111 resultados para Topological Strings


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Recurrence plot technique of DNA sequences is established on metric representation and employed to analyze correlation structure of nucleotide strings. It is found that, in the transference of nucleotide strings, a human DNA fragment has a major correlation distance, but a yeast chromosome's correlation distance has a constant increasing. (C) 2004 Elsevier B.V All rights reserved.

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We derive an explicit expression for predicting the thicknesses of shear bands in metallic glasses. The model demonstrates that the shear-band thickness is mainly dominated by the activation size of the shear transformation zone (STZ) and its activation free volume concentration. The predicted thicknesses agree well with the results of measurements and simulations. The underlying physics is attributed to the local topological instability of the activated STZ. The result is of significance in understanding the origin of inhomogeneous flow in metallic glasses. (C) 2009 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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According to Chen's theory, topological differences are perceived faster than feature differences in early visual perception. We hypothesized that topological perception is caused by the sensitivity in discriminating figures with and without "holes". An E

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Global information is considered the primitive of visual perception in Gestalt psychology. Further, L. Chen ( 2005) proposed a new theory of topological visual perception. According to this theory, the perception of topological difference is faster than o

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The phylogenetic relationships among peritrichs remain unresolved. In this study, the complete small subunit rRNA (SSrRNA) gene sequences of seven species (Epistylis galea, Campanella umbellaria, Carchesium polypinum, Zoothamnium arbuscula, Vaginicola crystallina, Ophrydium versatile, and Opercularia microdiscum) were determined. Trees were constructed using distance-matrix, maximum-likelihood and maximum-parsimony methods, all of which strongly supported the monophyly of the subclass Peritrichia. Within the peritrichs, 1) E. galea grouped with Opercularia microdiscum and Campanella umbellaria but not the other Epistylis species, which indicates that the genus Epistylis might not be monophyletic; 2) the topological position of Carchesium and Campanella suggested that Carchesium should be placed in the family Zoothammidae, or be elevated to a higher taxonomic rank, and that Campanella should be independent of the family Epistylididae, and probably be given a new rank; and 3) Opisthonecta grouped strongly with Asty/ozoon, which suggested that Opisthonecta species were not the ancestors of the stalked peritrichs.

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We demonstrate that a p-n junction created electrically in HgTe quantum wells with inverted band structure exhibits interesting intraband and interband tunneling processes. We find a perfect intraband transmission for electrons injected perpendicularly to the interface of the p-n junction. The opacity and transparency of electrons through the p-n junction can be tuned by changing the incidence angle, the Fermi energy and the strength of the Rashba spin-orbit interaction (RSOI). The occurrence of a conductance plateau due to the formation of topological edge states in a quasi-one-dimensional (Q1D) p-n junction can be switched on and off by tuning the gate voltage. The spin orientation can be substantially rotated when the samples exhibit a moderately strong RSOI.

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First, the compression-awaited data are regarded Lis character strings which are produced by virtual information source mapping M. then the model of the virtual information source M is established by neural network and SVM. Last we construct a lossless data compression (coding) scheme based oil neural network and SVM with the model, an integer function and a SVM discriminant. The scheme differs from the old entropy coding (compressions) inwardly, and it can compress some data compressed by the old entropy coding.

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In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

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Time-resolved Faraday rotation spectroscopy is currently exploited as a powerful technique to probe spin dynamics in semiconductors. We propose here an all-optical approach to geometrically manipulate electron spin and to detect the geometric phase by this type of extremely sensitive experiment. The global nature of the geometric phase can make the quantum manipulation more stable, which may find interesting applications in quantum devices.

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An algorithm of PCA face recognition based on Multi-degree of Freedom Neurons theory is proposed, which based on the sample sets' topological character in the feature space which is different from "classification". Compare with the traditional PCA+NN algorithm, experiments prove its efficiency.

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In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

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In this paper, we construct (d, r) networks from sequences of different irrational numbers. In detail, segment an irrational number sequence of length M into groups of d digits which represent the nodes while two consecutive groups overlap by r digits (r = 0,1,...,d-1), and the undirected edges indicate the adjacency between two consecutive groups. (3, r) and (4, r) networks are respectively constructed from 14 different irrational numbers and their topological properties are examined. By observation, we find that network topologies change with different values of d, r and even sequence length M instead of the types of irrational numbers, although they share some similar features with traditional random graphs. We make a further investigation to explain these interesting phenomena and propose the identical-degree random graph model. The results presented in this paper provide some insight into distributions of irrational number digits that may help better understanding of the nature of irrational numbers.

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The concept of traces has been introduced for describing non-sequential behaviour of concurrent systems via its sequential observations. Traces represent concurrent processes in the same way as strings represent sequential ones. The theory of traces can be used as a tool for reasoning about nets and it is hoped that applying this theory one can get a calculus of the concurrent processes anologous to that available for sequential systems. The following topics will be discussed: algebraic properties of traces, trace models of some concurrency phenomena, fixed-point calculus for finding the behaviour of nets, modularity, and some applications of the presented theory.

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本文建立了一个能用于含N、P、O、S、Si及卤素等多种杂原子的有机化合物结构自动解析专家系统ESESOC(Expert System for the Elucidation of the Structure of Orsanic Compounds)。它可从未知化合物的分子式、光谱数据(包括IR, MS,~1HNMK ~(13)CNMR, 2D-NMR等)及其它化学信息自动地推衍出与己知信息相一致的候选化合物结构。ESESOC系统由三个部分组成:(1)光谱知识库及其光谱解释模块;(2)结构产生器;(3)结构验证模块。其结构解析基本过程为:从分子式、光谱数据或其它化学信息出发,由未知化合物的光谱数据去检索光谱知识库,即进行数据分析并推断出该未知化合物中可能含有的结构碎片,然后由结构产生器从这些结构碎片进行候选化合物结构的穷举生成,最后对候选结构进行验证并输出结果。从而实现由化合物光谱数据鉴别未知化合物结构的自动化。结构产生器是系统的核心模块。对一个结构产生器的基本要求是:穷举性,非冗余性,有效性。要完成一个能实际使用的结构产生器,效率则是至关重要的。ESESOC系统生成结果的穷举和非冗余性己通过与图论计算结果及著名的DENDRAL系统的生成结果相比较得以证明。如由本系统生成的烷烃系列C_nH_(2n+2),及醇、醚系列C_nH_(2n+2)0的异构体数目与图论理论计算的数目相同;对C_5H_n n = 12,10,8,6,4,2,O;C_6H_n n = 14,12,lO,8,6,4,2,O系列,及含多种杂原子(O、N、S等)的复杂体系,其异构体生成结果则与DENDRAL系统的生成结果完全一致(DENDRAL系统的结构生成算法是经数学证明了是正确的,其结果已被很多系统引为穷举和非冗余性的例证)。关于ESESOC系统的有效性,在同一计算机上测试结果表明ESESOC系统的结构生成效率比著名的日本的CHEMICS系统高很多倍。结构解析专家系统另一重要组成部分为谱图知识库,它是逻辑推理的基础。专家系统的效能取决于其子结构一子光谱相关的知识库的有效性,所以要建造一个有效的~(13)CNMR知识库,关键在于建立一个好的子结构模型.在~(13)CNMR知识库中,子结构的概念与常规的子结构概念有所不同,它包括两个组成部分,(1)中心原子,它对应于一个化学位移;(2)环境部分,结构环境决定了中心原子的化学位移峰的位置。子结构模型的选择要适当兼顾信息全面和防止“组合爆炸”两个因素。ESESOC系统从~(13)CNMR本身的特征出发,提出了不确定层数的子结构模型。即以共振碳原子为中心,以与之相连的完整的官能团为外围环境,对这样的子结构,其外围环境根据官能团的不同可以是一层、或二层乃至多层,即环境层数是可变的。此即为ESESOC系统的广义-层子结构模型,它具有包含结构信息全,所有可能存在的子结构数量适中等优点。在此子结构模型的基础上,从CIAC-~(13)CNMR谱图数据库统计出。~(13)CNMR知识库,即子结构-~(13)CNMR化学位移相关表。ESESOC系统中结构验证方法有: ~(13)CNMR谱峰数预测,~(13)CNMR波谱模拟,应力能计算等。在结构解析专家系统研究中还涉及到如下三个问题:(1)结构编码;(2)结构之间相互比较;(3)结构中原子的对称性分析。在本研究中,对这些问题都提出了新的方案,并均获得较好结果。(1)在建造化合物结构信息系统时,首先要解决化合物结构的计算描述,即结构编码问题,以进行化合物结构的计算机存储和管理。为此我们提出了两种新的拓扑指数编码方案,即ID指数和EAID指数。由ESESOC结构产生器穷生成了含1-22个碳原子的380多万个链烷烃异构体,含1-12四价碳原子的20多万仑复杂多环异构体及40多万个含杂原子的化合物,通过对这3个系列共440多万个化合物结构的验证,结果表明,ID和EAID指数对这440多万个化合物结构均能唯一地区分,即没有出现简并(简并是指两个或多个不同的结构具有相同的拓扑指数值)。这是迄今未见报道的。(2)在计算机结构信息处理中,最常遇到的一个问题就是确认一个结构是新结构还是为已知结构,这就要把该结构与库中的结构进行逐个比较。为了结构的比较,我们以二维连接表描述化合物的结构,因连接表随化合中原子的编序的变化而变化,因而就需要有一套序号赋值规则,无论结构图在画法或形状以及原子的序号上如何变化,都可使得结构图中的各原子按该规则得到唯一的排序方案。ESESOC系统的唯一性序号方案集中了Morgan算法及其改进方案之所长,并加入新的图的不变量,如最小环指数等以正确地划分分子中的原子,从而得到一个新的唯一性排序方案,该方案效率较高,可适用于各类复杂化合物。在ESESOC系统中,我们还以一维的整数数组来存贮和管理二维连接表,即得到压缩连接表,这在结构比较时大大地节省了系统开销,提高了比较速度。在同一结构中,若各原子由两种不同编序方案得到同一连接矩阵,则与某一序号所对应的两个原子所在结构图中的拓扑环境是等价的,也就是说两个节点是拓扑等价的,或具有拓扑对称性(Topological Symmetry)。化合物结构中原子的唯一性排序算法,有机化物结构异构体穷举生成过程中冗余对接的消除,NMR谱模拟等都与拓扑对称性密切相关。在ESESOC系统建造过程中,我们提出了三个新的拓扑等价性分析算法,它们是基于节点矩阵的拓扑等价性算法,基于全通道算法的拓扑等价性算法,以及基于扩展连接矩阵算法的拓扑等价性算法。这些算法结果准确,效率高,适用于各类化合物。