Theoretical prediction of structural,electronic and optical properties of quaternary alloy Zn_(1-x)Be_xS_ySe_(1-y)

Within density functional theory based on the full potentiM-linearized augmented plane wave method, we carry out the first-principles calculation of the structural, electronic, and optical properties of the zinc blende quaternary alloy Zn1-xBexSySe1-y. The Perdew-Burke-Ernzerhof generaized gradient approximation based on the optimization of total energy and the Engel-Vosko generalized gradient approximation based on the optimization of the corresponding potential are used. Our investigation on the effect of the composition on lattice constants, bulk modulus, band gap, optical dielectric constant, and refractive index shows a non-linear dependence. The energy gap Eg（x, y） has been determined over the entire compositions x and y. In addition, the energy band gap of the technologically important quaternary alloy Znl-xBexSySe1-y in conditions of being lattice matched to ZnS substrate has been investigated. It is noteworthy that the present work is the first theoretical study of the quaternary alloy of interest.

PCA for predicting quaternary structure of protein

The number and arrangement of subunits that form a protein are referred to as quaternary structure.Knowing the quaternary structure of an uncharacterized protein provides clues to finding its biological function and interaction process with other molecules in a biological system.With the explosion of protein sequences generated in the Post-Genomic Age,it is vital to develop an automated method to deal with such a challenge.To explore this prob-lem,we adopted an approach based on the pseudo position-specific score matrix(Pse-PSSM)descriptor,proposed by Chou and Shen,representing a protein sample.The Pse-PSSM descriptor is advantageous in that it can combine the evolution information and sequence-correlated informa-tion.However,incorporating all these effects into a descriptor may cause‘high dimension disaster’.To over-come such a problem,the fusion approach was adopted by Chou and Shen.A completely different approach,linear dimensionality reduction algorithm principal component analysis(PCA)is introduced to extract key features from the high-dimensional Pse-PSSM space.The obtained dimension-reduced descriptor vector is a compact repre-sentation of the original high dimensional vector.The jack-knife test results indicate that the dimensionality reduction approach is efficient in coping with complicated problems in biological systems,such as predicting the quaternary struc-ture of proteins.