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Applying the CFD model, we predicted the local yielding rate of nanotubes along the axis of the reactor.
Without other adjustments to the model, we predicted the correct stress levels in the free and channel-die compression experiments as well as values of Lankford coefficients.
Based on the projections of our model, we predicted a large availability of high suitability areas across the entire alpine range, which promises great potential for wolf range expansion in the near future.
Through the use of our mathematical model, we predicted that (i) mutant Tf-CRM107 exhibits a greater cytotoxicity than wild-type Tf-CRM107 against cancerous cells, (ii) this improvement was more drastic with CRM107 conjugates than with DT conjugates, and (iii) mutant Tf-CRM107 conjugates were selective against non-neoplastic cells.
Using a mathematical model, we predicted the existence of an optimal programmed death rate that maximizes population growth under stress.
After estimating the probit model, we predicted the propensity scores and the common support region.
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Using this model, we predict the total logistics values for years 2010-2015.
Using the developed model, we predict the load drop during cyclic fatigue testing of the two chosen alloys.
Using a bioclimatic model we predict that it has a large potential distribution in South Africa, especially along the southern coast.
Using this model, we predict trap lifetimes based on the measurable noise spectra of the fluctuations.
In the regression model, we predict natural logged WTP by participation in intervention (main variable of interest) while controlling for demographic and socioeconomic characteristics.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com