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Institution

Curtin University

EducationPerth, Western Australia, Australia
About: Curtin University is a education organization based out in Perth, Western Australia, Australia. It is known for research contribution in the topics: Population & Zircon. The organization has 14257 authors who have published 48997 publications receiving 1336531 citations. The organization is also known as: WAIT & Western Australian Institute of Technology.


Papers
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Journal ArticleDOI
TL;DR: In this article, a one-step approach for synthesizing highly luminescent oil soluble carbon dots (quantum yield: 53%) and water-soluble carbon dots is introduced.
Abstract: A novel one-step approach for synthesizing highly luminescent oil soluble carbon dots (quantum yield: 53%) and water-soluble carbon dots is introduced. The superior luminescence efficiency, together with the simple, rapid, and reproducible synthesis method will facilitate fundamental studies and promising practical applications of these carbon-based quantum dots.

366 citations

Journal ArticleDOI
TL;DR: The prostate cancer risk declined with increasing frequency, duration and quantity of green tea consumption, suggesting that green tea is protective against prostate cancer.
Abstract: To investigate whether green tea consumption has an etiological association with prostate cancer, a case-control study was conducted in Hangzhou, southeast China during 2001-2002. The cases were 130 incident patients with histologically confirmed adenocarcinoma of the prostate. The controls were 274 hospital inpatients without prostate cancer or any other malignant diseases, and matched to the age of cases. Information on duration, quantity and frequency of usual tea consumption, as well as the number of new batches brewed per day, were collected by face-to-face interview using a structured questionnaire. The risk of prostate cancer for tea consumption was assessed using multivariate logistic regression adjusting for age, locality, education, income, body mass index, physical activity, alcohol consumption, tobacco smoking, total fat intake, marital status, age at marriage, number of children, history of vasectomy and family history of prostate cancer. Among the cases, 55.4% were tea drinkers compared to 79.9% for the controls. Almost all the tea consumed was green tea. The prostate cancer risk declined with increasing frequency, duration and quantity of green tea consumption. The adjusted odds ratio (OR), relative to non-tea drinkers, were 0.28 (95% CI = 0.17-0.47) for tea drinking, 0.12 (95% CI = 0.06-0.26) for drinking tea over 40 years, 0.09 (95% CI = 0.04-0.21) for those consuming more than 1.5 kg of tea leaves yearly, and 0.27 (95% CI = 0.15-0.48) for those drinking more than 3 cups (1 litre) daily. The dose response relationships were also significant, suggesting that green tea is protective against prostate cancer.

366 citations

Journal ArticleDOI
TL;DR: A novel neural network (NN) training method that employs the hybrid exponential smoothing method and the Levenberg-Marquardt (LM) algorithm, which aims to improve the generalization capabilities of previously used methods for training NNs for short-term traffic flow forecasting.
Abstract: This paper proposes a novel neural network (NN) training method that employs the hybrid exponential smoothing method and the Levenberg-Marquardt (LM) algorithm, which aims to improve the generalization capabilities of previously used methods for training NNs for short-term traffic flow forecasting. The approach uses exponential smoothing to preprocess traffic flow data by removing the lumpiness from collected traffic flow data, before employing a variant of the LM algorithm to train the NN weights of an NN model. This approach aids NN training, as the preprocessed traffic flow data are more smooth and continuous than the original unprocessed traffic flow data. The proposed method was evaluated by forecasting short-term traffic flow conditions on the Mitchell freeway in Western Australia. With regard to the generalization capabilities for short-term traffic flow forecasting, the NN models developed using the proposed approach outperform those that are developed based on the alternative tested algorithms, which are particularly designed either for short-term traffic flow forecasting or for enhancing generalization capabilities of NNs.

366 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present the results of research conducted amongst members of the public in England on their understanding of sustainable tourism; their response to four desired tourism behaviour goals, and expectations about the role of government and the tourism industry in encouraging sustainable tourism.

366 citations

Journal ArticleDOI
TL;DR: In this paper, a broad panel of large US bank holding companies over the period 1997-2011 was used to study whether board structure (board size, independence and gender diversity) in banks relates to performance.
Abstract: We study whether board structure (board size, independence and gender diversity) in banks relates to performance. Using a broad panel of large US bank holding companies over the period 1997–2011, we find that both board size and independent directors decrease bank performance. Although gender diversity improves bank performance in the pre-Sarbanes–Oxley Act (SOX) period (1997–2002), the positive effect of gender diminishes in both the post-SOX (2003–2006) and the crisis periods (2007–2011). Finally, we show that board structure is particularly relevant for banks with low market power, if they are immune to the threat of external takeover and/or they are small. Our two-step system generalised method of moments estimation accounts for endogeneity concerns (simultaneity, reverse causality and unobserved heterogeneity). The findings are robust to a wide range of other sensitivity checks including alternative proxies for bank performance.

365 citations


Authors

Showing all 14504 results

NameH-indexPapersCitations
David Smith1292184100917
Christopher G. Maher12894073131
Mike Wright12777564030
Shaobin Wang12687252463
Mietek Jaroniec12357179561
John B. Holcomb12073353760
Simon A. Wilde11839045547
Jian Liu117209073156
Meilin Liu11782752603
Guochun Zhao11340640886
Mark W. Chase11151950783
Robert U. Newton10975342527
Simon P. Driver10945546299
Peter R. Schofield10969350892
Gao Qing Lu10854653914
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202398
2022455
20214,200
20203,818
20193,822
20183,543