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recommendations will be generated to optimize glycemic control and reduce risk of complications. The research will integrate both observational analyses of CGM data and a subsequent clinical trial to evaluate
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, this project will Investigate current DES(s) on “controlled” mixed battery chemistries; specifically NMC:LFP ratios. It will also develop an extraction process to optimally recover metals from NMC:LFP black mass
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the optimal habitat reconstruction for declining bird species, how to best engage community and landholders in the recovery effort, and priority species-specific objectives for guiding restoration actions and
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into neural networks. PINNs can model real-world signals with sparse, non-uniform, and noisy data. A key question is determining the optimal method for integrating physical priors into neural networks
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treated differently, and whether the current arrangements are optimal or could be improved. Documenting cumulative Adelaide Park Lands losses, over time For a student interested in local history, heritage
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to different control measures, allowing us to develop strategies for optimal application of barrier treatment. This project is part of the national Analytics for the Australian Grains Industry (AAGI) initiative