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Scheme : Discovery Projects
Research Topic : tissue distribution
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  • Funded Activity

    Discovery Projects - Grant ID: DP130103131

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Generating multi-component scaffolding to influence the differentiation of embryonic stem cells. Nervous system diseases are debilitating and will develop in over 50 per cent of people at some time in their life. This project will develop strategies so that stem cells can be utilised to encourage brain repair for the treatment of Parkinson's disease. The technology developed will also be of benefit for the treatment of other nervous system disorders.
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    Funded Activity

    Discovery Projects - Grant ID: DP110101758

    Funder
    Australian Research Council
    Funding Amount
    $364,771.00
    Summary
    Development of an 'ageing household' model for assessing medium to long-term vaccine impact in populations. As birth rates in developed and newly industrialising countries fall, so too do the number of households containing children, with implications for the spread of infections in families. We aim to study the influence of this phenomenon on the risk of common childhood infections, and the length of time that vaccines given in infancy will protect.
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    Funded Activity

    Discovery Projects - Grant ID: DP140104219

    Funder
    Australian Research Council
    Funding Amount
    $480,000.00
    Summary
    Robust AI Planning for Hybrid Systems. Automated planning, a core area of Artificial Intelligence, can effectively deal with the automatic synthesis of optimised action strategies for discrete system models. Extending the reach of planning to hybrid discrete/continuous systems, under exogenous uncertainty, is a widely open problem which this project will address. This will enable the proactive, and therefore more effective, management of microgrids and other cyber-physical systems, based on fore .... Robust AI Planning for Hybrid Systems. Automated planning, a core area of Artificial Intelligence, can effectively deal with the automatic synthesis of optimised action strategies for discrete system models. Extending the reach of planning to hybrid discrete/continuous systems, under exogenous uncertainty, is a widely open problem which this project will address. This will enable the proactive, and therefore more effective, management of microgrids and other cyber-physical systems, based on forecast information.
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