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Institution

University of Bedfordshire

EducationLuton, Bedford, United Kingdom
About: University of Bedfordshire is a education organization based out in Luton, Bedford, United Kingdom. It is known for research contribution in the topics: Population & Social work. The organization has 3860 authors who have published 6079 publications receiving 143448 citations. The organization is also known as: University of Luton.


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17 Nov 1992
TL;DR: In this article, a comprehensive and analytical study of the international phenomenon of television sports coverage is presented, focusing on the historical development of sport on television, the growth of sponsorship and the way that television and sponsorship have re-shaped sport in the context of the enterprise culture.
Abstract: Fields in Vision offers a comprehensive and analytical study of the international phenomenon of television sports coverage. Garry Whannel considers the historical development of sport on television, the growth of sponsorship and the way that television and sponsorship have re-shaped sport in the context of the enterprise culture. Drawing on archival research, Whannel first charts the development of the BBC Outside Broadcast department, and the growing battle for dominance between BBC and ITV, showing how sponsorship and the rising power of sports agents began to transform sport - not only in the UK but across the world - in the 1960s. He goes on to examine the implications of this vast and escalating global network during the 1980s by analysing the central role that stars and narratives began to play in television sport, presenting case studies of major contests such as Coe versus Ovett and Decker versus Budd. His study also takes into account one of the more indirect, but no less significant results of international televised sport - the rise of popular fitness chic and the American monopoly of the workout boom of the 1980s. Fields in Vision explains the development of television sport by linking its economic transformation with the cultural forms through which it is represented, offering a study encompassing not simply the sports world, but our relationship with television and the media industries as a whole.

252 citations

Journal ArticleDOI
TL;DR: The results suggest that the Angiosperms353 probe set described here is effective for any group of flowering plants and would be useful for phylogenetic studies from the species level to higher-order groups, including the entire angiosperm clade itself.
Abstract: Sequencing of target-enriched libraries is an efficient and cost-effective method for obtaining DNA sequence data from hundreds of nuclear loci for phylogeny reconstruction. Much of the cost of developing targeted sequencing approaches is associated with the generation of preliminary data needed for the identification of orthologous loci for probe design. In plants, identifying orthologous loci has proven difficult due to a large number of whole-genome duplication events, especially in the angiosperms (flowering plants). We used multiple sequence alignments from over 600 angiosperms for 353 putatively single-copy protein-coding genes identified by the One Thousand Plant Transcriptomes Initiative to design a set of targeted sequencing probes for phylogenetic studies of any angiosperm group. To maximize the phylogenetic potential of the probes, while minimizing the cost of production, we introduce a k-medoids clustering approach to identify the minimum number of sequences necessary to represent each coding sequence in the final probe set. Using this method, 5-15 representative sequences were selected per orthologous locus, representing the sequence diversity of angiosperms more efficiently than if probes were designed using available sequenced genomes alone. To test our approximately 80,000 probes, we hybridized libraries from 42 species spanning all higher-order groups of angiosperms, with a focus on taxa not present in the sequence alignments used to design the probes. Out of a possible 353 coding sequences, we recovered an average of 283 per species and at least 100 in all species. Differences among taxa in sequence recovery could not be explained by relatedness to the representative taxa selected for probe design, suggesting that there is no phylogenetic bias in the probe set. Our probe set, which targeted 260 kbp of coding sequence, achieved a median recovery of 137 kbp per taxon in coding regions, a maximum recovery of 250 kbp, and an additional median of 212 kbp per taxon in flanking non-coding regions across all species. These results suggest that the Angiosperms353 probe set described here is effective for any group of flowering plants and would be useful for phylogenetic studies from the species level to higher-order groups, including the entire angiosperm clade itself.

251 citations

Journal ArticleDOI
TL;DR: A comprehensive survey of challenges of localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network is presented.
Abstract: Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network.

245 citations

Journal ArticleDOI
TL;DR: The major locus determining familial longevity up to high age as detected by GWAS was marked by rs2075650, which tags the deleterious effects of the ApoE ε4 allele, and no other major longevity locus was found.
Abstract: By studying the loci that contribute to human longevity, we aim to identify mechanisms that contribute to healthy aging To identify such loci, we performed a genome-wide association study (GWAS) comparing 403 unrelated nonagenarians from long-living families included in the Leiden Longevity Study (LLS) and 1670 younger population controls The strongest candidate SNPs from this GWAS have been analyzed in a meta-analysis of nonagenarian cases from the Rotterdam Study, Leiden 85-plus study, and Danish 1905 cohort Only one of the 62 prioritized SNPs from the GWAS analysis (P<1×10(-4) ) showed genome-wide significance with survival into old age in the meta-analysis of 4149 nonagenarian cases and 7582 younger controls [OR=071 (95% CI 065-077), P=339 × 10(-17) ] This SNP, rs2075650, is located in TOMM40 at chromosome 19q1332 close to the apolipoprotein E (APOE) gene Although there was only moderate linkage disequilibrium between rs2075650 and the ApoE e4 defining SNP rs429358, we could not find an APOE-independent effect of rs2075650 on longevity, either in cross-sectional or in longitudinal analyses As expected, rs429358 associated with metabolic phenotypes in the offspring of the nonagenarian cases from the LLS and their partners In addition, we observed a novel association between this locus and serum levels of IGF-1 in women (P=0005) In conclusion, the major locus determining familial longevity up to high age as detected by GWAS was marked by rs2075650, which tags the deleterious effects of the ApoE e4 allele No other major longevity locus was found

244 citations


Authors

Showing all 3892 results

NameH-indexPapersCitations
Jie Zhang1784857221720
Oscar H. Franco11182266649
Timothy J. Foster9842032338
Christopher P. Denton9567542040
Ian Kimber9162028629
Michael J. Gidley8642024313
David Carling8618645066
Anthony Turner7948924734
Rhys E. Green7828530428
Vijay Kumar Thakur7437517719
Dave J. Adams7328319526
Naresh Magan7240017511
Aedin Cassidy7021817788
David A. Basketter7032516639
Richard C. Strange6724917805
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20236
202248
2021345
2020363
2019323
2018329