Curs de càlcul: una nova metodologia per a la impartició i gestió, basades en l'entorn Moodle

Aquest projecte dissenya un curs de matemàtiques usant els diferents recursos de Moodle. Els temes que es tracten en el curs corresponen bàsicament a les assignatures de Càlcul i Matemàtiques de diferents titulacions a diversos centres de la UPC, concretament l’E.T.S. d’Enginyers de Camins, Canals i Ports, la Facultat de Matemàtiques i Estadística i l’E.U. d’Enginyeria Tècnica Agrícola de Barcelona. Moodle és un sistema per la creació de cursos i llocs web basats en Internet. Es tracta d’un projecte en desenvolupament i millora permanent per donar suport a un marc d’educació basat en el constructivisme social (col•laboració, activitats, reflexió crítica, etc). És un tipus de recurs fonamental per a una docència semipresencial i que sintonitzi amb les directrius de l’Espai Europeu d’Educació Superior. Per al disseny del curs i la seva experimentació en un curs pilot s’ha definit un grup de treball que aglutina: Professors de matemàtiques amb llarga experiència en la docència de les assignatures de Càlcul, estudiants de diferents titulacions, experts en el disseny d’activitats interactives de matemàtiques, de l’empresa Maths for More. Aquest grup o molts dels seus components ja han col•laborat anteriorment en els desenvolupament dels projectes, destaquem el projecte EVAM (http://wiris.upc.es/EVAM) i BasicMatWeb (http://wiris.upc.es/basicmatweb)

Coordinated response to imported vaccine-derived poliovirus infection, Barcelona, Spain, 2019-2020

In 2019, the Public Health Agency of Barcelona, Spain, was notifi ed of a vaccine-derived poliovirus infection. The patient had an underlying common variable immunodefi ciency and no signs of acute fl accid paralysis. We describe the ongoing coordinated response to contain the infection, which included compassionate-use treatment with pocapavir

The miniJPAS survey quasar selection – II. Machine learning classification with photometric measurements and uncertainties

Full list of authors: Rodrigues, Natalia V. N.; Raul Abramo, L.; Queiroz, Carolina; Martinez-Solaeche, Gines; Perez-Rafols, Ignasi; Bonoli, Silvia; Chaves-Montero, Jonas; Pieri, Matthew M.; Gonzalez Delgado, Rosa M.; Morrison, Sean S.; Marra, Valerio; Marquez, Isabel; Hernan-Caballero, A.; Diaz-Garcia, L. A.; Benitez, Narciso; Cenarro, A. Javier; Dupke, Renato A.; Ederoclite, Alessandro; Lopez-Sanjuan, Carlos; Marin-Franch, Antonio; de Oliveira, Claudia Mendes; Moles, Mariano; Sodre, Laerte, Jr.; Varela, Jesus; Ramio, Hector Vazquez; Taylor, Keith.Astrophysical surveys rely heavily on the classification of sources as stars, galaxies, or quasars from multiband photometry. Surveys in narrow-band filters allow for greater discriminatory power, but the variety of different types and redshifts of the objects present a challenge to standard template-based methods. In this work, which is part of a larger effort that aims at building a catalogue of quasars from the miniJPAS survey, we present a machine learning-based method that employs convolutional neural networks (CNNs) to classify point-like sources including the information in the measurement errors. We validate our methods using data from the miniJPAS survey, a proof-of-concept project of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) collaboration covering ∼1 deg2 of the northern sky using the 56 narrow-band filters of the J-PAS survey. Due to the scarcity of real data, we trained our algorithms using mocks that were purpose-built to reproduce the distributions of different types of objects that we expect to find in the miniJPAS survey, as well as the properties of the real observations in terms of signal and noise. We compare the performance of the CNNs with other well-established machine learning classification methods based on decision trees, finding that the CNNs improve the classification when the measurement errors are provided as inputs. The predicted distribution of objects in miniJPAS is consistent with the putative luminosity functions of stars, quasars, and unresolved galaxies. Our results are a proof of concept for the idea that the J-PAS survey will be able to detect unprecedented numbers of quasars with high confidence. © 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.This paper has gone through internal review by the J-PAS collaboration. NR acknowledges financial support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) – Finance Code 001. RA was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP). CQ acknowledges financial support from FAPESP (grants 2015/11442-0 and 2019/06766-1) and CAPES – Finance Code 001. IPR was supported by funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowskja-Curie grant agreement number 754510. MPP and SSM were supported by the Programme National de Cosmologie et Galaxies (PNCG) of CNRS/INSU with INP and IN2P3, co-funded by CEA and CNES, the A*MIDEX project (ANR-11-IDEX-0001-02) funded by the ‘Investissements d’Avenir’ French Government program, managed by the French National Research Agency (ANR), and by ANR under contract ANR-14-ACHN-0021. GMS, RMGD, and LADG acknowledge support from the State Agency for Research of the Spanish MCIU through the ‘Center of Excellence Severo Ochoa’ award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709) and the project PID2019-109067-GB100. JCM and SB acknowledge financial support from Spanish Ministry of Science, Innovation, and Universities through the project PGC2018-097585-B-C22. AFS acknowledges support from the Spanish Ministerio de Ciencia e Innovación through project PID2019-109592GB-I00 and the Generalitat Valenciana project PROMETEO/2020/085. RAD acknowledges partial support from CNPq grant 308105/2018-4. AE acknowledges the financial support from the Spanish Ministry of Science and Innovation and the European Union – NextGenerationEU through the Recovery and Resilience Facility project ICTS-MRR-2021-03-CEFCA. LSJ acknowledges support from CNPq (304819/2017-4) and FAPESP (2019/10923-5). This study is based on observations made with the JST250 telescope and PathFinder camera for the miniJPAS project at the Observatorio Astrofísico de Javalambre (OAJ), in Teruel, owned, managed, and operated by the Centro de Estudios de Física del Cosmos de Aragón (CEFCA). We acknowledge the OAJ Data Processing and Archiving Unit (UPAD) for reducing and calibrating the OAJ data used in this work. Funding for OAJ, UPAD, and CEFCA has been provided by the Governments of Spain and Aragón through the Fondo de Inversiones de Teruel; the Aragonese Government through the Research Groups E96, E103, E16_17R, and E16_20R; the Spanish Ministry of Science, Innovation, and Universities (MCIU/AEI/FEDER, UE) with grant PGC2018-097585-B-C21; the Spanish Ministry of Economy and Competitiveness (MINECO/FEDER, UE) under AYA2015-66211-C2-1-P, AYA2015-66211-C2-2, AYA2012-30789, and ICTS-2009-14; and European FEDER funding (FCDD10-4E-867 and FCDD13-4E-2685). Funding for the J-PAS Project has also been provided by the Brazilian agencies FINEP, FAPESP, and FAPERJ and by the National Observatory of Brazil, with additional funding provided by the Tartu Observatory and by the J-PAS Chinese Astronomical Consortium. Funding for the SDSS-III/IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-III/IV acknowledges support and resources from the Center for High Performance Computing at the University of Utah. The SDSS website is www.sdss.org. SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, Center for Astrophysics | Harvard & Smithsonian, the Chilean Participation Group, the French Participation Group, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, the Korean Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).Peer reviewe

Galaxy clusters and groups in the ALHAMBRA Survey

We present a catalogue of 348 galaxy clusters and groups with $0.2<z<1.2$ selected in the 2.78 $deg^2$ ALHAMBRA Survey. The high precision of our photometric redshifts, close to $1\%$, and the wide spread of the seven ALHAMBRA pointings ensure that this catalogue has better mass sensitivity and is less affected by cosmic variance than comparable samples. The detection has been carried out with the Bayesian Cluster Finder (BCF), whose performance has been checked in ALHAMBRA-like light-cone mock catalogues. Great care has been taken to ensure that the observable properties of the mocks photometry accurately correspond to those of real catalogues. From our simulations, we expect to detect galaxy clusters and groups with both $70\%$ completeness and purity down to dark matter halo masses of $M_h\sim3\times10^{13}\rm M_{\odot}$ for $z<0.85$. Cluster redshifts are expected to be recovered with $\sim0.6\%$ precision for $z<1$. We also expect to measure cluster masses with $\sigma_{M_h|M^*_{CL}}\sim0.25-0.35\, dex$ precision down to $\sim3\times10^{13}\rm M_{\odot}$, masses which are $50\%$ smaller than those reached by similar work. We have compared these detections with previous optical, spectroscopic and X-rays work, finding an excellent agreement with the rates reported from the simulations. We have also explored the overall properties of these detections such as the presence of a colour-magnitude relation, the evolution of the photometric blue fraction and the clustering of these sources in the different ALHAMBRA fields. Despite the small numbers, we observe tentative evidence that, for a fixed stellar mass, the environment is playing a crucial role at lower redshifts (z$<$0.5).Comment: Accepted for publication in MNRAS. Catalogues and figures available online and under the following link: http://bascaso.net46.net/ALHAMBRA_clusters.htm

The impact from survey depth and resolution on the morphological classification of galaxies

We consistently analyse for the first time the impact of survey depth and spatial resolution on the most used morphological parameters for classifying galaxies through non-parametric methods: Abraham and Conselice-Bershady concentration indices, Gini, M20moment of light, asymmetry, and smoothness. Three different non-local data sets are used, Advanced Large Homogeneous Area Medium Band Redshift Astronomical (ALHAMBRA) and Subaru/XMMNewton Deep Survey (SXDS, examples of deep ground-based surveys), and Cosmos Evolution Survey (COSMOS, deep space-based survey). We used a sample of 3000 local, visually classified galaxies, measuring their morphological parameters at their real redshifts (z ~ 0). Then we simulated them to match the redshift and magnitude distributions of galaxies in the non-local surveys. The comparisons of the two sets allow us to put constraints on the use of each parameter for morphological classification and evaluate the effectiveness of the commonly used morphological diagnostic diagrams. All analysed parameters suffer from biases related to spatial resolution and depth, the impact of the former being much stronger. When including asymmetry and smoothness in classification diagrams, the noise effects must be taken into account carefully, especially for ground-based surveys. M20 is significantly affected, changing both the shape and range of its distribution at all brightness levels. We suggest that diagnostic diagrams based on 2-3 parameters should be avoided when classifying galaxies in ground-based surveys, independently of their brightness; for COSMOS they should be avoided for galaxies fainter than F814 = 23.0. These results can be applied directly to surveys similar to ALHAMBRA, SXDS and COSMOS, and also can serve as an upper/lower limit for shallower/deeper ones.MP acknowledge financial support from JAE-Doc programme of the Spanish National Research Council (CSIC), co-funded by the European Social Fund. This research was supported by the Junta de Andalucia through project TIC114, and the Spanish Ministry of Economy and Competitiveness (MINECO) through projects AYA2010-15169, AYA2013-42227-P, and AYA2013-43188-P.Peer Reviewe

The ALHAMBRA survey: reliable morphological catalogue of 22 051 early- and late-type galaxies

Advanced Large Homogeneous Area Medium Band Redshift Astronomical (ALHAMBRA) is photometric survey designed to trace the cosmic evolution and cosmic variance. It covers a large area of ~4 deg2 in eight fields, where seven fields overlap with other surveys, allowing us to have complementary data in other wavelengths. All observations were carried out in 20 continuous, medium band (30 nm width) optical and 3 near-infrared (JHK) bands, providing the precise measurements of photometric redshifts. In addition, morphological classification of galaxies is crucial for any kind of galaxy formation and cosmic evolution studies, providing the information about star formation histories, their environment and interactions, internal perturbations, etc. We present a morphological classification of >40 000 galaxies in the ALHAMBRA survey. We associate to every galaxy a probability to be early type using the automated Bayesian code GALSVM. Despite of the spatial resolution of theALHAMBRAimages (~1 arcsec), for 22 051 galaxies, we obtained the contamination by other type of less than 10 per cent. Of those, 1640 and 10 322 galaxies are classified as early-(down to redshifts ~0.5) and late-type (down to redshifts ~1.0), respectively, with magnitudes F613W ≤ 22.0. In addition, for magnitude range 22.0 < F613W ≤ 23.0, we classified other 10 089 late-type galaxies with redshifts ≤1.3.We show that the classified objects populate the expected regions in the colour-mass and colour-magnitude planes. The presented data set is especially attractive given the homogeneous multiwavelength coverage available in the ALHAMBRA fields, and is intended to be used in a variety of scientific applications. The low-contamination catalogue (<10 per cent) is made publicly available with this paper. © 2013 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.This research was supported by the Junta de Andalucía through projects PO8-TIC-03531 and TIC114, the Spanish Ministry of Economy and Competitiveness (MINECO) through projects AYA2006-14046, AYA2010-15169, AYA2010-22111-C03-02, AYA2011-29517-C03-01, and the Generalitat Valenciana through project GV/Prometeo 2009/064. MP acknowledges financial support from JAE-Doc program of the Spanish National Research Council (CSIC), co-funded by the European Social Fund.Peer Reviewe

The miniJPAS survey quasar selection IV: Classification and redshift estimation with SQUEzE

We present a list of quasar candidates including photometric redshift estimates from the miniJPAS Data Release constructed using SQUEzE. This work is based on machine-learning classification of photometric data of quasar candidates using SQUEzE. It has the advantage that its classification procedure can be explained to some extent, making it less of a `black box' when compared with other classifiers. Another key advantage is that using user-defined metrics means the user has more control over the classification. While SQUEzE was designed for spectroscopic data, here we adapt it for multi-band photometric data, i.e. we treat multiple narrow-band filters as very low-resolution spectra. We train our models using specialized mocks from Queiroz et al. (2022). We estimate our redshift precision using the normalized median absolute deviation, $\sigma_{\rm NMAD}$ applied to our test sample. Our test sample returns an $f_1$ score (effectively the purity and completeness) of 0.49 for quasars down to magnitude $r=24.3$ with $z\geq2.1$ and 0.24 for quasars with $z<2.1$. For high-z quasars, this goes up to 0.9 for $r<21.0$. We present two catalogues of quasar candidates including redshift estimates: 301 from point-like sources and 1049 when also including extended sources. We discuss the impact of including extended sources in our predictions (they are not included in the mocks), as well as the impact of changing the noise model of the mocks. We also give an explanation of SQUEzE reasoning. Our estimates for the redshift precision using the test sample indicate a $\sigma_{NMAD}=0.92\%$ for the entire sample, reduced to 0.81\% for $r<22.5$ and 0.74\% for $r<21.3$. Spectroscopic follow-up of the candidates is required in order to confirm the validity of our findings.Comment: Accepted in A&A 24 pages, 24 figures, 7 table

The ALHAMBRA survey: Bayesian photometric redshifts with 23 bands for 3 deg2

A. Molino et al.The Advance Large Homogeneous Area Medium-Band Redshift Astronomical (ALHAMBRA) survey has observed eight different regions of the sky, including sections of the Cosmic Evolution Survey (COSMOS), DEEP2, European Large-Area Infrared Space Observatory Survey (ELAIS), Great Observatories Origins Deep Survey North (GOODS-N), Sloan Digital Sky Survey (SDSS) and Groth fields using a new photometric system with 20 optical, contiguous ~300-Å filters plus the JHKs bands. The filter system is designed to optimize the effective photometric redshift depth of the survey, while having enough wavelength resolution for the identification of faint emission lines. The observations, carried out with the Calar Alto 3.5-m telescope using the wide-field optical camera Large Area Imager for Calar Alto (LAICA) and the near-infrared (NIR) instrument Omega-2000, represent a total of ~700 h of on-target science images. Here we present multicolour point-spread function (PSF) corrected photometry and photometric redshifts for ~438 000 galaxies, detected in synthetic F814W images. The catalogues are complete down to a magnitude I~24.5AB and cover an effective area of 2.79 deg2. Photometric zero-points were calibrated using stellar transformation equations and refined internally, using a new technique based on the highly robust photometric redshifts measured for emission-line galaxies. We calculate Bayesian photometric redshifts with the Bayesian Photometric Redshift (BPZ)2.0 code, obtaining a precision of δz/(1+zs)=1 per cent for I<22.5 and δz/(1+zs)=1.4 per cent for 22.5<I<24.5. The global n(z) distribution shows a mean redshift 〈z〉=0.56 for I<22.5 AB and 〈z〉=0.86 for I<24.5 AB. Given its depth and small cosmic variance, ALHAMBRA is a unique data set for galaxy evolution studies. © 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.We acknowledge financial support from the Spanish MICINN under the Consolider-Ingenio 2010 Program grant CSD2006-00070: First Science with the GTC. Part of this work was supported by Junta de Andalucía, through grant TIC-114 and the Excellence Project P08-TIC-3531, and by the Spanish Ministry for Science and Innovation through grants AYA2006-1456, AYA2010-15169, AYA2010-22111-C03-02, AYA2010-22111-C03-01 and Generalitat Valenciana project Prometeo 2009/064.Peer Reviewe

The miniJPAS survey: Identification and characterization of galaxy populations with the J-PAS photometric system

Full list of authors: González Delgado, R. M.; Díaz-García, L. A.; de Amorim, A.; Bruzual, G.; Cid Fernandes, R.; Pérez, E.; Bonoli, S.; Cenarro, A. J.; Coelho, P. R. T.; Cortesi, A.; García-Benito, R.; López Fernández, R.; Martínez-Solaeche, G.; Rodríguez-Martín, J. E.; Magris, G.; Mejía-Narvaez, A.; Brito-Silva, D.; Abramo, L. R.; Diego, J. M. ; Dupke, R. A.; Hernán-Caballero, A.; Hernández-Monteagudo, C.; López-Sanjuan, C.; Marín-Franch, A.; Marra, V.; Moles, M.; Montero-Dorta, A.; Queiroz, C.; Sodré, L.; Varela, J.; Vázquez Ramió, H.; Vílchez, J. M.; Baqui, P. O.; Benítez, N.; Cristóbal-Hornillos, D.; Ederoclite, A.; Mendes de Oliveira, C.; Civera, T.; Muniesa, D.; Taylor, K.; Tempel, E.; J-PAS Collaboration.The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will soon start imaging thousands of square degrees of the northern sky with its unique set of 56 filters (spectral resolution of R - 60). Before the arrival of the final instrument, we observed 1 deg2 on the AEGIS field with an interim camera with all the J-PAS filters. Taking advantage of these data, dubbed miniJPAS, we aim at proving the scientific potential of the J-PAS to derive the stellar population properties of galaxies via fitting codes for spectral energy distributions (SEDs), with the ultimate goal of performing galaxy evolution studies across cosmic time. One parametric (BaySeAGal) and three non-parametric (MUFFIT, AlStar, and TGASPEX) SED-fitting codes are used to constrain the stellar mass, age, metallicity, extinction, and rest-frame and dust-corrected (u-r) colours of a complete flux-limited sample (rSDSS - 22.5 AB) of miniJPAS galaxies that extends up to z = 1. We generally find consistent results on the galaxy properties derived from the different codes, independently of the galaxy spectral type or redshift; this is remarkable considering that 25% of the J-spectra have signal-to-noise ratios (S/N) -3. For galaxies with S=N - 10, we estimate that the J-PAS photometric system will allow us to derive the stellar population properties of rest-frame (u - r) colour, stellar mass, extinction, and mass-weighted age with a precision of 0:04 - 0:02 mag, 0:07 - 0:03 dex, 0:2 - 0:09 mag, and 0:16 - 0:07 dex, respectively. This precision is equivalent to that obtained with spectroscopic surveys of similar S/N. By using the dust-corrected (u - r) colour mass diagram, a powerful proxy for characterizing galaxy populations, we find: (i) that the fraction of red and blue galaxies evolves with cosmic time, with red galaxies being -38% and -18% of the whole population at z = 0:1 and z = 0:5, respectively, and (ii) consistent results between codes for the average intrinsic (u-r) colour, stellar mass, age, and stellar metallicity of blue and red galaxies and their evolution up to z = 1. At all redshifts, the more massive galaxies belong to the red sequence, and these galaxies are typically older and more metal-rich than their counterparts in the blue cloud. Our results confirm that with J-PAS data we will be able to analyse large samples of galaxies up to z - 1, with galaxy stellar masses above log(M?=M-) - 8:9, 9.5, and 9.9 at z = 0:3, 0.5, and 0.7, respectively. The star formation history of a complete sub-sample of galaxies selected at z - 0:1 with log(M=M-) > 8:3 constrains the cosmic evolution of the star formation rate density up to z - 3, in good agreement with results from cosmological surveys. © ESO 2021.Acknowledgements. R.G.D., L.A.D.G., R.G.B., G.M.S., J.R.M., and E.P. acknowledge financial support from the State Agency for Research of the Spanish MCIU through the “Center of Excellence Severo Ochoa” award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709), and to the AYA2016-77846-P and PID2019-109067-GB100. L.A.D.G. also acknowledges financial support by the Ministry of Science and Technology of Taiwan (grant MOST 106-2628-M-001-003-MY3) and by the Academia Sinica (grant AS-IA-107-M01). G.B. acknowledges financial support from the National Autonomous University of México (UNAM) through grant DGAPA/PAPIIT IG100319 and from CONACyT through grant CB2015-252364. SB acknowledges PGC2018-097585-B-C22, MINECO/FEDER, UE of the Spanish Ministerio de Econo-mia, Industria y Competitividad. L.S.J. acknowledges support from Brazilian agencies FAPESP (2019/10923-5) and CNPq (304819/201794). P.O.B. acknowledges support from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. P.R.T.C. acknowledges financial support from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) process number 2018/05392-8 and Conselho Nacional de Desenvolvi-mento Científico e Tecnológico (CNPq) process number 310041/2018-0. V.M. thanks CNPq (Brazil) for partial financial support. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 888258. E.T. acknowledges support by ETAg grant PRG1006 and by EU through the ERDF CoE grant TK133. Based on observations made with the JST/T250 telescope and PathFinder camera for the miniJPAS project at the Observatorio Astrofísico de Javalambre (OAJ), in Teruel, owned, managed, and operated by the Centro de Estudios de Física del Cosmos de Aragón (CEFCA). We acknowledge the OAJ Data Processing and Archiving Unit (UPAD) for reducing and calibrating the OAJ data used in this work. Funding for OAJ, UPAD, and CEFCA has been provided by the Governments of Spain and Aragón through the Fondo de Inver-siones de Teruel; the Aragón Government through the Research Groups E96, E103, and E16_17R; the Spanish Ministry of Science, Innovation and Universities (MCIU/AEI/FEDER, UE) with grant PGC2018-097585-B-C21; the Spanish Ministry of Economy and Competitiveness (MINECO/FEDER, UE) under AYA2015-66211-C2-1-P, AYA2015-66211-C2-2, AYA2012-30789, and ICTS-2009-14; and European FEDER funding (FCDD10-4E-867, FCDD13-4E-2685).Peer reviewe