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Three solid lipid and liquid lipid matrices were chosen to prepare NLCs (as shown in Table 1).
The pairwise distance matrices were chosen as the output since they are the required input for the hierarchical agglomerative clustering process used during optimized clustering.
Oligonucleotides scoring more than 0.80 with at least one of the two matrices were chosen for further investigation.
Population covariance matrices were chosen to provide specific population sphericity values, ∊∈{0.282,0.505,0.720,1.00}.
Eight amino acid substitution matrices were chosen, but only 4 had a frequency exceeding 10 genes.
In the present study, the polymeric matrices were chosen as an optimal form to study copolymer chain microstructure.
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The advantage is that as many as possible of the Lyapunov matrices are chosen to be mode-dependent.
Two different orientation matrices are chosen to demonstrate that the representation of singularity loci is formulation dependent.
A detailed description how these matrices are chosen is given subsequently.
Each of the 2 B unitary matrices are chosen independently and are uniformly distributed over a Grassmannian.
If the coupling matrices are chosen as follows and b k = 0 (without impulsive controller), then the network (13) is not synchronized (see Figure 6).
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matrices were selected
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matrices were calculated
matrices were filtered
matrices were visualized
matrices were compared
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matrices were arranged
matrices were assigned
matrices were employed
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