Backscatter Transponder Based on Frequency Selective Surface for FMCW Radar Applications

This paper describes an actively-controlled frequency selective surface (FSS) to implement a backscatter transponder. The FSS is composed by dipoles loaded with switching PIN diodes. The transponder exploits the change in the radar cross section (RCS) of the FSS with the bias of the diodes to modulate the backscattered response of the tag to the FMCW radar. The basic operation theory of the system is explained here. An experimental setup based on a commercial X-band FMCW radar working as a reader is proposed to measure the transponders. The transponder response can be distinguished from the interference of non-modulated clutter, modulating the transponder’s RCS. Some FSS with different number of dipoles are studied, as a proof of concept. Experimental results at several distances are provided

Energy Analysis of Received Signal Strength Localization in Wireless Sensor Networks

This paper presents the investigation of energy demands during localization of wireless nodes in ad-hoc networks. We focus on the method based on the received signal strength (RSS) to estimate the distances between the nodes. To deal with the uncertainty of this technique, statistical methods are used. It implies more measurement samples to be taken and consequently more energy to be spent. Therefore, we investigate the accuracy of localization and the consumed energy in the relation to the number of measurement samples. The experimental measurements were conducted with IRIS sensor motes and their results related to the proposed energy model. The results show that the expended energy is not related linearly to the localization error. First, improvement of the accuracy rises fast with more measurement samples. Then, adding more samples, the accuracy increase is moderate, which means that the marginal energy cost of the additional improvement is higher

Classical and quantum ergodicity on orbifolds

We extend to orbifolds classical results on quantum ergodicity due to Shnirelman, Colin de Verdi\`ere and Zelditch, proving that, for any positive, first-order self-adjoint elliptic pseudodifferential operator P on a compact orbifold X with positive principal symbol p, ergodicity of the Hamiltonian flow of p implies quantum ergodicity for the operator P. We also prove ergodicity of the geodesic flow on a compact Riemannian orbifold of negative sectional curvature.Comment: 14 page

Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias

In order to determine the site of origin (SOO) in outflow tract ventricular arrhythmias (OTVAs) before an ablation procedure, several algorithms based on manual identification of electrocardiogram (ECG) features, have been developed. However, the reported accuracy decreases when tested with different datasets. Machine learning algorithms can automatize the process and improve generalization, but their performance is hampered by the lack of large enough OTVA databases. We propose the use of detailed electrophysiological simulations of OTVAs to train a machine learning classification model to predict the ventricular origin of the SOO of ectopic beats. We generated a synthetic database of 12-lead ECGs (2,496 signals) by running multiple simulations from the most typical OTVA SOO in 16 patient-specific geometries. Two types of input data were considered in the classification, raw and feature ECG signals. From the simulated raw 12-lead ECG, we analyzed the contribution of each lead in the predictions, keeping the best ones for the training process. For feature-based analysis, we used entropy-based methods to rank the obtained features. A cross-validation process was included to evaluate the machine learning model. Following, two clinical OTVA databases from different hospitals, including ECGs from 365 patients, were used as test-sets to assess the generalization of the proposed approach. The results show that V2 was the best lead for classification. Prediction of the SOO in OTVA, using both raw signals or features for classification, presented high accuracy values (>0.96). Generalization of the network trained on simulated data was good for both patient datasets (accuracy of 0.86 and 0.84, respectively) and presented better values than using exclusively real ECGs for classification (accuracy of 0.84 and 0.76 for each dataset). The use of simulated ECG data for training machine learning-based classification algorithms is critical to obtain good SOO predictions in OTVA compared to real data alone. The fast implementation and generalization of the proposed methodology may contribute towards its application to a clinical routine

Voz del anciano

La vejez es en sí un fenómeno biológico que no implica necesariamente una enfermedad. Los fenómenos biológicos del envejecimiento se inician en edades muy tempranas y tiene la capacidad de modificarse, preveerse y compensarse. La educación y la preparación para posibles deterioros debe de ser contemplada desde un plano preventivo. En el ser humano la aparición del lenguaje y su vehículo habitual, la voz; representó la posibilidad de aumentar su longevidad. El deterioro vocal del anciano se conoce como presbifonía y en ocasiones interfiere significativamente en la capacidad de comunicación y en la calidad de vida de las personas ancianas. Al considerar la presbifonía o voz senil hay que distinguir dos situaciones clínicas distintas desde el punto de vista conceptual: la disfonía del anciano y la disfonía en el anciano. Se comentan los aspectos del envejecimiento en relación con la voz, la valoración y la caracterización de la voz en el anciano y las estrategias para prevenir el deterioro y tratar los trastornos específicos de la voz en las personas mayores, bien sea desde el punto de vista funcional o rehabilitación o bien mediante cirugía

Combined Area of Left and Right Atria May Outperform Atrial Volumes as a Predictor of Recurrences after Ablation in Patients with Persistent Atrial Fibrillation—A Pilot Study

Background and Objectives: Left atrial (LA) remodelling and dilatation predicts atrial fibrillation (AF) recurrences after catheter ablation. However, whether right atrial (RA) remodelling and dilatation predicts AF recurrences after ablation has not been fully evaluated. Materials and Methods: This is an observational study of 85 consecutive patients (aged 57 ± 9 years; 70 [82%] men) who underwent cardiac magnetic resonance before first catheter ablation for AF (40 [47.1%] persistent AF). Four-chamber cine-sequence was selected to measure LA and RA area, and ventricular end-systolic image phase to obtain atrial 3D volumes. The effect of different variables on event-free survival was investigated using the Cox proportional hazards model. Results: In patients with persistent AF, combined LA and RA area indexed to body surface area (AILA + RA) predicted AF recurrences (HR = 1.08, 95% CI 1.00-1.17, p = 0.048). An AILA + RA cut-off value of 26.7 cm2/m2 had 72% sensitivity and 73% specificity for predicting recurrences in patients with persistent AF. In this group, 65% of patients with AILA + RA > 26.7 cm2/m2 experienced AF recurrence within 2 years of follow-up (median follow-up 11 months), compared to 25% of patients with AILA + RA ≤ 26.7 cm2/m2 (HR 4.28, 95% CI 1.50-12.22; p = 0.007). Indices of LA and RA dilatation did not predict AF recurrences in patients with paroxysmal AF. Atrial 3D volumes did not predict AF recurrences after ablation. Conclusions: In this pilot study, the simple measurement of AILA + RA may predict recurrences after ablation of persistent AF, and may outperform measurements of atrial volumes. In paroxysmal AF, atrial dilatation did not predict recurrences. Further studies on the role of RA and LA remodelling are needed

Vibrato de la voz cantada. Caracterización acústica y bases fisiológicas

El vibrato es uno de los ornamentos más comunes del canto clásico occidental y de la música destinada a aquellos instrumentos que pueden producirlo. El vibrato vocal corresponde físicamente a una modulación periódica sinusoidal de frecuencia fundamental de la fonación. El vibrato hace que la voz suene agradable, viva, excitante, cálida, menos mecánica que aquella que se consigue al emitir un tono plano. Da naturalidad y expresividad al sonido vocal. La mayoría de los cantantes lo consideran un elemento deseable pero no todos son capaces de desarrollarlo. Parece que la aparición del vibrato depende de un nivel técnico determinado. Se revisan las consideraciones históricas, las propiedades físicas, acústicas y aerodinámicas del vibrato. Se establecen hipótesis en lo referente a su origen y se plantean estrategias dirigidas a facilitar su desarrollo y aprendizaje