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Droplet size of 0.7 0.9 mm from the theory compared with the experiments estimates.
As shown in Fig. 10, in our experiments, estimates based on the force sensor were found to change linearly with a gradient of −40 dB/dec, indicating that the outputs from the sensor were mostly noise of a constant level.
The first part of our experiments estimates the appropriate threshold level in order to define an experimental framework.
This is because extrapolation from in vitro experiments estimates the number of NRP1 co-receptors on the tumor endothelium to be 39,500 molecules/cell, compared to the value of 100,000 molecules/cell used in Baseline Model 2, leading to more unbound VEGF.
When considering the power experiments estimates of average bias across the 20,000 replicate experiments were small for the linear regression model, the variable-dispersion beta regression model and the fractional logit regression model (of magnitude 1E-04 through 1E-06 respectively).
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Experiments estimating the impact of 3rd-RF are performed by assimilating oceanographic data in two realistic oceanographic applications.
According to our experiments ("Estimating α and T" section), the theoretical bounds are reasonable for 2-D but not for higher dimensions.
This was done by performing statistically designed experiments, estimating the coefficients in the mathematical models, predicting the response, checking for adequacy of the model and response optimization.
RSM consists of three major steps: performing statistically designed experiments, estimating the coefficients in a mathematical model and predicting the response and checking the adequacy of the model (Bhaumik et al. 2013).
Principally, this optimization process follows three major steps viz., performing the statistically designed experiments, estimating the coefficients in a mathematical model and predicting the responses and examining the adequacy of the model (Myers and Montgomery 1995; Sadhu et al. 2014).
In all our experiments, estimating interaction scores directly from the entire data set performed consistently better.
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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