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Institution

University of Southern Queensland

EducationToowoomba, Queensland, Australia
About: University of Southern Queensland is a education organization based out in Toowoomba, Queensland, Australia. It is known for research contribution in the topics: Population & Higher education. The organization has 3037 authors who have published 11241 publications receiving 234781 citations. The organization is also known as: USQ.


Papers
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Journal ArticleDOI
TL;DR: It is shown that the known issues of underestimation of the statistical error and spuriously overconfident estimates with the RE model can be resolved by the use of an estimator under the fixed effect model assumption with a quasi-likelihood based variance structure - the IVhet model.

386 citations

Journal ArticleDOI
TL;DR: In this article, the observed large-scale surface magnetic fields of low-mass stars were reconstructed through Zeeman-Doppler imaging (ZDI), and the results indicated that small and large scale fields could share the same dynamo field generation processes.
Abstract: We investigate how the observed large-scale surface magnetic fields of low-mass stars (~0.1 -- 2 Msun), reconstructed through Zeeman-Doppler imaging (ZDI), vary with age t, rotation and X-ray emission. Our sample consists of 104 magnetic maps of 73 stars, from accreting pre-main sequence to main-sequence objects (1 Myr is related to age as $t^{-0.655 \pm 0.045}$. This relation has a similar dependence to that identified by Skumanich (1972), used as the basis for gyrochronology. Likewise, our relation could be used as an age-dating method ("magnetochronology"). The trends with rotation we find for the large-scale stellar magnetism are consistent with the trends found from Zeeman broadening measurements (sensitive to large- and small-scale fields). These similarities indicate that the fields recovered from both techniques are coupled to each other, suggesting that small- and large-scale fields could share the same dynamo field generation processes. For the accreting objects, fewer statistically significant relations are found, with one being a correlation between the unsigned magnetic flux and rotation period. We attribute this to a signature of star-disc interaction, rather than being driven by the dynamo.

384 citations

Journal ArticleDOI
TL;DR: In this paper, an ANN model was developed to predict a correlation between brake power, torque, brake specific fuel consumption, brake thermal efficiency, volumetric efficiency and emission components using different gasoline-ethanol blends and speeds as inputs data.

384 citations

Journal ArticleDOI
TL;DR: This article provides an outline of the classification of the kingdom Fungi (including fossil fungi), and treats 19 phyla of fungi, including all currently described orders of fungi.
Abstract: This article provides an outline of the classification of the kingdom Fungi (including fossil fungi. i.e. dispersed spores, mycelia, sporophores, mycorrhizas). We treat 19 phyla of fungi. These are Aphelidiomycota, Ascomycota, Basidiobolomycota, Basidiomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Entorrhizomycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota. The placement of all fungal genera is provided at the class-, order- and family-level. The described number of species per genus is also given. Notes are provided of taxa for which recent changes or disagreements have been presented. Fungus-like taxa that were traditionally treated as fungi are also incorporated in this outline (i.e. Eumycetozoa, Dictyosteliomycetes, Ceratiomyxomycetes and Myxomycetes). Four new taxa are introduced: Amblyosporida ord. nov. Neopereziida ord. nov. and Ovavesiculida ord. nov. in Rozellomycota, and Protosporangiaceae fam. nov. in Dictyosteliomycetes. Two different classifications (in outline section and in discussion) are provided for Glomeromycota and Leotiomycetes based on recent studies. The phylogenetic reconstruction of a four-gene dataset (18S and 28S rRNA, RPB1, RPB2) of 433 taxa is presented, including all currently described orders of fungi.

381 citations

Journal ArticleDOI
TL;DR: In comparison with other models of diabetes and obesity, this diet-induced model more closely mimics the changes observed in human metabolic syndrome.
Abstract: The prevalence of metabolic syndrome including central obesity, insulin resistance, impaired glucose tolerance, hypertension, and dyslipidemia is increasing. Development of adequate therapy for metabolic syndrome requires an animal model that mimics the human disease state. Therefore, we have characterized the metabolic, cardiovascular, hepatic, renal, and pancreatic changes in male Wistar rats (8-9 weeks old) fed on a high-carbohydrate, high-fat diet including condensed milk (39.5%), beef tallow (20%), and fructose (17.5%) together with 25% fructose in drinking water; control rats were fed a cornstarch diet. During 16 weeks on this diet, rats showed progressive increases in body weight, energy intake, abdominal fat deposition, and abdominal circumference along with impaired glucose tolerance, dyslipidemia, hyperinsulinemia, and increased plasma leptin and malondialdehyde concentrations. Cardiovascular signs included increased systolic blood pressure and endothelial dysfunction together with inflammation, fibrosis, hypertrophy, increased stiffness, and delayed repolarization in the left ventricle of the heart. The liver showed increased wet weight, fat deposition, inflammation, and fibrosis with increased plasma activity of liver enzymes. The kidneys showed inflammation and fibrosis, whereas the pancreas showed increased islet size. In comparison with other models of diabetes and obesity, this diet-induced model more closely mimics the changes observed in human metabolic syndrome.

372 citations


Authors

Showing all 3156 results

NameH-indexPapersCitations
Howard Isaacson10357542963
Stuart J. H. Biddle10248441251
Lajos Hanzo101204054380
Mika Sillanpää96101944260
Zhigang Chen9678340892
U. Rajendra Acharya9057031592
Hao Wang89159943904
Jin Zou8881233645
Wendy J. Brown8658729735
Hua Wang8058047411
Dinesh Mohan7928335775
Tim J. Gabbett7930218910
Michael Thompson7691128151
Stephen R. Kane7356521583
Jolanda Jetten7029718948
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202352
2022201
20211,157
20201,103
2019874
2018925