We present Visbrain, a Python open-source package that offers a comprehensive visualization suite for neuroimaging and electrophysiological brain data. Visbrain consists of two levels of abstraction: (1) objects which represent highly configurable neurooriented visual primitives (3D brain, sources connectivity, etc.) and (2) graphical user interfaces for higher level interactions. The object level offers flexible and modular tools to produce and automate the production of figures using an approach similar to that of Matplotlib with subplots.

We introduce and analyze a new, nonlinear fourth-order regularization of forwardbackward parabolic equations. In one space dimension, under general assumptions on the potentials, which include those of Perona-Malik type, we prove existence of Radon measure-valued solutions under both natural and essential boundary conditions.

The evolution of a geothermal system is studied. A mathematical model is proposed and the corresponding free boundary problem is formulated in a one-dimensional geometry. A situation corresponding to the geothermal field in Larderello, Tuscany (Italy) is considered, showing that the problem has two characteristic time scales, related to the motion of interface and diffusion of vapor.

This paper studies a scheduling problem application for the optimization of the employees used in aircrafts' refueling in a medium size airport. The problem is modelled as a particular resource leveling problem for which we provide a mixed integer mathematical formulation that we solve with CPLEX. The model allows to evaluate and analyse different scenarios that could be considered by the company in place of the current one in order to rearrange the available human resources used in refueling activity.

Magnetoencephalography (MEG) aims at reconstructing the unknown neuroelectric activity in the brain from non-invasive measurements of the magnetic field induced by neural sources. The solution of this ill-posed, ill-conditioned inverse problem is usually dealt with using regularization techniques that are often time-consuming, and computationally and memory storage demanding. In this paper we analyze how a slimmer procedure, random sampling, affects the estimation of the brain activity generated by both synthetic and real sources.

Competition between biological species in marine environments is affected by the motion of the surrounding fluid. An effective 2D compressibility can arise, for example, from the convergence and divergence of water masses at the depth at which passively traveling photosynthetic organisms are restricted to live. In this report, we seek to quantitatively study genetics under flow. To this end, we couple an off-lattice agent-based simulation of two populations in 1D to a weakly compressible velocity field--first a sine wave and then a shell model of turbulence.

We consider a nonlinear system of partial differential equations which describes the dynamics of two types of cell densities with contact inhibition. After a change of variables the system turns out to be parabolic-hyperbolic and admits travelling wave solutions which solve a 3D dynamical system. Compared to the scalar Fisher-KPP equation, the structure of the travelling wave solutions is surprisingly rich and to unravel part of it is the aim of the present paper. In particular, we consider a parameter regime where the minimal wave velocity of the travelling wave solutions is negative.

Due to the limited field of view of the microscopes, acquisitions of macroscopic specimens require many parallel image stacks to cover the whole volume of interest. Overlapping regions are introduced among stacks in order to make it possible automatic alignment by means of a 3D stitching tool. Since state-of-the-art microscopes coupled with chemical clearing procedures can generate 3D images whose size exceeds the Terabyte, parallelization is required to keep stitching time within acceptable limits.

GPUs are very powerful computing accelerators that are often employed in single-device configuration. However, there is a steadily growing interest in using multiple GPUs in a concurrent way both to overcome the memory limitations of the single device and to further reduce execution times. Until recently, communication among GPUs had been carried out mainly by using networking technologies originally devised for standard CPUs with the CPU playing an active role in the communication.