Efficient Hardware Design Of Iterative Stencil Loops

A large number of algorithms for multidimensional signals processing and scientific computation come in the form of iterative stencil loops (ISLs), whose data dependencies span across multiple iterations. Because of their complex inner structure, automatic hardware acceleration of such algorithms is traditionally considered as a difficult task. In this paper, we introduce an automatic design flow that identifies, in a wide family of bidimensional data processing algorithms, sub-portions that exhibit a kind of parallelism close to that of ISLs; these are mapped onto a space of highly optimized ad-hoc architectures, which is efficiently explored to identify the best implementations with respect to both area and throughput. Experimental results show that the proposed methodology generates circuits whose performance is comparable to that of manually-optimized solutions, and orders of magnitude higher than those generated by commercial HLS tools

Pyrolysis of cashew nutshells: Characterization of products and energy balance

Cashew cultivation leads to the generation of large amounts of nutshells. In order to determine whether pyrolysis could be a suitable method for the valorization of this agricultural residue, cashew nutshells (CNS) from Burkina Faso were pyrolyzed in the temperature range between 400 and 600 °C in a laboratory-scale fixed bed reactor. The solid, liquid and gaseous fractions were quantified and characterized, with special focus on the solid product. Recovery of the cashew nutshell liquid (CNSL) was accomplished during pyrolysis separately from the pyrolysis liquid. Results suggest that, except for the aqueous fraction, all the products obtained from pyrolysis are suitable for fuel purposes, and that part of the CNSL can be recovered below 200 °C during the heating process. A preliminary energy balance of the process shows that burning the gases can provide the energy necessary for the process at a pyrolysis temperature of 500 °C

Electrophysiological characteristics of permanent atrial fibrillation: insights from research models of cardiac remodeling

[EN] Atrial fibrillation (AF) results in a remodeling of the electrical and structural characteristics of the cardiac tissue which dramatically reduces the efficacy of pharmacological and catheter-based ablation therapies. Recent experimental and clinical results have demonstrated that the complexity of the fibrillatory process significantly differs in paroxysmal versus persistent AF; however, the lack of appropriate research models of remodeled atrial tissue precludes the elucidation of the underlying AF mechanisms and the identification of appropriated therapeutic targets. Here, we summarize the different research models used to date, highlighting the lessons learned from them and pointing to the new doors that should be open for the development of innovative treatments for AF.The authors were supported by grants from the Spanish Ministry of Science and Innovation (PLE2009-0152), the Instituto de Salud Carlos III (Ministry of Economy and Competitiveness, Spain: PI13-01882 and PI13-00903) the Red de Investigacion Cardiovacular (RIC) from Instituto de Salud Carlos III (Ministry of Economy and Competitiveness, Spain). F Atienza served on the advisory board of Medtronic and has received research funding from St. Jude Medical Spain. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.Climent, A.; Guillem Sánchez, MS.; Atienza Fernández, F.; Fernandez-Aviles, F. (2014). Electrophysiological characteristics of permanent atrial fibrillation: insights from research models of cardiac remodeling. Expert Review of Cardiovascular Therapy. 13(1):1-3. https://doi.org/10.1586/14779072.2015.986465S1313

Detección de fibrilación ventricular mediante técnicas de aprendizaje profundo

Detección de fibrilación ventricular mediante técnicas de aprendizaje profundo La detección de arritmias ventriculares, en particular la fibrilación ventricular (FV), es parte fundamental de los algoritmos de clasificación de arritmias de los desfibriladores. Dichos algoritmos deciden si administrar la descarga de desfibrilación, para lo que clasifican los ritmos en desfibrilables (Sh) o no desfibrilables (NSh). Este trabajo propone un nuevo abordaje para la clasificación Sh/NSh de ritmos basado en un sistema de aprendizaje profundo. Para el trabajo se emplearon tres bases de datos públicas de la plataforma Physionet (CUDB, VFDB y AHADB), y se extrajeron segmentos de 4 y 8 segundos. Se anotaron los segmentos como Sh y NSh en base a las anotaciones de las bases de datos, que fueron auditadas por expertos. Los datos se dividieron por paciente en 80% para desarrollar los algoritmos y 20% para evaluación. El sistema de aprendizaje profundo emplea dos etapas convolucionales seguidas de, una red longshort- term-memory y una etapa final de clasificación basada en red neuronal. A modo de referencia se optimizó un clasificador SVM basado en las características de detección de arritmias ventriculares más eficientes publicadas en la literatura. Se calculó la sensibilidad (Se), ritmos desfibrilables, especificidad (Sp), ritmos no desfibrilables, y la precisión (Acc). El método de aprendizaje profundo proporcionó Se, Sp y Acc de 98.5%, 99.4% y 99.2% para segmentos de 4 segundos y 99.7%, 98.9%, 99.1% para segmentos de 8 segundos. El algoritmo permite detectar FV de forma fiable con segmentos de 4 segundos, corrigiendo un 30% de los errores del método basado en SVM.Este trabajo ha sido financiado por el Ministerio de Economía y Competitividad mediante el proyecto TEC2015-64678R junto con el Fondo Europeo de Desarrollo Regional (FEDER), así como por la UPVEHU mediante el proyecto EHU16/18

METODICA PREDITTIVA PER LA VALUTAZIONE DEI DIFETTI SU LAMINATI SOTTILI IN LEGA AA3005 PER IL SETTORE PACKAGING DERIVANTI DA INCLUSIONI SOLIDE NEI BAGNI DI FUSIONE

Nel presente lavoro si è cercato di mettere a punto una metodica di prova per l’ individuazione predittiva deimicrofori nei laminati sottili in lega di alluminio sin dalla fase di fusione delle placche (cioè a monte del ciclo difabbricazione.)Mettendo in relazione ripetutamente i risultati del “test PREFIL®” [1], effettuato nella fase di colata delmetallo, in grado di quantificare la presenza di inclusioni solide e ossidi, con i risultati, in termini di microfori,rilevati sul laminato al termine della laminazione a freddo mediante l’utilizzo di un rilevatore ottico laser,è stato possibile ricavare relazioni abbastanza affidabili circa la previsione delle difettosità sul laminato aspessore finale, già dalla fase di colata

Non-Invasive Electrophysiological Mapping Entropy Predicts Atrial Fibrillation Ablation Efficacy Better Than Clinical Characteristics

[EN] Success rate of atrial fibrillation (AF) ablation remains far from satisfactory. In this study, a 6 months AF freedom predictive model based on Fuzzy Entropy of non-invasive body surface potential maps is compared with clinical predictors. The study included 29 patients referred for pulmonary vein isolated catheter ablation procedure. Non-invasive electrocardiographic mapping with 54 ECG electrodes was recorded for all patients during the ablation procedure. Six months follow up was used to evaluate the efficacy of the ablation procedure. Predictions based on non-invasive electrocardiographic mappings during adenosine infusion (accuracy: 90%, AUC: 0.93) showed a clear improvement over standard-of-care clinical parameter models (accuracy: 62.1%, AUC: 0. 54). Our results indicate that measurements of electrophysiological complexity of AF signals could improve the clinical practice by predicting the efficacy of AF ablation procedures.This work was supported by the Instituto de Salud Carlos III FEDER (DTS16/00160; PI16/01123; PI17/01059; PI17/01106; EIT-Health 19600 AFFINE)De La Nava, AS.; Fabregat, MC.; Rodrigo, M.; Hernández, I.; Liberos, A.; Fernández-Avilés, F.; Guillem Sánchez, MS.... (2019). Non-Invasive Electrophysiological Mapping Entropy Predicts Atrial Fibrillation Ablation Efficacy Better Than Clinical Characteristics. IEEE. 1-4. https://doi.org/10.22489/CinC.2019.299S1

Allelic Variation, Alternative Splicing and Expression Analysis of Psy1 Gene in Hordeum chilense Roem. et Schult

Background: The wild barley Hordeum chilense Roem. et Schult. is a valuable source of genes for increasing carotenoid content in wheat. Tritordeums, the amphiploids derived from durum or common wheat and H. chilense, systematically show higher values of yellow pigment colour and carotenoid content than durum wheat. Phytoene synthase 1 gene (Psy1) is considered a key step limiting the carotenoid biosynthesis, and the correlation of Psy1 transcripts accumulation and endosperm carotenoid content has been demonstrated in the main grass species. Methodology/Principal findings: We analyze the variability of Psy1 alleles in three lines of H. chilense (H1, H7 and H16) representing the three ecotypes described in this species. Moreover, we analyze Psy1 expression in leaves and in two seed developing stages of H1 and H7, showing mRNA accumulation patterns similar to those of wheat. Finally, we identify thirtysix different transcripts forms originated by alternative splicing of the 59 UTR and/or exons 1 to 5 of Psy1 gene. Transcripts function is tested in a heterologous complementation assay, revealing that from the sixteen different predicted proteins only four types (those of 432, 370, 364 and 271 amino acids), are functional in the bacterial system. Conclusions/Significance: The large number of transcripts originated by alternative splicing of Psy1, and the coexistence of functional and non functional forms, suggest a fine regulation of PSY activity in H. chilense. This work is the first analysis of H. chilense Psy1 gene and the results reported here are the bases for its potential use in carotenoid enhancement in duru