamic chain order parameter, which reflects the conformational space of individual monomer units at which the signal is detected locally, is a rather narrowly distributed quantity. Constraints to the dynamics and the conformations of a network chain thus act uniformly and appear as a dynamic average over chains of different length and with different end‐to‐end separations. All our findings are in good agreement with large‐scale computer simulations. Anomalies on swelling such as chain desinterspersion at the early stages and the appearance of heterogeneities, are also discussed.

     

Dynamics of Polymer Networks with Strong Differences in the Viscous Characteristics of their Crosslinks and Strands

We study theoretically the relaxation properties of polymer networks, whose monomers and junction sites have different friction parameters (ζ and ζ_jun, respectively). For this, we focus on topologically regular cubic networks built from “bead‐and‐spring” Rouse chains. Setting σ = ζ_jun/ζ, we determine analytically both the eigenvalues and the eigenmodes of the model for arbitrary values of σ. This allows us to extend previous approaches (Macromolecules 2000 , 33, 6578) which were restricted by the condition σ = 3. We compute the frequency dependent storage, G′(ω), and loss, G″(ω), moduli (which for σ ≫ 3 or σ ≪ 3 display two plateaus and two maxima, respectively) and also the mean‐square displacements of the network junctions and of the beads; these turn out to obey power laws, whose validity ranges depend on σ.

     

具有扩散影响的Hopfield型神经网络的全局渐近稳定性

对具有扩散影响的Hopfield型神经网络平衡点的存在唯一性和全局渐近稳定性进行了研究．在激活函数单调非减、可微且关联矩阵和Liapunov对角稳定矩阵有关时,利用拓扑度理论得到了系统平衡点存在的充分条件．通过构造适当的平均Liapunov函数,分析了系统平衡点的全局渐近稳定性．所得结论表明系统的平衡点(如果存在)是全局渐近稳定的而且也蕴含着系统的平衡点的唯一性．     

基于神经网络的模板匹配方法求正常星系红移

星系通常分为正常星系(NG)与活动星系(AG)两类。文章提出了一种自动获取NG红移的快速有效方法: (1) 由NG模板根据红移范围Ⅰ: 0.0～0.3与Ⅱ: 0.3～0.5模拟得到两类星系样本, 进行PCA变换获得样本特征向量; (2) 利用概率神经网络设计两类样本特征向量的Bayes分类器; (3) 对于实际NG光谱数据, 利用Bayes分类器进行分类确定其红移的范围, 然后在此范围内进行模板匹配得到红移的准确值。与在整个红移范围内的模板匹配方法相比, 此方法不但节省了50%的模板匹配运算量, 而且还大大提高了红移值测量的精度。文章研究结果对于大型光谱巡天所产生的海量数据的自动处理具有重要意义。     

小波包分析-插值-RBF法同时测定铝合金中铁、锰、铜、锌

提出了一种在小波包分析对吸收光谱数据进行降噪处理的基础上,采用线性插值增加校正样样本数的新思路,为解决多组分分光光度同时测定中经常遇到的样本少变量多的问题,对提高预测结果的准确性提供了一种新方法。应用小波包分析-一维线性插值-RBF网络处理铝合金样品中铁、锰、铜、锌的同时测定。由于小波包分析-线性插值处理既能发挥良好的滤噪作用,又能使训练集样本对待辩识空间形成较好的覆盖,从而使RBF网络能提取到更多的特征信息,改善网络性能,研究结果表明,该方法可以显著降低测定样的相对误差,获得的测定结果令人满意。     

Combining classification and regression approaches for the quantification of highly overlapping capillary electrophoresis peaks by using evolutionary sigmoidal and product unit neural networks

This is a study of the potential of neural networks built by using different transfer functions (sigmoidal, product and sigmoidal–product units) designed by an evolutionary algorithm to quantify highly overlapping electrophoretic peaks. To test this approach, two aminoglycoside antibiotics, amikacin and paramomycin, were quantified from samples containing either only one component or mixtures of them though capillary zone electrophoresis (CZE) with laser‐induced fluorescence (LIF) detection. The three models assayed used as input data the four‐parameter Weibull curve associated with the profile of the electrophoretic peak and in some cases the class label for each sample estimated by cluster analysis. The combination of classification and regression approaches allowed the establishment of straightforward network topologies enabling the analytes to be quantified with great accuracy and precision. The best models for mixture samples were provided by product unit neural networks (PUNNs), 4:4:1 (14 weights) for both analytes, after discrimination by cluster analysis, allowing the analytes to be quantified with great accuracy: 8.2% for amikacin and 5.6% for paromomycin within the standard error of prediction for the generalization test, SEP_G. For comparison, partial least square regression was also used for the resolution of these mixtures; it provided a minor accuracy: SEP_G 11.8 and 15.7% for amikacin and paramomycin, respectively. The reduced dimensions of the neural networks models selected enabled the derivation of simple quantification equations to transform the input variables into the output variable. These equations can be more easily interpreted from a chemical point of view than those provided by other ANN models. Copyright © 2007 John Wiley & Sons, Ltd.     

Effects of Interactive Function Forms and Refractoryperiod in a Self-Organized Critical Model Based on Neural Networks

Based on the standard self-organizing map neural network model and an integrate-and-fire mechanism, we investigate the effect of the nonlinear interactive function on the self-organized criticality in our model. Based on the sewe also investigate the effect of the refractoryperiod on the self-organized criticality of the system.     

Pair correlations in scale-free networks

Correlation between nodes is found to be a common and important property in many complex networks. Here we investigate degree correlations of the Barabasi－Albert (BA) scale-free model with both analytical results and simulations, and find two neighbouring regions, a disassortative one for low degrees and a neutral one for high degrees. The average degree of the neighbours of a randomly picked node is expected to diverge in the limit of infinite network size. As a generalization of the concept of correlation, we also study the correlations of other scalar properties, including age and clustering coefficient. Finally we propose a correlation measurement in bipartite networks.     

Fabrication of CdS Nanorods in PVP Fiber Matrices by Electrospinning

Summary: A controlled fabrication of rod‐like nanostructures of cadmium sulfide (CdS) incorporated into polymer fiber matrices has been developed by an electrospinning method. Here, poly(vinyl pyrrolidone) (PVP) was used as a polymer capping reagent, utilizing the interactions of cadmium ions with the carbonyl groups in the PVP molecules. The formation of CdS nanorods inside the PVP was carried out via the reaction of Cd²⁺ with H₂S. SEM images showed that the electrospun films of PVP/CdS are composed of fibers with a diameter between 100 and 900 nm. TEM proved that most of the CdS nanorods are incorporated in the PVP fibrous film. The diameter of the rod is about 50 nm and the length is from 100 to 300 nm.

TEM image of the CdS nanorods formed in the PVP fibrous film.     

Liquid Crystalline Dendritic Networks Derived from Poly(propylene imine) (PPI) Dendrimers

Summary: A nematic liquid crystalline network based on a poly(propylene imine) dendrimer [PPI‐(NH₂)₃₂ (G = 4)] was prepared in the form of films. In the network the PPI dendritic molecules are partially functionalised with a chiral aldehyde and are connected to each other by an achiral dialdehyde. The phase behaviour of the network was investigated by polarising‐light optical microscopy, differential scanning calorimetry, and X‐ray diffractometry. Thermoelastic measurements ruled out the possible elastomeric nature of the material.

Schematic of the nematic dendritic network prepared here.