Testosterone Intervention For The Prevention Of Diabetes Mellitus In High Risk Men: A Randomised Trial
Funder
National Health and Medical Research Council
Funding Amount
$5,054,654.00
Summary
Type 2 diabetes (T2DM) is increasingly common, costly and deadly. Some men at risk of T2DM have low testosterone (T) levels. Our preliminary data suggests that T treatment may prevent the development of T2DM, and improve cardiovascular and sexual function, body composition and bone density, and mood. This remains to be fully tested in a randomized placebo-controlled trial, and this project will do so in a 2-year study of T treatment compared to placebo in men at risk of T2DM participating in a l ....Type 2 diabetes (T2DM) is increasingly common, costly and deadly. Some men at risk of T2DM have low testosterone (T) levels. Our preliminary data suggests that T treatment may prevent the development of T2DM, and improve cardiovascular and sexual function, body composition and bone density, and mood. This remains to be fully tested in a randomized placebo-controlled trial, and this project will do so in a 2-year study of T treatment compared to placebo in men at risk of T2DM participating in a lifestyle program.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies th ....ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies that will allow robots to see as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.Read moreRead less
Making Green Guard® greener: enhancing the efficacy of a biopesticide. The project aims to identify naturally occurring micro-organisms to increase the effectiveness of Green Guard ®, which is a biopesticide used against the Australian plague locust. The project will use next-generation sequencing and other molecular techniques to potentially identify candidate microbes or combinations of microbes that can be added to Green Guard to enhance locust susceptibility. The project also aims to quantif ....Making Green Guard® greener: enhancing the efficacy of a biopesticide. The project aims to identify naturally occurring micro-organisms to increase the effectiveness of Green Guard ®, which is a biopesticide used against the Australian plague locust. The project will use next-generation sequencing and other molecular techniques to potentially identify candidate microbes or combinations of microbes that can be added to Green Guard to enhance locust susceptibility. The project also aims to quantify the interactive impact of temperature and nutrition on immune function, disease resistance and host-plant quality of plague locusts; and to explore the combined effects of temperature, habitat and Green Guard, in combination with candidate microbes or pathogens, on the behaviour and collective movement of locusts. It is anticipated that this will have implications for management and control strategies.Read moreRead less