Circuit-switching networks with FIFO plus justifying blockout service on infinite graphs

A class of circuit-switching open queueing networks is discussed. The main result of the paper is that if extra message flows are not too intensive and the path distribution is mainly concentrated on the paths of (graph) distance 1 (nearest neighbour connections), then the network has a unique stationary working regime, no matter how large the configuration graph of the network is. Standard properties of this regime are established such as decay of correlation and continuity.     

卤代化合物的碳—13化学位移模拟

用人工神经网络和多元回归方法对含２个碳的２１个卤代化合物的３５个化学位移进行计算机图像模拟，结果表明，人工神经网络方法优于多元回归方法，同时此种方法处理这类问题有明显的优势，波谱模拟技术在有机化合物结构解析中是非常有用的方法。     

Monotone Chemical Reaction Networks

We analyze certain chemical reaction networks and show that every solution converges to some steady state. The reaction kinetics are assumed to be monotone but otherwise arbitrary. When diffusion effects are taken into account, the conclusions remain unchanged. The main tools used in our analysis come from the theory of monotone dynamical systems. We review some of the features of this theory and provide a self-contained proof of a particular attractivity result which is used in proving our main result.     

用人工神经网络处理谷物成分分析

本文用人工神经网络处理谷物的付立叶变换近红外漫反射光谱,对谷物中含量在10~(-1)～10~(-3)的蛋白质、脂肪和6种人体必需氨基酸定量分析数据进行了解析,分析结果与经典化学方法没有系统偏差,且优于逐步回归分析法的结果。     

Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using and nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the ‘measured’ and ‘estimated’ RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only NMR data) also showed high correlation between the ‘measured’ and ‘estimated’ RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets.     

Irreversible deformation of macromolecular networks

Based upon a thermodynamical approach, the generalized Onsager type of relaxation of van der Waals networks is presented. By linearly and identically coupling the set hidden variables to the network, the memory function of the system can be related to the equilibrium strain-energy function. The relaxation behavior of real networks on stretching can quantitatively be described by means of a distribution of relaxation times known from small strain experiments. Some new and interesting conclusions are discussed as to how the macroscopically non-linear visco-elastic response might be interpreted.     

Simulation of aerated lagoon using artificial neural networks and multivariate regression techniques

The aim of this study was to develop an empirical model that provides accurate predictions of the biochemical oxygen demand of the output stream from the aerated lagoon at International Paper of Brazil, one of the major pulp and paper plants in Brazil. Predictive models were calculated from functional link neural networks (FLNNs), multiple linear regression, principal components regression, and partial least-squares regression (PLSR). Improvement in FLNN modeling capability was observed when the data were preprocessed using the PLSR technique. PLSR also proved to be a powerful linear regression technique for this problem, which presents operational data limitations.     

New stage in living cationic polymerization: An array of effective Lewis acid catalysts and fast living polymerization in seconds

Our recent extensive research on Lewis acid catalysts with a weak base for the cationic polymerization of vinyl ethers led to unprecedented living reaction systems: fast living polymerization within 1–3 s; a wide choice of metal halides containing Al, Sn, Fe, Ti, Zr, Hf, Zn, Ga, In, Si, Ge, and Bi; and heterogeneously catalyzed living polymerization with Fe₂O₃. The use of added bases for the stabilization of the propagating carbocation and the appropriate selection of Lewis acid catalysts were crucial to the success of such new types of living polymerizations. In addition, the base‐stabilized living polymerization allowed the quantitative synthesis of star‐shaped polymers with a narrow molecular weight distribution via polymer‐linking reactions and the precision synthesis and self‐assembly of stimuli‐responsive block copolymers. © 2007 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 45: 1801–1813, 2007.     

Interpenetrating polymer networks of poly(dimethyl siloxane–urethane) and poly(methyl methacrylate)

Simultaneous IPNs of poly(dimethyl siloxane-urethane) (PDMSU)/poly(methyl methacrylate) (PMMA) and related isomers have been prepared by using new oligomers of bis(β-hydroxyethoxymethyl)poly(dimethyl siloxane)s (PDMS diols) and new crosslinkers biuret triisocyanate (BTI) and tris(β-hydroxylethoxymethyl dimethylsiloxy) phenylsilane (Si-triol). Their phase morphology have been characterized by DSC and SEM. The SEM phase domain size is decreased by increasing crosslink density of the PDMSU network. A single phase IPN of PDMSU/PMMA can be made at an M_c = 1000 and 80 wt % of PDMSU. All of the pseudo- or semi-IPNs and blends of PDMSU and PMMA were phase separated with phase domain sizes ranging from 0.2 to several micrometers. The full IPNs of PDMSU/PMMA have better thermal resistance compared to the blends of linear PDMSU and linear PMMA. © 1993 John Wiley & Sons, Inc.