Biological systems tend to display complex behaviour with a power-law (1/f - like) distribution. In the brain, this translates into neural activity that exhibits scale-free, temporal or spatial, properties (He, 2014). Scaleinvariance has been observed across different neuroimaging modalities and conditions (Linkenkaer-Hansen, 2001; He, 2014; Ciuciu et al. 2012). Beyond previously used features, recent electrophysiology studies have shown the presence of long-range temporal correlations (LRTCs) in the amplitude dynamics of alpha and beta oscillations (Nikulin et al. 2012).

Background. With the exponential increase in data dimension and methodological complexities, brain networks analysis with MEG and EEG has become an increasingly challenging and time-consuming endeavor. To date, performing all the data processing steps that are required for a complete MEG/EEG analysis pipeline often require the use of a multitude of software packages and in-house or custom tools (e.g. MRI segmentation, pre-processing, source reconstruction, graph theoretical analysis, statistics).

In order to understand the flow profiles of complex fluids, a crucial issue concerns the emergence of spatial correlations among plastic rearrangements exhibiting cooperativity flow behaviour at the macroscopic level. In this paper, the rate of plastic events in a Poiseuille flow is experimentally measured on a confined foam in a Hele-Shaw geometry. The correlation with independently measured velocity profiles is quantified by looking at the relationship between the localisation length of the velocity profiles and the localisation length of the spatial distribution of plastic events.

In this paper we present an implementation for the QPACE supercomputer of a Lattice Boltzmann model of a fluid-dynamics flow in 2 dimensions. QPACE is a massively parallel application-driven system powered by the Cell processor. We review the structure of the model, describe in details its implementation on QPACE and finally present performance data and preliminary physics results. (C) 2010 Published by Elsevier Ltd.

A numerical study of turbulence seeded with light particles is presented. We analyze the statistical properties of coherent, small-scale structures by looking at the trapping events of light particles inside vortex filaments. We study the properties of particles attracting set, measuring its fractal dimension and the probability that the separation between two particles remains within the dissipative scale, even for time lapses as long as the large-scale correlation time, T(L).

We compute the continuum thermohydrodynamical limit of a new formulation of lattice kinetic equations for thermal compressible flows, recently proposed by Sbragaglia [J. Fluid Mech. 628, 299 (2009)]. We show that the hydrodynamical manifold is given by the correct compressible Fourier-Navier-Stokes equations for a perfect fluid. We validate the numerical algorithm by means of exact results for transition to convection in Rayleigh-Beacutenard compressible systems and against direct comparison with finite-difference schemes.