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Institution

University of Wollongong

EducationWollongong, New South Wales, Australia
About: University of Wollongong is a education organization based out in Wollongong, New South Wales, Australia. It is known for research contribution in the topics: Population & Graphene. The organization has 15674 authors who have published 46658 publications receiving 1197471 citations. The organization is also known as: UOW & Wollongong University.
Topics: Population, Graphene, Mental health, Anode, Lithium


Papers
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Journal ArticleDOI
TL;DR: The relations between insulinemia, insulin resistance, and blood pressure differ among racial groups and may be mediated by mechanisms active in whites, but not in Pima Indians or blacks.
Abstract: Background. Insulin resistance and the concomitant compensatory hyperinsulinemia have been implicated in the pathogenesis of hypertension. However, reports on the relation between insulin and blood pressure are inconsistent. This study was designed to investigate the possibility of racial differences in this relation. Methods. We studied 116 Pima Indians, 53 whites, and 42 blacks who were normotensive and did not have diabetes; the groups were comparable with respect to mean age (29, 30, and 31 years, respectively) and blood pressure (113/70, 111/68, and 113/68 mm Hg, respectively). Insulin resistance was determined by the euglycemic—hyperinsulinemic clamp technique during low-dose (40 mU per square meter of body-surface area per minute) and high-dose (400 mU per square meter per minute) insulin infusions. Results. The Pima Indians had higher fasting plasma insulin concentrations than the whites or blacks (176, 138, and 122 pmol per liter, respectively; P = 0.002) and lower rates of whole-body gl...

433 citations

Book ChapterDOI
TL;DR: An attempt is made to clarify and tease apart the somewhat confusing terms genre, register, text type, domain, sublanguage, and style, and a spreadsheet/database containing genre labels and other types of information about the BNC texts will be described and its usefulness shown.
Abstract: In this paper, an attempt is first made to clarify and tease apart the somewhat confusing terms genre, register, text type, domain, sublanguage, and style. The use of these terms by various linguists and literary theorists working under different traditions or orientations will be examined and a possible way of synthesising their insights will be proposed and illustrated with reference to the disparate categories used to classify texts in various existing computer corpora. With this terminological problem resolved, a personal project which involved giving each of the 4,124 British National Corpus (BNC, version 1) files a descriptive "genre" label will then be described. The result of this work, a spreadsheet/database (the "BNC Index") containing genre labels and other types of information about the BNC texts will then be described and its usefulness shown. It is envisaged that this resource will allow linguists, language teachers, and other users to easily navigate through or scan the huge BNC jungle more easily, to quickly ascertain what is there (and how much) and to make informed selections from the mass of texts available. It should also greatly facilitate genre-based research (e.g., EAP, ESP, discourse analysis, lexicogrammatical, and collocational studies) and focus everyday classroom concordancing activities by making it easy for people to restrict their searches to highly specified sub-sets of the BNC using PC-based concordancers such as WordSmith, MonoConc, or the Web-based BNCWeb.

433 citations

Journal ArticleDOI
TL;DR: In this paper, the precursors of Li4Ti5O12 were characterized by thermogravimetry and differential scanning calorimetry using X-ray diffraction, transmission electron microscopy (TEM) and electrochemical measurements.
Abstract: Spinel Li4Ti5O12 nanoparticles were prepared via a high-temperature solid-state reaction by adding the prepared cellulose to an aqueous dispersion of lithium salts and titanium dioxide. The precursors of Li4Ti5O12 were characterized by thermogravimetry and differential scanning calorimetry. The obtained Li4Ti5O12 nanoparticles were characterized using X-ray diffraction, transmission electron microscopy (TEM) and electrochemical measurements. The TEM revealed that the Li4Ti5O12 prepared with cellulose is composed of nanoparticles with an average particle diameter of 20–30 nm. Galvanostatic battery testing showed that nano-sized Li4Ti5O12 exhibit better electrochemical properties than submicro-sized Li4Ti5O12 do especially at high current rates, which can deliver a reversible discharge capacity of 131 mAh g−1 at the rate of 10 C, whereas that of the submicro-sized sample decreases to 25 mAh g−1 at the same rate (10 C). Its reversible capacity is maintained at ~172.2 mAh g−1 with the voltage range 1.0–3.0 V (vs. Li) at the current rate of 0.5 C for over 80 cycles.

431 citations

Journal ArticleDOI
TL;DR: High removal efficiencies were observed with most compounds bearing electron donating functional groups such as hydroxyl and primary amine groups, whereas all hydrophilic and moderately hydrophobic compounds showed removal efficiency of less than 20%.

430 citations

Proceedings ArticleDOI
01 Jul 2017
TL;DR: Joint Geometrical and Statistical Alignment (JGSA) as mentioned in this paper learns two coupled projections that project the source domain and target domain data into low-dimensional subspaces where the geometrical shift and distribution shift are reduced simultaneously.
Abstract: This paper presents a novel unsupervised domain adaptation method for cross-domain visual recognition We propose a unified framework that reduces the shift between domains both statistically and geometrically, referred to as Joint Geometrical and Statistical Alignment (JGSA) Specifically, we learn two coupled projections that project the source domain and target domain data into low-dimensional subspaces where the geometrical shift and distribution shift are reduced simultaneously The objective function can be solved efficiently in a closed form Extensive experiments have verified that the proposed method significantly outperforms several state-of-the-art domain adaptation methods on a synthetic dataset and three different real world cross-domain visual recognition tasks

428 citations


Authors

Showing all 15918 results

NameH-indexPapersCitations
Lei Jiang1702244135205
Menachem Elimelech15754795285
Yoshio Bando147123480883
Paul Mitchell146137895659
Jun Chen136185677368
Zhen Li127171271351
Neville Owen12770074166
Chao Zhang127311984711
Jay Belsky12444155582
Shi Xue Dou122202874031
Keith A. Johnson12079851034
William R. Forman12080053717
Yang Li117131963111
Yusuke Yamauchi117100051685
Guoxiu Wang11765446145
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202388
2022483
20212,897
20203,018
20192,784