22 research outputs found

    Probing the Early Stages of Low-Mass Star Formation in LDN 1689N: Dust and Water in IRAS 16293-2422A, B, and E

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    We present deep images of dust continuum emission at 450, 800, and 850 micron of the dark cloud LDN 1689N which harbors the low-mass young stellar objects (YSOs) IRAS 16293-2422A and B (I16293A and I16293B) and the cold prestellar object I16293E. Toward the positions of I16293A and E we also obtained spectra of CO-isotopomers and deep submillimeter observations of chemically related molecules with high critical densities. To I16293A we report the detection of the HDO 1_01 - 0_00 and H2O 1_10 - 1_01 ground-state transitions as broad self-reversed emission profiles with narrow absorption, and a tentative detection of H2D+ 1_10 - 1_11. To I16293E we detect weak emission of subthermally excited HDO 1_01 - 0_00. Based on this set of submillimeter continuum and line data we model the envelopes around I16293A and E. The density and velocity structure of I16293A is fit by an inside-out collapse model, yielding a sound speed of a=0.7 km/s, an age of t=(0.6--2.5)e4 yr, and a mass of 6.1 Msun. The density in the envelope of I16293E is fit by a radial power law with index -1.0+/-0.2, a mass of 4.4 Msun, and a constant temperature of 16K. These respective models are used to study the chemistry of the envelopes of these pre- and protostellar objects. The [HDO]/[H2O] abundance ratio in the warm inner envelope of I16293A of a few times 1e-4 is comparable to that measured in comets. This supports the idea that the [HDO]/[H2O] ratio is determined in the cold prestellar core phase and conserved throughout the formation process of low-mass stars and planets.Comment: 61 pages, 17 figures. Accepted for publication in ApJ. To get Fig. 13: send email to [email protected]

    The Science Case for an Extended Spitzer Mission

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    Although the final observations of the Spitzer Warm Mission are currently scheduled for March 2019, it can continue operations through the end of the decade with no loss of photometric precision. As we will show, there is a strong science case for extending the current Warm Mission to December 2020. Spitzer has already made major impacts in the fields of exoplanets (including microlensing events), characterizing near Earth objects, enhancing our knowledge of nearby stars and brown dwarfs, understanding the properties and structure of our Milky Way galaxy, and deep wide-field extragalactic surveys to study galaxy birth and evolution. By extending Spitzer through 2020, it can continue to make ground-breaking discoveries in those fields, and provide crucial support to the NASA flagship missions JWST and WFIRST, as well as the upcoming TESS mission, and it will complement ground-based observations by LSST and the new large telescopes of the next decade. This scientific program addresses NASA's Science Mission Directive's objectives in astrophysics, which include discovering how the universe works, exploring how it began and evolved, and searching for life on planets around other stars.Comment: 75 pages. See page 3 for Table of Contents and page 4 for Executive Summar

    Key questions for modelling COVID-19 exit strategies

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    Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters; ii) understand sources of heterogeneity in populations; iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health

    Photometric redshifts for the next generation of deep radio continuum surveys - I: template fitting

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    We present a study of photometric redshift performance for galaxies and active galactic nuclei detected in deep radio continuum surveys. Using two multi-wavelength datasets, over the NOAO Deep Wide Field Survey Boötes and COSMOS fields, we assess photometric redshift (photo-z) performance for a sample of 4; 500 radio continuum sources with spectroscopic redshifts relative to those of 63; 000 non radio-detected sources in the same fields. We investigate the performance of three photometric redshift template sets as a function of redshift, radio luminosity and infrared/X-ray properties. We find that no single template library is able to provide the best performance across all subsets of the radio detected population, with variation in the optimum template set both between subsets and between fields. Through a hierarchical Bayesian combination of the photo-z estimates from all three template sets, we are able to produce a consensus photo-z estimate which equals or improves upon the performance of any individual template set

    The ABC130 barrel module prototyping programme for the ATLAS strip tracker

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    For the Phase-II Upgrade of the ATLAS Detector, its Inner Detector, consisting of silicon pixel, silicon strip and transition radiation sub-detectors, will be replaced with an all new 100 % silicon tracker, composed of a pixel tracker at inner radii and a strip tracker at outer radii. The future ATLAS strip tracker will include 11,000 silicon sensor modules in the central region (barrel) and 7,000 modules in the forward region (end-caps), which are foreseen to be constructed over a period of 3.5 years. The construction of each module consists of a series of assembly and quality control steps, which were engineered to be identical for all production sites. In order to develop the tooling and procedures for assembly and testing of these modules, two series of major prototyping programs were conducted: an early program using readout chips designed using a 250 nm fabrication process (ABCN-25) and a subsequent program using a follow-up chip set made using 130 nm processing (ABC130 and HCC130 chips). This second generation of readout chips was used for an extensive prototyping program that produced around 100 barrel-type modules and contributed significantly to the development of the final module layout. This paper gives an overview of the components used in ABC130 barrel modules, their assembly procedure and findings resulting from their tests.Comment: 82 pages, 66 figure

    Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

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    SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

    Key questions for modelling COVID-19 exit strategies

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    Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.</p

    Key questions for modelling COVID-19 exit strategies

    Get PDF
    Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health
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