TSuNAMi: Time Series Network Animal Modelling. Our proposal is motivated by and based upon the successful representation of time series as a network (or graph). We construct an abstract representation of a system from measurements of its changing behaviour over time. Properties of that structure (the network) then allow us to infer diagnostic information of the system. Specifically, we propose to apply this to livestock welfare during transport. By measuring the biological and environment condi ....TSuNAMi: Time Series Network Animal Modelling. Our proposal is motivated by and based upon the successful representation of time series as a network (or graph). We construct an abstract representation of a system from measurements of its changing behaviour over time. Properties of that structure (the network) then allow us to infer diagnostic information of the system. Specifically, we propose to apply this to livestock welfare during transport. By measuring the biological and environment condition of the animal we construct a network representation of that system. Geometric features of that network can then be used to infer health or duress of the subject. This proposal will develop the generic mathematical machinery to connect geometric features of the network with system behaviour. Read moreRead less
Metaphotonics and metasurfaces for disruptive sensing technologies. This project aims to address a big challenge in nanophotonics by developing revolutionary methods for efficient chiral sensing of molecules without the need for spectrometry, frequency scanning, or moving mechanical parts, and to enhance chiroptical signals a hundredfold with the help of metasurface structures. Resonant metasurfaces are arrays of engineered dielectric nanoparticles with extraordinary characteristics, and they wo ....Metaphotonics and metasurfaces for disruptive sensing technologies. This project aims to address a big challenge in nanophotonics by developing revolutionary methods for efficient chiral sensing of molecules without the need for spectrometry, frequency scanning, or moving mechanical parts, and to enhance chiroptical signals a hundredfold with the help of metasurface structures. Resonant metasurfaces are arrays of engineered dielectric nanoparticles with extraordinary characteristics, and they would allow to overcome current limitations of chiral sensing analytical tools. Detecting chiral molecules in low concentrations is crucially important to many fields of biology, chemistry, and pharmacy, as well as to the food and cosmetics industries, constituting a market of tens of billions of dollars.Read moreRead less
Understanding the implications of pandemic delays for the end of life. The untold toll of Covid-19 is emerging in ‘avoidable deaths’ linked to late(r) diagnosis or treatment due to pandemic-related delay. How delays are experienced and felt across families and communities requires urgent attention. This project aims to understand the implications of pandemic delay for dying and bereavement, including the sociocultural factors that shape experiences of illness and care amid delay. The significanc ....Understanding the implications of pandemic delays for the end of life. The untold toll of Covid-19 is emerging in ‘avoidable deaths’ linked to late(r) diagnosis or treatment due to pandemic-related delay. How delays are experienced and felt across families and communities requires urgent attention. This project aims to understand the implications of pandemic delay for dying and bereavement, including the sociocultural factors that shape experiences of illness and care amid delay. The significance of this project lies in its innovative sociological approach; expected outcomes include the generation of new knowledge on needs at the end of life that move across contexts and settings. Benefits include provision of findings that will inform social and health policy and practice improvements to enable good deaths.Read moreRead less
The Implementation And Evaluation Of Living Evidence In The Management Of Chronic Kidney Disease.
Funder
National Health and Medical Research Council
Funding Amount
$645,205.00
Summary
Chronic kidney disease (CKD) is a growing health problem. Improving outcomes for patients with CKD requires the translation of research into clinical care. However, scientific research that underpins the management of CKD has rapidly increased, and traditional methods to summarise and inform clinical care are out of date. This project will develop, evaluate, and implement a new approach, known as ‘living-evidence’, that translates research evidence in real-time into the management of patients.
High-resolution multiscale modelling of pandemics: COVID-19 and beyond. The project aims to develop high-resolution computational models for pandemic mitigation and control, focussing on the novel coronavirus and its emerging variants, and leveraging demographic, genomic and epidemiological data. It expects to rigorously compare multi-scale effects of complex vaccination and social distancing strategies and quantify optimal responses under the COVID-19 induced uncertainty. The intended outcomes ....High-resolution multiscale modelling of pandemics: COVID-19 and beyond. The project aims to develop high-resolution computational models for pandemic mitigation and control, focussing on the novel coronavirus and its emerging variants, and leveraging demographic, genomic and epidemiological data. It expects to rigorously compare multi-scale effects of complex vaccination and social distancing strategies and quantify optimal responses under the COVID-19 induced uncertainty. The intended outcomes include computational models of how the most infectious viral variants emerge and spread in presence of interventions, how to predict the outbreaks, and which are the most vulnerable communities. This should make a significant economic and social impact, improving population health while maintaining a resilient economy.Read moreRead less
Quantifying emergence and dynamics of foodborne epidemics in Australia. The project aims to greatly improve the accuracy and scope of computational epidemiological models predicting emergence and evolution of foodborne diseases in Australia. It expects to reveal key pathways for both biological evolution of microorganisms, and their spread though food supply chains and human interactions. The intended outcomes include discovering how the most dominant strains of foodborne infection emerge and se ....Quantifying emergence and dynamics of foodborne epidemics in Australia. The project aims to greatly improve the accuracy and scope of computational epidemiological models predicting emergence and evolution of foodborne diseases in Australia. It expects to reveal key pathways for both biological evolution of microorganisms, and their spread though food supply chains and human interactions. The intended outcomes include discovering how the most dominant strains of foodborne infection emerge and self-organise in complex networks, how to predict and contain the epidemics closer to their source, and which are the most vulnerable groups and communities. This should make a significant economic and social impact, improving health of the population, while also safeguarding national and international supply chains.Read moreRead less
Learning the meso-scale organization of complex networks. This project aims to model and learn the organization of online social networks. We will combine mathematical models, inference, and domain knowledge from computational social sciences to obtain interpretable descriptions of the role groups of users play in the network. The expected outcomes are new mathematical models and computational methods that learn from data how to best decompose a complex network into building blocks and their int ....Learning the meso-scale organization of complex networks. This project aims to model and learn the organization of online social networks. We will combine mathematical models, inference, and domain knowledge from computational social sciences to obtain interpretable descriptions of the role groups of users play in the network. The expected outcomes are new mathematical models and computational methods that learn from data how to best decompose a complex network into building blocks and their interactions, linking connectivity to function. This should provide benefits to industries and policy makers interested in how information spreads in social media, including the critical questions of understanding the mechanisms contributing to political polarization and fragmentation.Read moreRead less
Improved Early Respiratory Support Of Infants And Children
Funder
National Health and Medical Research Council
Funding Amount
$645,205.00
Summary
Worldwide respiratory disease in children has the highest health care burden on society. Children aged <5 years in particular, are increasing in hospital admissions and to intensive care where the cost is elevated. New ways of oxygen therapy have been studied and shown that we can reduce ICU admission if a therapy known as Nasal High Flow (NHF) therapy is applied earlier in the progression of the disease. Further research is needed in NHF therapy and to improve upon our patient outcomes.
Variable Structure Complex Network Systems with Smart Grid Applications. This project aims to establish a breakthrough theory and technology to help deliver reliability and security of complex network systems, which are subject to structure changes, against faults and cyberattacks. Expected outcomes include a new theory that lays the foundation for understanding such systems, innovative algorithms and tools for their design, and a practical software platform used for ensuring reliability and sec ....Variable Structure Complex Network Systems with Smart Grid Applications. This project aims to establish a breakthrough theory and technology to help deliver reliability and security of complex network systems, which are subject to structure changes, against faults and cyberattacks. Expected outcomes include a new theory that lays the foundation for understanding such systems, innovative algorithms and tools for their design, and a practical software platform used for ensuring reliability and security of such systems. It will be applied directly to critical infrastructure such as the national power grid to help maintain lifeline resilience and achieve economic benefits. It will also provide an opportunity to train the next generation engineers in this cutting-edge technology for Australia.Read moreRead less
Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algori ....Feature Learning for High-dimensional Functional Time Series. This project aims to develop new methods and theories for common features on high-dimensional functional time series observed in empirical applications. The significance includes addressing a key gap in adaptive and efficient feature learning, improving forecasting accuracy and understanding forecasting-driven factors comprehensively for empirical data. Expected outcomes involve advances in big data theory and easy-to-implement algorithms for applied researchers. This project benefits not only advanced manufacturing by finding optimal stopping time for wood panel compression, but also superior forecasting for mortality in demography, climate data in environmental science, asset returns in finance, and electricity consumption in economics. Read moreRead less