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Institution

University of Bath

EducationBath, Bath and North East Somerset, United Kingdom
About: University of Bath is a education organization based out in Bath, Bath and North East Somerset, United Kingdom. It is known for research contribution in the topics: Population & Photonic-crystal fiber. The organization has 15830 authors who have published 39608 publications receiving 1358769 citations. The organization is also known as: Bath University.


Papers
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Journal ArticleDOI
S. Agostinelli1, John Allison2, K. Amako3, J. Apostolakis4, Henrique Araujo5, P. Arce4, Makoto Asai6, D. Axen4, S. Banerjee7, G. Barrand, F. Behner4, Lorenzo Bellagamba8, J. Boudreau9, L. Broglia10, A. Brunengo8, H. Burkhardt4, Stephane Chauvie, J. Chuma11, R. Chytracek4, Gene Cooperman12, G. Cosmo4, P. V. Degtyarenko13, Andrea Dell'Acqua4, G. Depaola14, D. Dietrich15, R. Enami, A. Feliciello, C. Ferguson16, H. Fesefeldt4, Gunter Folger4, Franca Foppiano, Alessandra Forti2, S. Garelli, S. Gianì4, R. Giannitrapani17, D. Gibin4, J. J. Gomez Y Cadenas4, I. González4, G. Gracia Abril4, G. Greeniaus18, Walter Greiner15, Vladimir Grichine, A. Grossheim4, Susanna Guatelli, P. Gumplinger11, R. Hamatsu19, K. Hashimoto, H. Hasui, A. Heikkinen20, A. S. Howard5, Vladimir Ivanchenko4, A. Johnson6, F.W. Jones11, J. Kallenbach, Naoko Kanaya4, M. Kawabata, Y. Kawabata, M. Kawaguti, S.R. Kelner21, Paul R. C. Kent22, A. Kimura23, T. Kodama24, R. P. Kokoulin21, M. Kossov13, Hisaya Kurashige25, E. Lamanna26, Tapio Lampén20, V. Lara4, Veronique Lefebure4, F. Lei16, M. Liendl4, W. S. Lockman, Francesco Longo27, S. Magni, M. Maire, E. Medernach4, K. Minamimoto24, P. Mora de Freitas, Yoshiyuki Morita3, K. Murakami3, M. Nagamatu24, R. Nartallo28, Petteri Nieminen28, T. Nishimura, K. Ohtsubo, M. Okamura, S. W. O'Neale29, Y. Oohata19, K. Paech15, J Perl6, Andreas Pfeiffer4, Maria Grazia Pia, F. Ranjard4, A.M. Rybin, S.S Sadilov4, E. Di Salvo8, Giovanni Santin27, Takashi Sasaki3, N. Savvas2, Y. Sawada, Stefan Scherer15, S. Sei24, V. Sirotenko4, David J. Smith6, N. Starkov, H. Stoecker15, J. Sulkimo20, M. Takahata23, Satoshi Tanaka30, E. Tcherniaev4, E. Safai Tehrani6, M. Tropeano1, P. Truscott31, H. Uno24, L. Urbán, P. Urban32, M. Verderi, A. Walkden2, W. Wander33, H. Weber15, J.P. Wellisch4, Torre Wenaus34, D.C. Williams, Douglas Wright6, T. Yamada24, H. Yoshida24, D. Zschiesche15 
TL;DR: The Gelfant 4 toolkit as discussed by the authors is a toolkit for simulating the passage of particles through matter, including a complete range of functionality including tracking, geometry, physics models and hits.
Abstract: G eant 4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics.

18,904 citations

Journal ArticleDOI
TL;DR: The compelling combination of enhanced optical properties and chemical robustness makes CsPbX3 nanocrystals appealing for optoelectronic applications, particularly for blue and green spectral regions (410–530 nm), where typical metal chalcogenide-based quantum dots suffer from photodegradation.
Abstract: Metal halides perovskites, such as hybrid organic–inorganic CH3NH3PbI3, are newcomer optoelectronic materials that have attracted enormous attention as solution-deposited absorbing layers in solar cells with power conversion efficiencies reaching 20%. Herein we demonstrate a new avenue for halide perovskites by designing highly luminescent perovskite-based colloidal quantum dot materials. We have synthesized monodisperse colloidal nanocubes (4–15 nm edge lengths) of fully inorganic cesium lead halide perovskites (CsPbX3, X = Cl, Br, and I or mixed halide systems Cl/Br and Br/I) using inexpensive commercial precursors. Through compositional modulations and quantum size-effects, the bandgap energies and emission spectra are readily tunable over the entire visible spectral region of 410–700 nm. The photoluminescence of CsPbX3 nanocrystals is characterized by narrow emission line-widths of 12–42 nm, wide color gamut covering up to 140% of the NTSC color standard, high quantum yields of up to 90%, and radiativ...

6,170 citations

Journal ArticleDOI
Theo Vos1, Theo Vos2, Theo Vos3, Stephen S Lim  +2416 moreInstitutions (246)
TL;DR: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates, and there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries.

5,802 citations

Journal ArticleDOI
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as discussed by the authors provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.

5,668 citations

Journal ArticleDOI
Simon N. Wood1
TL;DR: In this article, a Laplace approximation is used to obtain an approximate restricted maximum likelihood (REML) or marginal likelihood (ML) for smoothing parameter selection in semiparametric regression.
Abstract: Summary. Recent work by Reiss and Ogden provides a theoretical basis for sometimes preferring restricted maximum likelihood (REML) to generalized cross-validation (GCV) for smoothing parameter selection in semiparametric regression. However, existing REML or marginal likelihood (ML) based methods for semiparametric generalized linear models (GLMs) use iterative REML or ML estimation of the smoothing parameters of working linear approximations to the GLM. Such indirect schemes need not converge and fail to do so in a non-negligible proportion of practical analyses. By contrast, very reliable prediction error criteria smoothing parameter selection methods are available, based on direct optimization of GCV, or related criteria, for the GLM itself. Since such methods directly optimize properly defined functions of the smoothing parameters, they have much more reliable convergence properties. The paper develops the first such method for REML or ML estimation of smoothing parameters. A Laplace approximation is used to obtain an approximate REML or ML for any GLM, which is suitable for efficient direct optimization. This REML or ML criterion requires that Newton–Raphson iteration, rather than Fisher scoring, be used for GLM fitting, and a computationally stable approach to this is proposed. The REML or ML criterion itself is optimized by a Newton method, with the derivatives required obtained by a mixture of implicit differentiation and direct methods. The method will cope with numerical rank deficiency in the fitted model and in fact provides a slight improvement in numerical robustness on the earlier method of Wood for prediction error criteria based smoothness selection. Simulation results suggest that the new REML and ML methods offer some improvement in mean-square error performance relative to GCV or Akaike's information criterion in most cases, without the small number of severe undersmoothing failures to which Akaike's information criterion and GCV are prone. This is achieved at the same computational cost as GCV or Akaike's information criterion. The new approach also eliminates the convergence failures of previous REML- or ML-based approaches for penalized GLMs and usually has lower computational cost than these alternatives. Example applications are presented in adaptive smoothing, scalar on function regression and generalized additive model selection.

4,846 citations


Authors

Showing all 16056 results

NameH-indexPapersCitations
Michael Grätzel2481423303599
Brenda W.J.H. Penninx1701139119082
Amartya Sen149689141907
Gilbert Laporte12873062608
Andre K. Geim125445206833
Matthew Jones125116196909
Benoît Roux12049362215
Stephen Mann12066955008
Bruno S. Frey11990065368
Raymond A. Dwek11860352259
David Cutts11477864215
John Campbell107115056067
David Chandler10742452396
Peter H.R. Green10684360113
Huajian Gao10566746748
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202386
2022404
20212,474
20202,371
20192,144
20181,972