Spectral-Kinetic Properties and Energy Transfer in Nanoparticles of Y<inf>0.5–x</inf>Ce<inf>0.5</inf>Tb<inf> x</inf>F<inf>3</inf> Solid Solution

© 2020, Springer Science+Business Media, LLC, part of Springer Nature. Crystalline nanoparticles of Y0.5–xCe0.5TbxF3, doped with various concentrations (x = 0, 0.005, 0.01, 0.05, 0.1, 0.15, and 0.2) of Tb3+ ions were synthesized by co-precipitation. The crystal structure and chemical composition of nanoparticles were studied using transmission electron microscopy, scanning electron microscopy, and X-ray diffractometry. The obtained nanoparticles of solid solutions had an elliptical shape with a size of 10–15 nm along the long axis and good crystallinity with the structure of a CeF3 crystal. The spectral-kinetic properties of the obtained nanoparticles, and the effect of the concentration of Tb3+ activator ions on the energy transfer from Ce3+ to Tb3+ ions were investigated. Energy transfer from Ce3+ to Tb3+ ions in nanocrystals of the Y0.5–xCe0.5TbxF3 solid solutions occurs mainly through the dipole–dipole interaction. The results of evaluating the efficiency of energy transfer from Ce3+ to Tb3+ ions show its increase with increasing concentration of Tb3+ ions

On the upper bound of the prediction accuracy of residue contacts in proteins with correlated mutations: the case study of the similarity matrices

Correlated mutations in proteins are believed to occur in order to preserve the protein functional folding through evolution. Their values can be deduced from sequence and/or structural alignments and are indicative of residue contacts in the protein three-dimensional structure. A correlation among pairs of residues is routinely evaluated with the Pearson correlation coefficient and the MCLACHLAN similarity matrix. In this paper, we describe an optimization procedure that maximizes the correlation between the Pearson coefficient and the protein residue contacts with respect to different similarity matrices, including random. Our results indicate that there is a large number of equivalent matrices that perform similarly to MCLACHLAN. We also obtain that the upper limit to the accuracy achievable in the prediction of the protein residue contacts is independent of the optimized similarity matrix. This suggests that poor scoring may be due to the choice of the linear correlation function in evaluating correlated mutations

On the upper bound of the prediction accuracy of residue contacts in proteins with correlated mutations: the case study of the similarity matrices

Correlated mutations in proteins are believed to occur in order to preserve the protein functional folding through evolution. Their values can be deduced from sequence and/or structural alignments and are indicative of residue contacts in the protein three-dimensional structure. A correlation among pairs of residues is routinely evaluated with the Pearson correlation coefficient and the MCLACHLAN similarity matrix. In this paper, we describe an optimization procedure that maximizes the correlation between the Pearson coefficient and the protein residue contacts with respect to different similarity matrices, including random. Our results indicate that there is a large number of equivalent matrices that perform similarly to MCLACHLAN. We also obtain that the upper limit to the accuracy achievable in the prediction of the protein residue contacts is independent of the optimized similarity matrix. This suggests that poor scoring may be due to the choice of the linear correlation function in evaluating correlated mutations