Association of Rhinitis With Asthma Prevalence and Severity

Multicenter study[Abstract] Asthma and rhinitis often co-exist in the same patient. Although some authors observed a higher prevalence and/or greater severity of asthma in patients with rhinitis, this view is not homogeneous and the debate continues. The aim of our study is to describe the prevalence of rhinitis in children and adolescents and to analyse their relationship with the prevalence of asthma. A multicentre study was conducted using the methodology of the International Study of Asthma and Allergies in Childhood (ISAAC). The target population of the study was all those school children aged 6-7 and 13-14 years from 6 of the main health catchment areas of Galicia (1.9 million inhabitants). The schools required were randomly selected, and all children in the targeted age ranges were included. Multiple logistic regression was used to obtain adjusted prevalence odds ratios (OR) between asthma symptoms of the schoolchildren and rhinitis prevalence. The results were adjusted for parental smoking habits, maternal education level, cat and dog exposure, and obesity. A total of 21,420 valid questionnaires were finally obtained. Rhinitis was associated with a significant increase in the prevalence of asthma in both age groups. The highest OR were 11.375 for exercise induced asthma (EIA) for children with recent rhinoconjunctivitis and 9.807 for children with recent rhinitis in 6-7 years old group. The prevalence OR's are higher in EIA and severe asthmatics. Rhinitis in children and adolescents is associated with a higher prevalence and severity of asthma.This work was funded by the Maria Jose Jove Foundatio

Cross‐sectional study about impact of parental smoking on rhinitis symptoms in children

[Abstract] Objective. Assess the prevalence of rhinitis and exposure to environmental tobacco smoke (ETS) of children in our community and its relationship with symptoms of rhinitis Methods (design, setting, participants, main outcome measures). Cross‐sectional study using questionnaire on rhinitis of the International Study of Asthma and Allergies in Childhood, in children (6‐7 years) and adolescents (13‐14 years). Categories: “rhinitis ever”, “recent rhinitis”, “recent rhinoconjunctivitis”, “severe rhinoconjunctivitis”. Parental smoking: (i) neither parent smokes; (ii) only the mother smokes; (iii) only the father smokes; and (iv) both parents smoke. Odds ratio of the prevalence of symptoms of rhinitis according to ETS exposure was calculated using logistic regression. Results. 10 690 children and 10 730 adolescents. The prevalence of “rhinitis ever” in children: 29.4%, “recent rhinitis” 24%, “recent rhinoconjunctivitis” 11.5% and “severe rhinoconjunctivitis” 0.1%. In adolescents: 46.2%, 34.5%, 16.2% and 0.2%, respectively. Environmental tobacco smoke exposure in the home occurred in 51% of cases. Parental smoking was associated with a higher prevalence of forms of rhinitis in adolescents when only the mother was a smoker. In children when both parents were smokers. Conclusion. Rhinitis is highly prevalent in our community. Environmental tobacco smoke exposure is still very common. The relationship between ETS and rhinitis symptoms in children of this community is not as robust as that found for asthma

Tonality estimation in electronic dance music: a computational and musically informed examination

This dissertation revolves around the task of computational key estimation in electronic dance music, upon which we perform three interrelated operations. First, we attempt to detect possible misconceptions within the task, which is typically accomplished with a tonal vocabulary overly centred in Western classical tonality, reduced to a binary major-minor model which might not accomodate popular music styles. Second, we present a study of tonal practises in electronic dance music, developed hand in hand with the curation of a corpus of over 2,000 audio excerpts, including multiple subgenres and degrees of complexity. Based on this corpus, we propose the creation of more open-ended key labels, accounting for other modal practises and ambivalent tonal configurations. Last, we describe our own key finding methods, adapting existing models to the musical idiosyncrasies and tonal distributions of electronic dance music, with new statistical key profiles derived from the newly created corpus.Aquesta tesi doctoral versa sobre anàlisi computacional de tonalitat en música electrònica de ball. El nostre estudi es concentra en tres operacions fonamentals. Primer, intentem assenyalar possibles equívocs dins de la pròpia tasca, que normalment es desenvolupa sobre un vocabulari tonal extremadament centrat en el llenguatge de la música clàssica europea, reduït a un model binari major-menor que podria no acomodar fàcilment estils de música popular. Seguidament, presentem un estudi de pràctiques tonals en música electrònica de ball, efectuat en paral·lel a la recol·lecció i anàlisi d'un corpus de més de 2.000 fragments de música electrònica, incloent diversos subgèneres i graus de complexitat tonal. Basat en aquest corpus, suggerim la creació d'etiquetes tonals més obertes, que incloguin pràctiques modals així com configuracions tonals ambigües. Finalment, descrivim el nostre sistema d'extracció automàtica de tonalitat, adaptant models existents a les particularitats de la música electrònica de ball, amb la creació de distribucions tonals específiques a partir d'anàlisis estadístiques del recentment creat corpus.Esta tesis doctoral versa sobre análisis computacional de tonalidad en música electrónica de baile. Nuestro estudio se concentra en tres operaciones fundamentales. Primero, intentamos señalar posibles equívocos dentro de la propia tarea, que normalmente se desarrolla sobre un vocabulario tonal extremadamente centrado en el lenguaje de la música clásica europea, reducido a un modelo binario mayor-menor que podría no acomodar fácilmente estilos de música popular. Seguidamente, presentamos un estudio de prácticas tonales en música electrónica de baile, efectuado en paralelo a la recolección y análisis de un corpus de más de 2.000 fragmentos de música electrónica, incluyendo varios subgéneros y grados de complejidad tonal. Basado en dicho corpus, sugerimos la creación de etiquetas tonales más abiertas, que incluyan prácticas modales así como configuraciones tonales ambiguas. Por último, describimos nuestro sistema de extracción automática de tonalidad, adaptando modelos existentes a las particularidades de la música electrónica de baile, con la creación de distribuciones tonales específicas a partir de análisis estadísticos del recién creado corpus

The House Harmonic Filler: interactive exploration of chord sequences by means of an intuitive representation

Comunicació presentada a: Third International Conference on Technologies for Music Notation and Representation (TENOR) celebrat el 25 i 26 de maig de 2017 a A Coruña, Espanya.In this paper we present an interactive two-dimensional representation of musical chord progressions, integrated into a computer program that generates house music harmonic loops in MIDI format, based on a user’s input. Our aim is to encapsulate relevant tonal information and display it in ways that are easy to understand for novices and untrained musicians, facilitating the creative exploration of musical ideas. We briefly reference previous work on tonal visualisation and interaction, and introduce some measures of tonal properties from the literature. We then present our system and describe the two-dimensional harmonic map, before discussing its outcomes and shortcomings, pointing at future lines of research in the conclusions.This research has been partially supported by the EUfunded GiantSteps project (FP7-ICT-2013-10 grant agreement number 610591)

The House Harmonic Filler: interactive exploration of chord sequences by means of an intuitive representation

Comunicació presentada a: Third International Conference on Technologies for Music Notation and Representation (TENOR) celebrat el 25 i 26 de maig de 2017 a A Coruña, Espanya.In this paper we present an interactive two-dimensional representation of musical chord progressions, integrated into a computer program that generates house music harmonic loops in MIDI format, based on a user’s input. Our aim is to encapsulate relevant tonal information and display it in ways that are easy to understand for novices and untrained musicians, facilitating the creative exploration of musical ideas. We briefly reference previous work on tonal visualisation and interaction, and introduce some measures of tonal properties from the literature. We then present our system and describe the two-dimensional harmonic map, before discussing its outcomes and shortcomings, pointing at future lines of research in the conclusions.This research has been partially supported by the EUfunded GiantSteps project (FP7-ICT-2013-10 grant agreement number 610591)

A multi-profile method for key estimation in EDM

Comunicació presentada a: 2017 AES International Conference on Semantic Audio, celebrada del 22 al 24 de juny de 2017 a Erlangen, Alemanya.Key detection in electronic dance music is important for producers and DJ’s who want to mix their tracks harmonically or organise their music collection by tonal content. In this paper, we present an algorithm that improves the performance of an existing method by introducing a system of multiple profiles, addressing difficult minor tracks as well as possibly amodal ones. After the explanation of our method, we use three independent datasets of electronic dance music to evaluate its performance, comparing it to other academic algorithms and commercially available solutions.This research has been partially supported the EUfunded GiantSteps project (FP7-ICT-2013-10 grant agreement number 610591)

Drumming with style: from user needs to a working prototype

Comunicació presentada a la NIME 2016, International Conference on New Interfaces for Musical Expression, celebrada els dies 11 a 15 de juliol de 2016 a Brisbane, Austràlia.This paper documents and discusses the process of developing a generative drumming agent built from the results of an extensive survey carried out with electronic music producers. Following the techniques of user-centered interaction design, an international group of beat producers was reviewed on the possibility of using AI algorithms to help them in the beat production work-flow. The results of these tests were used as design requirements for constructing a system that would indeed perform some tasks alongside the producer. The first results of this working prototype, a stylistic drum generator that creates new rhythmic patterns after being trained with a collection of drum tracks, are presented with a description of the system. Further stages of development and potential algorithms are also discussed.This research has been partially supported by the EU funded GiantSteps project (FP7-ICT-2013-10 Grant agreement nr 610591)

Key estimation in electronic dance music

Comunicació presentada a la 38th European Conference on IR Research (ECIR 2016), celebrada els dies 20 a 23 de març de 2016 a Pàdua, Itàlia.In this paper we study key estimation in electronic dance music, an umbrella term referring to a variety of electronic music subgenres intended for dancing at nightclubs and raves. We start by defining notions of tonality and key before outlining the basic architecture of a template-based key estimation method. Then, we report on the tonal characteristics of electronic dance music, in order to infer possible modifications of the method described. We create new key profiles combining these observations with corpus analysis, and add two pre-processing stages to the basic algorithm. We conclude by comparing our profiles to existing ones, and testing our modifications on independent datasets of pop and electronic dance music, observing interesting improvements in the performance or our algorithms, and suggesting paths for future research.This research has been partially supported by the EU-funded GiantSteps project (FP7-ICT-2013-10. Grant agreement number 610591)

Drumming with style: from user needs to a working prototype

Comunicació presentada a la NIME 2016, International Conference on New Interfaces for Musical Expression, celebrada els dies 11 a 15 de juliol de 2016 a Brisbane, Austràlia.This paper documents and discusses the process of developing a generative drumming agent built from the results of an extensive survey carried out with electronic music producers. Following the techniques of user-centered interaction design, an international group of beat producers was reviewed on the possibility of using AI algorithms to help them in the beat production work-flow. The results of these tests were used as design requirements for constructing a system that would indeed perform some tasks alongside the producer. The first results of this working prototype, a stylistic drum generator that creates new rhythmic patterns after being trained with a collection of drum tracks, are presented with a description of the system. Further stages of development and potential algorithms are also discussed.This research has been partially supported by the EU funded GiantSteps project (FP7-ICT-2013-10 Grant agreement nr 610591)

Key estimation in electronic dance music

Comunicació presentada a la 38th European Conference on IR Research (ECIR 2016), celebrada els dies 20 a 23 de març de 2016 a Pàdua, Itàlia.In this paper we study key estimation in electronic dance music, an umbrella term referring to a variety of electronic music subgenres intended for dancing at nightclubs and raves. We start by defining notions of tonality and key before outlining the basic architecture of a template-based key estimation method. Then, we report on the tonal characteristics of electronic dance music, in order to infer possible modifications of the method described. We create new key profiles combining these observations with corpus analysis, and add two pre-processing stages to the basic algorithm. We conclude by comparing our profiles to existing ones, and testing our modifications on independent datasets of pop and electronic dance music, observing interesting improvements in the performance or our algorithms, and suggesting paths for future research.This research has been partially supported by the EU-funded GiantSteps project (FP7-ICT-2013-10. Grant agreement number 610591)