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Institution

University of Edinburgh

EducationEdinburgh, United Kingdom
About: University of Edinburgh is a education organization based out in Edinburgh, United Kingdom. It is known for research contribution in the topics: Population & Galaxy. The organization has 57604 authors who have published 151616 publications receiving 6687334 citations. The organization is also known as: Edinburgh University & The University of Edinburgh.
Topics: Population, Galaxy, Redshift, Gene, Poison control


Papers
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Journal ArticleDOI
TL;DR: An inventory of 20 items with a set of instructions and response- and computational-conventions is proposed and the results obtained from a young adult population numbering some 1100 individuals are reported.

33,268 citations

Journal ArticleDOI
TL;DR: This paper describes a method of transferring fragments of DNA from agarose gels to cellulose nitrate filters that can be hybridized to radioactive RNA and hybrids detected by radioautography or fluorography.

30,291 citations

Journal ArticleDOI
TL;DR: Findings indicate that the "diabetes epidemic" will continue even if levels of obesity remain constant, and given the increasing prevalence of obesity, it is likely that these figures provide an underestimate of future diabetes prevalence.
Abstract: OBJECTIVE —The goal of this study was to estimate the prevalence of diabetes and the number of people of all ages with diabetes for years 2000 and 2030. RESEARCH DESIGN AND METHODS —Data on diabetes prevalence by age and sex from a limited number of countries were extrapolated to all 191 World Health Organization member states and applied to United Nations’ population estimates for 2000 and 2030. Urban and rural populations were considered separately for developing countries. RESULTS —The prevalence of diabetes for all age-groups worldwide was estimated to be 2.8% in 2000 and 4.4% in 2030. The total number of people with diabetes is projected to rise from 171 million in 2000 to 366 million in 2030. The prevalence of diabetes is higher in men than women, but there are more women with diabetes than men. The urban population in developing countries is projected to double between 2000 and 2030. The most important demographic change to diabetes prevalence across the world appears to be the increase in the proportion of people >65 years of age. CONCLUSIONS —These findings indicate that the “diabetes epidemic” will continue even if levels of obesity remain constant. Given the increasing prevalence of obesity, it is likely that these figures provide an underestimate of future diabetes prevalence.

16,648 citations

Journal ArticleDOI
TL;DR: The state-of-the-art in evaluated methods for both classification and detection are reviewed, whether the methods are statistically different, what they are learning from the images, and what the methods find easy or confuse.
Abstract: The Pascal Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection. This paper describes the dataset and evaluation procedure. We review the state-of-the-art in evaluated methods for both classification and detection, analyse whether the methods are statistically different, what they are learning from the images (e.g. the object or its context), and what the methods find easy or confuse. The paper concludes with lessons learnt in the three year history of the challenge, and proposes directions for future improvement and extension.

15,935 citations

Journal ArticleDOI
TL;DR: In this paper, the authors developed a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary.
Abstract: This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary. The proposed tests are based on standard F- and t-statistics used to test the significance of the lagged levels of the variables in a univariate equilibrium correction mechanism. The asymptotic distributions of these statistics are non-standard under the null hypothesis that there exists no level relationship, irrespective of whether the regressors are I(0) or I(1). Two sets of asymptotic critical values are provided: one when all regressors are purely I(1) and the other if they are all purely I(0). These two sets of critical values provide a band covering all possible classifications of the regressors into purely I(0), purely I(1) or mutually cointegrated. Accordingly, various bounds testing procedures are proposed. It is shown that the proposed tests are consistent, and their asymptotic distribution under the null and suitably defined local alternatives are derived. The empirical relevance of the bounds procedures is demonstrated by a re-examination of the earnings equation included in the UK Treasury macroeconometric model. Copyright © 2001 John Wiley & Sons, Ltd.

13,898 citations


Authors

Showing all 58514 results

NameH-indexPapersCitations
Paul M. Ridker2331242245097
David J. Hunter2131836207050
Mark J. Daly204763304452
Robert M. Califf1961561167961
Martin White1962038232387
Michael Marmot1931147170338
Paul M. Thompson1832271146736
Peter W.F. Wilson181680139852
Gonçalo R. Abecasis179595230323
John J.V. McMurray1781389184502
Douglas Scott1781111185229
Michael I. Jordan1761016216204
Hyun-Chul Kim1764076183227
Andrea Bocci1722402176461
Simon Baron-Cohen172773118071
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023383
20221,308
20219,243
20209,103
20198,124
20187,336