Detección de fibrilación auricular en señales ECG usando Redes Neuronales para pacientes específicos

Atrial Fibrillation (AF) is the most common cardiac arrhythmia worldwide. It is associated with reduced quality of life and increases the risk of stroke and myocardial infarction. Unfortunately, many cases of AF are asymptomatic and undiagnosed, which increases the risk for the patients. Due to its paroxysmal nature, the detection of AF requires the evaluation, by a cardiologist, of long-term ECG signals. In Colombia, it is difficult to have access to an early diagnosis of AF because of the associated costs to the detection and the geographical distribution of cardiologists. This work is part of a macro project that aims to develop a specific-patient portable device for the detection of AF. This device will be based on a Convolutional Neural Network (CNN). We aim to find a suitable CNN model, which later could be implemented in hardware. Diverse techniques were applied to improve the answer regarding accuracy, sensitivity, specificity, and precision. The final model achieves an accuracy of , a specificity of , a sensitivity of  and a precision of . During the development of the model, the computational cost and memory resources were taking into account in order to obtain an efficient hardware model in a future implementation of the device.La fibrilación auricular (FA) es la arritmia cardíaca más común en todo el mundo. Se asocia con una reducción de la calidad de vida y aumenta el riesgo de accidente cerebrovascular e infarto de miocardio. Desafortunadamente muchos casos de FA son asintomáticos, lo cual aumenta el riesgo para los pacientes. Debido a su naturaleza paroxística, la detección de la FA requiere la evaluación, por parte de un cardiologo, de señales ECG de larda duración. En Colombia, es difícil dificil tener dianóstico temprano de la FA debido a los costos asociados a la detección de la FA y la distribución geográfica de los cardiólogos. Este trabajo es parte de un proyecto macro que tiene como objetivo desarrollar un dispositivo portátil para pacientes específicos que permita detectar la FA, el cual estará basado en una red neuronal convolucional (CNN). Nuestro objetivo es encontrar un modelo CNN adecuado, que luego se pueda implementar en hardware. Se aplicaron diversas técnicas para mejorar la respuesta con respecto a la exactitud, la sensibilidad, la especificidad y la precisión. El modelo final alcanza una exactitud del 97,44%, una especificidad del 97,76%, una sensibilidad del 96,97% y una precisión del 96,80%. Durante el desarrollo del modelo, el costo computacional y los recursos de memoria se tuvieron en cuenta para obtener un modelo de hardware eficiente en una futura  implementación del dispositivo

Influence of Soft Wheat Characteristics on Quality of Batter-based Products

Wheat is a globally traded staple crop. Wheat is important in human diets because of its agronomic adaptability, physical characteristics, functionality for the production of leavened products and nutritional value. Two significant characteristics make wheat an important staple food-crop. First, the proteins present in wheat endosperm have attributes that enable gas retention after the proteins are hydrated and mechanically worked during dough production. Second, a wider variety of products can be made out of wheat compared to other cereals. Wheat quality is defined in terms of suitability for specific end-uses. This is important for breeders, farmers, flour millers, and food producers and consumers. In the U.S. Pacific Northwest (PNW) climatic conditions favor production of soft wheat. Three soft wheat types are planted in the PNW, soft white winter (SWW), soft white spring (SWS), and club (CLUB). Batter-based products are important applications for soft wheats and include a wide range of products such as pancakes and waffles, cakes, and coatings. Pancakes are produced from fluid batters using a single step mixing process and contain sugar concentrations < 30% in their formulations. Cakes are complex food systems where their classification is based on mixing process to produce the batters and the sugar-flour ratio concentrations in their formulations. This dissertation is focused on the functionality, analysis, and selection of soft wheat quality traits that affect end-product performance and also developing a methodology to rapidly predict cake quality. The first study (Chapter 3) was concerned with the functionality of SWW wheats in pancake making. The aim of this study was to observe the differences in genotype and protein concentration on batter flow and pancake making performance of a collection of SWW wheats. Two formulations were used in the study: one based on Finnie et al (2006) called "old" and another based on the AACC-I Approved Method 10-80.01 called "new". The "new" lean formulation had an improved ability to distinguish the performance of different flours compared with the “old” as a result of wider range of pancake diameters. This study showed that pancake making performance would not be optimized by conventional superior high-quality soft wheat flours with soft kernel texture, high break flour yield, and low water-, carbonate-, and sucrose SRCs. From our results it appears that for unchlorinated flours, at least for thicker pancakes, the most appropriate flour would have higher water and sucrose SRCs and be grown under management conditions conductive to higher protein. The second study (Chapter 4) was a meta-analysis of data collected by the USDA Western Wheat Quality Laboratory (Pullman, WA). This study was done to advance understanding soft wheat quality traits that differentially affect sugar-snap cookie diameter (CODI) and Japanese sponge cake (SC) volume (CAVOL). Principal component analysis (PCA) and partial least square (PLS) regression models were used to obtain useful actionable information from the data. The overall data showed that break flour yield (BKFY) was the single most important trait positively associated with both CAVOL and CODI. SWW wheats showed CVs > 10% for kernel hardness (SKHRD), grain and flour protein concentrations, ash, sucrose-, and lactic acid SRCs. These observations suggested that hardness, protein, ash, and the two SRCs were more sensitive to G&E effects than were the end-product traits that had CVs < 10%. The third study (Chapter 5) was built on the second study by adding two additional quality tests, oxidative gelation capacity (PeakOXI) and median particle size, to the potential prediction of CODI and CAVOL. Similar to the second study, BKFY was the single most important trait positively associated with both CAVOL and CODI. Virtual selection of SWWs based on either BKFY or SKHRD alone showed (in both the second and third studies) that using these enabled a gain of 134 mL for CAVOL and 0.6 cm for CODI using SKHRD and 122 mL for CAVOL and 0.58 cm for CODI using BKFY (Chapter 5). PeakOXI was significantly correlated with CODI but not with CAVOL. This contrasted with our hypothesis that PeakOXI would affect both products similarly. Notably 13 SWW samples had PeakOXI values higher than 800 cP. PeakOXI values this high have never been observed in soft wheats prior to this study. This is a valuable genetic resource for further studies that may lead to ways to better exploit oxidative gelation. The fourth study (Chapter 6) expanded the concepts in previous studies and included the use of a test to measure cake-batter viscosity in an attempt to predict cake quality. This study investigated the relationships between wheat quality traits, cake batters, and cake making quality in three cake types: SC, layer cake (LC), and pound cake (PoC). This study differed from the studies in Chapters 4 and 5 and was similar to Chapter 3 as the samples were fewer but specifically chosen to span the entire range of typical SWW quality. In this study we also developed a viscosity-based method to predict SC and LC quality that takes only eight minutes. This could be useful for screening or selection for cake quality in soft wheat breeding programs. In SC, there were no significant differences in cake quality traits between varieties. However, SC volume had a strong negative association with PeakOXI. For LC, the variety Tubbs, with harder kernel and higher absorption characteristics, had the largest LC volume. In contrast to SC, LC volume was significantly and positively associated with PeakOXI. In PoC, Kaseburg, with the highest protein content, had the largest cake volume. PoC was significantly and positively associated with flour protein concentration suggesting that flour proteins were important for larger volumes and confirming other observations in the literature. In contrast to LC and SC, PoC was not significantly associated with PeakOXI. The overall impact of the studies reported is: - For pancakes, the most important soft wheat trait is flour protein concentration. Water-, and sucrose SRCs were potentially useful parameters for predicting pancake quality. - For SC and sugar-snap cookies, break flour yield was the most important single trait in predicting higher SC volumes and larger cookie diameters. Therefore, selection in soft wheat breeding should be focused on kernel hardness and break flour yields as primary factors

Arquitectura Computacional para la Inferencia deuna CNN Cuantizada para Detectar FibrilaciónAuricular

Atrial Fibrillation is a common cardiac arrhythmia, which is characterized by an abnormal heartbeat rhythm that can be life-threatening. Recently, researchers have proposed several Convolutional Neural Networks (CNNs) to detect Atrial Fibrillation. CNNs have high requirements on computing and memory resources, which usually demand the use of High Performance Computing (eg, GPUs). This high energy demand is a challenge for portable devices. Therefore, efficient hardware implementations are required. We propose a computational architecture for the inference of a Quantized Convolutional Neural Network (Q-CNN) that allows the detection of the Atrial Fibrillation (AF). The architecture exploits data-level parallelism by incorporating SIMD-based vector units, which is optimized in terms of computation and storage and also optimized to perform both the convolutional and fully connected layers. The computational architecture was implemented and tested in a Xilinx Artix-7 FPGA. We present the experimental results regarding the quantization process in a different number of bits, hardware resources, and precision. The results show an accuracy of 94% accuracy for 22-bits. This work aims to be the basis for the future implementation of a portable, low-cost, and high-reliability device for the diagnosis of Atrial Fibrillation.La fibrilación auricular es una arritmia cardíaca común, que se caracte-riza por un ritmo cardíaco anormal que puede poner en peligro la vida.Recientemente, se han propuesto varias Redes Neuronales Convoluciona-les (CNNs, por sus siglas en inglés) para detectar la fibrilación auricular.Las CNN tienen altos requisitos de recursos informáticos y de memoria,lo que generalmente demanda el uso Computación de Altro Rendimientocomo por ejemplo GPUs. Esta alta demanda de energía es un desafío pa-ra los dispositivos portátiles. Por lo tanto, se requieren implementacionesde hardware eficientes. Proponemos una arquitectura computacional pa-ra la inferencia de una Red Neural Convolucional Cuantizada (Q-CNN)que permite la detección de la Fibrilación Auricular (FA). La arquitecturaaprovecha el paralelismo a nivel de datos, incorporando unidades vecto-riales basadas en SIMD, que están optimizadas en términos de cálculoy almacenamiento. El diseño también se optimizó para realizar tanto lascapas convolucionales como las capas completamente conectadas. La ar-quitectura computacional se implementó y probó en una FPGA XilinxArtix-7. Presentamos los resultados experimentales con respecto al proce-so de cuantización en un número diferente de bits, recursos de hardwarey precisión. Los resultados muestran una precisión del 94 % para 22 bits.Este trabajo pretende ser la base para la futura implementación de undispositivo portátil, de bajo costo y alta confiabilidad para el diagnósticode Fibrilación Auricular

Phthalocyanines: Alternative Sensitizers of TiO2 to be Used in Photocatalysis

Currently, titanium dioxide is a most researched semiconductor in photocatalysis field; however, practical applications of TiO2 are limited due to high band gap (3.2 eV). In last decades, researchers implemented several strategies to improve photoactivity of TiO2 in visible electromagnetic spectrum. Titanium dioxide (TiO2) sensitization for absorption of naturals and/or synthetics organic dyes is an important research subject in the field, and it is an efficient method to develop practical application in waste treatment. In this chapter, we review main theoretical aspects of sensitization process of TiO2 by phthalocyanines and its effect in photocatalytic properties. In the last section, we review reports of photocatalytic systems

Evaluation of the dioxin and furan formation thermodynamics in combustion processes of urban solid wastes

Specific combustion programs (Gaseq, Chemical equilibria in perfect gases, Chris Morley) are used to model dioxin and formation in the incineration processes of urban solid wastes. Thanks to these programs, it is possible to establish correlations with the formation mechanisms postulated in literature on the subject. It was found that minimum oxygen quantities are required to obtain a significant formation of these compounds and that more furans than dioxins are formed. Likewise, dioxin and furan formation is related to the presence of carbon monoxide, and dioxin and furan distribution among its different compounds depends on the chlorine and hydrogen relative composition. This is due to the fact that an increased chlorine availability leads to the formation of compounds bearing a higher chlorine concentration (penta-, hexa-, hepta-, and octachlorides), whereas an increased hydrogen availability leads to the formation of compounds bearing a lower chlorine number (mono, di-, tri-, and tetrachlorides).Fil: Moreno Piraján, Juan Carlos. Universidad de los Andes; ColombiaFil: García Ubaque, C. A.. Universidad de los Andes; ColombiaFil: Fajardo, R.. Universidad de los Andes; ColombiaFil: Giraldo, L.. Universidad Nacional de Colombia; ColombiaFil: Sapag, Manuel Karim. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Física Aplicada "Dr. Jorge Andrés Zgrablich". Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto de Física Aplicada "Dr. Jorge Andrés Zgrablich"; Argentin

Rendimiento y distribución del tiempo de los trabajadores en la construcción masiva de la vivienda

15 páginasSe presenta un análisis de campo sobre la productividad de los trabajadores de la industria de la construcción, en específico los encargados de las obras de albañilería, empleados para la construcción de viviendas en serie en el Estado de Yucatán. Se muestra la metodología seguida y los resultados de los estudios realizados de tiempos y movimientos. Se concluye que “el trabajo de albañilería no está bien administrado y es susceptible de ser mejorado significativamente”

Development of New Antiproliferative Compound against Human Tumor Cells from the Marine Microalgae Nannochloropsis gaditana by Applied Proteomics

Proteomics is a crucial tool for unravelling the molecular dynamics of essential biological processes, becoming a pivotal technique for basic and applied research. Diverse bioinformatic tools are required to manage and explore the huge amount of information obtained from a single proteomics experiment. Thus, functional annotation and protein-protein interactions are evaluated in depth leading to the biological conclusions that best fit the proteomic response in the system under study. To gain insight into potential applications of the identified proteins, a novel approach named "Applied Proteomics" has been developed by comparing the obtained protein information with the existing patents database. The development of massive sequencing technology and mass spectrometry (MS/MS) improvements has allowed the application of proteomics nonmodel microorganisms, which have been deeply described as a novel source of metabolites. Between them, Nannochloropsis gaditana has been pointed out as an alternative source of biomolecules. Recently, our research group has reported the first complete proteome analysis of this microalga, which was analysed using the applied proteomics concept with the identification of 488 proteins with potential industrial applications. To validate our approach, we selected the UCA01 protein from the prohibitin family. The recombinant version of this protein showed antiproliferative activity against two tumor cell lines, Caco2 (colon adenocarcinoma) and HepG-2 (hepatocellular carcinoma), proving that proteome data have been transformed into relevant biotechnological information. From Nannochloropsis gaditana has been developed a new tool against cancer-the protein named UCA01. This protein has selective effects inhibiting the growth of tumor cells, but does not show any effect on control cells. This approach describes the first practical approach to transform proteome information in a potential industrial application, named "applied proteomics". It is based on a novel bioalgorithm, which is able to identify proteins with potential industrial applications. From hundreds of proteins described in the proteome of N. gaditana, the bioalgorithm identified over 400 proteins with potential uses; one of them was selected as UCA01, "in vitro" and its potential was demonstrated against cancer. This approach has great potential, but the applications are potentially numerous and undefined

Caracterización mecánica y microestructural de acero naval sometido a cargas dinámicas por explosión

The work presents the mechanical and micro-structural characterization of the grade A ASTM A 131 steel laminate that form naval panels (reinforced laminate with defined ratios aspect l/b), attained by means of destructive testing, to establish the mechanical response of naval structures submitted to those types of charges. Measurements of micro-hardness, grain size and tension tests of specimens of the material were carried out before and after the impact. The material hit was selected from structural panels submitted to controlled explosions generated nearby with 25g charges of pentolite, placed at predetermined distances. For the characterization, panels with the presence of fissures were rejected. Important variations in micro-hardness and mechanical characteristics appeared; nevertheless, significant micro-structural changes were not observed in grain size.El trabajo presenta la caracterización mecánica y microestructural de láminas de acero ASTM A 131 grado A que conforman paneles navales (láminas reforzadas con relaciones de aspecto l/b definidas), realizada mediante ensayos destructivos, para establecer la respuesta mecánica de estructuras navales sometidas a ese tipo de cargas. Se hicieron mediciones de microdureza, tamaño de grano y ensayos de tensión a especímenes del material antes y después del impacto. El material impactado fue seleccionado de paneles estructurales sometidos a explosiones controladas cercanas generadas con cargas de 250 g de pentolita, dispuestas a distancias predeterminadas. Para la caracterización se rechazaron paneles con la presencia de fisuras. Se presentaron variaciones importantes en microdureza y características mecánicas, sin embargo, no se observaron cambios microestructurales en tamaño de grano que fueran significativos

Myeloid cell deficiency of p38γ/p38δ protects against candidiasis and regulates antifungal immunity

Fundació la Marató de TV3 (GrantNumber(s): 20133431; Grant recipient(s): Ana Cuenda) Wellcome Trust (GrantNumber(s): 97377, 102705; Grant recipient(s): GORDON D. BROWN) Ministerio de Economía y Competitividad (GrantNumber(s): SAF2016-79792-R, SAF2014- 52009-R, SAF2013-45331-R; Grant recipient(s): Ana Cuenda, SUSANA ALEMANY) Medical Research Council (GrantNumber(s): MR/N006364/1; Grant recipient(s): GORDON D. BROWN) ERC Consolidator Grant (GrantNumber(s): 310372; Grant recipient(s): Mihai Netea)Peer reviewedPublisher PD

TRPA1 channels mediate acute neurogenic inflammation and pain produced by bacterial endotoxins

Producción CientíficaGram-negative bacterial infections are accompanied by inflammation and somatic or visceral pain. These symptoms are generally attributed to sensitization of nociceptors by inflammatory mediators released by immune cells. Nociceptor sensitization during inflammation occurs through activation of the Toll-like receptor 4 (TLR4) signalling pathway by lipopolysaccharide (LPS), a toxic by-product of bacterial lysis. Here we show that LPS exerts fast, membrane delimited, excitatory actions via TRPA1, a transient receptor potential cation channel that is critical for transducing environmental irritant stimuli into nociceptor activity. Moreover, we find that pain and acute vascular reactions, including neurogenic inflammation (CGRP release) caused by LPS are primarily dependent on TRPA1 channel activation in nociceptive sensory neurons, and develop independently of TLR4 activation. The identification of TRPA1 as a molecular determinant of direct LPS effects on nociceptors offers new insights into the pathogenesis of pain and neurovascular responses during bacterial infections and opens novel avenues for their treatment.Projects SAF2010-14990 and PROMETEO2010-046. Instituto de Salud Carlos III. CONSOLIDER-INGENIO 2010. ISCIII grants R006/009 (Red Heracles), the Spanish Fundación Marcelino Botín and Belgian Federal Government (IUAP P6/28 and P7/13), the Research Foundation-Flanders and the Research Council of the KU Leuven