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As a consequence, analysis dependent on such matrices are especially vulnerable to the original error due to the sampling size.
Proteins are known to satisfactorily retain their stability on such matrices.
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The existing methods dependent on such matrixes cannot effectively characterize some important aspects associated with land change such as status, direction, trend and regional variations.
However, so far, no study has been reported on the influence of such matrices, namely the presence or absence of extracellular matrix motifs, on BM-MSCs secretome and its effects in neuronal cell populations.
The matrices H and S are respectively named the matrices of hard and soft limits, and they have the same dimensions of the matrix of bandwidths F. The entries on the main diagonals of such matrices are respectively the hard and soft limits for each node.
An accurate prediction algorithm would ensure that the highest similarity values lay on the diagonal of such matrix, i.e. the experimental spectrum of any given molecule would be more similar to its simulation than to simulated spectra of other molecules.
Because there is no consensus on the best threshold for such matrices, a set of thresholds was applied, producing a series of binarized matrices.
We reliably determined such matrices with, dependent on site and component, coefficients of determination between 0.59 and 0.90.
The action descriptors proposed are based on such covariance matrices computed at different scales.
The formation mechanisms of silica, phosphate, and calcium carbonate particles on such protein matrices are likely fundamentally similar.
Based on such a matrix, a clustering algorithm is developed to decompose and allocate the product components regarding IP protection issue.
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