Institution
University of British Columbia
Education•Vancouver, British Columbia, Canada•
About: University of British Columbia is a education organization based out in Vancouver, British Columbia, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 89939 authors who have published 209679 publications receiving 9226862 citations. The organization is also known as: UBC & The University of British Columbia.
Papers published on a yearly basis
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TL;DR: It is found that environmental conditions strongly influence the distribution of functional groups in marine microbial communities by shaping metabolic niches, but only weakly influence taxonomic composition within individual functional groups.
Abstract: Microbial metabolism powers biogeochemical cycling in Earth’s ecosystems. The taxonomic composition of microbial communities varies substantially between environments, but the ecological causes of this variation remain largely unknown. We analyzed taxonomic and functional community profiles to determine the factors that shape marine bacterial and archaeal communities across the global ocean. By classifying >30,000 marine microorganisms into metabolic functional groups, we were able to disentangle functional from taxonomic community variation. We find that environmental conditions strongly influence the distribution of functional groups in marine microbial communities by shaping metabolic niches, but only weakly influence taxonomic composition within individual functional groups. Hence, functional structure and composition within functional groups constitute complementary and roughly independent “axes of variation” shaped by markedly different processes.
1,566 citations
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TL;DR: In the noncooperative game, subsidies change the initial conditions of the game that firms play as mentioned in this paper, and the terms of trade move against the subsidizing country, but its welfare can increase if price exceeds the marginal cost of exports.
1,566 citations
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German Cancer Research Center1, Helmholtz-Zentrum Dresden-Rossendorf2, McGill University3, Moffitt Cancer Center4, Harvard University5, Brigham and Women's Hospital6, Kettering University7, Johns Hopkins University8, University of Pennsylvania9, University Medical Center Groningen10, University of Zurich11, King's College London12, University of Lausanne13, Netherlands Cancer Institute14, Stanford University15, University of Michigan16, Maastricht University Medical Centre17, University of Tübingen18, University of Bergen19, University of California, San Francisco20, University of Geneva21, University of British Columbia22, Cardiff University23, Leiden University Medical Center24
TL;DR: A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software and could be excellently reproduced.
Abstract: Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuhl and Truhn in this issue.
1,563 citations
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TL;DR: The Personal Involvement Inventory (PII) as discussed by the authors is a context-free measure applicable to involvement with products, with advertisements, and with purchase situations, and it has been shown that the PII may be reliably reduced from twenty items to ten items.
Abstract: The conceptualization of the Personal Involvement Inventory was a context-free measure applicable to involvement with products, with advertisements, and with purchase situations. The empirical work to develop this measure was mainly validated with respect to product categories. This paper extends the construct validation of the PII to involvement with advertisements and also demonstrates that the PII may be reliably reduced from twenty items to ten items. There is some indication the revised PII may then be broken into two subscales representing a cognitive and affective grouping.
1,562 citations
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26 Apr 2009TL;DR: In this paper, the performance of non-graphics applications written in NVIDIA's CUDA programming model is evaluated on a microarchitecture performance simulator that runs NVIDIA's parallel thread execution (PTX) virtual instruction set.
Abstract: Modern Graphic Processing Units (GPUs) provide sufficiently flexible programming models that understanding their performance can provide insight in designing tomorrow's manycore processors, whether those are GPUs or otherwise. The combination of multiple, multithreaded, SIMD cores makes studying these GPUs useful in understanding tradeoffs among memory, data, and thread level parallelism. While modern GPUs offer orders of magnitude more raw computing power than contemporary CPUs, many important applications, even those with abundant data level parallelism, do not achieve peak performance. This paper characterizes several non-graphics applications written in NVIDIA's CUDA programming model by running them on a novel detailed microarchitecture performance simulator that runs NVIDIA's parallel thread execution (PTX) virtual instruction set. For this study, we selected twelve non-trivial CUDA applications demonstrating varying levels of performance improvement on GPU hardware (versus a CPU-only sequential version of the application). We study the performance of these applications on our GPU performance simulator with configurations comparable to contemporary high-end graphics cards. We characterize the performance impact of several microarchitecture design choices including choice of interconnect topology, use of caches, design of memory controller, parallel workload distribution mechanisms, and memory request coalescing hardware. Two observations we make are (1) that for the applications we study, performance is more sensitive to interconnect bisection bandwidth rather than latency, and (2) that, for some applications, running fewer threads concurrently than on-chip resources might otherwise allow can improve performance by reducing contention in the memory system.
1,558 citations
Authors
Showing all 90682 results
Name | H-index | Papers | Citations |
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Gordon H. Guyatt | 231 | 1620 | 228631 |
John C. Morris | 183 | 1441 | 168413 |
Douglas Scott | 178 | 1111 | 185229 |
John R. Yates | 177 | 1036 | 129029 |
Deborah J. Cook | 173 | 907 | 148928 |
Richard A. Gibbs | 172 | 889 | 249708 |
Evan E. Eichler | 170 | 567 | 150409 |
James F. Sallis | 169 | 825 | 144836 |
Michael Snyder | 169 | 840 | 130225 |
Jiawei Han | 168 | 1233 | 143427 |
Michael Kramer | 167 | 1713 | 127224 |
Bruce L. Miller | 163 | 1153 | 115975 |
Peter A. R. Ade | 162 | 1387 | 138051 |
Marc W. Kirschner | 162 | 457 | 102145 |
Kaj Blennow | 160 | 1845 | 116237 |