Recent theories predict phase separation among orientationally disordered active particles whose propulsion speed decreases rapidly enough with density. Coarse-grained models of this process show time-reversal symmetry (detailed balance) to be restored for uniform states, but broken by gradient terms; hence, detailed-balance violation is strongly coupled to interfacial phenomena. To explore the subtle generic physics resulting from such coupling, we here introduce 'Active Model B'.

Cell motility in higher organisms (eukaryotes) is crucial to biological functions ranging from wound healing to immune response, and also implicated in diseases such as cancer. For cells crawling on hard surfaces, significant insights into motility have been gained from experiments replicating such motion in vitro. Such experiments show that crawling uses a combination of actin treadmilling (polymerization), which pushes the front of a cell forward, and myosin-induced stress (contractility), which retracts the rear.

The importance of faster drug development has never been more evident than in present time when the whole world is struggling to cope up with the COVID-19 pandemic. At times when timely development of effective drugs and treatment plans could potentially save millions of lives, drug repurposing is one area of medicine that has garnered much of research interest. Apart from experimental drug repurposing studies that happen within wet labs, lot many new quantitative methods have been proposed in the literature.

The development of turbulence closure models, parametrizing the influence of small nonresolved scales on the dynamics of large resolved ones, is an outstanding theoretical challenge with vast applicative relevance. We present a closure, based on deep recur- rent neural networks, that quantitatively reproduces, within statistical errors, Eulerian and Lagrangian structure functions and the intermittent statistics of the energy cascade, including those of subgrid fluxes. To achieve high-order statistical accuracy, and thus a stringent statistical test, we employ shell models of turbulence.

In this work we numerically study the switching dynamics of a 2D cholesteric emulsion droplet immersed in an isotropic fluid under an electric field, which is either uniform or rotating with constant speed. The overall dynamics depend strongly on the magnitude and on the direction (with respect to the cholesteric axis) of the applied field, on the anchoring of the director at the droplet surface and on the elasticity.

We present a new image scaling method both for downscaling and upscaling, running with any scale factor or desired size. The resized image is achieved by sampling a bivariate polynomial which globally interpolates the data at the new scale. The method's particularities lay in both the sampling model and the interpolation polynomial we use. Rather than classical uniform grids, we consider an unusual sampling system based on Chebyshev zeros of the first kind.

Dispersing colloidal particles into liquid crystals provides a promising avenue to build a novel class of materials, with potential applications, among others, as photonic crystals, biosensors, metamaterials and new generation liquid crystal devices. Understanding the physics and dynamical properties of such composite materials is then of high-technological relevance; it also provides a remarkable challenge from a fundamental science point of view due to the intricacies of the hydrodynamic equations governing their dynamical evolution.

In liquid crystal devices it is important to understand the physics underlying their switching between different states, which is usually achieved by applying or removing an electric field. Flow is known to be a key determinant of the timescales and pathways of the switching kinetics. Incorporating hydrodynamic effects into theories for liquid crystal devices is therefore important; however this is also highly non-trivial, and typically requires the use of accurate numerical methods.

Tra novembre 2020 e giugno 2021, l'Istituto per le Applicazioni del Calcolo "Mauro Picone" (IAC) ha realizzato un ciclo di seminari dedicati al rapporto tra Intelligenza Artificiale e Matematica, denominato AIM - Artificial Intelligence and Mathematics - Fundamentlas and beyond.

MIPAS is a Fourier Transform spectrometer that measured the atmospheric limb emission spectra in the middle infrared on board the ENVISAT satellite. These measurements allowed the global monitoring of the three-dimensional (latitude, longitude and altitude) distribution of temperature and of the concentrations of many species, during both day and night, for 10 years, from July 2002 to April 2012. MIPAS measurements allowed to study the atmosphere from the upper troposphere to the stratosphere and above, up to the thermosphere.