87 research outputs found

    Period Change Rates of Large Magellanic Cloud Cepheids using MESA

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    Pulsating stars, such as Cepheids and RR Lyrae, offer us a window to measure and study changes due to stellar evolution. In this work, we study the former by calculating a set of evolutionary tracks of stars with an initial mass of 4 to 7 MM_\odot, varying the initial rotation rate and metallicity, using the stellar evolution code Modules for Experiments in Stellar Astrophysics (MESA). Using Radial Stellar Pulsations (RSP), a recently added functionality of MESA, we obtained theoretical instability strip (IS) edges and linear periods for the radial fundamental mode. Period-age, period-age-temperature, period-luminosity, and period-luminosity-temperature relationships were derived for three rotation rates and metallicities, showing a dependence on crossing number, position in the IS, rotation, and metallicity. We calculated period change rates (PCRs) based on the linear periods from RSP. We compared our models with literature results using the Geneva code, and found large differences, as expected due to the different implementations of rotation between codes. In addition, we compared our theoretical PCRs with those measured in our recent work for Large Magellanic Cloud Cepheids. We found good overall agreement, even though our models do not reach the short-period regime exhibited by the empirical data. Implementations of physical processes not yet included in our models, such as pulsation-driven mass loss, an improved treatment of convection that may lead to a better description of the instability strip edges, as well as consideration of a wider initial mass range, could all help improve the agreement with the observed PCRs.Comment: 19 pages, 17 figures. Accepted by MNRA

    Características clínicas del estado epiléptico en niños de un hospital de tercer nivel de Lima.

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    Status Epilepticus (SE) in children exhibits high levels of morbidity and mortality and has been poorly studied in Perú. Objective: To describe the frequency and clinical characteristics of children with Status Epilepticus treated at Cayetano Heredia Hospital in Lima. Material and Methods: Retrospective and observational study, case series type, in children under 14 years of age, with Status Epilepticus treated between January and December of 2021. Results: SE was recorded in 28.8% of children with epileptic seizures seen during 2021. Twenty-three children presenting 46 SEs were included. The median age was 2 years, the majority (73,9%) being males, with diagnosis of epilepsy or brain malformation (21.7%) and treated in the pediatric emergency (91%). The predominant semiological pattern was of generalized motor type (52.2%), with remote symptomatic etiology (73.9%), and EEG recorded in a 63% of all cases, mainly reported as normal (75,9%). The median duration was 22 minutes of total resolution, 7 minutes, and of partial resolution, 2 minutes. Midazolam was used as the first line of treatment (78%), and phenytoin as the second line (85%). Conclusions: SE was a frequent condition observed in children throughout the year 2021. Most affected children were male, the predominant etiology was remote symptomatic, and the most common semiological type was the generalized motor. The children were treated according to international management guidelines. A systematic epidemiological surveillance approach is highly encouraged.El estado epiléptico (EE) en niños exhibe altos niveles de morbi-mortalidad y ha sido poco estudiado en el Perú. Objetivo: Describir la frecuencia y características clínicas de niños con estado epiléptico, atendidos en el Hospital Cayetano Heredia de Lima. Material y métodos: Estudio retrospectivo y observacional, tipo serie de casos de niños menores de 14 años con diagnóstico de estado epiléptico, atendidos entre enero y diciembre de 2021. Resultados: Se registró EE en un 28,8% de todos los niños atendidos por crisis epilépticas durante el año 2021. Se incluyeron 23 niños que presentaron 46 EE, varones (73,9%), con una mediana de la edad de 2 años, diagnóstico subyacente de epilepsia o malformación cerebral (21,7%), atendidos en emergencia pediátrica (91%). El tipo semiológico predominante fue el EE motor generalizado (52,2%), con etiología sintomática remota (87%) y EEG registrado en un 63% de los casos, predominantemente de tipo normal (75,9%). La mediana de duración fue de 22 minutos, de resolución total, 7 minutos y resolución parcial, 2 minutos. Se empleó midazolam (78%) como primera línea de tratamiento y fenitoína (85%), como segunda línea. Conclusiones: El EE en niños fue una emergencia prevalente durante el año 2021. La mayoría fueron varones, cuya etiología predominante fue sintomática remota y el tipo semiológico más común fue el motor generalizado. Los niños fueron atendidos de acuerdo con las guías internacionales de manejo. Se insiste en la necesidad de un sistemático afronte de vigilancia epidemiológica

    Deep Drilling in the Time Domain with DECam: Survey Characterization

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    This paper presents a new optical imaging survey of four deep drilling fields (DDFs), two Galactic and two extragalactic, with the Dark Energy Camera (DECam) on the 4 meter Blanco telescope at the Cerro Tololo Inter-American Observatory (CTIO). During the first year of observations in 2021, >>4000 images covering 21 square degrees (7 DECam pointings), with \sim40 epochs (nights) per field and 5 to 6 images per night per filter in gg, rr, ii, and/or zz, have become publicly available (the proprietary period for this program is waived). We describe the real-time difference-image pipeline and how alerts are distributed to brokers via the same distribution system as the Zwicky Transient Facility (ZTF). In this paper, we focus on the two extragalactic deep fields (COSMOS and ELAIS-S1), characterizing the detected sources and demonstrating that the survey design is effective for probing the discovery space of faint and fast variable and transient sources. We describe and make publicly available 4413 calibrated light curves based on difference-image detection photometry of transients and variables in the extragalactic fields. We also present preliminary scientific analysis regarding Solar System small bodies, stellar flares and variables, Galactic anomaly detection, fast-rising transients and variables, supernovae, and active galactic nuclei.Comment: 22 pages, 17 figures, 2 tables. Accepted to MNRA

    SARS-CoV-2 viral load in nasopharyngeal swabs is not an independent predictor of unfavorable outcome

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    The aim was to assess the ability of nasopharyngeal SARS-CoV-2 viral load at first patient’s hospital evaluation to predict unfavorable outcomes. We conducted a prospective cohort study including 321 adult patients with confirmed COVID-19 through RT-PCR in nasopharyngeal swabs. Quantitative Synthetic SARS-CoV-2 RNA cycle threshold values were used to calculate the viral load in log10 copies/mL. Disease severity at the end of follow up was categorized into mild, moderate, and severe. Primary endpoint was a composite of intensive care unit (ICU) admission and/or death (n = 85, 26.4%). Univariable and multivariable logistic regression analyses were performed. Nasopharyngeal SARS-CoV-2 viral load over the second quartile (≥ 7.35 log10 copies/mL, p = 0.003) and second tertile (≥ 8.27 log10 copies/mL, p = 0.01) were associated to unfavorable outcome in the unadjusted logistic regression analysis. However, in the final multivariable analysis, viral load was not independently associated with an unfavorable outcome. Five predictors were independently associated with increased odds of ICU admission and/or death: age ≥ 70 years, SpO2, neutrophils > 7.5 × 103/µL, lactate dehydrogenase ≥ 300 U/L, and C-reactive protein ≥ 100 mg/L. In summary, nasopharyngeal SARS-CoV-2 viral load on admission is generally high in patients with COVID-19, regardless of illness severity, but it cannot be used as an independent predictor of unfavorable clinical outcome

    Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

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    Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

    Computational approaches to Explainable Artificial Intelligence:Advances in theory, applications and trends

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    Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.</p

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

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    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

    Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

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    The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

    Strong Interaction Physics at the Luminosity Frontier with 22 GeV Electrons at Jefferson Lab

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    This document presents the initial scientific case for upgrading the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab (JLab) to 22 GeV. It is the result of a community effort, incorporating insights from a series of workshops conducted between March 2022 and April 2023. With a track record of over 25 years in delivering the world's most intense and precise multi-GeV electron beams, CEBAF's potential for a higher energy upgrade presents a unique opportunity for an innovative nuclear physics program, which seamlessly integrates a rich historical background with a promising future. The proposed physics program encompass a diverse range of investigations centered around the nonperturbative dynamics inherent in hadron structure and the exploration of strongly interacting systems. It builds upon the exceptional capabilities of CEBAF in high-luminosity operations, the availability of existing or planned Hall equipment, and recent advancements in accelerator technology. The proposed program cover various scientific topics, including Hadron Spectroscopy, Partonic Structure and Spin, Hadronization and Transverse Momentum, Spatial Structure, Mechanical Properties, Form Factors and Emergent Hadron Mass, Hadron-Quark Transition, and Nuclear Dynamics at Extreme Conditions, as well as QCD Confinement and Fundamental Symmetries. Each topic highlights the key measurements achievable at a 22 GeV CEBAF accelerator. Furthermore, this document outlines the significant physics outcomes and unique aspects of these programs that distinguish them from other existing or planned facilities. In summary, this document provides an exciting rationale for the energy upgrade of CEBAF to 22 GeV, outlining the transformative scientific potential that lies within reach, and the remarkable opportunities it offers for advancing our understanding of hadron physics and related fundamental phenomena.Comment: Updates to the list of authors; Preprint number changed from theory to experiment; Updates to sections 4 and 6, including additional figure
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