Analyzing complex networks evolution through Information Theory quantifiers

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.     

Systems biology reveals biology of systems

In the last decades, genomic and postgenomic technologies obtained a great amount of information on molecular bases of cell physiology and organization. In spite of this, the knowledge of cells and living organisms in their entirety, is far from being achieved. In order to deal with biological complexity, Systems Biology uses a new approach to overcome this inadequacy. Despite different definitions, Systems Biology's view of biological phenomena highlights that a holistic perspective is needed to integrate and understand the huge amount of empirical data which have been collected. This is one of the aspects that makes Systems Biology so interesting, from a theoretical and epistemological point of view, and that renders it a useful tool to help students approach living beings' dynamics within a comprehensive framework of their biological features as well. © 2010 Wiley Periodicals, Inc. Complexity, 2010     

Examples of entropy generating sequence

We introduce the notion of entropy generating sequence for infinite words and define its dimension when it exists. We construct an entropy generating sequence for each symbolic example constructed by Cassaigne such that the dimension of the sequence is the same as its topological entropy dimension. Hence the complexity can be measured via the dimension of an entropy generating sequence. Moreover, we construct a weakly mixing example with subexponential growth rate.     

Evaluating nonlinear variability of mental fatigue behavioral indices during long‐term attentive task

This study investigates the behavioral indices of attention. A simple repetitive attentive task that resulted in mental fatigue was used consecutively in four trials. In the first step, reaction time and error responses were recorded to evaluate differences among trials. During the task, subjects showed different responses to stimulations. In the second part, to recognize the strategies, multiple clustering methods such as k‐means and fuzzy c‐means were performed in which behavioral indices and nonlinear features were used. In the last section, mental behavior was identified as a result of the chaotic properties of variations in reaction time. Therefore, the Lyapunov exponent of reaction times was evaluated. Results revealed that behavioral indices could distinguish attention from the occurrence of mental fatigue in trials. In addition, the three strategies used by subjects during the test protocol were assessed. Finally, variation of indices extracted from nonlinear analysis, that is, decrease in degree of chaotic behavior determined the transition from attention to mental fatigue. © 2012 Wiley Periodicals, Inc. Complexity, 2012     

Path-following interior point algorithms for the Cartesian <Emphasis Type="Italic">P</Emphasis><Subscript>*</Subscript>(κ)-LCP over symmetric cones

In this paper, we establish a theoretical framework of path-following interior point algorithms for the linear complementarity problems over symmetric cones (SCLCP) with the Cartesian P _*(κ)-property, a weaker condition than the monotonicity. Based on the Nesterov-Todd, xy and yx directions employed as commutative search directions for semidefinite programming, we extend the variants of the short-, semilong-, and long-step path-following algorithms for symmetric conic linear programming proposed by Schmieta and Alizadeh to the Cartesian P _*(κ)-SCLCP, and particularly show the global convergence and the iteration complexities of the proposed algorithms. This work was supported by National Natural Science Foundation of China (Grant Nos. 10671010, 70841008)     

Two Interior-Point Methods for Nonlinear P *(τ)-Complementarity Problems

Two interior-point algorithms using a wide neighborhood of the central path are proposed to solve nonlinear P _*-complementarity problems. The proof of the polynomial complexity of the first method requires the problem to satisfy a scaled Lipschitz condition. When specialized to monotone complementarity problems, the results of the first method are similar to those in Ref. 1. The second method is quite different from the first in that the global convergence proof does not require the scaled Lipschitz assumption. However, at each step of this algorithm, one has to compute an approximate solution of a nonlinear system such that a certain accuracy requirement is satisfied.     

About Segment Complexity of Turing Reductions

We apply complexity concepts to define a new sort of sub-Turing reducibilities ≤ ?? make the degree hierarchy thinner and to obtain some new specifications of the well known jump inversion theorem of Friedberg. We show that this theorem doesn't hold when ≤ T is replaced with ≤ ??, where ?? is any countable subset of the class ?? of all total increasing functions f : ? → ?.     

多供应商多零售商下经济批量问题的多项式时间算法研究

基于多供应商和多零售商构成的经济批量问题,通过构建优化模型,分析了订购费用为全部单位数量折扣和增加数量折扣两种情形模型最优解的相关性质。将这些性质应用到动态规划算法设计中,对订购费用为全部单位数量折扣时的一种特殊情形及增加数量折扣的一般情形分别设计了求解问题最优解的多项式时间算法,并用算例说明了算法的执行过程和有效性。