Charged anisotropic compact objects by gravitational decoupling

In the present article, we have constructed a static charged anisotropic compact star model of Einstein field equations for a spherically symmetric space-time geometry. Specifically, we have extended the charged isotropic Heintzmann solution to an anisotropic domain. To address this work, we have employed the gravitational decoupling through the so called minimal geometric deformation approach. The charged anisotropic model is representing the realistic compact objects such as $RXJ1856-37$ and $SAX J1808.4-3658(SS2)$. We have reported our results in details for the compact star $RXJ1856-37$ on the ground of physical properties such as pressure, density, velocity of sound, energy conditions, stability conditions, Tolman-Oppenheimer-Volkoff equation and redshift etc

Molecular Mechanisms Used by Salmonella to Evade the Immune System

Human and animal pathogens are able to circumvent, at least temporarily, the sophisticated immune defenses of their hosts. Several serovars of the Gram-negative bacterium Salmonella enterica have been used as models for the study of pathogen-host interactions. In this review we discuss the strategies used by Salmonella to evade or manipulate three levels of host immune defenses: physical barriers, innate immunity and adaptive immunity. During its passage through the digestive system, Salmonella has to face the acidic pH of the stomach, bile and antimicrobial peptides in the intestine, as well as the competition with resident microbiota. After host cell invasion, Salmonella manipulates inflammatory pathways and the autophagy process. Finally, Salmonella evades the adaptive immune system by interacting with dendritic cells, and T and B lymphocytes. Mechanisms allowing the establishment of persistent infections are also discussed.European Regional Development Fund SAF2013-46229-R, SAF2016-75365-

Enseñar en competencias en educación infantil y primaria. La agenda telefónica

Las leyes educativas van cambiando, adaptándose a las necesidades de las nuevas sociedades presentes en nuestro entorno. Lo mismo debe suceder con nuestra forma de enseñar, de utilizar los recursos y de presentar los conocimientos y experiencias. Con la finalidad de trabajar en la línea de las competencias básicas, se presenta esta actividad, realizada conjuntamente con el alumnado de infantil y primaria. Se trata con ella de dar un sentido a la enseñanza de la numeración en el primer contacto que se tiene en la escuela

Deep Neural Networks for the Recognition and Classification of Heart Murmurs Using Neuromorphic Auditory Sensors

Auscultation is one of the most used techniques for detecting cardiovascular diseases, which is one of the main causes of death in the world. Heart murmurs are the most common abnormal finding when a patient visits the physician for auscultation. These heart sounds can either be innocent, which are harmless, or abnormal, which may be a sign of a more serious heart condition. However, the accuracy rate of primary care physicians and expert cardiologists when auscultating is not good enough to avoid most of both type-I (healthy patients are sent for echocardiogram) and type-II (pathological patients are sent home without medication or treatment) errors made. In this paper, the authors present a novel convolutional neural network based tool for classifying between healthy people and pathological patients using a neuromorphic auditory sensor for FPGA that is able to decompose the audio into frequency bands in real time. For this purpose, different networks have been trained with the heart murmur information contained in heart sound recordings obtained from nine different heart sound databases sourced from multiple research groups. These samples are segmented and preprocessed using the neuromorphic auditory sensor to decompose their audio information into frequency bands and, after that, sonogram images with the same size are generated. These images have been used to train and test different convolutional neural network architectures. The best results have been obtained with a modified version of the AlexNet model, achieving 97% accuracy (specificity: 95.12%, sensitivity: 93.20%, PhysioNet/CinC Challenge 2016 score: 0.9416). This tool could aid cardiologists and primary care physicians in the auscultation process, improving the decision making task and reducing type-I and type-II errors.Ministerio de Economía y Competitividad TEC2016-77785-

Correction:Carbonyl trapping and antiglycative activities of olive oil mill wastewater

Correction for ‘Carbonyl trapping and antiglycative activities of olive oil mill wastewater’ by Marta Navarro et al., Food Funct., 2015, 6, 574–583