Non-linear HRV analysis to quantify the effects of intermittent hypoxia using an OSA rat model

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksIn this paper, a non-linear HRV analysis was performed to assess fragmentation signatures observed in heartbeat time series after intermittent hypoxia (IH). Three markers quantifying short-term fragmentation levels, PIP, IALS and PSS, were evaluated on R-R interval series obtained in a rat model of recurrent apnea. Through airway obstructions, apnea episodes were periodically simulated in six anesthetized Sprague-Dawley rats. The number of apnea events per hour (AHI index) was varied during the first half of the experiment while apnea episodes lasted 15 s. For the second part, apnea episodes lasted 5, 10 or 15 s, but the AHI index was fixed. Recurrent apnea was repeated for 15-min time intervals in all cases, alternating with basal periods of the same duration. The fragmentation markers were evaluated in segments of 5 minutes, selected at the beginning and end of the experiment. The impact of the heart and breathing rates (HR and BR, respectively) on the parameter estimates was also investigated. The results obtained show a significant increase (from 5 to 10%, p 0.9) between these markers and BR, as well as with the ratio given by HR/BR. Although fragmentation may be impacted by IH, we found that it is highly dependent on HR and BR values and thus, they should be considered during its calculation or used to normalize the fragmentation estimatesPeer ReviewedPostprint (published version

Operator Spectrum and Exact Exponents of the Fully Packed Loop Model

We develop a Coulomb gas description of the critical fluctuations in the fully packed loop model on the honeycomb lattice. We identify the complete operator spectrum of this model in terms of electric and magnetic {\em vector}-charges, and we calculate the scaling dimensions of these operators exactly. We also study the geometrical properties of loops in this model, and we derive exact results for the fractal dimension and the loop size distribution function. A review of the many different representations of this model that have recently appeared in the literature, is given.Comment: 17 pages latex, 3 postscript figures, IOP style files include

Sobre les traduccions de novel·la policíaca

L'article analitza el model de llengua de la novel·la policíaca traduïda basant-se en títols de dues de les col·leccions més representatives del gènere, «La Cua de Palla» i «Col·lecció Nova Terra. Sèrie Agata Christie». A partir d'un seguit d'exemples, l'autor detalla calcs i solucionsartificioses que troba que no es corresponen amb la llengua viva genuïna.This paper analyses the language used in Catalan translations from crime fiction by studying two of its main collections, La Cua de Palla and Col·lecció Nova Terra. Sèrie Agata Christie. A series of examples are given to explain loan translations and usages that are not appropriatein Catalan

Entrevista a Montserrat Jané, Técnica del Centro de Patentes de la Universidad de Barcelona

En este documento se presenta la entrevista a Montserrat Jané, técnica de patentes del Centro de Patentes de la Universidad de Barcelona, que se hizo en Mayo del 2007 para la publicación QUIC & VECT. En la entrevista, Montserrat Jané habló de las tareas que se llevan a cabo en el centro, del personal que trabaja, de sus perfiles profesionales, de cómo se estructura el centro, y de las relaciones del centro con otras agencias, organismos, y entidades en el ámbito público y privado, así como de los flujos de información y los procedimientos que se hacen dentro del ámbito de las patentes

Performance evaluation of the Hilbert–Huang transform for respiratory sound analysis and its application to continuous adventitious sound characterization

© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The use of the Hilbert–Huang transform in the analysis of biomedical signals has increased during the past few years, but its use for respiratory sound (RS) analysis is still limited. The technique includes two steps: empirical mode decomposition (EMD) and instantaneous frequency (IF) estimation. Although the mode mixing (MM) problem of EMD has been widely discussed, this technique continues to be used in many RS analysis algorithms. In this study, we analyzed the MM effect in RS signals recorded from 30 asthmatic patients, and studied the performance of ensemble EMD (EEMD) and noise-assisted multivariate EMD (NA-MEMD) as means for preventing this effect. We propose quantitative parameters for measuring the size, reduction of MM, and residual noise level of each method. These parameters showed that EEMD is a good solution for MM, thus outperforming NA-MEMD. After testing different IF estimators, we propose Kay¿s method to calculate an EEMD-Kay-based Hilbert spectrum that offers high energy concentrations and high time and high frequency resolutions. We also propose an algorithm for the automatic characterization of continuous adventitious sounds (CAS). The tests performed showed that the proposed EEMD-Kay-based Hilbert spectrum makes it possible to determine CAS more precisely than other conventional time-frequency techniques.Postprint (author's final draft