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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.


Papers
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Journal ArticleDOI
B. P. Abbott1, Richard J. Abbott1, T. D. Abbott2, Matthew Abernathy1  +1008 moreInstitutions (96)
TL;DR: This is the first direct detection of gravitational waves and the first observation of a binary black hole merger, and these observations demonstrate the existence of binary stellar-mass black hole systems.
Abstract: On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of $1.0 \times 10^{-21}$. It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203 000 years, equivalent to a significance greater than 5.1 {\sigma}. The source lies at a luminosity distance of $410^{+160}_{-180}$ Mpc corresponding to a redshift $z = 0.09^{+0.03}_{-0.04}$. In the source frame, the initial black hole masses are $36^{+5}_{-4} M_\odot$ and $29^{+4}_{-4} M_\odot$, and the final black hole mass is $62^{+4}_{-4} M_\odot$, with $3.0^{+0.5}_{-0.5} M_\odot c^2$ radiated in gravitational waves. All uncertainties define 90% credible intervals.These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.

9,596 citations

Journal ArticleDOI
Georges Aad1, T. Abajyan2, Brad Abbott3, Jalal Abdallah4  +2964 moreInstitutions (200)
TL;DR: In this article, a search for the Standard Model Higgs boson in proton-proton collisions with the ATLAS detector at the LHC is presented, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9.

9,282 citations

Journal ArticleDOI
Marie Ng1, Tom P Fleming1, Margaret Robinson1, Blake Thomson1, Nicholas Graetz1, Christopher Margono1, Erin C Mullany1, Stan Biryukov1, Cristiana Abbafati2, Semaw Ferede Abera3, Jerry Abraham4, Niveen M E Abu-Rmeileh, Tom Achoki1, Fadia AlBuhairan5, Zewdie Aderaw Alemu6, Rafael Alfonso1, Mohammed K. Ali7, Raghib Ali8, Nelson Alvis Guzmán9, Walid Ammar, Palwasha Anwari10, Amitava Banerjee11, Simón Barquera, Sanjay Basu12, Derrick A Bennett8, Zulfiqar A Bhutta13, Jed D. Blore14, N Cabral, Ismael Ricardo Campos Nonato, Jung-Chen Chang15, Rajiv Chowdhury16, Karen J. Courville, Michael H. Criqui17, David K. Cundiff, Kaustubh Dabhadkar7, Lalit Dandona1, Lalit Dandona18, Adrian Davis19, Anand Dayama7, Samath D Dharmaratne20, Eric L. Ding21, Adnan M. Durrani22, Alireza Esteghamati23, Farshad Farzadfar23, Derek F J Fay19, Valery L. Feigin24, Abraham D. Flaxman1, Mohammad H. Forouzanfar1, Atsushi Goto, Mark A. Green25, Rajeev Gupta, Nima Hafezi-Nejad23, Graeme J. Hankey26, Heather Harewood, Rasmus Havmoeller27, Simon I. Hay8, Lucia Hernandez, Abdullatif Husseini28, Bulat Idrisov29, Nayu Ikeda, Farhad Islami30, Eiman Jahangir31, Simerjot K. Jassal17, Sun Ha Jee32, Mona Jeffreys33, Jost B. Jonas34, Edmond K. Kabagambe35, Shams Eldin Ali Hassan Khalifa, Andre Pascal Kengne36, Yousef Khader37, Young-Ho Khang38, Daniel Kim39, Ruth W Kimokoti40, Jonas Minet Kinge41, Yoshihiro Kokubo, Soewarta Kosen, Gene F. Kwan42, Taavi Lai, Mall Leinsalu22, Yichong Li, Xiaofeng Liang43, Shiwei Liu43, Giancarlo Logroscino44, Paulo A. Lotufo45, Yuan Qiang Lu21, Jixiang Ma43, Nana Kwaku Mainoo, George A. Mensah22, Tony R. Merriman46, Ali H. Mokdad1, Joanna Moschandreas47, Mohsen Naghavi1, Aliya Naheed48, Devina Nand, K.M. Venkat Narayan7, Erica Leigh Nelson1, Marian L. Neuhouser49, Muhammad Imran Nisar13, Takayoshi Ohkubo50, Samuel Oti, Andrea Pedroza, Dorairaj Prabhakaran, Nobhojit Roy51, Uchechukwu K.A. Sampson35, Hyeyoung Seo, Sadaf G. Sepanlou23, Kenji Shibuya52, Rahman Shiri53, Ivy Shiue54, Gitanjali M Singh21, Jasvinder A. Singh55, Vegard Skirbekk41, Nicolas J. C. Stapelberg56, Lela Sturua57, Bryan L. Sykes58, Martin Tobias1, Bach Xuan Tran59, Leonardo Trasande60, Hideaki Toyoshima, Steven van de Vijver, Tommi Vasankari, J. Lennert Veerman61, Gustavo Velasquez-Melendez62, Vasiliy Victorovich Vlassov63, Stein Emil Vollset41, Stein Emil Vollset64, Theo Vos1, Claire L. Wang65, Xiao Rong Wang66, Elisabete Weiderpass, Andrea Werdecker, Jonathan L. Wright1, Y Claire Yang67, Hiroshi Yatsuya68, Jihyun Yoon, Seok Jun Yoon69, Yong Zhao70, Maigeng Zhou, Shankuan Zhu71, Alan D. Lopez14, Christopher J L Murray1, Emmanuela Gakidou1 
University of Washington1, Sapienza University of Rome2, Mekelle University3, University of Texas at San Antonio4, King Saud bin Abdulaziz University for Health Sciences5, Debre markos University6, Emory University7, University of Oxford8, University of Cartagena9, United Nations Population Fund10, University of Birmingham11, Stanford University12, Aga Khan University13, University of Melbourne14, National Taiwan University15, University of Cambridge16, University of California, San Diego17, Public Health Foundation of India18, Public Health England19, University of Peradeniya20, Harvard University21, National Institutes of Health22, Tehran University of Medical Sciences23, Auckland University of Technology24, University of Sheffield25, University of Western Australia26, Karolinska Institutet27, Birzeit University28, Brandeis University29, American Cancer Society30, Ochsner Medical Center31, Yonsei University32, University of Bristol33, Heidelberg University34, Vanderbilt University35, South African Medical Research Council36, Jordan University of Science and Technology37, New Generation University College38, Northeastern University39, Simmons College40, Norwegian Institute of Public Health41, Boston University42, Chinese Center for Disease Control and Prevention43, University of Bari44, University of São Paulo45, University of Otago46, University of Crete47, International Centre for Diarrhoeal Disease Research, Bangladesh48, Fred Hutchinson Cancer Research Center49, Teikyo University50, Bhabha Atomic Research Centre51, University of Tokyo52, Finnish Institute of Occupational Health53, Heriot-Watt University54, University of Alabama at Birmingham55, Griffith University56, National Center for Disease Control and Public Health57, University of California, Irvine58, Johns Hopkins University59, New York University60, University of Queensland61, Universidade Federal de Minas Gerais62, National Research University – Higher School of Economics63, University of Bergen64, Columbia University65, Shandong University66, University of North Carolina at Chapel Hill67, Fujita Health University68, Korea University69, Chongqing Medical University70, Zhejiang University71
TL;DR: The global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013 is estimated using a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).

9,180 citations

Journal ArticleDOI
12 Oct 2016-BMJ
TL;DR: Risk of Bias In Non-randomised Studies - of Interventions is developed, a new tool for evaluating risk of bias in estimates of the comparative effectiveness of interventions from studies that did not use randomisation to allocate units or clusters of individuals to comparison groups.
Abstract: Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.

8,028 citations

Journal ArticleDOI
TL;DR: In this paper, the authors used a Geiger counter spectrometer to measure the changes in intensity distribution in the spectra of cold worked aluminium and wolfram and found that the line breadths may be attributed to simultaneous small particle size and strain broadening, the latter predominating at the higher Bragg angles.

7,802 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