J-PLUS: las regiones de formación estelar extrema en el Universo a bajo desplazamiento al rojo

En este trabajo se analizan clumps de formación estelar intensa en EELGs a bajo redshift detectados por las utilidades del NoiseChisel y Segment recientemente añadidas al paquete GNUAstro para la manipulación y análisis de datos astronómicos. Se valida su correcto funcionamiento y se concluye que las imágenes del cartografiado JPLUS son suficientemente precisas para el estudio de estos clumps. Una vez identificados los clumps, se analiza la información fotométrica dada por JPLUS con el software CIGALE y se concluyen algunas propiedades de ellos.<br /

Evolution of the anti-truncated stellar profiles of SO galaxies since z=0.6 in the SHARDS survey II. Structural and photometric evolution

Context. Anti-truncated lenticular galaxies (Type-III S0s) present tight scaling relations between their surface brightness photometric and structural parameters. Although several evolutionary models have been proposed for the formation of these structures, the observations of Type-III S0 galaxies are usually limited to the local Universe. Aims. We aim to compare the properties of Type-III discs in a sample of S0 galaxies at 0.2 < z < 0.6with those of the local Universe. In this paper, we study the evolution of the photometric and structural scaling relations measured in the rest-frame R-band with z and the possible differences between the rest-frame (B - R) colours of the inner and outer disc profiles. Methods. We make use of a sample of 14 Type-III E/ S0-S0 galaxies at 0.2 < z < 0 : 6 from the GOODS-N field identified and characterised in a previous paper. We study whether or not the correlations found in local Type-III S0 galaxies were present similar to 6 Gyr ago. We analyse the distribution of the surface brightness characteristic parameters (R-break, mu(break), h(i), h(o), mu(0;) i and mu(0; o)) as a function of the stellar mass and look to see if there is a significant change with z. We also derive their rest-frame (B - R) colour profiles. Finally, we compare these results with the predictions from a grid of SSP models. Results. We find that the inner and outer scale-lengths of Type-III S0 galaxies at 0.4 < z < 0.6follow compatible trends and scaling relations with those observed in local S0 galaxies as a function of the break radius, R-break. We do not detect any significant differences between the location of R-break between z similar to 0.6 and z similar to 0 for a fixed stellar mass of the object, whereas the surface brightness at the break radius mu(break) is similar to 1.5 mag arcsec 2 dimmer in the local Universe than at z similar to 0.6 for a fixed stellar mass. We find no significant differences in the (B - R) colour between the inner and outer profiles of the Type-III S0 galaxies at 0.2 < z < 0.6. Conclusions. In contrast to Type-II (down-bending) profiles, the anti-truncated surface brightness profiles of S0 galaxies present compatible R-break values and scaling relations during the last 6 Gyr. This result and the similarity of the colours of the inner and outer discs point to a highly scalable and stable formation process, probably more related to gravitational and dynamical processes than to the evolution of stellar populations

Probing the Star Formation Main Sequence down to 10810^{8} M⊙_\odot at 1.0<z<3.01.0<z<3.0

We investigate the star formation main sequence (MS) (SFR-M$_{\star}$) down to 10$^{8-9}\mathrm{M}_\odot$ using a sample of 34,061 newly-discovered ultra-faint ($27\lesssim i \lesssim 30$ mag) galaxies at $1<z<3$ detected in the GOODS-N field. Virtually these galaxies are not contained in previous public catalogs, effectively doubling the number of known sources in the field. The sample was constructed by stacking the optical broad-band observations taken by the HST/GOODS-CANDELS surveys as well as the 25 ultra-deep medium-band images gathered by the GTC/SHARDS project. Our sources are faint (average observed magnitudes $\sim28.2$ mag, $\sim27.9$ mag), blue (UV-slope $\sim-1.9$), star-forming (rest-frame colors $\sim0.10$ mag, $\sim0.17$ mag) galaxies. These observational characteristics are identified with young (mass-weighted age $\sim0.014$ Gyr) stellar populations subject to low attenuations ($\sim0.30$ mag). Our sample allows us to probe the MS down to $10^{8.0}\,\mathrm{M}_\odot$ at $z=1$ and $10^{8.5}\,\mathrm{M}_\odot$ at $z=3$, around 0.6 dex deeper than previous analysis. In the low-mass galaxy regime, we find an average value for the slope of 0.97 at $1<z<2$ and 1.12 at $2<z<3$. Nearly $\sim$60% of our sample presents stellar masses in the range $10^{6-8}$ M$_\odot$ between $1<z<3$. If the slope of the MS remained constant in this regime, the sources populating the low-mass tail of our sample would qualify as starburst galaxies.Comment: 34 pages, 16 figures, 9 tables. Accepted for publication to Ap

Clinical Characteristics and Prognosis of COPD Patients Hospitalized with SARS-CoV-2

Objective To describe the characteristics and prognosis of patients with COPD admitted to the hospital due to SARS-CoV-2 infection. Methods The SEMI-COVID registry is an ongoing retrospective cohort comprising consecutive COVID-19 patients hospitalized in Spain since the beginning of the pandemic in March 2020. Data on demographics, clinical characteristics, comorbidities, laboratory tests, radiology, treatment, and progress are collected. Patients with COPD were selected and compared to patients without COPD. Factors associated with a poor prognosis were analyzed. Results Of the 10,420 patients included in the SEMI-COVID registry as of May 21, 2020, 746 (7.16%) had a diagnosis of COPD. Patients with COPD are older than those without COPD (77 years vs 68 years) and more frequently male. They have more comorbidities (hypertension, hyperlipidemia, diabetes mellitus, atrial fibrillation, heart failure, ischemic heart disease, peripheral vascular disease, kidney failure) and a higher Charlson Comorbidity Index (2 vs 1, p<0.001). The mortality rate in COPD patients was 38.3% compared to 19.2% in patients without COPD (p<0.001). Male sex, a history of hypertension, heart failure, moderate–severe chronic kidney disease, presence of cerebrovascular disease with sequelae, degenerative neurological disease, dementia, functional dependence, and a higher Charlson Comorbidity Index have been associated with increased mortality due to COVID-19 in COPD patients. Survival was higher among patients with COPD who were treated with hydroxychloroquine (87.1% vs 74.9%, p<0.001) and with macrolides (57.9% vs 50%, p<0.037). Neither prone positioning nor non-invasive mechanical ventilation, high-flow nasal cannula, or invasive mechanical ventilation were associated with a better prognosis. Conclusion COPD patients admitted to the hospital with SARS-CoV-2 infection have more severe disease and a worse prognosis than non-COPD patients

The missing light of the Hubble Ultra Deep Field

Context. The Hubble Ultra Deep field (HUDF) is the deepest region ever observed with the Hubble Space Telescope. With the main objective of unveiling the nature of galaxies up to z ∼ 7−8, the observing and reduction strategy have focused on the properties of small and unresolved objects, rather than the outskirts of the largest objects, which are usually over-subtracted. Aims. We aim to create a new set of WFC3 IR mosaics of the HUDF using novel techniques to preserve the properties of the low surface brightness regions. Methods. We created ABYSS: a pipeline that optimises the estimate and modelling of low-level systematic effects to obtain a robust background subtraction. We have improved four key points in the reduction: 1) creation of new absolute sky flat fields, 2) extended persistence models, 3) dedicated sky background subtraction and 4) robust co-adding. Results. The new mosaics successfully recover the low surface brightness structure removed on the previous HUDF published reductions. The amount of light recovered with a mean surface brightness dimmer than µ = 26 mag arcsec^(−2) is equivalent to a m = 19 mag source when compared to the XDF and a m = 20 mag compared to the HUDF12. Conclusions. We present a set of techniques to reduce ultra-deep images ( µ > 32.5 mag arcsec^(−2) , 3σ in 10 × 10 arcsec boxes), that successfully allow us to detect the low surface brightness structure of extended sources on ultra deep surveys. The developed procedures are applicable to HST, JWST, EUCLID and many other space and ground-based observatories

Healthcare workers hospitalized due to COVID-19 have no higher risk of death than general population. Data from the Spanish SEMI-COVID-19 Registry

Aim To determine whether healthcare workers (HCW) hospitalized in Spain due to COVID-19 have a worse prognosis than non-healthcare workers (NHCW). Methods Observational cohort study based on the SEMI-COVID-19 Registry, a nationwide registry that collects sociodemographic, clinical, laboratory, and treatment data on patients hospitalised with COVID-19 in Spain. Patients aged 20-65 years were selected. A multivariate logistic regression model was performed to identify factors associated with mortality. Results As of 22 May 2020, 4393 patients were included, of whom 419 (9.5%) were HCW. Median (interquartile range) age of HCW was 52 (15) years and 62.4% were women. Prevalence of comorbidities and severe radiological findings upon admission were less frequent in HCW. There were no difference in need of respiratory support and admission to intensive care unit, but occurrence of sepsis and in-hospital mortality was lower in HCW (1.7% vs. 3.9%; p = 0.024 and 0.7% vs. 4.8%; p<0.001 respectively). Age, male sex and comorbidity, were independently associated with higher in-hospital mortality and healthcare working with lower mortality (OR 0.211, 95%CI 0.067-0.667, p = 0.008). 30-days survival was higher in HCW (0.968 vs. 0.851 p<0.001). Conclusions Hospitalized COVID-19 HCW had fewer comorbidities and a better prognosis than NHCW. Our results suggest that professional exposure to COVID-19 in HCW does not carry more clinical severity nor mortality

The miniJPAS survey quasar selection I: Mock catalogues for classification

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper we develop a pipeline to compute synthetic photometry of quasars, galaxies and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey. To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range $17.5\leq r<24$, we augment our sample of available spectra by shifting the original $r$-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modeling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys

The miniJPAS survey quasar selection I: Mock catalogues for classification

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper we develop a pipeline to compute synthetic photometry of quasars, galaxies and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey. To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range $17.5\leq r<24$, we augment our sample of available spectra by shifting the original $r$-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modeling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys

The miniJPAS survey quasar selection I: Mock catalogues for classification

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper we develop a pipeline to compute synthetic photometry of quasars, galaxies and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey. To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range $17.5\leq r<24$, we augment our sample of available spectra by shifting the original $r$-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modeling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60&nbsp;years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death.&nbsp;The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death