Institution
University of Warwick
Education•Coventry, Warwickshire, United Kingdom•
About: University of Warwick is a education organization based out in Coventry, Warwickshire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 26212 authors who have published 77127 publications receiving 2666552 citations. The organization is also known as: Warwick University & The University of Warwick.
Papers published on a yearly basis
Papers
More filters
••
384 citations
••
TL;DR: It is demonstrated that the strongest risks are from socio-economic deprivation and from factors in the parents' own background and that parental background factors are largely, but not entirely, mediated through their impact on socio- economic factors.
384 citations
••
TL;DR: In this paper, the authors argue that there is inevitably a range of possible estimates for industrial output growth given the inherent index number and data problems, and that Hoppit and Berg and Hudson substantially overstate the industrial revolution.
Abstract: n the early i98os we published revised estimates of aggregate economic performance during the British industrial revolution which have stimulated reappraisal of the beginnings of modern economic growth.2 These new estimates have led most scholars to abandon the previous orthodoxy which had been based on the pioneering work of Deane and Cole.3 We have subsequently explored further aspects of the industrial revolution using our i982/3 estimates of the rate of growth as acceptable best guesses.4 Recently, however, several papers published in this journal have, with varying degrees of hostility, expressed doubts about our estimates.5 We think it is now opportune to respond to these comments. Our critics have questioned the appropriateness of our estimation techniques and have suggested that our overall view of the industrial revolution is misconceived. While we do not wish to dismiss the points that have been made, we feel both that many of the specific criticisms of our estimating techniques have been erroneous and that our overall view of the late eighteenth and early nineteenth centuries has been misunderstood. Initially in section I we present a brief summary of a coherent new view of British growth that emerged from our aggregate estimates. The bulk of the paper then takes up the technical issues that have recently been raised. In particular, we argue the following main points. First, that there is inevitably a range of possible estimates for industrial output growth given the inherent index number and data problems. Both Crafts's and Harley's original estimates fall within this range, as do Jackson's new estimates, whereas Deane and Cole's do not. Second, that we do not accept Jackson's case for preferring what he calls a Crafts rather than a Harley view of industrial output growth nor do we accept his dismissal of the indices of industrial output presented by Crafts, Leybourne, and Mills (CLM) and by Harley. Third, that Hoppit and Berg and Hudson substantially overstate
383 citations
••
TL;DR: An algorithm that enhances the contrast of an input image using interpixel contextual information and produces better or comparable enhanced images than four state-of-the-art algorithms is proposed.
Abstract: This paper proposes an algorithm that enhances the contrast of an input image using interpixel contextual information. The algorithm uses a 2-D histogram of the input image constructed using a mutual relationship between each pixel and its neighboring pixels. A smooth 2-D target histogram is obtained by minimizing the sum of Frobenius norms of the differences from the input histogram and the uniformly distributed histogram. The enhancement is achieved by mapping the diagonal elements of the input histogram to the diagonal elements of the target histogram. Experimental results show that the algorithm produces better or comparable enhanced images than four state-of-the-art algorithms.
383 citations
••
TL;DR: Multiparameter experimental and computational methods that integrate quantitative measurement and mathematical simulation of these noisy and complex processes are required to understand the highly dynamic mechanisms that control cell plasticity and fate.
Abstract: Populations of cells are almost always heterogeneous in function and fate. To understand the plasticity of cells, it is vital to measure quantitatively and dynamically the molecular processes that underlie cell-fate decisions in single cells. Early events in cell signalling often occur within seconds of the stimulus, whereas intracellular signalling processes and transcriptional changes can take minutes or hours. By contrast, cell-fate decisions, such as whether a cell divides, differentiates or dies, can take many hours or days. Multiparameter experimental and computational methods that integrate quantitative measurement and mathematical simulation of these noisy and complex processes are required to understand the highly dynamic mechanisms that control cell plasticity and fate.
383 citations
Authors
Showing all 26659 results
Name | H-index | Papers | Citations |
---|---|---|---|
David Miller | 203 | 2573 | 204840 |
Daniel R. Weinberger | 177 | 879 | 128450 |
Kay-Tee Khaw | 174 | 1389 | 138782 |
Joseph E. Stiglitz | 164 | 1142 | 152469 |
Edmund T. Rolls | 153 | 612 | 77928 |
Thomas J. Smith | 140 | 1775 | 113919 |
Tim Jones | 135 | 1314 | 91422 |
Ian Ford | 134 | 678 | 85769 |
Paul Harrison | 133 | 1400 | 80539 |
Sinead Farrington | 133 | 1422 | 91099 |
Peter Hall | 132 | 1640 | 85019 |
Paul Brennan | 132 | 1221 | 72748 |
G. T. Jones | 131 | 864 | 75491 |
Peter Simmonds | 131 | 823 | 62953 |
Tim Martin | 129 | 878 | 82390 |