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Institution

Queensland University of Technology

EducationBrisbane, Queensland, Australia
About: Queensland University of Technology is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 14188 authors who have published 55022 publications receiving 1496237 citations. The organization is also known as: QUT.


Papers
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Journal ArticleDOI
TL;DR: A comprehensive multidisciplinary literature review with an aim to identify the critical issues organizations might need to consider when implementing dashboards and recommend that dashboards come with some level of flexibility, i.e. allowing users to switch between alternative presentation formats.

278 citations

01 Jan 2006
TL;DR: In this article, the authors outline the overall characteristics of produsers and produsage, identify key questions for the produsage model, and highlight the economic, educational, and democratic potential of produsage.
Abstract: The increasing prevalence of user-led content production especially in online environments from the Wikipedia to open news publications and open source software development communities is indicative of an ongoing paradigm shift from industrial-style content production to what is here described as produsage: the collaborative, iterative, and user-led production of content by participants in a hybrid user-producer, or produser role. This paper outlines the overall characteristics of produsers and produsage, identifies key questions for the produsage model, and highlights the economic, educational, and democratic potential of produsage.

278 citations

Journal ArticleDOI
01 Sep 2019
TL;DR: In this paper, a high-throughput screening of catalysts for N2 reduction among (nitrogen-doped) graphene-supported single atom catalysts is performed based on a general two-step strategy.
Abstract: Electrocatalytic or photocatalytic N2 reduction holds great promise for green and sustainable NH3 production under ambient conditions, where an efficient catalyst plays a crucial role but remains a long‐standing challenge. Here, a high‐throughput screening of catalysts for N2 reduction among (nitrogen‐doped) graphene‐supported single atom catalysts is performed based on a general two‐step strategy. 10 promising candidates with excellent performance are extracted from 540 systems. Most strikingly, a single W atom embedded in graphene with three C atom coordination (W1C3) exhibits the best performance with an extremely low onset potential of 0.25 V. This study not only provides a series of promising catalysts for N2 fixation, but also paves a new way for the rational design of catalysts for N2 fixation under ambient conditions.

278 citations

Journal ArticleDOI
TL;DR: Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations and can be extended to other kinds of themulti-term fractional time-space models with fractional Laplacian.
Abstract: In this paper, the multi-term time-fractional wave-diffusion equations are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and techniques can also be extended to other kinds of the multi-term fractional time-space models with fractional Laplacian.

278 citations


Authors

Showing all 14597 results

NameH-indexPapersCitations
Nicholas G. Martin1921770161952
Paul M. Thompson1832271146736
Christopher J. O'Donnell159869126278
Robert G. Parton13645959737
Tim J Cole13682792998
Daniel I. Chasman13448472180
David Smith1292184100917
Dmitri Golberg129102461788
Chao Zhang127311984711
Shi Xue Dou122202874031
Thomas H. Marwick121106358763
Peter J. Anderson12096663635
Bruno S. Frey11990065368
David M. Evans11663274420
Michael Pollak11466357793
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023205
2022641
20214,218
20204,026
20193,623
20183,374