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Institution

University of Westminster

EducationLondon, United Kingdom
About: University of Westminster is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Politics. The organization has 2944 authors who have published 8426 publications receiving 200236 citations. The organization is also known as: Westminster University & Royal Polytechnic Institution.


Papers
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Journal ArticleDOI
TL;DR: The results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large‐scale human phenotypic studies.
Abstract: Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as MRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat-muscle quantitation system (AMRA(TM) Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRA(TM) Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRA(TM) Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRA(TM) Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variation was 1.4% for IAAT and 1.2% for ASAT, the intra-observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRA(TM) Profiler, opening up the possibility of large-scale human phenotypic studies.

57 citations

Book
01 Apr 2003
TL;DR: In this article, a discussion of managerial challenges details the most recent research on how organizations can better create, share, and exploit knowledge, covering practical issues such as measuring returns, establishing trust, and integrating technology.
Abstract: From the Publisher: This scholarly discussion of managerial challenges details the most recent research on how organizations can better create, share, and exploit knowledge. Spanning the business and public service context, the information provided covers practical issues such as measuring returns, establishing trust, and integrating technology. Also discussed are knowledge management systems, Internet support, and information systems development. Author Biography: Elayne Coakes is a senior lecturer in business information management at the University of Westminster. She is the author of Socio-Technical and Human Cognition Elements of Information Systems, The New Sociotech, and Knowledge Management in the Socio-Technical World.

57 citations

Journal ArticleDOI
TL;DR: The rate of recolonization has been slow and neither the annual natural recruitment nor distribution of the pre-pollution stock of the 1800s appears to have been achieved, and the future management of the stock in relation to its commercial scientific and conservation value is considered.
Abstract: Improvements in water quality in the Thames Estuary since the 1960s have removed a barrier to fish migration into the Thames catchment. The extent of recolonization by the eel is examined, using data from 235 electrofished and fyke-netted sites, compared with information on pre-pollution distribution. Density is highest in the lower parts of the catchment and decreases significantly with increasing distance from the tidal limit. Only sparse populations are found beyond 50 km from the tidal limit and are characterized by an increasing bias towards larger, slower-growing females. Artificial stocking is believed to be a significant factor in certain areas. The rate of recolonization has been slow and neither the annual natural recruitment nor distribution of the pre-pollution stock of the 1800s appears to have been achieved. The future management of the stock in relation to its commercial scientific and conservation value is considered.

57 citations

Book
01 Apr 1993
TL;DR: Operators, values and types functions lists higher order functions managing environments user defined types modules, including SML procedural language features of SML, and UNIX - SML interfaces.
Abstract: Operators, values and types functions lists higher order functions managing environments user defined types modules. Appendices: File handling additional features of SML procedural language features of SML the initial SML environment UNIX - SML interfaces.

57 citations

Journal ArticleDOI
TL;DR: The results imply that knowing does not index an automatic familiarity process, as conceived in some dual-process models of recognition, and that both remembering and knowing increase with the slower, more controlled processing permitted by the longer response time.

57 citations


Authors

Showing all 3028 results

NameH-indexPapersCitations
Barbara J. Sahakian14561269190
Peter B. Jones145185794641
Andrew Steptoe137100373431
Robert West112106153904
Aldo R. Boccaccini103123454155
Kevin Morgan9565549644
Shaogang Gong9243031444
Thomas A. Buchanan9134948865
Mauro Perretti9049728463
Jimmy D. Bell8858925983
Andrew D. McCulloch7535819319
Mark S. Goldberg7323518067
Dimitrios Buhalis7231623830
Ali Mobasheri6937014642
Michael E. Boulton6933123747
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202334
2022111
2021439
2020501
2019434
2018461