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CFD predictions with quantum gas LiDAR measurements, using simulated and experimental data to relate observed concentration fields to underlying emission sources. This will include the development
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modelling: -Weighted PINNs, -Bayesian PINNs, -Stochastic PINNs, -Ensemble PINNs, -Domain-decomposition PINNs. Selected approaches will be tested within a dedicated data-assimilation framework
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Helmholtz-Zentrum für Infektionsforschung GmbH | Braunschweig, Niedersachsen | Germany | 15 days ago
climate,environmental, land-use and socio-economic drivers to predict vector distribution, transmission potential andoutbreak risk for pathogens such as West Nile fever,tick-borne infections and Aedes-borne
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conditions. However, current global climate models (GCMs) lack the spatial resolution to capture these processes, while high-resolution regional models remain too computationally expensive for large ensemble
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implemented within an ensemble variational data assimilation system, enabling short-term forecasts based on sea ice concentration and thickness data while providing associated uncertainty estimates. In a second