The Impact of the Network Topology on the Viral Prevalence: A Node-Based Approach.

This paper addresses the impact of the structure of the viral propagation network on the viral prevalence. For that purpose, a new epidemic model of computer virus, known as the node-based SLBS model, is proposed. Our analysis shows that the maximum eigenvalue of the underlying network is a key factor determining the viral prevalence.

Opinion formation models on a gradient.

Statistical physicists have become interested in models of collective social behavior such as opinion formation, where individuals change their inherently preferred opinion if their friends disagree. Real preferences often depend on regional cultural differences, which we model here as a spatial gradient g in the initial opinion. The gradient does not only add reality to the model.

[Superior vena cava syndrome and internal mammary nodes in breast cancer: two cases].

Background: The association of superior vena cava syndrome with involvement of the internal mammary lymph nodes in breast cancer has not been reported in the literature.

Aim: To report two cases of association of superior vena cava with involvement of the internal mammary lymph nodes in breast cancer.

Cases Report: We report two observations in two patients 45 and 52 years with breast cancer classified T4N2M0 and T3N2M0 treated.

A random walk model for infection on graphs: spread of epidemics & rumours with mobile agents.

We address the question of understanding the effect of the underlying network topology on the spread of a virus and the dissemination of information when users are mobile performing independent random walks on a graph. To this end, we propose a simple model of infection that enables to study the coincidence time of two random walkers on an arbitrary graph. By studying the coincidence time of a susceptible and an infected individual both moving in the graph we obtain estimates of the infection probability.