EEG-based outcome prediction after cardiac arrest with convolutional neural networks: Performance and visualization of discriminative features.

Prognostication for comatose patients after cardiac arrest is a difficult but essential task. Currently, visual interpretation of electroencephalogram (EEG) is one of the main modality used in outcome prediction. There is a growing interest in computer-assisted EEG interpretation, either to overcome the possible subjectivity of visual interpretation, or to identify complex features of the EEG signal. We used a one-dimensional convolutional neural network (CNN) to predict functional outcome based on 19-channel-EEG recorded from 267 adult comatose patients during targeted temperature management after CA. The area under the receiver operating characteristic curve (AUC) on the test set was 0.885. Interestingly, model architecture and fine-tuning only played a marginal role in classification performance. We then used gradient-weighted class activation mapping (Grad-CAM) as visualization technique to identify which EEG features were used by the network to classify an EEG epoch as favorable or unfavorable outcome, and also to understand failures of the network. Grad-CAM showed that the network relied on similar features than classical visual analysis for predicting unfavorable outcome (suppressed background, epileptiform transients). This study confirms that CNNs are promising models for EEG-based prognostication in comatose patients, and that Grad-CAM can provide explanation for the models' decision-making, which is of utmost importance for future use of deep learning models in a clinical setting

Prediction of bulk milk fatty acid composition based on farming practices collected through on-farm surveys

International audience; The aim of this study was to predict the fatty acid (FA) composition of bulk milk using data describing farming practices collected via on-farm surveys. The FA composition of 1,248 bulk cow milk samples and the related farming practices were collected from 20 experiments led in 10 different European countries at 44 degrees N to 60 degrees N latitude and sea level to 2,000 m altitude. Farming practice-based FA predictions [coefficient of determination (R-2) >0.50] were good for C16:0, C17:0, saturated FA, polyunsaturated FA, and odd-chain FA, and very good (R-2 >= 0.60) for trans-11 C18:1, trans-10 + trans-11 C18:1, cis-9,trans-11 conjugated linoleic acid, total trans FA, C18:3n-3, n-6:n-3 ratio, and branched-chain FA. Fatty acids were predicted by cow diet composition and by the altitude at which milk was produced, whereas animal-related factors (i.e., lactation stage, breed, milk yield, and proportion of primiparous cows in the herd) were not significant in any of the models. Proportion of fresh herbage in the cow diet was the main predictor, with the highest effect in almost all FA models. However, models built solely on conserved forage-derived samples gave good predictions for odd-chain FA, branched-chain FA, trans-10 C18:1 and C18:3n-3 (R-2 >= 0.46, 0.54, 0.52, and 0.70, respectively). These prediction models could offer farmers a valuable tool to help improve the nutritional quality of the milk they produce

Evaluación comparativa mediante simulación con EnergyPlus del comportamiento energético de una vivienda tipo dúplex y su mejoramiento térmico

El objetivo del trabajo consiste en mostrar un protocolo de capacitación para el uso del programa Energy Plus mediante la modelización de viviendas unifamiliares usuales en La Plata y a partir de su comportamiento higrotérmico y energético implementar mejoras tendientes a transformarlas en viviendas de baja energía. Los casos de partida surgen de relevamientos realizados con anterioridad y responden a los sistemas constructivos encontrados en la región. El modo e intensidad de uso de los casos se sustenta en una media del comportamiento social encuestado por los proyectos de investigación del laboratorio. En cuanto a ocupación se determinó en primer lugar el comportamiento térmico de los casos en evolución natural sin personas. Se presentan resultados y se los discute a fin de obtener entrenamiento en modelización y simulación numérica.The aim of this work is to show the training protocol for the use of Energy Plus program by modeling conventional single-family homes in La Plata and from their hygrothermal and energetic behavior to introduce improvements which are aimed at transforming them into low-energy houses. The cases arise from surveys conducted before and respond to the building systems found in the region. The mode and intensity of using of these cases is based on an average of social behavior surveyed by laboratory research projects. Concerning occupation first is determined the thermal behavior of natural evolution without people. Results are presented and are discussed in order to obtain training in modeling and numerical simulation.Asociación Argentina de Energías Renovables y Medio Ambiente (ASADES

IMPACT OF VIDEO TRANSCODING ARTIFACTS ON THE SUBJECTIVE QUALITY

Video transcoding is an important step to enable interoperability between different networks, terminals, applications, and services for video communication. This paper studies the influence of typical video transcoding artifacts due to frame rate reduction and drift error on the subjective quality. Given a realistic dataset for a DVB-T to DVB-H transcoding scenario, the subjective quality before and after the transcoding is compared against each other. In order to quantify the influence of both artifacts, a pixel domain and an open loop transcoding solution have been considered. Since the strength of both artifacts depends largely on the initial encoding parameters, additional experiments have been conducted to quantify the influence of the distance between I frames and the number of consecutive B frames on the subjective quality

Smart ground project: a new approach to data accessibility and collection for raw materials and secondary raw materials in Europe

Steady Raw Materials (RM) supply is essential for the EU economy and increasingly under pressure to sustain the businesses and industries demand. The supply of RM is not only a matter of availability of primary but also of secondary raw materials (SRM). In fact a great amount of waste can be regained as practical and valuable SRM by enhancing the recovery processes from industrial, mining and municipal landfill sites, especially if we consider that Europe is highly dependent on the imports of several RM. Nevertheless, there is to date no inventory of SRM at EU level. Smart Ground project aims to facilitate the availability and accessibility of data and information on SRM in the EU, as well as creating synergy and collaboration between the different stakeholders involved in the SRM value chain. In order to do so, the Smart Ground consortium is carrying out a set of activities to integrate in a single EU database all the data from existing sources and new information retrieving pilot landfills as progress is made. Such database will enable the exchange of contacts and information among the relevant stakeholders, interested in providing or obtaining SRM. Finally, Smart Ground project will also spin out the SRM economy and employment thanks to targeted training activities, organized during congresses and dedicated meeting with stakeholders and end users interested in calculating the potentiality for SRM recovery from selected landfills, contemporary constituting a dedicated network of stakeholders committed to cost-effective research, technology transfer and training

Fifteen years SIB Swiss Institute of Bioinformatics: life science databases, tools and support

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 year

XIPE: the X-ray Imaging Polarimetry Explorer

X-ray polarimetry, sometimes alone, and sometimes coupled to spectral and temporal variability measurements and to imaging, allows a wealth of physical phenomena in astrophysics to be studied. X-ray polarimetry investigates the acceleration process, for example, including those typical of magnetic reconnection in solar flares, but also emission in the strong magnetic fields of neutron stars and white dwarfs. It detects scattering in asymmetric structures such as accretion disks and columns, and in the so-called molecular torus and ionization cones. In addition, it allows fundamental physics in regimes of gravity and of magnetic field intensity not accessible to experiments on the Earth to be probed. Finally, models that describe fundamental interactions (e.g. quantum gravity and the extension of the Standard Model) can be tested. We describe in this paper the X-ray Imaging Polarimetry Explorer (XIPE), proposed in June 2012 to the first ESA call for a small mission with a launch in 2017 but not selected. XIPE is composed of two out of the three existing JET-X telescopes with two Gas Pixel Detectors (GPD) filled with a He-DME mixture at their focus and two additional GPDs filled with pressurized Ar-DME facing the sun. The Minimum Detectable Polarization is 14 % at 1 mCrab in 10E5 s (2-10 keV) and 0.6 % for an X10 class flare. The Half Energy Width, measured at PANTER X-ray test facility (MPE, Germany) with JET-X optics is 24 arcsec. XIPE takes advantage of a low-earth equatorial orbit with Malindi as down-link station and of a Mission Operation Center (MOC) at INPE (Brazil).Comment: 49 pages, 14 figures, 6 tables. Paper published in Experimental Astronomy http://link.springer.com/journal/1068

US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report

This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference

The Matecat Tool

© 2014 The Authors. Published by Dublin City University and Association for Computational Linguistics. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://www.aclweb.org/anthology/C14-2028We present a new web-based CAT tool providing translators with a professional work environment, integrating translation memories, terminology bases, concordancers, and machine translation. The tool is completely developed as open source software and has been already successfully deployed for business, research and education. The MateCat Tool represents today probably the best available open source platform for investigating, integrating, and evaluating under realistic conditions the impact of new machine translation technology on human post-editing