The PAU survey: classifying low-z SEDs using Machine Learning clustering

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record Monthly Notices of the Royal Astronomical Society 524.3 (2023): 3569-3581 is available online at: https://academic.oup.com/mnras/article-abstract/524/3/3569/7225529?redirectedFrom=fulltextWe present an application of unsupervised Machine Learning clustering to the PAU survey of galaxy spectral energy distribution (SED) within the COSMOS field. The clustering algorithm is implemented and optimized to get the relevant groups in the data SEDs. We find 12 groups from a total number of 5234 targets in the survey at 0.01 < z < 0.28. Among the groups, 3545 galaxies (68 per cent) show emission lines in the SEDs. These groups also include 1689 old galaxies with no active star formation. We have fitted the SED to every single galaxy in each group with CIGALE. The mass, age, and specific star formation rates (sSFR) of the galaxies range from 0.15 < age/Gyr <11; 6 < log (M/M⊙) <11.26, and -14.67 < log (sSFR/yr-1) <-8. The groups are well-defined in their properties with galaxies having clear emission lines also having lower mass, are younger and have higher sSFR than those with elliptical like patterns. The characteristic values of galaxies showing clear emission lines are in agreement with the literature for starburst galaxies in COSMOS and GOODS-N fields at low redshift. The star-forming main sequence, sSFR versus stellar mass and UVJ diagram show clearly that different groups fall into different regions with some overlap among groups. Our main result is that the joint of low- resolution (R ∼50) photometric spectra provided by the PAU survey together with the unsupervised classification provides an excellent way to classify galaxies. Moreover, it helps to find and extend the analysis of extreme ELGs to lower masses and lower SFRs in the local UniverseThis work has been supported by the Ministry of Science and Innovation of Spain, project PID2019-107408GB-C43 (ESTALLIDOS), and the Government of the Canary Islands through EU FEDER funding, projects PID2020010050 and PID2021010077. This article is based on observations made in the Observatorios de Canarias of the Instituto de Astrofísica de Canarias (IAC) with the WHT operated on the island of La Palma by the Isaac Newton Group of Telescopes (ING) in the Observatorio del Roque de los Muchachos. The PAU Survey is partially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2017-89838, PGC2018-094773, PGC2018-102021, PID2019-111317GB, SEV-2016-0588, SEV-2016-0597, MDM-2015-0509 and Juan de la Cierva fellowship and LACEGAL and EWC Marie Sklodowska-Curie grant No 734374 and no.776247 with ERDF funds from the EU Horizon 2020 Programme, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA and Beatriu de Pinos program of the Generalitat de Catalunya. Funding for PAUS has also been provided by Durham Univer sity (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scientific Research (NWO) Vici grant 639.043.512), University College London and from the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 776247 EWC. The PAU data center is hosted by the Port d’Información Científica (PIC), maintained through a collaboration of CIEMAT and IFAE, with additional support from Universitat Autónoma de Barcelona and ERDF. We acknowledge the PIC services department team for their support and fruitful discussion

CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Efecto de la densidad de siembra y nivel de fertilizacion nitrogenada sobre el rendimiento de Moringa oleifera en suelo franco arcilloso. Universidad Nacional Agraria (UNA). Managua, Nicaragua

El presente trabajo se realizó con el objetivo de evaluar el efecto de dos densidades de siembra y cuatro niveles nitrogenados sobre la producción de Moringa oleífera. El ensayo se llevó a cabo en la finca Santa Rosa, localizada geográficamente de 12°08’15’’ a latitud Norte y 86°09’36’’ a longitud e ste, municipio de Managua, de mayo 2008 a septiembre 2009; el diseño experimental fue un bifactorial con parcela dividida usando las densidades como parcela principal (100,000 plantas ha-1 y 166,666 plantas ha-1) y los niveles de fertilización (0 kg N ha año-1, 446 kg N ha año-1, 906.2 kg N ha año-1, 1334 kg N ha año-1)como sub -parcela. Las variables de estudio fueron: rendimiento de materia fresca total (RMFT), rendimiento de materia fresca fracción fina (RMFFF), rendimiento de materia fresca fracción gruesa (RMFFG), rendimiento de materia seca total (RMST), rendimiento de materia seca fracción fina (RMSFF), rendimiento de materia seca fracción gruesa (RMFFG), a ltura promedio de plantas, Mortalidad de plantas y Tasa de crecimiento (TC). Se realizó análisis de varianza (ANDEVA) y comparaciones con la prueba de Tukey utilizando MINITAB, versión 13.0. Los resultados en el ANDEVA, mostraron que la fertilización presentó efecto significativo (P<0.05) con los mejores rendimientos el nivel 150 %, con RMFT (69.17 to n ha año-1), RMFFF (60.72 ton ha año-1), RMFG (8.45 ton ha año-1), RMST (10.81 ton ha año-1), RMSFF (9.69 ton ha año -1), RMSFG (1.12 ton ha año-1), Altura de las plantas(1.33 m) y TC( 28.91), la densidad de siembra presentó efectos significativos (P<0.05)sólo para la variable Mortalidad con (18.08 %)

Evaluación de la aplicación del mix-marketing por parte del sector de Hospedería Mayor del Municipio de León en el período compredido de febrero-agosto del año 2009

Tesis (Lic. en Mercadotecnia)-Universidad Nacional Autónoma de Nicaragua, LeónEvaluación de la aplicación del Mix-marketing por parte del sector de hospedería mayor del municipio de León en el período de Febrero – Agosto del año 2009.UNAN-Leó

Propuesta de un plan de desarrollo turístico para el Municipio de Corinto

Tesis (Lic. en Gestión de Empresas Turísticas)-Universidad Nacional Autónoma de Nicaragua, LeónUNAN-Leó