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Table 1 lists the two kernel functions which are subsequently used to estimate diffusion coefficients from cyclic voltammograms.
In a first step (Section "Estimation from simulated data") the approach based on the Nicholson-Shain equation and the regression algorithms SVR and GPR were used to estimate diffusion coefficients for simulated cyclic voltammograms with known diffusion coefficients.
To corroborate these indicators, the complete heat conduction moisture diffusion problem was numerically solved, and the predictions showed, precisely, that analytical solutions may be used to estimate diffusion coefficients in wheat.
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In order to estimate the dissolution rate of the nanoparticles in blood upon IV administration, the Stokes-Einstein equation [33, 34] was used to estimate the diffusion coefficient (for free diffusion assuming a spherical molecule): D = kT 6 πrη.
For one-photon excitation, the characteristic diffusion time can be used to estimate the diffusion coefficient by.
In order to eliminate the uncertainties associated with a non-uniform distribution of the applied current over the membrane surface, the relaxation zone of the obtained chronopotentiograms was used to estimate the diffusion boundary layer thickness.
Voxels retained in the white matter skeleton were used to estimate the diffusion response function.
The RESTORE approach [ 53] was used to estimate the diffusion tensor.
A two-layer configuration system was used to estimate the diffusion coefficient by Mach Zehnder interferometry.
The same protocol was used to estimate the diffusion coefficient of Alexa 488.
Presently, however, existing formulae and information from the literature are used to estimate the diffusion coefficients in the model.
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