Institution
University of Toronto
Education•Toronto, Ontario, Canada•
About: University of Toronto is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 126067 authors who have published 294940 publications receiving 13536856 citations. The organization is also known as: UToronto & U of T.
Papers published on a yearly basis
Papers
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TL;DR: In 2019, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9 and the Virgo detector was also taking data that did not contribute to detection due to a low SINR but were used for subsequent parameter estimation as discussed by the authors.
Abstract: On 2019 April 25, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9. The Virgo detector was also taking data that did not contribute to detection due to a low signal-to-noise ratio, but were used for subsequent parameter estimation. The 90% credible intervals for the component masses range from to if we restrict the dimensionless component spin magnitudes to be smaller than 0.05). These mass parameters are consistent with the individual binary components being neutron stars. However, both the source-frame chirp mass and the total mass of this system are significantly larger than those of any other known binary neutron star (BNS) system. The possibility that one or both binary components of the system are black holes cannot be ruled out from gravitational-wave data. We discuss possible origins of the system based on its inconsistency with the known Galactic BNS population. Under the assumption that the signal was produced by a BNS coalescence, the local rate of neutron star mergers is updated to 250-2810.
1,189 citations
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Christopher P. Ahn1, Rachael M. Alexandroff2, Carlos Allende Prieto3, Carlos Allende Prieto4 +272 more•Institutions (69)
TL;DR: The 10th public data release (DR10) from the Sloan Digital Sky Survey (SDSS-III) was released in 2013 as mentioned in this paper, which includes the first spectroscopic data from the Apache Point Observatory Galaxy Evolution Experiment (APOGEE), along with spectroscopy data from Baryon Oscillation Spectroscopic Survey (BOSS) taken through 2012 July.
Abstract: The Sloan Digital Sky Survey (SDSS) has been in operation since 2000 April. This paper presents the Tenth Public Data Release (DR10) from its current incarnation, SDSS-III. This data release includes the first spectroscopic data from the Apache Point Observatory Galaxy Evolution Experiment (APOGEE), along with spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS) taken through 2012 July. The APOGEE instrument is a near-infrared R ~ 22,500 300 fiber spectrograph covering 1.514-1.696 μm. The APOGEE survey is studying the chemical abundances and radial velocities of roughly 100,000 red giant star candidates in the bulge, bar, disk, and halo of the Milky Way. DR10 includes 178,397 spectra of 57,454 stars, each typically observed three or more times, from APOGEE. Derived quantities from these spectra (radial velocities, effective temperatures, surface gravities, and metallicities) are also included. DR10 also roughly doubles the number of BOSS spectra over those included in the Ninth Data Release. DR10 includes a total of 1,507,954 BOSS spectra comprising 927,844 galaxy spectra, 182,009 quasar spectra, and 159,327 stellar spectra selected over 6373.2 deg2.
1,188 citations
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01 Dec 2004TL;DR: A novel approach to collaborative prediction is presented, using low-norm instead of low-rank factorizations, inspired by, and has strong connections to, large-margin linear discrimination.
Abstract: We present a novel approach to collaborative prediction, using low-norm instead of low-rank factorizations. The approach is inspired by, and has strong connections to, large-margin linear discrimination. We show how to learn low-norm factorizations by solving a semi-definite program, and discuss generalization error bounds for them.
1,188 citations
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University of Birmingham1, Bernhard Nocht Institute for Tropical Medicine2, Ontario Institute for Cancer Research3, University of Toronto4, Public Health England5, European Centre for Disease Prevention and Control6, University of Edinburgh7, Robert Koch Institute8, Swiss Tropical and Public Health Institute9, University College London10, Paul Ehrlich Institute11, University of Liverpool12, Rega Institute for Medical Research13, Kenya Medical Research Institute14, Friedrich Loeffler Institute15, Janssen-Cilag16, Technische Universität München17, Public Health Agency of Canada18, Pasteur Institute19, Sandia National Laboratories20, MRIGlobal21, World Health Organization22, University of London23, Norwegian Institute of Public Health24, Defence Science and Technology Laboratory25, Bundeswehr Institute of Microbiology26, National Institutes of Health27
TL;DR: This paper presents sequence data and analysis of 142 EBOV samples collected during the period March to October 2015 and shows that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.
Abstract: A nanopore DNA sequencer is used for real-time genomic surveillance of the Ebola virus epidemic in the field in Guinea; the authors demonstrate that it is possible to pack a genomic surveillance laboratory in a suitcase and transport it to the field for on-site virus sequencing, generating results within 24 hours of sample collection. This paper reports the use of nanopore DNA sequencers (known as MinIONs) for real-time genomic surveillance of the Ebola virus epidemic, in the field in Guinea. The authors demonstrate that it is possible to pack a genomic surveillance laboratory in a suitcase and transport it to the field for on-site virus sequencing, generating results within 24 hours of sample collection. The Ebola virus disease epidemic in West Africa is the largest on record, responsible for over 28,599 cases and more than 11,299 deaths1. Genome sequencing in viral outbreaks is desirable to characterize the infectious agent and determine its evolutionary rate. Genome sequencing also allows the identification of signatures of host adaptation, identification and monitoring of diagnostic targets, and characterization of responses to vaccines and treatments. The Ebola virus (EBOV) genome substitution rate in the Makona strain has been estimated at between 0.87 × 10−3 and 1.42 × 10−3 mutations per site per year. This is equivalent to 16–27 mutations in each genome, meaning that sequences diverge rapidly enough to identify distinct sub-lineages during a prolonged epidemic2,3,4,5,6,7. Genome sequencing provides a high-resolution view of pathogen evolution and is increasingly sought after for outbreak surveillance. Sequence data may be used to guide control measures, but only if the results are generated quickly enough to inform interventions8. Genomic surveillance during the epidemic has been sporadic owing to a lack of local sequencing capacity coupled with practical difficulties transporting samples to remote sequencing facilities9. To address this problem, here we devise a genomic surveillance system that utilizes a novel nanopore DNA sequencing instrument. In April 2015 this system was transported in standard airline luggage to Guinea and used for real-time genomic surveillance of the ongoing epidemic. We present sequence data and analysis of 142 EBOV samples collected during the period March to October 2015. We were able to generate results less than 24 h after receiving an Ebola-positive sample, with the sequencing process taking as little as 15–60 min. We show that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.
1,187 citations
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TL;DR: In this article, the authors review the underlying physical processes and the existing experimental database of plasma-material interactions both in tokamaks and laboratory simulation facilities for conditions of direct relevance to next-step fusion reactors.
Abstract: The major increase in discharge duration and plasma energy in a next step DT fusion reactor will give rise to important plasma-material effects that will critically influence its operation, safety and performance. Erosion will increase to a scale of several centimetres from being barely measurable at a micron scale in today's tokamaks. Tritium co-deposited with carbon will strongly affect the operation of machines with carbon plasma facing components. Controlling plasma-wall interactions is critical to achieving high performance in present day tokamaks, and this is likely to continue to be the case in the approach to practical fusion reactors. Recognition of the important consequences of these phenomena stimulated an internationally co-ordinated effort in the field of plasma-surface interactions supporting the Engineering Design Activities of the International Thermonuclear Experimental Reactor project (ITER), and significant progress has been made in better understanding these issues. The paper reviews the underlying physical processes and the existing experimental database of plasma-material interactions both in tokamaks and laboratory simulation facilities for conditions of direct relevance to next step fusion reactors. Two main topical groups of interaction are considered: (i) erosion/redeposition from plasma sputtering and disruptions, including dust and flake generation and (ii) tritium retention and removal. The use of modelling tools to interpret the experimental results and make projections for conditions expected in future devices is explained. Outstanding technical issues and specific recommendations on potential R&D avenues for their resolution are presented.
1,187 citations
Authors
Showing all 127245 results
Name | H-index | Papers | Citations |
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Gordon H. Guyatt | 231 | 1620 | 228631 |
David J. Hunter | 213 | 1836 | 207050 |
Rakesh K. Jain | 200 | 1467 | 177727 |
Thomas C. Südhof | 191 | 653 | 118007 |
Gordon B. Mills | 187 | 1273 | 186451 |
George Efstathiou | 187 | 637 | 156228 |
John P. A. Ioannidis | 185 | 1311 | 193612 |
Paul M. Thompson | 183 | 2271 | 146736 |
Yusuke Nakamura | 179 | 2076 | 160313 |
Chris Sander | 178 | 713 | 233287 |
David R. Williams | 178 | 2034 | 138789 |
David L. Kaplan | 177 | 1944 | 146082 |
Jasvinder A. Singh | 176 | 2382 | 223370 |
Hyun-Chul Kim | 176 | 4076 | 183227 |
Deborah J. Cook | 173 | 907 | 148928 |