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For each pair of functions, we examined their evolution in two types of environment; in the first case only one function was selected to increase (and the other evolved only as a correlated response to selection on the first), whereas in the second case one function was selected to increase while the other was selected to decrease.
Then, a desirable non-linear function was selected to fit the data.
For the other roundabouts the situation resulted more homogeneous and the gamma function was selected to interpret the empirical distributions.
The Gompertz function was selected to describe kernel growth based on information criteria, biological interpretation of the parameters, and computational ease.
The Kosambi mapping function was selected to convert a recombination frequency to genetic distance (cM).
Similar(55)
Their transfer function is selected to be the tan-sigmoid.
A utility function is selected to reflect the objectives of the optimization problem.
The mean squared error performance function is selected to estimate the ANN performance.
Ten SPH kernels with different orders of function are selected to demonstrate the application of the criterions.
Then the switching action that minimizes a predefined cost function is selected to be applied in the next sampling instant.
The optimal switching state that minimizes the cost function is selected to be applied at the next sampling time.
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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