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In order to find an optimized point at which delay is minimized (and consequently throughput maximized), it is necessary to find the maximal point of above equation by taking first derivative and equating it to zero.
Maximal point of fat oxidation.
(i a minimal point of if ; (ii)a weakly minimal point of if ; (iii)a maximal point of if ; (iv a weakly maximal point of if.
Here, and denote the sets of weakly minimal point of and weakly maximal point of, respectively.
Then is the maximal point of the problem (2.6) on and from step : (2.26).
Here, and denote the sets of minimal point of and maximal point of, respectively.
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This implies that the maximal points of ⋃ y ∈ Y min ⋃ x ∈ X G ( x, y ) exist.
And two input vectors, i.e. the minimal and maximal input vectors, are dimension-wisely assembled by the minimal and maximal points of all sectional curves.
By,,,, we denote, respectively, the set of all minimal points, the set of all weakly minimal points, the set of all maximal points, the set of all weakly maximal points of.
In this method, a sectional curve of the system response surface along each input dimensionality is firstly extracted, the minimal and maximal points of which are identified based on its Legendre polynomial approximation.
For any given nonnegative number (a in [0, 3)), let (S_{a}) be the intersection of S and the line (v = - u + 1 + a), that is, S_{a} = S capbigl{ (u, - u + 1 + a): u in Rbigr}. We have (bigcup_{0 le a < 3}S_{a}= Sbackslash{ 2, 2)}). It can be shown that every two distinct points in (S_{a}) are not ⪰2-comparable. Then (S_{a}) is inductive and every point in (S_{a}) is a ⪰2-maximal point of (S_{a}).
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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