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end{aligned} This estimation shows that F maps Q into itself.
In particular, this estimation shows that the recovery accuracy of the mixed l 2/l q minimization can be controlled by the degree of sparsity of the signal and the exponential number q.
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This estimation showed that survivors (n=10) had a significantly larger number of tumour cells in their grafts than did patients who died of relapse (n=14) (P=0.01, Wilcoxon rank-sum test, Figure 2A ).
However, the estimation shows discrepancies with the observed TEC in the year 2009.
However, with limited amounts of adaptation data, the estimation shows severe over-fitting, resulting in very bad adaptation performance[3].
This simple estimation shows that more than a decade will likely be required for the activity levels to return to pre-accident levels.
The required time interval for the S-WPIA based on the estimation shown in Fig. 2c is evaluated.
The incidence rate ratios (IRR) from the estimation show the relative effect of a characteristic holding other factors constant.
The various intervals of time used for the estimation showed important variations among health regions, as presented in Additional file 1: Proxy dates for estimating date of onset.
Our estimation shows this variation is linked to the degree of capacity constraint of a hospital.
Road slope estimation shows bigger estimation error due to the severer vibration caused by climbing up the steep road.
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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