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By continuing this procedure, we can obtain images of the microstructures as a function of depth with a 4-nm lateral resolution and a 10-nm depth resolution.
Continuing this procedure we get a sequence satisfying (3.2).
Continuing this procedure we obtain that and hence.
Continuing this procedure gives x ∈ ⋂ n = 1 ∞ F ( T n ) = F ( W ).
Continuing this procedure we get two sequences and satisfying and (4.2).
The scheme is based on demodulating the strongest interferer and removing its effect from the received signal [15] and then continuing this procedure for the next strongest user.
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I continue this procedure until (S, H, F g ) converges.
If we continue this procedure, we can have (3.9).
We continue this procedure to obtain estimates of the census counts up to and including March 30th 2009, the last date in our testing data.
We continue this procedure until we obtain the function w j such that ∑ u ∈ T w j (u ) = m or the MAF of x i = b for all 1 ≤ i ≤ d.
After the equality of variances is satisfied, the iterative weighting method continues, and this procedure continues as long as a minor change in the estimation occurs from each iteration to the next one.
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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