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The proposed method first determines the number of delaminations using Bayesian model class selection method.
The proposed method first determines what MDFs should be included and what their weights should be.
This method first determines the knot vectors in a way that guarantees the existence of an interpolating B-spline.
For multiple different and desired paths to be traced by a point on the coupler, a two stage method first determines the parameters of the possible driving dyads.
Our method first determines TFAs, which were then further analyzed with cluster and periodicity analysis to determine transcription factor function.
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In contrast to preclustering methods that compute the palette only once, postclustering methods first determine an initial palette and then improve it iteratively.
In this method, each sensor first determines a local set which approximates the local posterior density.
In our proposed method, each user first determines its belonging area according to the RSRPs and then calculates feedback information correspondingly.
Using the LC-MS method we first determined the detection limit to be in the low picomolar range, even with the background of canonical nucleosides in digested samples (Figure 7B).
To validate this method, we first determined the minimum cell number required to achieve reproducible RNA amplification.
In this method, first RBFNN determines the fault distance from each fault source and second RBFNN identifies the exact faulty line.
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