Environmental contamination and pig disease: an Australian microbe evolves. The Australian pig industry produces pork commodities from over 4.75 million pigs per year. Infectious diseases in industrial-scale piggeries can have a devastating effect on pork production, particularly on feed conversion efficiency and growth rates, and can pose downstream environmental contamination and food safety risks. This project aims to assess a current infectious disease problem in pigs by studying a microbe t ....Environmental contamination and pig disease: an Australian microbe evolves. The Australian pig industry produces pork commodities from over 4.75 million pigs per year. Infectious diseases in industrial-scale piggeries can have a devastating effect on pork production, particularly on feed conversion efficiency and growth rates, and can pose downstream environmental contamination and food safety risks. This project aims to assess a current infectious disease problem in pigs by studying a microbe that appears to have uniquely evolved in Australia. These results could inform the rational design of monitoring, prevention and treatment strategies to minimise infection outbreaks in Australian pigs and may result in production benefits to the pork industry, reduced environmental microbial contamination and safer food.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/NHMRC Research Network for Parasitology. The ARC Network for Parasitology will focus and coordinate Australia's world class fundamental, strategic and applied parasitology research. This targeted approach will raise Australia's standing in the field, assist in the community's understanding of parasitology and biosecurity and maintain and improve Australia's capacity for keeping its stock, crops, wildlife and people disease-free. On an international scale, the Network will work with other cou ....ARC/NHMRC Research Network for Parasitology. The ARC Network for Parasitology will focus and coordinate Australia's world class fundamental, strategic and applied parasitology research. This targeted approach will raise Australia's standing in the field, assist in the community's understanding of parasitology and biosecurity and maintain and improve Australia's capacity for keeping its stock, crops, wildlife and people disease-free. On an international scale, the Network will work with other countries to develop new technologies for the detection and eradication of parasites. This emphasis will not only protect Australia's borders but will assist our near neighbours and lead to the development of technologies with an economic benefit to Australia.
Read moreRead less
A National Population-based Study Of Rheumatic Heart Disease In Pregnancy
Funder
National Health and Medical Research Council
Funding Amount
$877,826.00
Summary
Whilst overall a rare disease, Indigenous peoples have disproportionately high rates of rheumatic heart disease (RHD). This study explores the prevalence and distribution of RHD in pregnancy in Australia and New Zealand. It details current management, diagnostic and referral process and risk factors. Key attributes of culturally safe models of care for RHD in pregnancy are explored, particularly as they relate to Indigenous women. Findings will inform policy, guidelines and education resources.
Industrial Transformation Research Hubs - Grant ID: IH210100030
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The ex ....ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The expected outcomes are robots with the ability to autonomously collect data for integration into a digital twin that provides a real-time representation of the true state of a physical asset. The benefits include both improved asset management and establishing Australia as a leading manufacturer of advanced robotic systems.Read moreRead less
A hierarchical quantum mechanical and classical simulation of biological ion channels. I aim to develop a methodology incorporating molecular quantum
mechanics and classical Brownian mechanics in a way that can be
applied practically to large macromolecular systems, thus relating
fine structural details to experimentally measurable
properties. Specifically, I will apply this methodology to study ion
channels in which the challenge is to relate electronic and atomic
structure to the conduct ....A hierarchical quantum mechanical and classical simulation of biological ion channels. I aim to develop a methodology incorporating molecular quantum
mechanics and classical Brownian mechanics in a way that can be
applied practically to large macromolecular systems, thus relating
fine structural details to experimentally measurable
properties. Specifically, I will apply this methodology to study ion
channels in which the challenge is to relate electronic and atomic
structure to the conductance properties of the channel. Accurately
determining these relationships provides a pathway to developing cures
for many neurological, cardiac, and muscular diseases.
Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100203
Funder
Australian Research Council
Funding Amount
$385,000.00
Summary
Autonomous benthic observing system. This project seeks to improve our ability to monitor marine habitats and characterise their variability by enhancing the Integrated Marine Observing system (IMOS) Autonomous Underwater Vehicle (AUV) Facility. The new AUV infrastructure will reduce operating costs, increase robustness of the sampling effort and insure continued operation for the next decade.