Examinando por Autor "Delgado, A."

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Acceso Abierto
Electromagnetic counterparts to gravitational wave events from Gaia
(Oxford Academics: Blackwell Publishing, 2020-02-13) Kostrzewa Rutkowska, Z.; Jonker, P. G.; Hodgkin, S. T.; Eappachen, D.; Harrison, D. L.; Koposov, S. E.; Rixon, G.; Wyrzykowski, L.; Yoldas, A.; Breedt, E.; Delgado, A.; Van Leeuwen, M.; Wevers, T.; Burgess, P. W.; De Angeli, D.; Evans, D. W.; Osborne, Paul; Riello, M.; European Research Council (ERC); National Science Centre, Poland (NCN); European Commission (EC); National Aeronautics and Space Administration (NASA); Koposov, S. E. [0000-0003-2644-135X]; Harrison, D. [0000-0001-8687-6588]; Wyrzykowski, L. [0000-0002-9658-6151]; Koposov, S. [0000-0003-2644-135X]; Breedt, E. [0000-0001-6180-3438]; Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737
The recent discoveries of gravitational wave events and in one case also its electromagnetic (EM) counterpart allow us to study the Universe in a novel way. The increased sensitivity of the LIGO and Virgo detectors has opened the possibility for regular detections of EM transient events from mergers of stellar remnants. Gravitational wave sources are expected to have sky localization up to a few hundred square degrees, thus Gaia as an all-sky multi-epoch photometric survey has the potential to be a good tool to search for the EM counterparts. In this paper, we study the possibility of detecting EM counterparts to gravitational wave sources using the Gaia Science Alerts system. We develop an extension to current used algorithms to find transients and test its capabilities in discovering candidate transients on a sample of events from the observation periods O1 and O2 of LIGO and Virgo. For the gravitational wave events from the current run O3, we expect that about 16 (25) per cent should fall in sky regions observed by Gaia 7 (10) d after gravitational wave. The new algorithm will provide about 21 candidates per day from the whole sky.
Acceso Abierto
Morphology Clustering Software for AFM Images, Based on Particle Isolation and Artificial Neural Networks
(Institute of Electrical and Electronics Engineers, 2019-11-04) Delgado, A.; Moreno, M.; Vázquez, L. F.; Martín Gago, J. A.; Briones, C.; Ministerio de Economía y Competitividad (MINECO); Comunidad de Madrid; Agencia Estatal de Investigación (AEI); Delgado, A. [0000-0003-4868-3712]; Moreno, M. [0000-0002-6065-4095]; MartínGago, J. A. [0000-0003-2663-491X]; Briones, C. [0000-0003-2213-8353]; Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737
Advanced microscopy techniques currently allow scientists to visualize biomolecules at high resolution. Among them, atomic force microscopy (AFM) shows the advantage of imaging molecules in their native state, without requiring any staining or coating of the sample. Biopolymers, including proteins and structured nucleic acids, are flexible molecules that can fold into alternative conformations for any given monomer sequence, as exemplified by the different three-dimensional structures adopted by RNA in solution. Therefore, the manual analysis of images visualized by AFM and other microscopy techniques becomes very laborious and time-consuming (and may also be inadvertently biased) when large populations of biomolecules are studied. Here we present a novel morphology clustering software, based on particle isolation and artificial neural networks, which allows the automatic image analysis and classification of biomolecules that can show alternative conformations. It has been tested with a set of AFM images of RNA molecules (a 574 nucleotides-long functional region of the hepatitis C virus genome that contains its internal ribosome entry site element) structured in folding buffers containing 0, 2, 4, 6 or 10 mM Mg 2+ . The developed software shows a broad applicability in the microscopy-based analysis of biopolymers and other complex biomolecules.