Furthermore, by adding another atom to the previously selected atoms, we calculate their SSIM-based linear combination approximating each y i, and then, the optimal atom maximizing the SSIM index with the previously selected atoms is selected.
To compare the concentration of doping atoms (Li and K atoms), we also calculated the GCMC simulations with consideration to these seven sites, when the full doping position of the sites were occupied by Li or K atoms.
For each atom in an amino acid, we calculated the Euclidean distance between it and all atoms in the other amino acids in the crystal structure.
We calculated the average atom adsorption energies and open-circuit voltage profiles as a function of adatoms coverage.
We calculated the hydrogen-atom abstraction with QM/MM using snapshot Sn300, Sn400 and Sn500, whereas the rebound was only investigated for Sn500.
To exclude this possibility, we calculated the fraction of atoms that form the binding-site interface for each protein.
To each dictionary atom D i, we calculate its projection matrix P i using the same method as A+, which has took the image sparse prior into account.
To study the NMR parameters of adsorption of CO molecule on the surface of pristine and As, B atoms doped of AlNNTs, we calculate the CSI and CSA parameters of 13Alnuclei and 15N nuclei by Eqs.
Knowing the coordinates of random defects, namely Fe atoms and V(O) vacancies, we calculate the distance d between them.
As mentioned before, we restrict our attention to the case of modal dictionaries whose atoms are calculated by evaluating a function over a multidimensional grid, the grid dimension being equal to the number of unknown modal parameters.
