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Next, the sample features are extracted by performing wavelet decomposition to obtain the low-frequency coefficients.
Sample features are listed in Table S2.
Details about Sample identifiers and main sample features are listed in Additional file 1 (available at: http://apollo11.isto.unibo.it/suppl).
Sample identifiers and main sample features are listed in Table 1 and Additional file 1 (available at: http://apollo11.isto.unibo.it/suppl).
The sample features are described in Table 1.> -wrap-foot> *For intentional weight loss, the numbers and % in the table refer to participants responding yes 82.7%% (43 our of 52) of patients presented a strong preoccupation with a healthy food intake based on the cut-off of 24 for the Polish version of the ORTO-15 test.
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The scoring of the sample features is done through normalization functions that are used to combine different measure values and to standardize their magnitudes within similar ranges.
To identify which of the parameters (ion energy or fluence) might have major impact on Ag+ dissolution and consequently the antimicrobial effect of the coating the third testing group with rearranged sample features was conducted.
All sample features were aligned according to retention times by automatic alignment to maximally overlay all the two-dimensional (m/ z and retention time) feature maps.
Usually, the number of sample features is much less than the number of samples, and kernel function k provides a convenient and cheap transformation.
The sample features were represented by the wheat line name and a letter (A, B, E or F) followed by a number referring to the anther length when samples were taken.
Then, the samples' features are extracted by performing wavelet decomposition to obtain the low-frequency coefficients.
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