Institution
Queensland University of Technology
Education•Brisbane, 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 & Context (language use). The organization has 14188 authors who have published 55022 publications receiving 1496237 citations. The organization is also known as: QUT.
Papers published on a yearly basis
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TL;DR: In this article, the authors highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community and ecosystem-level processes.
Abstract: One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a 'Holy Grail' in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community- and ecosystem-level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized.
475 citations
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Broad Institute1, Harvard University2, Oslo University Hospital3, University of Oslo4, University of Helsinki5, Boston Children's Hospital6, University of Tartu7, Illumina8, Brigham and Women's Hospital9, Charité10, deCODE genetics11, Medical Research Council12, VU University Amsterdam13, Leiden University14, Helsinki University Central Hospital15, University of Tübingen16, Ludwig Maximilian University of Munich17, Karolinska Institutet18, QIMR Berghofer Medical Research Institute19, University of Ulm20, University of Oulu21, King's College London22, Erasmus University Medical Center23, University of Tampere24, University of Duisburg-Essen25, Washington University in St. Louis26, University Medical Center Groningen27, Wellcome Trust Sanger Institute28, University of Oxford29, John Radcliffe Hospital30, Max Planck Society31, University of Kiel32, Technische Universität München33, National Institutes of Health34, Norwegian Institute of Public Health35, University of Copenhagen36, Lundbeck37, Mental Health Services38, University of Turku39, Turku University Hospital40, University of Hamburg41, St George's, University of London42, University of Iceland43, Queensland University of Technology44
TL;DR: For example, the authors identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10−8) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to date is the first to be identified on chromosome X.
Abstract: Migraine is a debilitating neurological disorder affecting around one in seven people worldwide, but its molecular mechanisms remain poorly understood. There is some debate about whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we carried out a genetic study of migraine on 59,674 affected subjects and 316,078 controls from 22 GWA studies. We identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10−8) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to our knowledge is the first to be identified on chromosome X. In subsequent computational analyses, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.
471 citations
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TL;DR: The chlamydiae are an evolutionarily distinct group of eubacteria sharing an obligate intracellular lifestyle and a unique developmental cycle that has been well characterized under favorable cell culture conditions.
Abstract: The chlamydiae are an evolutionarily distinct group of eubacteria sharing an obligate intracellular lifestyle and a unique developmental cycle that has been well characterized under favorable cell culture conditions. This cycle begins when infectious, metabolically inert elementary bodies (EB)
469 citations
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TL;DR: In this paper, confirmatory modeling was used to test models of situational and individual influences on women's and men's managerial advancement and found that although an overall model fitted the data well, separate models f...
Abstract: Confirmatory modeling was used to test models of situational and individual influences on women's and men's managerial advancement. Although an overall model fitted the data well, separate models f...
469 citations
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17 Dec 2015TL;DR: In this paper, the authors evaluated and compared the utility of three state-of-the-art ConvNets on the problems of particular relevance to navigation for robots; viewpoint-invariance and condition-variance, and for the first time enabled real-time place recognition performance using convNets with large maps.
Abstract: After the incredible success of deep learning in the computer vision domain, there has been much interest in applying Convolutional Network (ConvNet) features in robotic fields such as visual navigation and SLAM. Unfortunately, there are fundamental differences and challenges involved. Computer vision datasets are very different in character to robotic camera data, real-time performance is essential, and performance priorities can be different. This paper comprehensively evaluates and compares the utility of three state-of-the-art ConvNets on the problems of particular relevance to navigation for robots; viewpoint-invariance and condition-invariance, and for the first time enables real-time place recognition performance using ConvNets with large maps by integrating a variety of existing (locality-sensitive hashing) and novel (semantic search space partitioning) optimization techniques. We present extensive experiments on four real world datasets cultivated to evaluate each of the specific challenges in place recognition. The results demonstrate that speed-ups of two orders of magnitude can be achieved with minimal accuracy degradation, enabling real-time performance. We confirm that networks trained for semantic place categorization also perform better at (specific) place recognition when faced with severe appearance changes and provide a reference for which networks and layers are optimal for different aspects of the place recognition problem.
466 citations
Authors
Showing all 14597 results
Name | H-index | Papers | Citations |
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Nicholas G. Martin | 192 | 1770 | 161952 |
Paul M. Thompson | 183 | 2271 | 146736 |
Christopher J. O'Donnell | 159 | 869 | 126278 |
Robert G. Parton | 136 | 459 | 59737 |
Tim J Cole | 136 | 827 | 92998 |
Daniel I. Chasman | 134 | 484 | 72180 |
David Smith | 129 | 2184 | 100917 |
Dmitri Golberg | 129 | 1024 | 61788 |
Chao Zhang | 127 | 3119 | 84711 |
Shi Xue Dou | 122 | 2028 | 74031 |
Thomas H. Marwick | 121 | 1063 | 58763 |
Peter J. Anderson | 120 | 966 | 63635 |
Bruno S. Frey | 119 | 900 | 65368 |
David M. Evans | 116 | 632 | 74420 |
Michael Pollak | 114 | 663 | 57793 |