Disturbance of patterns in EEG spatial correlations

In the study of epileptic seizure or epileptic attack, a strategy receiving increased attention is the use of nonlinear methods in detecting the earliest dynamical changes preceding seizures. The methods usually consider continuous EEG measurements from epileptic patients to predict and ultimately control seizures. As part of the inquiry into the structure of the dynamics of the brain activity we investigate changes amongst the EEG signals being recorded at different locations on the scalp. Patterns emerging from the correlation coefficients between the EEG channels seem to be disturbed with the approach of a crisis. Results show that those patterns are often disturbed 10 to 15 minutes before the beginning of crises, helping to detect the earliest dynamical changes preceding seizures.EEG spatial correlations; epileptic seizures

Complex evolution of the electronic structure from polycrystalline to monocrystalline graphene: generation of a new Dirac point

First principles calculations, employed to address the properties of polycrystalline graphene, indicate that the electronic structure of tilt grain boundaries in this system displays a rather complex evolution towards graphene bulk, as the tilt angle decreases, with the generation of a new Dirac point at the Fermi level, and an anisotropic Dirac cone of low energy excitations. Moreover, the usual Dirac point at the {\bf K} point falls below the Fermi level, and rises towards it as the tilt angle decreases. Further, our calculations indicate that the grain-boundary formation energy behaves non-monotonically with the tilt angle, due to a change in the the spatial distribution and relative contributions of the bond-stretching and bond-bending deformations associated with the formation of the defect.Comment: 4 pages (+ a few references on 5th page). Contains text (.tex) file + 4 figures + pdf fil

Gravity with extra dimensions and dark matter interpretation: A straightforward approach

Any connection between dark matter and extra dimensions can be cognizably evinced from the associated effective energy-momentum tensor. In order to investigate and test such relationship, a higher dimensional spacetime endowed with a factorizable general metric is regarded to derive a general expression for the stress tensor -- from the Einstein-Hilbert action -- and to elicit the effective gravitational potential. A particular construction for the case of six dimensions is provided, and it is forthwith revealed that the missing mass phenomenon may be explained, irrespective of the dark matter existence. Moreover, the existence of extra dimensions in the universe accrues the possibility of a straightforward mechanism for such explanation. A configuration which density profile coincides with the Newtonian potential for spiral galaxies is constructed, from a 4-dimensional isotropic metric plus extra-dimensional components. A Miyamoto-Nagai \emph{ansatz} is used to solve Einstein equations. The stable rotation curves associated to such system are computed, in full compliance to the observational data, without fitting techniques. The density profiles are reconstructed and compared to that ones obtained from the Newtonian potential.Comment: 13 pages, 6 figure

Automatic offensive language detection from Twitter data using machine learning and feature selection of metadata

The popularity of social networks has only increased in recent years. In theory, the use of social media was proposed so we could share our views online, keep in contact with loved ones or share good moments of life. However, the reality is not so perfect, so you have people sharing hate speech-related messages, or using it to bully specific individuals, for instance, or even creating robots where their only goal is to target specific situations or people. Identifying who wrote such text is not easy and there are several possible ways of doing it, such as using natural language processing or machine learning algorithms that can investigate and perform predictions using the metadata associated with it. In this work, we present an initial investigation of which are the best machine learning techniques to detect offensive language in tweets. After an analysis of the current trend in the literature about the recent text classification techniques, we have selected Linear SVM and Naive Bayes algorithms for our initial tests. For the preprocessing of data, we have used different techniques for attribute selection that will be justified in the literature section. After our experiments, we have obtained 92% of accuracy and 95% of recall to detect offensive language with Naive Bayes and 90% of accuracy and 92% of recall with Linear SVM. From our understanding, these results overcome our related literature and are a good indicative of the importance of the data description approach we have used

Zero-temperature TAP equations for the Ghatak-Sherrington model

The zero-temperature TAP equations for the spin-1 Ghatak-Sherrington model are investigated. The spin-glass energy density (ground state) is determined as a function of the anisotropy crystal field $D$ for a large number of spins. This allows us to locate a first-order transition between the spin-glass and paramagnetic phases within a good accuracy. The total number of solutions is also determined as a function of $D$.Comment: 11 pages, 2 ps figures include

Automatic Test Generation for Space

The European Space Agency (ESA) uses an engine to perform tests in the Ground Segment infrastructure, specially the Operational Simulator. This engine uses many different tools to ensure the development of regression testing infrastructure and these tests perform black-box testing to the C++ simulator implementation. VST (VisionSpace Technologies) is one of the companies that provides these services to ESA and they need a tool to infer automatically tests from the existing C++ code, instead of writing manually scripts to perform tests. With this motivation in mind, this paper explores automatic testing approaches and tools in order to propose a system that satisfies VST needs

Effects of Random Biquadratic Couplings in a Spin-1 Spin-Glass Model

A spin-1 model, appropriated to study the competition between bilinear (J_{ij}S_{i}S_{j}) and biquadratic (K_{ij}S_{i}^{2}S_{j}^{2}) random interactions, both of them with zero mean, is investigated. The interactions are infinite-ranged and the replica method is employed. Within the replica-symmetric assumption, the system presents two phases, namely, paramagnetic and spin-glass, separated by a continuous transition line. The stability analysis of the replica-symmetric solution yields, besides the usual instability associated with the spin-glass ordering, a new phase due to the random biquadratic couplings between the spins.Comment: 16 pages plus 2 ps figure