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Institution

University of Birmingham

EducationBirmingham, United Kingdom
About: University of Birmingham is a education organization based out in Birmingham, United Kingdom. It is known for research contribution in the topics: Population & Poison control. The organization has 51794 authors who have published 115304 publications receiving 4335316 citations. The organization is also known as: Birmingham University & Uni of Birmingham.


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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: SciPy as discussed by the authors is an open source scientific computing library for the Python programming language, which includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics.
Abstract: SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments.

12,774 citations

Journal ArticleDOI
TL;DR: In this paper, it is shown that to answer several questions of physical or engineering interest, it is necessary to know only the relatively simple elastic field inside the ellipsoid.
Abstract: It is supposed that a region within an isotropic elastic solid undergoes a spontaneous change of form which, if the surrounding material were absent, would be some prescribed homogeneous deformation. Because of the presence of the surrounding material stresses will be present both inside and outside the region. The resulting elastic field may be found very simply with the help of a sequence of imaginary cutting, straining and welding operations. In particular, if the region is an ellipsoid the strain inside it is uniform and may be expressed in terms of tabu­lated elliptic integrals. In this case a further problem may be solved. An ellipsoidal region in an infinite medium has elastic constants different from those of the rest of the material; how does the presence of this inhomogeneity disturb an applied stress-field uniform at large distances? It is shown that to answer several questions of physical or engineering interest it is necessary to know only the relatively simple elastic field inside the ellipsoid.

11,784 citations

Journal ArticleDOI
07 Jan 1993-Nature
TL;DR: The best understood form of long-term potentiation is induced by the activation of the N-methyl-d-aspartate receptor complex, which allows electrical events at the postsynaptic membrane to be transduced into chemical signals which, in turn, are thought to activate both pre- and post Synaptic mechanisms to generate a persistent increase in synaptic strength.
Abstract: Long-term potentiation of synaptic transmission in the hippocampus is the primary experimental model for investigating the synaptic basis of learning and memory in vertebrates. The best understood form of long-term potentiation is induced by the activation of the N-methyl-D-aspartate receptor complex. This subtype of glutamate receptor endows long-term potentiation with Hebbian characteristics, and allows electrical events at the postsynaptic membrane to be transduced into chemical signals which, in turn, are thought to activate both pre- and postsynaptic mechanisms to generate a persistent increase in synaptic strength.

11,123 citations

Journal ArticleDOI
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.

10,401 citations


Authors

Showing all 52384 results

NameH-indexPapersCitations
Nicholas G. Martin1921770161952
Paul G. Richardson1831533155912
Jie Zhang1784857221720
David R. Williams1782034138789
Masayuki Yamamoto1711576123028
Gregory Y.H. Lip1693159171742
Dennis R. Burton16468390959
J. E. Brau1621949157675
L. Joseph Melton16153197861
Paul Emery1581314121293
Wolfgang Wagner1562342123391
David H. Adams1551613117783
Julian Parkhill149759104736
J. Fraser Stoddart147123996083
Robert A. Kyle146122189997
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023273
20221,004
20216,572
20206,200
20195,625
20185,088