Spontaneous symmetry breaking and frustrated phases.

We study a system involving a single quantum degree of freedom per site of the lattice interacting with a few neighbors (up to second neighbors), with the interactions chosen so as to produce frustration. At zero temperature, this system undergoes several quantum phase transitions from both gapped to gapless and gapless to gapless phases, providing a very rich phase structure with disordered, homogeneous, and modulated ordered phases meeting in a quantum Lifshitz point. The gapless phases spontaneously break spatial lattice translations as well as internal symmetries of the form U(1)^{N_{c}}, where N_{c} is the number of independent pitch vectors that arise in the homogeneous and modulated ordered phases. We carry out a detailed analysis of the quantum critical behavior, discussing the mechanism leading to the phase transitions. We also discuss a proper characterization of all the gapless phases as well as the nature of the Goldstone excitations. We study the behavior of the correlation functions and identify regions in the phase diagram where the system exhibits generalized symmetries such as polynomial shift symmetry. This type of symmetry plays an important role in the so-called fractonic phase, which is an exotic form of matter recently discovered.

Task-Based Automatic Evaluation of People with Intellectual Disabilities Performed on a Robotic Table Soccer.

This paper is concerned with the automatic evaluation of selected tasks performed by people with intellectual Disabilities. According to the International Classification of Functioning, Disability and Health (ICF) system, subjects must be divided into two groups: group with no difficulty (N) and group with difficulty (D) being this classification based on performances obtained in a conventional table (CT) soccer. Three tasks, with different levels of difficulty, were proposed for performance evaluation. Experimental results were obtained on the basis of the task execution in both a CT and a robotics table (RT) soccer. All participants were able to perform tasks with the joystick on the RT soccer and the automatic evaluation system identified differences in reaction times with and without red color flag in the participants, on RT soccer. One of the tasks was completely performed by all the participants by using the RT soccer.

Duality Between 3D Massive Thirring and Maxwell-Chern-Simons Models from 2D Bosonization.

Bosonization techniques are important nonperturbative tools in quantum field theory. In three dimensions they possess interesting connections to topologically ordered systems and ultimately have driven the observation of an impressive web of dualities. In this work, we use the quantum wires formalism to show how the fermion-boson mapping relating the low-energy regime of the massive Thirring model in three spacetime dimensions with the Maxwell-Chern-Simons model can be obtained from the exact bosonization in two dimensions.

An adapted double threshold protocol for spastic muscles.

The onset of muscle contraction has been an important element in the understanding of human motor control system as well as in the development of medical devices. This task is problematic in the study of spasticity using surface Electromyography (sEMG). In fact, spasticity is characterized by involuntary muscle contractions that can be seen as both, a non-stationary background if they are weak or a severe non-stationary EMG signal if they are strong. In other hand, these sEMG signals present a very low signal to noise ratio, beyond the added noise that contaminates this signal. The double threshold protocol presumes non-stationary muscle activation under a stationary environment which does not accommodate non-stationary background conditions. Apart from that the Shewhart protocol which makes part of the Double Threshold Protocol (DTP) presumes an initial segment containing only noise which can't be guaranteed under spastic conditions. These are the main causes of failures of state of the art approaches when applied to sEMG spastic muscles. This paper proposes dealing with these constraints by adapting the first threshold to the noise conditions via Signal to Noise Ratio (SNR) estimation, which depends on the severity of the disease. The main idea is tuning the first threshold to low SNR conditions since it is where the DTP most degrades. This tuning is done in sEMG artificially contaminated at different SNRs where the multiple of standard deviation is heuristically determined based on experimentation. Noise is estimated in low energy segments instead of in an initial segment that can be contaminated by involuntary muscle contractions. The proposed algorithm was tested in sEMG signals from the Biceps Braquialis of 13 healthy individuals and in 9315 signals recorded in 23 subjects with spasticity. Improvements of more than 23% were obtained when compared with the classical DTP in moderate to severe spasticity.

Quantum spherical spins with local symmetry.

We construct a quantum system of spherical spins with a continuous local symmetry. The model is exactly soluble in the thermodynamic limit and exhibits a number of interesting properties. We show that the local symmetry is spontaneously broken at finite as well as zero temperatures, implying the existence of classical and quantum phase transitions with a nontrivial critical behavior. The dynamical generation of gauge fields and the equivalence with the CP((N-1)) model in the limit N→∞ are investigated. The dynamical generation of gauge fields is a consequence of the restoration of the local symmetry.

Supersymmetric extension of the quantum spherical model.

In this work, we present a supersymmetric extension of the quantum spherical model, both in components and also in the superspace formalisms. We find the solution for short- and long-range interactions through the imaginary time formalism path integral approach. The existence of critical points (classical and quantum) is analyzed and the corresponding critical dimensions are determined.

Automatic continuous ECG monitoring system for over-drug detection in Brugada Syndrome.

This paper is concerned with the automatic control of drug administration in patients suffering from Brugada Syndrome (BS). Drugs such as flecainide, procainamide, ajmaline and pilsicainide should be administrated under carefully controlled electrocardiogram (ECG) monitoring given that the treatment must be stopped if some ECG disturbing conditions appear. These conditions are, among others the development of premature ventricular contraction (PVC), atrial fibrillation (AF) and the widening of the QRS wave. The proposed system can detect these abnormalities by using a pattern recognition approach based on Hidden Markov Models (HMM) with features extracted from three scales of the Wavelet Transform (WT). Performances higher than 98% were reached regarding the classification of normal and abnormal pulses. The system was trained and tested mainly in data from the standard MIT-BIH arrhythmia database.

ECG Data-Acquisition and classification system by using wavelet-domain Hidden Markov Models.

This article is concerned with the classification of ECG pulses by using state of the art Continuous Density Hidden Markov Models (CDHMM's). The ECG signal is simultaneously observed at three different level of focus by means of the Wavelet Transform (WT). The types of beat being selected are normal (N), premature ventricular contraction (V) which is often precursor of ventricular arrhythmia, two of the most common class of supra-ventricular arrhythmia (S), named atrial fibrillation (AF), atrial flutter (AFL), and normal rhythm (N). Both MLII and V1 derivations are used. Run time classification errors can be detected at the decoding stage if the classification of each derivation is different. These pulses are selected for a posterior physician analysis. Experimental results were obtained in real data from MIT-BIH Arrhythmia Database and also in data acquired from a developed low-cost Data-Acquisition System.

Cardiac arrhythmia classification using wavelets and Hidden Markov Models - a comparative approach.

This paper reports a comparative study of feature extraction methods regarding cardiac arrhythmia classification, using state of the art Hidden Markov Models. The types of beat being selected are normal (N), premature ventricular contraction (V) which is often precursor of ventricular arrhythmia, two of the most common class of supra-ventricular arrhythmia (S), named atrial fibrillation (AF), atrial flutter (AFL), and normal rhythm (N). The considered feature extraction methods are the standard linear segmentation and wavelet based feature extraction. The followed approach regarding wavelets was to observe simultaneously the signal at different scales, which means with different level of focus. Experimental results are obtained in real data from MIT-BIH Arrhythmia Database and show that wavelet transform outperforms the conventional standard linear segmentation.