Power accretion in social systems.

We consider a model of power distribution in a social system where a set of agents plays a simple game on a graph: The probability of winning each round is proportional to the agent's current power, and the winner gets more power as a result. We show that when the agents are distributed on simple one-dimensional and two-dimensional networks, inequality grows naturally up to a certain stationary value characterized by a clear division between a higher and a lower class of agents. High class agents are separated by one or several lower class agents which serve as a geometrical barrier preventing further flow of power between them.

Information and topology in attractor neural networks.

A wide range of networks, including those with small-world topology, can be modeled by the connectivity ratio and randomness of the links. Both learning and attractor abilities of a neural network can be measured by the mutual information (MI) as a function of the load and the overlap between patterns and retrieval states. In this letter, we use MI to search for the optimal topology with regard to the storage and attractor properties of the network in an Amari-Hopfield model.

Bump formation in a binary attractor neural network.

The conditions for the formation of local bumps in the activity of binary attractor neural networks with spatially dependent connectivity are investigated. We show that these formations are observed when asymmetry between the activity during the retrieval and learning is imposed. An analytical approximation for the order parameters is derived.

Functional phylogeny: the use of the sensitivity of ribosomes to protein synthesis inhibitors as a tool to study the evolution of organisms.

In order to study the functional phylogeny of organisms, forty different protein synthesis inhibitors with diverse domain and functional specificities have been used to analyze forty archaeal, bacterial and eukaryotic translational systems. The inhibition curves generated with the different ribosome-antibiotic pairs have shown very interesting similarities among organisms belonging to the same phylogenetic group, confirming the feasibility of using such information in the development of evolutionary studies. A new method to extract most of the information contained in the inhibition curves is presented.