Chaos game representation （CGR）-walk model for DNA sequences

Chaos game representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their positions in a continuous space. This distribution of positions has two features: one is unique, and the other is source sequence that can be recovered from the coordinates so that the distance between positions may serve as a measure of similarity between the corresponding sequences. A CGR-walk model is proposed based on CGR coordinates for the DNA sequences. The CGR coordinates are converted into a time series, and a long-memory ARFIMA (p, d, q) model, where ARFIMA stands for autoregressive fractionally integrated moving average, is introduced into the DNA sequence analysis. This model is applied to simulating real CGR-walk sequence data of ten genomic sequences. Remarkably long-range correlations are uncovered in the data, and the results from these models are reasonably fitted with those from the ARFIMA (p, d, q) model.     

基于模糊树模型的混沌时间序列预测

应用模糊树模型,对混沌时间序列进行建模和预测.该方法可以根据建模数据在空间中的分布信息,基于二叉树结构自适应划分输入空间,得到模糊子空间,在与叶节点对应的子空间上建立线性函数作为模糊规则的后件,用隶属度函数将各分片线性函数光滑连接,最后得到一个精度比较高的非线性映射.通过对Mackey-Glass、Lorenz和Henon混沌时间序列的建模和预测研究,仿真结果表明,该方法具有建模精度高、运行速度快、泛化能力强、预测步数多、适用范围广等优点. 关键词： 模糊树模型 混沌时间序列 预测     

基于expectation maximization算法的Mamdani-Larsen模糊系统及其在时间序列预测中的应用

Epanechnikov混合模型和Mamdani-Larsen模糊系统之间的对应关系被建立:任何一个Epanechnikov混合模型都唯一对应着一个Mamdani-Larsen模糊系统,在一定条件下,Epanechnikov混合模型的条件均值和Mamdani-Larsen模糊模型的输出是等价的.一个设计模糊系统的新方法被提出,即利用expectation maximization算法设计模糊系统.将设计的模糊系统应用于时间序列预测,仿真结果表明：利用EM算法设计的模糊系统比其他模糊系统精度更高,抗噪性更强 关键词： expectation maximization(EM)算法 Mamdani-Larsen模糊系统 Epanechnikov混合模型 混沌时间序列     

基于时间序列的网络失效模型

随着网络科学的发展,静态网络已不能清晰刻画网络的动态过程.在现实网络中,个体之间的交互随时间而快速演化.这种网络模式将时间与交互过程紧密联系,能够清晰刻画节点的动态过程.因此,如何更好地基于时间序列刻画网络行为变化是现有级联失效研究的重要问题.为了更好地研究该问题,本文提出一种基于时间序列的失效模型.通过随机攻击某时刻的节点,分析了时间、激活比例、连边数、连接概率4个参数对失效的影响并发现网络相变现象.同时为验证该模型的有效性与科学性,采用真实网络进行研究.实验表明,该模型兼顾时序以及传播动力学,具有较好的可行性,为解释现实动态网络的级联传播提供了参考.     

基于模糊模型的混沌时间序列预测

对于复杂、病态、非线性动态系统，基于模糊集合的模糊模型，利用模糊推理规则描述动态系统的特性，是一种有效方法.讨论了利用模糊建模方法实现非线性系统的建模和预测.首先，利用在线模糊竞争学习方法划分输入变量的模糊输入空间，然后利用卡尔曼滤波算法估计模糊模型的参数.采用该方法对Mackey Glass混沌时间序列进行预测试验，结果表明利用本方法可以在线或者离线能对Mackey Glass混沌时间序列进行准确预测，证明了本方法的有效性. 关键词： 模糊竞争学习 混沌时间序列 卡尔曼滤波     

基于模糊模型支持向量机的混沌时间序列预测

基于支持向量机强大的非线性映射能力和模糊逻辑易于将先验的系统知识结合到模糊规则的 特性, 根据混沌动力系统的相空间重构理论, 提出了一种混沌时间序列的模糊模型的支持向 量机预测模型,并采用适用于大规模问题求解的最小二乘法来训练预测模型,利用该模型分别 对模型的整体预测性能与嵌入维数及延迟时间的关系进行了探讨.最后利用Mackey-Glass时 间序列和典型的Lorenz系统生成的时间序列对该模型进行了验证,结果表明该预测模型不仅 能够自动的从学习数据中获取知识产生模糊规则，提取能够代表混沌时间序列内在规律的支 持向量，大大减少支持向量的数目，精确地预测未来的混沌时间序列,而且在混沌时间序列 的嵌入维数未知和延迟时间不能合理选择的情况下,也能取得比较好的预测效果.这一结论预 示着基于模糊模型的支持向量机是一种研究混沌时间序列的有效方法. 关键词： 模糊模型 混沌时间序列 支持向量机 最小二乘法     

在体检测γ-氨基丁酸的MEGA-PRESS序列优化设计

γ-氨基丁酸（γ-aminobutyric acid,GABA）含量异常会引发一系列大脑疾病,因此在体检测人脑GABA含量成为一种十分必要的医疗技术.本文基于GABA检测常用的谱编辑方法MEGA-PRESS,引入性能更好的SLR脉冲代替常用的高斯脉冲,并使用单频带和双频带结合的方法激发特定频率的物质,在联影（United Imaging Healthcare,UIH）的uMR780磁共振系统上实现了一种优化的MEGA-PRESS序列.结果表明：SLR脉冲可以减少大分子（macromolecule,MM）信号对GABA信号的干扰;单频带和双频带结合可以更好地抑制残余水信号对GABA^*信号的影响.水模实验和人体实验结果均证实优化的MEGA-PRESS序列可以更好地实现GABA^*含量在体检测.     

混沌时间序列的模糊神经网络预测

设计一种新型混合模糊神经推理系统，该系统仅从期望输入输出数据集即可达到获取知识、确定模糊初始规则基的目的.再利用神经网络学习能力便不难修改规则库中的模糊规则以及隶属函数和网络权值等参数，这样大大减少了规则匹配过程，加快了推理速度，从而极大程度地提高了系统的自适应能力.用它对Mackey-Glass混沌时间序列进行预测试验,结果表明利用该网络模型无论离线还是在线学习均能对Mackey-Glass混沌时间序列进行准确的预测，证明了该系统的有效性. 关键词： 神经网络模型 模糊逻辑 混合推理系统 混沌时间序列     

E—DAM共聚物序列结构的^13CNMR研究

本文用COM和APT~(13)C NMR方法研究了三种乙烯(E)和甲基丙烯酸N,N—二甲胺乙酯(DAM)共聚物(E—DAM),找到了一组化学位移屏蔽参数,并用这种参数进一步研究了E—DAM共聚物序列结构.     

基于高斯过程的混沌时间序列单步与多步预测

针对混沌时间序列单步和多步预测,提出基于复合协方差函数的高斯过程 (GP)模型方法.GP模型的确立由协方差函数决定,通过对训练数据集的学习,在证据最大化框架内,利用矩阵运算和优化算法自适应地确定协方差函数和均值函数中的超参数.GP模型与神经网络、模糊模型相比,其可调整参数很少.将不同复合协方差函数的GP模型应用在混沌时间序列单步及多步提前预测中,并与单一协方差函数的GP、支持向量机、最小二乘支持向量机、径向基函数神经网络等方法进行了比较.仿真结果表明,基于不同复合协方差函数的GP方法能精确地预测混沌时间序 关键词： 高斯过程 混沌时间序列 预测 模型比较     

Early-warning signals for an outbreak of the influenza pandemic

Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been performed over the years on the biological properties, chemical characteristics, external environmental factors and other aspects of the virus, and some results have been achieved. Based on the chaos game representation walk model, this paper uses the time series analysis method to study the DNA sequences of the influenza virus from 1913 to 2010, and works out the early-warning signals indicator value for the outbreak of an influenza pandemic. The variances in the CGR walk sequences for the pandemic years (or + -1 to 2 years) are significantly higher than those for the adjacent years, while those in the non-pandemic years are usually smaller. In this way we can provide an influenza early-warning mechanism so that people can take precautions and be well prepared prior to a pandemic.     

Chaos game representation walk model for the protein sequences

A new chaos game representation of protein sequences based on the detailed hydrophobic--hydrophilic (HP) model has been proposed by Yu et al (Physica A 337 (2004) 171). A CGR-walk model is proposed based on the new CGR coordinates for the protein sequences from complete genomes in the present paper. The new CGR coordinates based on the detailed HP model are converted into a time series, and a long-memory ARFIMA(p, d, q) model is introduced into the protein sequence analysis. This model is applied to simulating real CGR-walk sequence data of twelve protein sequences. Remarkably long-range correlations are uncovered in the data and the results obtained from these models are reasonably consistent with those available from the ARFIMA(p, d, q) model.     

Wavelet-based multifractal analysis of DNA sequences by using chaos-game representation

Chaos game representation (CGR) is proposed as a scale-independent representation for DNA sequences and provides information about the statistical distribution of oligonucleotides in a DNA sequence. CGR images of DNA sequences represent some kinds of fractal patterns, but the common multifractal analysis based on the box counting method cannot deal with CGR images perfectly. Here, the wavelet transform modulus maxima (WTMM) method is applied to the multifractal analysis of CGR images. The results show that the scale-invariance range of CGR edge images can be extended to three orders of magnitude, and complete singularity spectra can be calculated. Spectrum parameters such as the singularity spectrum span are extracted to describe the statistical character of DNA sequences. Compared with the singularity spectrum span, exon sequences with a minimal spectrum span have the most uniform fractal structure. Also, the singularity spectrum parameters are related to oligonucleotide length, sequence component and species, thereby providing a method of studying the length polymorphism of repeat oligonucleotides.     

Electrochemical DNA biosensor based on avidin-biotin conjugation for influenza virus (type A) detection

An electrochemical DNA biosensor (E-DNA biosensor) was fabricated by avidin-biotin conjugation of a biotinylated probe DNA, 5′-biotin-ATG AGT CTT CTA ACC GAG GTC GAA-3′, and an avidin-modified glassy carbon electrode (GCE) to detect the influenza virus (type A). An avidin-modified GCE was prepared by the reaction of avidin and a carboxylic acid-modified GCE, which was synthesized by the electrochemical reduction of 4-carboxyphenyl diazonium salt. The current value of the E-DNA biosensor was evaluated after hybridization of the probe DNA and target DNA using cyclic voltammetry (CV). The current value decreased after the hybridization of the probe DNA and target DNA. The DNA that was used follows: complementary target DNA, 5′-TTC GAC CTC GGT TAG AAG ACT CAT-3′ and two-base mismatched DNA, 5′-TTC GAC AGC GGT TAT AAG ACT CAT-3′.     

A specific state variable for a class of 3D continuous fractional-order chaotic systems

A specific state variable in a class of 3D continuous fractional-order chaotic systems is presented.All state variables of fractional-order chaotic systems of this class can be obtained via a specific state variable and its (q-order and 2q-order) time derivatives.This idea is demonstrated by using several well-known fractional-order chaotic systems.Finally,a synchronization scheme is investigated for this fractional-order chaotic system via a specific state variable and its (q-order and 2q-order) time derivatives.Some examples are used to illustrate the effectiveness of the proposed synchronization method.     

A numerical study of the phase structure of the q-state generalization of the hard-square model

An investigation is made of how a recently foundq-state generalization of the hard-square model fits into a more general phase diagram. The investigation is done by Monte Carlo and series expansion methods. Evidence is presented that the one-dimensional manifold of parameters along which the model is exactly solvable represents a line of first-order phase transitions.     

Migdal-Kadanoff renormalization group for theO(n) model

We perform a Migdal-Kadanoff renormalization group calculation on anO(n) symmetric model on ad-dimensional hypercubic lattice,d=2, 3. We find that in two dimensions the critical fixed point disappears asn=n _KT1.96, which is in good agreement with the exact valuen _KT=2. In three dimensions the fixed point persists much longer, albeit not all the way up to infinity. Surface critical phenomena in a semiinfiniteO(n) model are also considered.     

The quadrupole plus pairing interaction model in large configuration space for W,Os and Pt nuclei

The equilibrium deformations of tungsten, osmium and platinum nuclei are studied with the self-consistent quadrupole plus pairing interaction model by considering all the nucleons in nucleus explicitly. It is shown that similar results can be obtained by performing calculations with or without the assumption of an inert core. The only difference is in the strength of the quadrupole and pairing interactions to be employed in the respective calculations. The experimental static quadrupole moments and theB (E2) values are correctly reproduced by performing calculations with bare nucleon charge for all the nucleons.     

Correlation and anticorrelation of fractal aggregates. A model for «spinodal-type» aggregation

Summary We present a simple phenomenological model, based on mass conservation arguments, in order to describe aggregation in dense solutions. It has been previously shown that fordiffusion-limited processes scattered intensity distributions exhibit a peak atq≠0 which grows in time and moves to smaller and smallerq vectors. According to the model, each aggregate is surrounded by a depletion region whose size depends on the aggregation kinetics. The form factor for such a cluster should satisfy local mass conservation and hence exhibit a pronounced depression atq=0. the initial stages of aggregation, when the clusters are far apart, are accounted on the basis of a form factor alone. The model shows good agreement with the data and also explains the experimental evidence that the peak does not appear inreaction-limited conditions. Paper presented at the I International Conference on Scaling Concepts and Complex Fluids, Copanello, Italy, July 4–8, 1994.