Statistics of extinction and survival in Lotka-Volterra systems

We analyze purely competitive many-species Lotka-Volterra systems with random interaction matrices, focusing the attention on statistical properties of their asymptotic states. Generic features of the evolution are outlined from a semiquantitative analysis of the phase-space structure, and extensive numerical simulations are performed to study the statistics of the extinctions. We find that the number of surviving species depends strongly on the statistical properties of the interaction matrix, and that the probability of survival is weakly correlated to specific initial conditions.Comment: Previous version had error in authors. 11 pages, including 5 figure

Prospectively predicting dietary restraint: The role of interpersonal self-efficacy, weight/shape self-efficacy, and interpersonal stress

This study investigated how the precursors of interpersonal self-efficacy and weight/shape self-efficacy would interact in the face of interpersonal stress to prospectively predict dietary restraint. Three models were explored, each with a different type of interpersonal stress: stress from same sex friendships, opposite sex friendships, or romantic relationships

Collective motions in globally coupled tent maps with stochastic updating

We study a generalization of globally coupled maps, where the elements are updated with probability $p$. When $p$ is below a threshold $p_c$, the collective motion vanishes and the system is the stationary state in the large size limit. We present the linear stability analysis.Comment: 6 pages including 5 figure

Mutual synchronization and clustering in randomly coupled chaotic dynamical networks

We introduce and study systems of randomly coupled maps (RCM) where the relevant parameter is the degree of connectivity in the system. Global (almost-) synchronized states are found (equivalent to the synchronization observed in globally coupled maps) until a certain critical threshold for the connectivity is reached. We further show that not only the average connectivity, but also the architecture of the couplings is responsible for the cluster structure observed. We analyse the different phases of the system and use various correlation measures in order to detect ordered non-synchronized states. Finally, it is shown that the system displays a dynamical hierarchical clustering which allows the definition of emerging graphs.Comment: 13 pages, to appear in Phys. Rev.