Curtin University

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.

A Multilab Preregistered Replication of the Ego-Depletion Effect

Abstract: Good self-control has been linked to adaptive outcomes such as better health, cohesive personal relationships, success in the workplace and at school, and less susceptibility to crime and addictions. In contrast, self-control failure is linked to maladaptive outcomes. Understanding the mechanisms by which self-control predicts behavior may assist in promoting better regulation and outcomes. A popular approach to understanding self-control is the strength or resource depletion model. Self-control is conceptualized as a limited resource that becomes depleted after a period of exertion resulting in self-control failure. The model has typically been tested using a sequential-task experimental paradigm, in which people completing an initial self-control task have reduced self-control capacity and poorer performance on a subsequent task, a state known as ego depletion Although a meta-analysis of ego-depletion experiments found a medium-sized effect, subsequent meta-analyses have questioned the size and existence of the effect and identified instances of possible bias. The analyses served as a catalyst for the current Registered Replication Report of the ego-depletion effect. Multiple laboratories (k = 23, total N = 2,141) conducted replications of a standardized ego-depletion protocol based on a sequential-task paradigm by Sripada et al. Meta-analysis of the studies revealed that the size of the ego-depletion effect was small with 95% confidence intervals (CIs) that encompassed zero (d = 0.04, 95% CI [-0.07, 0.15]. We discuss implications of the findings for the ego-depletion effect and the resource depletion model of self-control.

Research progress of perovskite materials in photocatalysis- and photovoltaics-related energy conversion and environmental treatment.

Abstract: Meeting the growing global energy demand is one of the important challenges of the 21st century. Currently over 80% of the world's energy requirements are supplied by the combustion of fossil fuels, which promotes global warming and has deleterious effects on our environment. Moreover, fossil fuels are non-renewable energy and will eventually be exhausted due to the high consumption rate. A new type of alternative energy that is clean, renewable and inexpensive is urgently needed. Several candidates are currently available such as hydraulic power, wind force and nuclear power. Solar energy is particularly attractive because it is essentially clean and inexhaustible. A year's worth of sunlight would provide more than 100 times the energy of the world's entire known fossil fuel reserves. Photocatalysis and photovoltaics are two of the most important routes for the utilization of solar energy. However, environmental protection is also critical to realize a sustainable future, and water pollution is a serious problem of current society. Photocatalysis is also an essential route for the degradation of organic dyes in wastewater. A type of compound with the defined structure of perovskite (ABX3) was observed to play important roles in photocatalysis and photovoltaics. These materials can be used as photocatalysts for water splitting reaction for hydrogen production and photo-degradation of organic dyes in wastewater as well as for photoanodes in dye-sensitized solar cells and light absorbers in perovskite-based solar cells for electricity generation. In this review paper, the recent progress of perovskites for applications in these fields is comprehensively summarized. A description of the basic principles of the water splitting reaction, photo-degradation of organic dyes and solar cells as well as the requirements for efficient photocatalysts is first provided. Then, emphasis is placed on the designation and strategies for perovskite catalysts to improve their photocatalytic activity and/or light adsorption capability. Comments on current and future challenges are also provided. The main purpose of this review paper is to provide a current summary of recent progress in perovskite materials for use in these important areas and to provide some useful guidelines for future development in these hot research areas.

Optimum control strategies in energy conversion of PMSG wind turbine system without mechanical sensors

Abstract: The amount of energy obtained from a wind energy conversion system (WECS) depends not only on the characteristics of the wind regime at the site, but it also depends on the control strategy used for the WECS. In order to determine the gain in energy derived from one concept as compared against another, models of several autonomous WECS have been developed using Matlab Simulink software. These allow easy performance evaluations and comparisons on different control strategies used, and determine the amount of energy injected to the grid in the case of the grid-connected systems. This paper also proposes a prototype version of the control strategy of a 20-kW permanent-magnet synchronous generator (PMSG) for maximum power tracking and compares with the results produced by previous strategies. Advantages of this mechanical sensorless control strategy for maximum power estimation are demonstrated by digital simulation of the system.

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Abstract: Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.