Binary time series generated by chaotic logistic maps

This paper examines stochastic pairwise dependence structures in binary time series obtained from discretised versions of standard chaotic logistic maps. It is motivated by applications in communications modelling which make use of so-called chaotic binary sequences. The strength of non-linear stochastic dependence of the binary sequences is explored. In contrast to the original chaotic sequence, the binary version is non-chaotic with non-Markovian non-linear dependence, except in a special case. Marginal and joint probability distributions, and autocorrelation functions are elicited. Multivariate binary and more discretised time series from a single realisation of the logistic map are developed from the binary paradigm. Proposals for extension of the methodology to other cases of the general logistic map are developed. Finally, a brief illustration of the place of chaos-based binary processes in chaos communications is given.Binary sequence; chaos; chaos communications; dependence; discretisation; invariant distribution; logistic map; randomness

Genetic Differentiation Among Three Species of \u3ci\u3eParadosa\u3c/i\u3e (Arachnida: Lycosidae)

Allozymic variation in nine protein producing loci was examined in three species of Pardosa using starch gel electrophoresis. Allozyme frequencies showed a high degree of geographic uniformity among conspecific populations. Estimated heterozygosities for the three species ranged from 0.05 to 0.15. Rogers\u27 coefficients of genetic similarity based on allozyme frequencies averaged over conspecific populations ranged from 0.16 to 0.37 fo rthe three species

Innate Immunity and the Pathogenicity of Inhaled Microbial Particles

Non-infectious inhaled microbial particles can cause illness by triggering an inappropriate immunological response. From the pathogenic point of view these illnesses can be seen to be related to on one hand autoimmune diseases and on the other infectious diseases

Energy Distribution in disordered elastic Networks

Disordered networks are found in many natural and artificial materials, from gels or cytoskeletal structures to metallic foams or bones. Here, the energy distribution in this type of networks is modeled, taking into account the orientation of the struts. A correlation between the orientation and the energy per unit volume is found and described as a function of the connectivity in the network and the relative bending stiffness of the struts. If one or both parameters have relatively large values, the struts aligned in the loading direction present the highest values of energy. On the contrary, if these have relatively small values, the highest values of energy can be reached in the struts oriented transversally. This result allows explaining in a simple way remodeling processes in biological materials, for example, the remodeling of trabecular bone and the reorganization in the cytoskeleton. Additionally, the correlation between the orientation, the affinity, and the bending-stretching ratio in the network is discussed