For this purpose, using samples of plasma of 80 μl in multiwell dark plates, AGE were measured by duplicate in a multi-mode reader (Synergy 2, Biotek) with a coefficient of variation of less than 8%.
Mathematically, muscle synergies can be expressed by the following equation, which describes the activation of a muscle m i (t): (1) m i (t ) = ∑ j K h j (t ) w j i, where m i (t) is the time function of muscle activation (EMG signal) for muscle i, w ji is the coefficient of jth synergy to the ith muscle, h j (t) is the temporal function of the neuronal command j, and K is the number of synergies.
Finally, Nusselt number and mass transfer coefficient models revised by synergy angles are developed to include the multi-ion effects for engineering application.
In general, a relatively high correlation (SRCC=0.6251) between the meet/min coefficient and the NIMS synergy score was observed for all agent pairs.
When used in combination, these drugs exhibited very potent synergy in all cell lines, with coefficients of drug interaction (CDIs) clearly < 0.7; remarkably, in some cases, CDI values were < 0.1.
In order to calculate the desired muscle activations, the controller uses synergies (W) and activation coefficients (H) obtained during ML and AT experiments previously described.
Protein concentrations of αHisPC solutions were determined spectrophotometrically with a Synergy Mx spectrophotometer (Biotek, Switzerland) and using an extinction coefficient of 140000 M−1 cm−1 at 620 nm.
These results are attributed to the synergy improvement of the conductivity, the lithium ion diffusion coefficient, and the degree of freedom for volume change of LFP/CZIF-8 cathode.
It can be shown algebraically that this synergy corresponds to an interaction term with a regression coefficient larger than zero in a regression model whereas the antagonism corresponds to an interaction term with a coefficient less than zero.
Considering a synergy with the domain of speech analysis, the authors introduced Mel-frequency cepstral coefficient (MFCC) to extract representative features and develop hidden Markov model (HMM) for signal classification.
