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Quasi-equilibrium states that can be prepared in solids through Nuclear Magnetic Resonance (NMR) techniques are out-of-equilibrium states that slowly relax towards thermodynamic equilibrium with the lattice. In this work, we use the quantum discord dynamics as a witness of the quantum correlation in this kind of state. The studied system is a dipole interacting spin pair whose initial state is prepared with the NMR Jeener-Broekaert pulse sequence, starting from equilibrium at high temperature and high external magnetic field. It then evolves as an open quantum system within two different dynamic scenarios: adiabatic decoherence driven by the coupling of the pairs to a common phonon field, described within a non-markovian approach; and spin-lattice relaxation represented by a markovian master equation, and driven by thermal fluctuations. In this way, the studied model is endowed with the dynamics of a realistic solid sample. The quantum discord rapidly increases during the preparation of the initial state, escalating several orders of magnitude compared with thermal equilibrium at room temperature. Despite the vanishing of coherences during decoherence, the quantum discord oscillates around this high value and undergoes a minor attenuation, holding the same order of magnitude as the initial state. Finally, the quantum discord dissipates within a time scale shorter than but comparable to spin-lattice relaxation., Comment: 19 pages, 5 figures

Divisive Normalization and the Wilson-Cowan equations are influential models of neural interaction and saturation [Carandini and Heeger Nat.Rev.Neurosci. 2012; Wilson and Cowan Kybernetik 1973]. However, they have not been analytically related yet. In this work we show that Divisive Normalization can be obtained from the Wilson-Cowan model. Specifically, assuming that Divisive Normalization is the steady state solution of the Wilson-Cowan differential equation, we find that the kernel that controls neural interactions in Divisive Normalization depends on the Wilson-Cowan kernel but also has a signal-dependent contribution. A standard stability analysis of a Wilson-Cowan model with the parameters obtained from our relation shows that the Divisive Normalization solution is a stable node. This stability demonstrates the consistency of our steady state assumption. The proposed theory provides a physiological foundation (a relation to a dynamical network with fixed wiring among neurons) for the functional suggestions that have been done on the need of signal-dependent Divisive Normalization [e.g. in Coen-Cagli et al., PLoS Comp.Biol. 2012]. Moreover, this theory explains the modifications that had to be introduced ad-hoc in Gaussian kernels of Divisive Normalization in [Martinez et al. Front. Neurosci. 2019] to reproduce contrast responses. The proposed relation implies that the Wilson-Cowan dynamics also reproduces visual masking and subjective image distortion metrics, which up to now had been mainly explained via Divisive Normalization. Finally, this relation allows to apply to Divisive Normalization the methods which up to now had been developed for dynamical systems such as Wilson-Cowan networks., Comment: In press at the Journal of Nonlinear Science (to appear in 2024)

Measuring the eye's mechanical properties in vivo and with minimally invasive techniques can be the key for individualized solutions to a number of eye pathologies. The development of such techniques largely relies on a computational modelling of the eyeball and, it optimally requires the synergic interplay between experimentation and numerical simulation. In Astrophysics and Geophysics the remote measurement of structural properties of the systems of their realm is performed on the basis of (helio-)seismic techniques. As a biomechanical system, the eyeball possesses normal vibrational modes encompassing rich information about its structure and mechanical properties. However, the integral analysis of the eyeball vibrational modes has not been performed yet. Here we develop a new finite difference method to compute both the spheroidal and, specially, the toroidal eigenfrequencies of the human eye. Using this numerical model, we show that the vibrational eigenfrequencies of the human eye fall in the interval 100 Hz - 10 MHz. We find that compressible vibrational modes may release a trace on high frequency changes of the intraocular pressure, while incompressible normal modes could be registered analyzing the scattering pattern that the motions of the vitreous humour leave on the retina. Existing contact lenses with embebed devices operating at high sampling frequency could be used to register the microfluctuations of the eyeball shape we obtain. We advance that an inverse problem to obtain the mechanical properties of a given eye (e.g., Young's modulus, Poisson ratio) measuring its normal frequencies is doable. These measurements can be done using non-invasive techniques, opening very interesting perspectives to estimate the mechanical properties of eyes in vivo. Future research might relate various ocular pathologies with anomalies in measured vibrational frequencies of the eye., Comment: Published in PLoS ONE as Open Access Research Article. 17 pages, 5 color figures

Cosmic rays originating from extraterrestrial sources are permanently arriving at Earth atmosphere, where they produce up to billions of secondary particles. The analysis of the secondary particles reaching to the surface of the Earth may provide a very valuable information about the Sun activity, changes in the geomagnetic field and the atmosphere, among others. In this article, we present the first preliminary results of the analysis of the cosmic rays measured with a high resolution tracking detector, TRAGALDABAS, located at the Univ. of Santiago de Compostela, in Spain., Comment: XXV ECRS 2016 Proceedings - eConf TBA

We present in this paper an application which automatically generates textual short-term weather forecasts for every municipality in Galicia (NW Spain), using the real data provided by the Galician Meteorology Agency (MeteoGalicia). This solution combines in an innovative way computing with perceptions techniques and strategies for linguistic description of data together with a natural language generation (NLG) system. The application, named GALiWeather, extracts relevant information from weather forecast input data and encodes it into intermediate descriptions using linguistic variables and temporal references. These descriptions are later translated into natural language texts by the natural language generation system. The obtained forecast results have been thoroughly validated by an expert meteorologist from MeteoGalicia using a quality assessment methodology which covers two key dimensions of a text: the accuracy of its content and the correctness of its form. Following this validation GALiWeather will be released as a real service offering custom forecasts for a wide public., Comment: 13 pages, 20 figures, IEEE Transactions on Fuzzy Systems, 2014