With all the problems nonequity clubs are facing, he said, "The model we chose is resonating more than ever".
As a cell model, we chose epithelial ovarian cancer, an aggressive disease typically diagnosed at an advanced stage when chemoresistance occurs.
As our model comprised quadratic terms instead of a simple linear model, we chose a D-optimal design in order to minimize the experiment number.
As another in vivo model, we chose to evaluate malignant gliomas because these tumors secrete high levels of VEGF and are refractory to bevacizumab, a monoclonal antibody to inhibit VEGF23,25.
Based on our previous experience with this model, we chose a time point – 4 hours – at which mice with parenchymal TLR4 expression were starting to develop manifestations of SIRS but before animals showed signs of multiorgan failure.
Instead, we wanted to distribute the brute-force foam as a thin layer on top of whatever reflection model we chose to approximate the internal scattering in the foam.
To evaluate our model, we chose to create our custom test environment.
For this model, we chose to focus on eight survey responses, all pertaining to students' participatory behavior.
As a model we chose gold nanoparticles which are considered nontoxic [19] and can be traced histochemically by AMG, even ultrastructurally.
As already stated in the introduction, the model we chose is a linear, deterministic variant of the multiplier accelerator model coupled with the government budget constraint.
Therefore, rather than a single fault model, we chose to use a more realistic fault model to analyze the source process of this earthquake.
