Attention to the adolescent in primary care centers

Trabajo fin de grado en EnfermeríaIntroducción: La adolescencia se presenta como un periodo singularmente vulnerable en el desarrollo humano. Por ello los profesionales de la salud deben aspirar a una Atención Primaria integral que contemple y actúe en base a las singularidades de este grupo. Objetivo: Conocer las opiniones de adolescentes sobre la atención recibida en Centros de Atención Primaria de Salud. Metodología: Revisión narrativa mediante una búsqueda bibliográfica en las bases de datos Pubmed®, Cinahl®, PsycINFO®, Cochrane Library®, Cuiden®, Scielo® y en revistas especializadas, de estudios publicados entre 2011 y 2018. Los artículos fueron seleccionados en base a criterios de inclusión, exclusión y limitadores. Resultados: Se seleccionaron y analizaron 9 artículos cuyo contenido fue clasificado en tres temáticas: 1) Accesibilidad y utilización de los servicios de Atención Primaria, donde se obtuvieron los datos relacionados con la utilización de este grupo, así como las barreras que limitan el acceso. 2) Relación de los adolescentes con los profesionales de la salud, donde se recogen el respeto, la comunicación y la confianza percibidos por los adolescentes, que influyen en el establecimiento de la relación terapéutica. 3) Problemas o consultas atendidos en los centros de Atención Primaria hacia este grupo. Conclusiones: A pesar de encontrar datos contradictorios y escasos, los adolescentes manifiestan: dificultades a la hora de relacionarse con los profesionales de Atención Primaria, e insatisfacción ante el trato recibido. Refieren además barreras que disminuyen la utilización de los servicios. Los profesionales deben tomar conciencia de sus acciones e identificar las necesidades de este grupo.Background: Adolescence appears as a vulnerable period in human development. Therefore, health professionals should aspire to comprehensive primary care that includes and acts based on the unique characteristics of this group. Purpose: To know the opinions of adolescents about Primary Health Care. Method: A narrative review was conducted using the databases Pubmed®, Cinahl®, PsycINFO®, Cochrane Library®, Cuiden®, Scielo® and specialized journals, searching studies published between 2011 and 2018 Inclusive, exclusive criteria and limiters were established. Articles were selected based on inclusion, exclusion and limiting criteria. Results: There were selected and analyzed 9 articles whose content was classified into three themes: 1) Accessibility and utilization of Primary Care services, where there were obtained data related with the utilization of the adolescents, as well as accessibility barriers that decrease their access. 2) Relationship of adolescents with health professionals, where the respect, the communicative abilities and the confidence perceived by the adolescents were addressed requirements of the therapeutic relationship. 3) Problems or consultations attended in Primary Care Centers towards this group Conclusions: Despite finding contradictory and scarce data, the adolescents state: difficulties when interacting with Primary Care professionals, and dissatisfaction with the treatment received. They also refer to barriers that reduce the use of services. Professionals should be aware of their actions and identify the needs of this grou

Production of Fock Mixtures in Trapped Ions for Motional Metrology

J.C. acknowledges support from Ministerio de Ciencia, Innovación y Universidades (Spain) (“Beatriz Galindo” Fellowship BEAGAL18/00081). D.R. acknowledges support from Junta de Andalucía through the project P18-FR-3432.We present a protocol to produce a class of non-thermal Fock state mixtures in trapped ions. This class of states features a clear metrological advantage with respect to the ground state, thus overcoming the standard quantum limit without the need for full sideband cooling and Fock-state preparation on a narrow electronic transition. The protocol consists in the cyclic repetition of red-sideband, measurement and preparation laser pulses. By means of the Kraus map representation of the protocol, it is possible to relate the length of the red sideband pulses to the specific class of states that can be generated. With the help of numerical simulations, we analyze the parametric regime where these states can be reliably reproduced.Ministerio de Ciencia, Innovación y Universidades (Spain) BEAGAL18/00081Junta de Andalucía P18-FR-343

Medical data wrangling with sequential variational autoencoders

Medical data sets are usually corrupted by noise and missing data. These missing patterns are commonly assumed to be completely random, but in medical scenarios, the reality is that these patterns occur in bursts due to sensors that are off for some time or data collected in a misaligned uneven fashion, among other causes. This paper proposes to model medical data records with heterogeneous data types and bursty missing data using sequential variational autoencoders (VAEs). In particular, we propose a new methodology, the Shi-VAE, which extends the capabilities of VAEs to sequential streams of data with missing observations. We compare our model against state-of-theart solutions in an intensive care unit database (ICU) and a dataset of passive human monitoring. Furthermore, we find that standard error metrics such as RMSE are not conclusive enough to assess temporal models and include in our analysis the cross-correlation between the ground truth nd the imputed signal. We show that Shi-VAE achieves the best performance in terms of using both metrics, with lower computational complexity than the GP-VAE model, which is the state-of-the-art method for medical records.This work was supported in part by Spanish Government MCI under Grants TEC2017-92552-EXP and RTI2018-099655-B-100, in part by Comunidad de Madrid under Grants IND2017/TIC-7618, IND2018/TIC-9649, IND2020/TIC-17372, and Y2018/TCS-4705, in part by BBVA Foundation under the Deep-DARWiN Project, and in part by the European Union (FEDER) and the European Research Council (ERC) through the European Union's Horizon 2020 research and innovation program under Grant 714161

Simulación numérica de flujos convectivos a altos números de Rayleigh en sistemas pasivos de climatización

El objetivo principal del proyecto es la simulación numérica de los flujos inducidos por convección natural que pueden aparecer en sistemas pasivos de climatización tales como chimeneas solares o paredes “Trombe” junto con la adquisición de conocimientos generales sobre los problemas referidos en la introducción. Se llevará a cabo la simulación sistemática de los flujos en distintas configuraciones y con distintas condiciones de calentamiento, suponiendo la uniformidad de temperatura o de flujo de calor en las paredes verticales. Se intentarán obtener correlaciones sistemáticas del coeficiente de transmisión de calor en función de los parámetros adimensionales relevantes que definen el problema, partiendo de una configuración simplificada siguiendo modelos encontrados en la bibliografía, como los mencionados en el apartado anterior. El estudio de la independencia de los resultados numéricos obtenidos respecto de la malla, y la influencia de la finura del mallado junto a las paredes, constituye un aspecto importante del presente proyecto. En las simulaciones numéricas desarrolladas en el transcurso del presente trabajo utilizaremos el modelo de turbulencia k-ω antes citado, intentando delimitar las condiciones de transición a la turbulencia, y se validará con resultados tanto numéricos como experimentales encontrados en la bibliografía. También se desarrollarán simulaciones laminares que nos servirán para comparar los resultados obtenidos con los de otros autores, valorando el alcance y precisión de los resultados numéricos encontrados en la simulación del régimen turbulento. El proyecto se centrará fundamentalmente en el estudio de los flujos establecidos en chimeneas solares. Se obtendrán correlaciones prácticas para el cálculo del flujo del aire inducido y de la transmisión de calor entre el fluido y las paredes en este tipo de configuraciones. Se intentará conseguir además la optimización geométrica y térmica de dichos sistemas a partir de los resultados numéricos para ayudar al diseño integral de edificios y construcciones industriales climatizadas de forma pasiva. A lo largo de este trabajo se trataran estos temas de la siguiente forma; en el Capítulo 2 se expondrán las características más significativas de los sistemas pasivos de climatización en estudio; en el Capítulo 3 se describen las configuraciones básicas consideradas, el modelo matemático, las condiciones de contorno y el modelo de turbulencia empleado para gran parte de los casos considerados; en el Capítulo 4 se expone el modelo numérico, describiendo de forma breve los algoritmos empleados para la simulación numérica de los problemas planteados; en los Capítulos 5, 6 y 7 se relacionan los resultados obtenidos para distintas configuraciones y condiciones de calentamiento; por último, en el Capítulo 8 se resumen las conclusiones más importantes alcanzadas en este trabajo.Escuela Técnica Superior de Ingeniería Industria

Home detection of freezing of gait using Support Vector Machines through a single waist-worn triaxial accelerometer

Among Parkinson’s disease (PD) symptoms, freezing of gait (FoG) is one of the most debilitating. To assess FoG, current clinical practice mostly employs repeated evaluations over weeks and months based on questionnaires, which may not accurately map the severity of this symptom. The use of a non-invasive system to monitor the activities of daily living (ADL) and the PD symptoms experienced by patients throughout the day could provide a more accurate and objective evaluation of FoG in order to better understand the evolution of the disease and allow for a more informed decision-making process in making adjustments to the patient’s treatment plan. This paper presents a new algorithm to detect FoG with a machine learning approach based on Support Vector Machines (SVM) and a single tri-axial accelerometer worn at the waist. The method is evaluated through the acceleration signals in an outpatient setting gathered from 21 PD patients at their home and evaluated under two different conditions: first, a generic model is tested by using a leave-one-out approach and, second, a personalised model that also uses part of the dataset from each patient. Results show a significant improvement in the accuracy of the personalised model compared to the generic model, showing enhancement in the specificity and sensitivity geometric mean (GM) of 7.2%. Furthermore, the SVM approach adopted has been compared to the most comprehensive FoG detection method currently in use (referred to as MBFA in this paper). Results of our novel generic method provide an enhancement of 11.2% in the GM compared to the MBFA generic model and, in the case of the personalised model, a 10% of improvement with respect to the MBFA personalised model. Thus, our results show that a machine learning approach can be used to monitor FoG during the daily life of PD patients and, furthermore, personalised models for FoG detection can be used to improve monitoring accuracy.Peer ReviewedPostprint (published version

Support vector regression in NIST SRE 2008 multichannel core task

Actas de las V Jornadas en Tecnología del Habla (JTH 2008)This paper explores two alternatives for speaker verification using Generalized Linear Discriminant Sequence (GLDS) kernel: classical Support Vector Classification (SVC), and Support Vector Regression (SVR), recently proposed by the authors as a more robust approach for telephone speech. In this work we address a more challenging environment, the NIST SRE 2008 multichannel core task, where strong mismatch is introduced by the use of different microphones and recordings from interviews. Channel compensation based in Nuisance Attribute Projection (NAP) has also been investigated in order to analyze its impact for both approaches. Experiments show that, although both techniques show a significant improvement over SVC-GLDS when NAP is used, SVR is also robust to channel mismatch even when channel compensation is not used. This avoids the need of a considerable set of training data adapted to the operational scenario, whose availability is not frequent in general. Results show a similar performance for SVR-GLDS without NAP and SVC-GLDS with NAP. Moreover, SVR-GLDS results are promising, since other configurations and methods for channel compensation can further improve performance.This work has been supported by the Spanish Ministry of Education under project TEC2006-13170-C02-01

Support vector machine regression for robust speaker verification in mismatching and forensic conditions

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-01793-3_50Proceedings of Third International Conference, ICB 2009, Alghero, ItalyIn this paper we propose the use of Support Vector Machine Regression (SVR) for robust speaker verification in two scenarios: i) strong mismatch in speech conditions and ii) forensic environment. The proposed approach seeks robustness to situations where a proper background database is reduced or not present, a situation typical in forensic cases which has been called database mismatch. For the mismatching condition scenario, we use the NIST SRE 2008 core task as a highly variable environment, but with a mostly representative background set coming from past NIST evaluations. For the forensic scenario, we use the Ahumada III database, a public corpus in Spanish coming from real authored forensic cases collected by Spanish Guardia Civil. We show experiments illustrating the robustness of a SVR scheme using a GLDS kernel under strong session variability, even when no session variability is applied, and especially in the forensic scenario, under database mismatch.This work has been supported by the Spanish Ministry of Education under project TEC2006-13170-C02-0

Von Mises-Fisher models in the total variability subspace for language recognition

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 works. I. Lopez-Moreno, D. Ramos, J. Gonzalez-Dominguez, and J. Gonzalez-Rodriguez, "Von Mises-Fisher models in the total variability subspace for language recognition", IEEE Signal Processing Letters, vol. 18, no. 12, pp. 705-708, October 2011This letter proposes a new modeling approach for the Total Variability subspace within a Language Recognition task. Motivated by previous works in directional statistics, von Mises-Fisher distributions are used for assigning language-conditioned probabilities to language data, assumed to be spherically distributed in this subspace. The two proposed methods use Kernel Density Functions or Finite Mixture Models of such distributions. Experiments conducted on NIST LRE 2009 show that the proposed techniques significantly outperform the baseline cosine distance approach in most of the considered experimental conditions, including different speech conditions, durations and the presence of unseen languages.This work was supported by the Ministerio de Ciencia e Innovación under FPI Grant TEC2009-14719-C02-01 and cátedra UAM-Telefónic