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Using three mouse models, we explore the effects of suPAR on kidney function and morphology.
Second, based on descriptive analysis, correspondence analysis and multivariate probit models, we explore factors explaining the perception of obstacles, and study complementarities between those obstacles.
On the basis of generic and realistic computer models we explore the concept of acute seizure control through state-dependent feedback stimulation.
To handle such correlation when building predictive models, we explore the usage of a multi-task learning (MTL) framework to search for a combination of tasks and features that highly correlate with the leadership and extraversion traits of humans.
Indeed, both variables change in the models we explore in the Dynamical Models section.
Using simulation models, we explore the impacts of indirect transmission on CWD dynamics among cervids.
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Using a set of thermomechanical models, we explored whether the process of frothing would allow xenoliths to escape sinking once they have dropped into a magma reservoir.
In the four models we explored the impact from STRUCTURE (model 2), kinship coefficients (model 3) or both (model 4) in the association models.
Through the use of ARIMA models, we explored the relationship between environmental variables and influenza cases in two regions characterized by warm climate, Hong Kong (China and Maricopa County Arizonana, USA).
Recognizing that alternative theories of evolution generate different models, we explored alternative datasets and parameters.
Unlike previous prognostic models, we explored more complex relations between continuous predictors and mortality and captured non-linear relations.
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CEO of Professional Science Editing for Scientists @ prosciediting.com