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Institution

Brunel University London

EducationLondon, United Kingdom
About: Brunel University London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Context (language use) & Large Hadron Collider. The organization has 10918 authors who have published 29515 publications receiving 893330 citations. The organization is also known as: Brunel & University of Brunel.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors show that climate change can directly affect human health by varying exposure to non-optimal outdoor temperature, however, evidence on this direct impact at a global scale is limited.

436 citations

Journal ArticleDOI
TL;DR: In this article, the authors provide a comprehensive review for those who are interested in using optical diagnostics for in-cylinder soot and combustion temperature measurement in diesel engines, including laser induced incandescence (LII) and light scattering.

435 citations

Journal ArticleDOI
TL;DR: This contribution reports how a European set of general population preference weights was derived from the data collected in the 11 valuation studies to suggest that VAS values for EQ-5D health states in six Western European countries can be described by a common model
Abstract: The EQ-5D questionnaire is a widely used generic instrument for describing and valuing health that was developed by the EuroQol Group. A primary objective of the EuroQol Group is the investigation of values for health states in the general population in different countries. As part of the EuroQol enterprise 11 population surveys were carried out in six Western European countries (Finland, Germany, The Netherlands, Spain, Sweden and the UK) to value health states as defined by the EQ-5D using a standardised visual analogue scale (EQ-5D VAS). This contribution reports how a European set of general population preference weights was derived from the data collected in the 11 valuation studies. The scores from this set of preference weights can be applied to generate a VAS-based weighted health status index for all the potential 243 EQ-5D health states for use in multi-national studies. To estimate the preference weights a multi-level regression analysis was performed on 82,910 valuations of 44 EQ-5D health states elicited from 6,870 respondents. Stable and plausible solutions were found for the model parameters. The R(2) value was 75%. The analysis showed that the major source of variance, apart from 'random error', was variance between individuals (28.3% of the total residual variance). These results suggest that VAS values for EQ-5D health states in six Western European countries can be described by a common model.

434 citations

Journal ArticleDOI
TL;DR: It is shown that the addressed stochastic Cohen-Grossberg neural networks with mixed delays are globally asymptotically stable in the mean square if two LMIs are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox.
Abstract: In this letter, the global asymptotic stability analysis problem is considered for a class of stochastic Cohen-Grossberg neural networks with mixed time delays, which consist of both the discrete and distributed time delays. Based on an Lyapunov-Krasovskii functional and the stochastic stability analysis theory, a linear matrix inequality (LMI) approach is developed to derive several sufficient conditions guaranteeing the global asymptotic convergence of the equilibrium point in the mean square. It is shown that the addressed stochastic Cohen-Grossberg neural networks with mixed delays are globally asymptotically stable in the mean square if two LMIs are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox. It is also pointed out that the main results comprise some existing results as special cases. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria

433 citations

Journal ArticleDOI
TL;DR: In this article, the authors evaluate the technological readiness of different elements of BEV technology and highlight those technological areas where important progress is expected, and investigate the economic issues linked with the development of BEVs.
Abstract: As concerns of oil depletion and security of supply remain as severe as ever, and faced with the consequences of climate change due to greenhouse gas emissions, Europe is increasingly looking at alternatives to traditional road transport technologies. Battery Electric Vehicles (BEVs) are seen as a promising technology, which could lead to the decarbonisation of the Light Duty Vehicle fleet and to independence from oil. However it still has to overcome some significant barriers to gain social acceptance and obtain appreciable market penetration. This review evaluates the technological readiness of the different elements of BEV technology and highlights those technological areas where important progress is expected. Techno-economic issues linked with the development of BEVs are investigated. Current BEVs in the market need to be more competitive than other low carbon vehicles, a requirement which stimulates the necessity for new business models. Finally, the all-important role of politics in this development is, also, discussed. As the benefit of BEVs can help countries meet their environmental targets, governments have included them in their roadmaps and have developed incentives to help them penetrate the market.

432 citations


Authors

Showing all 11074 results

NameH-indexPapersCitations
Yang Yang1712644153049
Hongfang Liu1662356156290
Gavin Davies1592036149835
Marjo-Riitta Järvelin156923100939
Matt J. Jarvis144106485559
Alexander Belyaev1421895100796
Louis Lyons138174798864
Silvano Tosi135171297559
John A Coughlan135131296578
Kenichi Hatakeyama1341731102438
Kristian Harder134161396571
Peter R Hobson133159094257
Christopher Seez132125689943
Liliana Teodorescu132147190106
Umesh Joshi131124990323
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202380
2022235
20211,532
20201,475
20191,445
20181,345