Institution
University of Western Australia
Education•Perth, Western Australia, Australia•
About: University of Western Australia is a education organization based out in Perth, Western Australia, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 29613 authors who have published 87405 publications receiving 3064466 citations. The organization is also known as: UWA & University of WA.
Topics: Population, Poison control, Galaxy, Context (language use), Medicine
Papers published on a yearly basis
Papers
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Stanford University1, Cleveland Clinic2, University of Toronto3, Centre national de la recherche scientifique4, Université Paris-Saclay5, University of Paris-Sud6, Rutgers University7, Avaya8, RAND Corporation9, IBM10, University of Pennsylvania11, University of Western Australia12, University of Minnesota13
TL;DR: A publicly available algorithm that requires only the same order of magnitude of computational effort as ordinary least squares applied to the full set of covariates is described.
Abstract: The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we have available a large collection of possible covariates from which we hope to select a parsimonious set for the efficient prediction of a response variable. Least Angle Regression (LARS), a new model selection algorithm, is a useful and less greedy version of traditional forward selection methods. Three main properties are derived: (1) A simple modification of the LARS algorithm implements the Lasso, an attractive version of ordinary least squares that constrains the sum of the absolute regression coefficients; the LARS modification calculates all possible Lasso estimates for a given problem, using an order of magnitude less computer time than previous methods. (2) A different LARS modification efficiently implements Forward Stagewise linear regression, another promising new model selection method; this connection explains the similar numerical results previously observed for the Lasso and Stagewise, and helps us understand the properties of both methods, which are seen as constrained versions of the simpler LARS algorithm. (3) A simple approximation for the degrees of freedom of a LARS estimate is available, from which we derive a Cp estimate of prediction error; this allows a principled choice among the range of possible LARS estimates. LARS and its variants are computationally efficient: the paper describes a publicly available algorithm that requires only the same order of magnitude of computational effort as ordinary least squares applied to the full set of covariates.
7,828 citations
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TL;DR: The association of GRB 170817A, detected by Fermi-GBM 1.7 s after the coalescence, corroborates the hypothesis of a neutron star merger and provides the first direct evidence of a link between these mergers and short γ-ray bursts.
Abstract: On August 17, 2017 at 12∶41:04 UTC the Advanced LIGO and Advanced Virgo gravitational-wave detectors made their first observation of a binary neutron star inspiral. The signal, GW170817, was detected with a combined signal-to-noise ratio of 32.4 and a false-alarm-rate estimate of less than one per 8.0×10^{4} years. We infer the component masses of the binary to be between 0.86 and 2.26 M_{⊙}, in agreement with masses of known neutron stars. Restricting the component spins to the range inferred in binary neutron stars, we find the component masses to be in the range 1.17-1.60 M_{⊙}, with the total mass of the system 2.74_{-0.01}^{+0.04}M_{⊙}. The source was localized within a sky region of 28 deg^{2} (90% probability) and had a luminosity distance of 40_{-14}^{+8} Mpc, the closest and most precisely localized gravitational-wave signal yet. The association with the γ-ray burst GRB 170817A, detected by Fermi-GBM 1.7 s after the coalescence, corroborates the hypothesis of a neutron star merger and provides the first direct evidence of a link between these mergers and short γ-ray bursts. Subsequent identification of transient counterparts across the electromagnetic spectrum in the same location further supports the interpretation of this event as a neutron star merger. This unprecedented joint gravitational and electromagnetic observation provides insight into astrophysics, dense matter, gravitation, and cosmology.
7,327 citations
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TL;DR: Prevalence and severity of health loss were weakly correlated and age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010, but population growth and ageing have increased YLD numbers and crude rates over the past two decades.
7,021 citations
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TL;DR: Associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses.
Abstract: Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.
6,809 citations
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Macquarie University1, University of Minnesota2, Stanford University3, Simón Bolívar University4, Wageningen University and Research Centre5, Smithsonian Environmental Research Center6, University of Alaska Fairbanks7, VU University Amsterdam8, University of Zurich9, Centre national de la recherche scientifique10, Curtin University11, Tohoku University12, University of Wisconsin–Eau Claire13, Landcare Research14, University of Concepción15, University of Cape Town16, University of Tartu17, Polish Academy of Sciences18, University of Tokyo19, Utrecht University20, University of Western Australia21, Charles Darwin University22, Ural State University23, University of Toronto24, Texas A&M University25, University of Córdoba (Spain)26
TL;DR: Reliable quantification of the leaf economics spectrum and its interaction with climate will prove valuable for modelling nutrient fluxes and vegetation boundaries under changing land-use and climate.
Abstract: Bringing together leaf trait data spanning 2,548 species and 175 sites we describe, for the first time at global scale, a universal spectrum of leaf economics consisting of key chemical, structural and physiological properties. The spectrum runs from quick to slow return on investments of nutrients and dry mass in leaves, and operates largely independently of growth form, plant functional type or biome. Categories along the spectrum would, in general, describe leaf economic variation at the global scale better than plant functional types, because functional types overlap substantially in their leaf traits. Overall, modulation of leaf traits and trait relationships by climate is surprisingly modest, although some striking and significant patterns can be seen. Reliable quantification of the leaf economics spectrum and its interaction with climate will prove valuable for modelling nutrient fluxes and vegetation boundaries under changing land-use and climate.
6,360 citations
Authors
Showing all 29972 results
Name | H-index | Papers | Citations |
---|---|---|---|
Nicholas G. Martin | 192 | 1770 | 161952 |
Cornelia M. van Duijn | 183 | 1030 | 146009 |
Kay-Tee Khaw | 174 | 1389 | 138782 |
Steven N. Blair | 165 | 879 | 132929 |
David W. Bates | 159 | 1239 | 116698 |
Mark E. Cooper | 158 | 1463 | 124887 |
David Cameron | 154 | 1586 | 126067 |
Stephen T. Holgate | 142 | 870 | 82345 |
Jeremy K. Nicholson | 141 | 773 | 80275 |
Xin Chen | 139 | 1008 | 113088 |
Graeme J. Hankey | 137 | 844 | 143373 |
David Stuart | 136 | 1665 | 103759 |
Joachim Heinrich | 136 | 1309 | 76887 |
Carlos M. Duarte | 132 | 1173 | 86672 |
David Smith | 129 | 2184 | 100917 |