46 research outputs found
The Third Gravitational Lensing Accuracy Testing (GREAT3) Challenge Handbook
The GRavitational lEnsing Accuracy Testing 3 (GREAT3) challenge is the third
in a series of image analysis challenges, with a goal of testing and
facilitating the development of methods for analyzing astronomical images that
will be used to measure weak gravitational lensing. This measurement requires
extremely precise estimation of very small galaxy shape distortions, in the
presence of far larger intrinsic galaxy shapes and distortions due to the
blurring kernel caused by the atmosphere, telescope optics, and instrumental
effects. The GREAT3 challenge is posed to the astronomy, machine learning, and
statistics communities, and includes tests of three specific effects that are
of immediate relevance to upcoming weak lensing surveys, two of which have
never been tested in a community challenge before. These effects include
realistically complex galaxy models based on high-resolution imaging from
space; spatially varying, physically-motivated blurring kernel; and combination
of multiple different exposures. To facilitate entry by people new to the
field, and for use as a diagnostic tool, the simulation software for the
challenge is publicly available, though the exact parameters used for the
challenge are blinded. Sample scripts to analyze the challenge data using
existing methods will also be provided. See http://great3challenge.info and
http://great3.projects.phys.ucl.ac.uk/leaderboard/ for more information.Comment: 30 pages, 13 figures, submitted for publication, with minor edits
(v2) to address comments from the anonymous referee. Simulated data are
available for download and participants can find more information at
http://great3.projects.phys.ucl.ac.uk/leaderboard
The DESI Sky Continuum Monitor System
The Dark Energy Spectroscopic Instrument (DESI) is an ongoing spectroscopic
survey to measure the dark energy equation of state to unprecedented precision.
We describe the DESI Sky Continuum Monitor System, which tracks the night sky
brightness as part of a system that dynamically adjusts the spectroscopic
exposure time to produce more uniform data quality and to maximize observing
efficiency. The DESI dynamic exposure time calculator (ETC) will combine sky
brightness measurements from the Sky Monitor with data from the guider system
to calculate the exposure time to achieve uniform signal-to-noise ratio (SNR)
in the spectra under various observing conditions. The DESI design includes 20
sky fibers, and these are split between two identical Sky Monitor units to
provide redundancy. Each Sky Monitor unit uses an SBIG STXL-6303e CCD camera
and supports an eight-position filter wheel. Both units have been completed and
delivered to the Mayall Telescope at the Kitt Peak National Observatory.
Commissioning results show that the Sky Monitor delivers the required
performance necessary for the ETC.Comment: 9 pages, 7 figures, 1 tabl
Investigating the Complex Arrhythmic Phenotype Caused by the Gain-of-Function Mutation KCNQ1-G229D
British Heart Foundation (BHF) (FS/12/59/29756 to SH, RG/15/15/31742 to AT, FS/17/22/32644 to AB-O, and SP/15/9/31605, RG/15/6/31436, PG/14/59/31000, RG/14/1/30588, P47352/Centre for Regenerative Medicine to CD)National Institute for Health Research Barts Biomedical Research CentreWellcome Trust (100246/Z/12/Z to BR and XZ)National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/P001076/1 to AB-O, CRACK-IT. FULL PROPOSAL code 35911-259146., NC/K000225/1 to CD)Engineering and Physical Sciences Research Council Impact Acceleration Award (EP/K503769/1 to BR)CompBioMed project (No. 675451 to BR)Oxford BHF Centre of Research Excellence (RE/08/004/23915 and RE/13/1/30181 to BR)China Scholarship Council to XZBIRAX (04BX14CDLG to CD)Medical Research Council (MR/M017354/1 to CD)Heart Research United Kingdom (TRP01/12 to CD
Anticipating and Managing Future Trade-offs and Complementarities between Ecosystem Services
This paper shows how, with the aid of computer models developed in close collaboration with decision makers and other stakeholders, it is possible to quantify and map how policy decisions are likely to affect multiple ecosystem services in future. In this way, potential trade-offs and complementarities between different ecosystem services can be identified, so that policies can be designed to avoid the worst trade-offs, and where possible, enhance multiple services. The paper brings together evidence from across the Rural Economy and Land Use Programme’s Sustainable Uplands project for the first time, with previously unpublished model outputs relating to runoff, agricultural suitability, biomass, heather cover, age, and utility for Red Grouse (Lagopus scotica), grass cover, and accompanying scenario narratives and video. Two contrasting scenarios, based on policies to extensify or intensify land management up to 2030, were developed through a combination of interviews and discussions during site visits with stakeholders, literature review, conceptual modeling, and process-based computer models, using the Dark Peak of the Peak District National Park in the UK as a case study. Where extensification leads to a significant reduction in managed burning and grazing or land abandonment, changes in vegetation type and structure could compromise a range of species that are important for conservation, while compromising provisioning services, amenity value, and increasing wildfire risk. However, where extensification leads to the restoration of peatlands damaged by former intensive management, there would be an increase in carbon sequestration and storage, with a number of cobenefits, which could counter the loss of habitats and species elsewhere in the landscape. In the second scenario, land use and management was significantly intensified to boost UK self-sufficiency in food. This would benefit certain provisioning services but would have negative consequences for carbon storage and water quality and would lead to a reduction in the abundance of certain species of conservation concern. The paper emphasizes the need for spatially explicit models that can track how ecosystem services might change over time, in response to policy or environmental drivers, and in response to the changing demands and preferences of society, which are far harder to anticipate. By developing such models in close collaboration with decision makers and other stakeholders, it is possible to depict scenarios of real concern to those who need to use the research findings. By engaging these collaborators with the research findings through film, it was possible to discuss adaptive options to minimize trade-offs and enhance the provision of multiple ecosystem services under the very different future conditions depicted by each scenario. By preparing for as wide a range of futures as possible in this way, it may be possible for decision makers to act rapidly and effectively to protect and enhance the provision of ecosystem services in the face of unpredictable future change.Additional co-authors: Nanlin Jin, Brian J Irvine, Mike J Kirkby, William E Kunin, Christina Prell, Claire H Quinn, Bill Slee, Sigrid Stagl, Mette Termansen, Simon Thorp, and Fred Worral
LSST: from Science Drivers to Reference Design and Anticipated Data Products
(Abridged) We describe here the most ambitious survey currently planned in
the optical, the Large Synoptic Survey Telescope (LSST). A vast array of
science will be enabled by a single wide-deep-fast sky survey, and LSST will
have unique survey capability in the faint time domain. The LSST design is
driven by four main science themes: probing dark energy and dark matter, taking
an inventory of the Solar System, exploring the transient optical sky, and
mapping the Milky Way. LSST will be a wide-field ground-based system sited at
Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m
effective) primary mirror, a 9.6 deg field of view, and a 3.2 Gigapixel
camera. The standard observing sequence will consist of pairs of 15-second
exposures in a given field, with two such visits in each pointing in a given
night. With these repeats, the LSST system is capable of imaging about 10,000
square degrees of sky in a single filter in three nights. The typical 5
point-source depth in a single visit in will be (AB). The
project is in the construction phase and will begin regular survey operations
by 2022. The survey area will be contained within 30,000 deg with
, and will be imaged multiple times in six bands, ,
covering the wavelength range 320--1050 nm. About 90\% of the observing time
will be devoted to a deep-wide-fast survey mode which will uniformly observe a
18,000 deg region about 800 times (summed over all six bands) during the
anticipated 10 years of operations, and yield a coadded map to . The
remaining 10\% of the observing time will be allocated to projects such as a
Very Deep and Fast time domain survey. The goal is to make LSST data products,
including a relational database of about 32 trillion observations of 40 billion
objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures
available from https://www.lsst.org/overvie
Twenty-three unsolved problems in hydrology (UPH) – a community perspective
This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through on-line media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focussed on process-based understanding of hydrological variability and causality at all space and time scales.
Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come
A Primary Prevention Clinical Risk Score Model for Patients With Brugada Syndrome (BRUGADA-RISK).
OBJECTIVES: The goal of this study was to develop a risk score model for patients with Brugada syndrome (BrS). BACKGROUND: Risk stratification in BrS is a significant challenge due to the low event rates and conflicting evidence. METHODS: A multicenter international cohort of patients with BrS and no previous cardiac arrest was used to evaluate the role of 16 proposed clinical or electrocardiogram (ECG) markers in predicting ventricular arrhythmias (VAs)/sudden cardiac death (SCD) during follow-up. Predictive markers were incorporated into a risk score model, and this model was validated by using out-of-sample cross-validation. RESULTS: A total of 1,110 patients with BrS from 16 centers in 8 countries were included (mean age 51.8 ± 13.6 years; 71.8% male). Median follow-up was 5.33 years; 114 patients had VA/SCD (10.3%) with an annual event rate of 1.5%. Of the 16 proposed risk factors, probable arrhythmia-related syncope (hazard ratio [HR]: 3.71; p < 0.001), spontaneous type 1 ECG (HR: 3.80; p < 0.001), early repolarization (HR: 3.42; p < 0.001), and a type 1 Brugada ECG pattern in peripheral leads (HR: 2.33; p < 0.001) were associated with a higher risk of VA/SCD. A risk score model incorporating these factors revealed a sensitivity of 71.2% (95% confidence interval: 61.5% to 84.6%) and a specificity of 80.2% (95% confidence interval: 75.7% to 82.3%) in predicting VA/SCD at 5 years. Calibration plots showed a mean prediction error of 1.2%. The model was effectively validated by using out-of-sample cross-validation according to country. CONCLUSIONS: This multicenter study identified 4 risk factors for VA/SCD in a primary prevention BrS population. A risk score model was generated to quantify risk of VA/SCD in BrS and inform implantable cardioverter-defibrillator prescription
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Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.
Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707