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These findings provide useful inputs for numerical models to include the effects of microstructural changes in the study of transport phenomena within the GDL and to increase the accuracy and predictability of cell performance.
Inspired by notch filter theory, we extend the well-known time-varying AR (TVAR) models to include the effects of additive noise, and arrive at two types of time-varying notch filter (TVNF).
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However, we hope to soon extend our model to include the effects of other such strategies.
Using climate model simulations, the team found such an event was incredibly unusual in models that did not include the effects of greenhouse gasses.
In line with previous two-sex models, we include the effect of demographic sex differences.
We can also include the effects of transmural heterogeneity in the TNNP model.
The derived results suffer from model-dependency problems including the effects of model biases.
We established three different models, the first one without the effects of adjuvant therapy (which consists of the MISCAN model including nodal status), the second including effects of chemotherapy and the third model including the effects of tamoxifen.
The model includes the effects of Brownian motion and cross-diffusion effects.
Among them, model 1 only included the effects of control variables.
The statistical model included the effects of group, sex, and the regression of carcass weight.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com