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Institution

University of New South Wales

EducationSydney, New South Wales, Australia
About: University of New South Wales is a education organization based out in Sydney, New South Wales, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 51197 authors who have published 153634 publications receiving 4880608 citations. The organization is also known as: UNSW & UNSW Australia.


Papers
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Journal ArticleDOI
TL;DR: The Southern Hemisphere SHCal04 radiocarbon calibration curve has been updated with the addition of new data sets extending measurements to 2145 cal BP and including the ANSTO Younger Dryas Huon pine data set as mentioned in this paper.
Abstract: The Southern Hemisphere SHCal04 radiocarbon calibration curve has been updated with the addition of new data sets extending measurements to 2145 cal BP and including the ANSTO Younger Dryas Huon pine data set. Outside the range of measured data, the curve is based upon the Northern Hemisphere data sets as presented in IntCal13, with an interhemispheric offset averaging 43 ± 23 yr modeled by an autoregressive process to represent the short-term correlations in the offset. DOI: 10.2458/azu_js_rc.55.16783

1,596 citations

Book
14 Aug 2007
TL;DR: In this paper, the microscopic connection is used to model the Green-Kubo relations of steady states and the nonlinear response theory of linear irreversible thermodynamics is used for steady states.
Abstract: 1. Introduction 2. Linear irreversible thermodynamics 3. The microscopic connection 4. The Green-Kubo relations 5. Linear response theory 6. Computer simulation algorithms 7. Nonlinear response theory 8. Dynamical stability 9. Nonequilibrium fluctuations 10. Thermodynamics of steady states References Index.

1,586 citations

Journal ArticleDOI
Daniel J. Benjamin1, James O. Berger2, Magnus Johannesson1, Magnus Johannesson3, Brian A. Nosek4, Brian A. Nosek5, Eric-Jan Wagenmakers6, Richard A. Berk7, Kenneth A. Bollen8, Björn Brembs9, Lawrence D. Brown7, Colin F. Camerer10, David Cesarini11, David Cesarini12, Christopher D. Chambers13, Merlise A. Clyde2, Thomas D. Cook14, Thomas D. Cook15, Paul De Boeck16, Zoltan Dienes17, Anna Dreber3, Kenny Easwaran18, Charles Efferson19, Ernst Fehr20, Fiona Fidler21, Andy P. Field17, Malcolm R. Forster22, Edward I. George7, Richard Gonzalez23, Steven N. Goodman24, Edwin J. Green25, Donald P. Green26, Anthony G. Greenwald27, Jarrod D. Hadfield28, Larry V. Hedges15, Leonhard Held20, Teck-Hua Ho29, Herbert Hoijtink30, Daniel J. Hruschka31, Kosuke Imai32, Guido W. Imbens24, John P. A. Ioannidis24, Minjeong Jeon33, James Holland Jones34, Michael Kirchler35, David Laibson36, John A. List37, Roderick J. A. Little23, Arthur Lupia23, Edouard Machery38, Scott E. Maxwell39, Michael A. McCarthy21, Don A. Moore40, Stephen L. Morgan41, Marcus R. Munafò42, Shinichi Nakagawa43, Brendan Nyhan44, Timothy H. Parker45, Luis R. Pericchi46, Marco Perugini47, Jeffrey N. Rouder48, Judith Rousseau49, Victoria Savalei50, Felix D. Schönbrodt51, Thomas Sellke52, Betsy Sinclair53, Dustin Tingley36, Trisha Van Zandt16, Simine Vazire54, Duncan J. Watts55, Christopher Winship36, Robert L. Wolpert2, Yu Xie32, Cristobal Young24, Jonathan Zinman44, Valen E. Johnson18, Valen E. Johnson1 
University of Southern California1, Duke University2, Stockholm School of Economics3, University of Virginia4, Center for Open Science5, University of Amsterdam6, University of Pennsylvania7, University of North Carolina at Chapel Hill8, University of Regensburg9, California Institute of Technology10, New York University11, Research Institute of Industrial Economics12, Cardiff University13, Mathematica Policy Research14, Northwestern University15, Ohio State University16, University of Sussex17, Texas A&M University18, Royal Holloway, University of London19, University of Zurich20, University of Melbourne21, University of Wisconsin-Madison22, University of Michigan23, Stanford University24, Rutgers University25, Columbia University26, University of Washington27, University of Edinburgh28, National University of Singapore29, Utrecht University30, Arizona State University31, Princeton University32, University of California, Los Angeles33, Imperial College London34, University of Innsbruck35, Harvard University36, University of Chicago37, University of Pittsburgh38, University of Notre Dame39, University of California, Berkeley40, Johns Hopkins University41, University of Bristol42, University of New South Wales43, Dartmouth College44, Whitman College45, University of Puerto Rico46, University of Milan47, University of California, Irvine48, Paris Dauphine University49, University of British Columbia50, Ludwig Maximilian University of Munich51, Purdue University52, Washington University in St. Louis53, University of California, Davis54, Microsoft55
TL;DR: The default P-value threshold for statistical significance is proposed to be changed from 0.05 to 0.005 for claims of new discoveries in order to reduce uncertainty in the number of discoveries.
Abstract: We propose to change the default P-value threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries.

1,586 citations

Journal ArticleDOI
TL;DR: The as-prepared three-dimensional structured electrodes developed by electrodepositing amorphous mesoporous nickel–iron composite nanosheets directly onto macroporous nickel foam substrates is the most efficient oxygen evolution electrode in alkaline electrolytes reported to the best of the knowledge.
Abstract: Development of efficient and affordable oxygen evolution catalysts is essential for large-scale electrolytic water splitting. Here, the authors report mesoporous nickel–iron composite nanosheets loaded on macroporous nickel foam substrates, and evaluate their electrocatalytic oxygen evolution in basic media.

1,583 citations

Proceedings Article
23 Jun 2010
TL;DR: A detailed analysis of the power consumption of a recent mobile phone, the Openmoko Neo Freerunner, measuring not only overall system power, but the exact breakdown of power consumption by the device's main hardware components.
Abstract: Mobile consumer-electronics devices, especially phones, are powered from batteries which are limited in size and therefore capacity. This implies that managing energy well is paramount in such devices. Good energy management requires a good understanding of where and how the energy is used. To this end we present a detailed analysis of the power consumption of a recent mobile phone, the Openmoko Neo Freerunner. We measure not only overall system power, but the exact breakdown of power consumption by the device's main hardware components. We present this power breakdown for micro-benchmarks as well as for a number of realistic usage scenarios. These results are validated by overall power measurements of two other devices: the HTC Dream and Google Nexus One. We develop a power model of the Freerunner device and analyse the energy usage and battery lifetime under a number of usage patterns. We discuss the significance of the power drawn by various components, and identify the most promising areas to focus on for further improvements of power management. We also analyse the energy impact of dynamic voltage and frequency scaling of the device's application processor.

1,579 citations


Authors

Showing all 51897 results

NameH-indexPapersCitations
Ronald C. Kessler2741332328983
Nicholas G. Martin1921770161952
John C. Morris1831441168413
Richard S. Ellis169882136011
Ian J. Deary1661795114161
Nicholas J. Talley158157190197
Wolfgang Wagner1562342123391
Bruce D. Walker15577986020
Xiang Zhang1541733117576
Ian Smail15189583777
Rui Zhang1512625107917
Marvin Johnson1491827119520
John R. Hodges14981282709
Amartya Sen149689141907
J. Fraser Stoddart147123996083
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023389
20221,183
202111,342
202011,235
20199,891
20189,145