It appeared recently that the classical random graph model used to represent real-world complex networks does not capture their main properties. Since then, various attempts have been made to provide accurate models. We study here a model which achieves the following challenges: it produces...

The solution structure of simple and complex proteins can be modeled efficaciously, starting either from solution scattering data or from the 3D structures derived from crystallographic work or from electron microscopy. Best fitting low-resolution bead models of proteins in solution can be...

We analyze the return of the S & P 500 index and characterize its evolution as being typical of a low-dimensional recurrent deterministic system. The first Poincaré return time of the chaotic logistic mapping trajectories is used to model the return evolution. The efficiency of the model is...

In this contribution, particle size distributions (PSD) of soil samples are analyzed by fractal methods. Different scaling domains, characterizing different ranges of particle sizes, are identified. Numerical models based on cellular automata are presented with the aim to understand the basic...

We analyze fluctuating observables of high-dimensional systems as the New York Stock Market S&P 500 index, the amino-acid sequence in the M. genitalium DNA, the maximum temperature of the San Francisco Bay area, and the toroidal magneto plasma potential. The probability measures of these...

The relaxation behavior of glass is of great scientific and technological importance. However, prediction of glass relaxation behavior using direct first principles techniques is currently infeasible for realistic laboratory time scales. The enthalpy landscape approach has proven to be...

A modified van der Pol oscillator model was designed in order to reproduce the time series of the action potential generated by a natural pacemaker of the heart (i.e., the SA or the AV node). The main motivation was that the models published up to now were not altogether adequate for research on...

An interacting lattice gas model is used to study flow of immiscible components A and B (molecular weights MA and MB,MA<MB) by Monte Carlo simulations. Concentration gradients and hydrostatic pressure bias (H) drive these constituents from their source at the bottom against gravitational sedimentation in an effective medium. Response of their flux densities (jA,jB) to the hydrostatic bias H are examined. If both constituents are released with equal probabilities (a non-interacting source), their flux densities respond linearly to bias with jA>jB except at the extreme bias H→1 where jA→jB. Flow response becomes complex if the constituents from their source are released according to their current lattice...</mb)>