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As the comparisons are shown, our methods can make an apparent improvement on the performances of function prediction than other methods, such as neighbor counting [ 10], Chi-square [ 11], Zhang-DC [ 24], Markov random field (MRF) model [ 7] and relaxation labelling classifier (RLC) [ 16].
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In our method, the use of multiple images and the relaxation labeling technique reduce the erroneous match (H17a).
Traditional relational classification algorithms, such as WvRN [4] and SCRN [5] classifier, make statistical estimations of the labels through statistics, class label propagation or relaxation labeling.
The methods involved graph matching [30, 31], self-organizing maps [32], expectation maximization [33, 34], Hough transform [28], and relaxation labeling [6].
The method also supports a sophisticated error correction with the relaxation labeling technique, which is similar to that used by Kouyama et al. (2012) but is significantly improved (H17a).
These polymers exhibit prominent α peaks, associated to the dynamic glass transitions, and then poorly defined β-relaxations and two other relaxation zones labelled as γ- and δ-relaxation in order of decreasing temperatures.
Genes for which no primers could be found, even after parameter relaxation, are labeled with the statement 'no primers'.
However, incorporating Tm3+ into a host crystal with reduced multi-phonon relaxation rates enables emission from the 3H5 state that is fed by the cross-relaxation process labelled C2.
Two relaxations processes labeled α and β in order of decreasing temperature were observed.
The 'two for one' cross-relaxation process labelled C1 that feeds the 3F4 state is well known for Tm3+ and has been used in YAG [7] and YLF [8] host crystals to sensitize 2-μm sources for diode pumping.
As a result, the N longitudinal relaxation of both labeled httNT α-helix residues slowed to R1 values of 0.02 ± 0.03 s–1 (for M8) and 0.03 ± 0.04 s–1 (A10), which match those of residues in a structured polyQ core.
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