Propagation velocity of the reaction front in addition polymerization systems

Traveling polymerization fronts in unstirred solutions of methylmethacrylate, methacrylic acid, or acrylamide with some free radicals initiators (through thermal decomposition) have been observed experimentally. A local heating of the initial reactant mixture, under suitable conditions, leads to a reaction front that propagates along the space coordinate with a constant velocity. In this article, a physical interpretation of this phenomenon is provided through a mathematical model that accounts for the depolimerization reaction and is based on the constant pattern approach. Moreover, an approximate explicit analytic expression for the velocity of propagation of the polymerization front is proposed. The theoretical values are compared with those measured experimentally as a function of the initiator concentration for different addition polymerization systems. © 1997 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 35:1047–1059, 1997     

最近十年中国头发微量元素研究进展

2006—2015年,是中国头发微量元素研究继续取得重要成果的10年,也是该项研究量质转变的10年。概述了10年内中国头发微量元素研究的进展、现状和发展方向,高通量微量元素组学研究和微量微区分析技术的发展将引领头发微量元素研究领域走向新的高度。     

地方工科院校《功能高分子材料》课程教学内容的精选与实践

随着材料学的蓬勃发展,功能高分子材料的种类及用途日益繁多,因而《功能高分子材料》课程教学内容涵盖也不断延伸。针对地方工科院校高分子材料与工程专业人才培养的机制和目标,作者探索实践了如何以学生为本、以社会和行业的人才需求为导向,紧密联系地方经济与行业格局,因时因势对课程教学内容进行优化和完善。在此基础上,通过科学合理的教学实践,使学生既能牢固掌握功能高分子材料的基础知识,又能了解本领域最前沿的科学发展动态,拓宽学习思路,提高学习积极性,增强对专业的认可与对行业的期待。     

The nonexistence of expansive homeomorphisms of a class of continua which contains all decomposable circle-like continua

A homeomorphism of a compactum with metric is expansive if there is such that if and , then there is an integer such that . It is well-known that -adic solenoids () admit expansive homeomorphisms, each is an indecomposable continuum, and cannot be embedded into the plane. In case of plane continua, the following interesting problem remains open: For each , does there exist a plane continuum so that admits an expansive homeomorphism and separates the plane into components? For the case , the typical plane continua are circle-like continua, and every decomposable circle-like continuum can be embedded into the plane. Naturally, one may ask the following question: Does there exist a decomposable circle-like continuum admitting expansive homeomorphisms? In this paper, we prove that a class of continua, which contains all chainable continua, some continuous curves of pseudo-arcs constructed by W. Lewis and all decomposable circle-like continua, admits no expansive homeomorphisms. In particular, any decomposable circle-like continuum admits no expansive homeomorphism. Also, we show that if is an expansive homeomorphism of a circle-like continuum , then is itself weakly chaotic in the sense of Devaney.

     

± sign pattern matrices that allow orthogonality

A sign pattern A is a ± sign pattern if A has no zero entries. A allows orthogonality if there exists a real orthogonal matrix B whose sign pattern equals A. Some sufficient conditions are given for a sign pattern matrix to allow orthogonality, and a complete characterization is given for ± sign patterns with n − 1 ⩽ N₋(A) ⩽ n + 1 to allow orthogonality.     

On the inertia sets of some symmetric sign patterns

A matrix whose entries consist of elements from the set {+, −, 0} is a sign pattern matrix. Using a linear algebra theoretical approach we generalize of some recent results due to Hall, Li and others involving the inertia of symmetric tridiagonal sign matrices.     

Asynchronous cellular automata and pattern classification

This article designs an efficient two‐class pattern classifier utilizing asynchronous cellular automata (ACAs). The two‐state three‐neighborhood one‐dimensional ACAs that converge to fixed points from arbitrary seeds are used here for pattern classification. To design the classifier, (1) we first identify a set of ACAs that always converge to fixed points from any seeds, (2) each ACA should have at least two but not huge number of fixed point attractors, and (3) the convergence time of these ACAs are not to be exponential. To address the second issue, we propose a graph, coined as fixed point graph of an ACA that facilitates in counting the fixed points. We further perform an experimental study to estimate the convergence time of ACAs, and find there are some convergent ACAs which demand exponential convergence time. Finally, we identify there are 73 (out of 256) ACAs which can be effective candidates as pattern classifier. We use each of the candidate ACAs on some standard datasets, and observe the effectiveness of each ACAs as pattern classifier. It is observed that the proposed classifier is very competitive and performs reliably better than many standard existing classifier algorithms. © 2016 Wiley Periodicals, Inc. Complexity 21: 370–386, 2016     

Structure of random 312‐avoiding permutations

We evaluate the probabilities of various events under the uniform distribution on the set of 312‐avoiding permutations of . We derive exact formulas for the probability that the i^th element of a random permutation is a specific value less than i, and for joint probabilities of two such events. In addition, we obtain asymptotic approximations to these probabilities for large N when the elements are not close to the boundaries or to each other. We also evaluate the probability that the graph of a random 312‐avoiding permutation has k specified decreasing points, and we show that for large N the points below the diagonal look like trajectories of a random walk. © 2015 Wiley Periodicals, Inc. Random Struct. Alg., 49, 599–631, 2016     

Fast detection of common sequence structure patterns in RNAs

We developed a dynamic programming approach for computing common exact sequential and structural patterns between two RNAs, given their sequences and their secondary structures. An RNA consists of a sequence of nucleotides and a secondary structure defined via bonds linking together complementary nucleotides. It is known that secondary structures are more preserved than sequences in the evolution of RNAs.We are able to compute all patterns between two RNAs in time O(nm) and space O(nm), where n and m are the lengths of the RNAs. Our method is useful for describing and detecting local motifs. It is especially suitable for finding similar regions of large RNAs that do not share global similarities. An implementation is available in C++ and can be obtained by contacting one of the authors.