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Solution to the optimal model then allowed us to infer the stem cell number.
The model then allowed us to predict the response to different configurations of the Ds or Fj gradients.
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The radial density model then allows a hard sphere model to be applied to the liquid portions of the planet to predict seismic wavespeeds.
The resulting model then allows a deep semantic understanding of what a computer program is trying to do, from which a number of aspects of software development can be automated.
For this reason, created models were optimized using the MultiRes modifier, which works by first computing the number of vertices and faces in a model, then allows the user to eliminate some of them manually.
The dynamic systems model then allows a space-time functional positioning of a system that broadly reflects its health or disease status; it also offers principle pathways to recovery if a system is considered outside of the favorable health territory.
This model then allows us to test simultaneously the relationship of various factors (associated directly or indirectly with the notion of activity) and cognitive scores driven by cognitive reserve.
Mathematical modelling then allowed to improve our understanding of the complex data obtained.
The relationship between these models then allowed us to dissect exactly the contribution of each order to the total group behavior.
Mathematical analysis and computer simulations of such models then allow us to compare model predictions with experimental observations in order to test, and ultimately improve these models.
Complex physical models then allow the measurement of the relative concentrations of oxy and deoxyhemoglobin, and thus tissue saturation (StO2), as well as an approximation of the tissue hemoglobin, given as tissue hemoglobin index.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com