Arbitrary Choice of Basic Variables in Density Functional Theory. II. Illustrative Applications

Our recent theory (Ref. 1) enables us to choose arbitrary quantities as the basic variables of the density functional theory. In this paper we apply it to several cases. In the case where the occupation matrix of localized orbitals is chosen as a basic variable, we can obtain the single-particle equation which is equivalent to that of the LDA+U method. The theory also leads to the Hartree-Fock-Kohn-Sham equation by letting the exchange energy be a basic variable. Furthermore, if the quantity associated with the density of states near the Fermi level is chosen as a basic variable, the resulting single-particle equation includes the additional potential which could mainly modify the energy-band structures near the Fermi level.Comment: 27 page

Analysing superimposed oriented patterns

journal = {IEEE Transactions on Image Processing}, publisher = {IEEE}, volume = {15}, number = {12}, year = {2006}, pages = {3690--3700}} © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

Analysing superimposed oriented patterns

Abstract—Estimation of local orientation in images may be posed as the problem of finding the minimum gray-level variance axis in a local neighborhood. In bivariate images, the solution is given by the eigenvector corresponding to the smaller eigenvalue of a 2 2 tensor. For an ideal single orientation, the tensor is rank-deficient, i.e., the smaller eigenvalue vanishes. A large minimal eigenvalue signals the presence of more than one local orientation, what may be caused by non-opaque additive or opaque occluding objects, crossings, bifurcations, or corners. We describe a framework for estimating such superimposed orientations. Our analysis is based on the eigensystem analysis of suitably extended tensors for both additive and occluding superpositions. Unlike in the single-orientation case, the eigensystem analysis does not directly yield the orientations, rather, it provides so-called mixed-orientation parameters (MOPs). We, therefore, show how to decompose the MOPs into the individual orientations. We also show how to use tensor invariants to increase efficiency, and derive a new feature for describing local neighborhoods which is invariant to rigid transformations. Applications are, e.g., in texture analysis, directional filtering and interpolation, feature extraction for corners and crossings, tracking, and signal separation. I

Systematic analysis of viral and cellular microRNA targets in cells latently infected with human γ-herpesviruses by RISC immunoprecipitation assay

International audienceThe mRNA targets of microRNAs (miRNAs) can be identified by immunoprecipitation of Argonaute (Ago) protein-containing RNA-induced silencing complexes (RISCs) followed by microarray analysis (RIP-Chip). Here we used Ago2-based RIP-Chip to identify transcripts targeted by Kaposi's sarcoma-associated herpesvirus (KSHV) miRNAs (n = 114), Epstein-Barr virus (EBV) miRNAs (n = 44), and cellular miRNAs (n = 2337) in six latently infected or stably transduced human B cell lines. Of the six KSHV miRNA targets chosen for validation, four showed regulation via their 3'UTR, while two showed regulation via binding sites within coding sequences. Two genes governing cellular transport processes (TOMM22 and IPO7) were confirmed to be targeted by EBV miRNAs. A significant number of viral miRNA targets were upregulated in infected cells, suggesting that viral miRNAs preferentially target cellular genes induced upon infection. Transcript half-life both of cellular and viral miRNA targets negatively correlated with recruitment to RISC complexes, indicating that RIP-Chip offers a quantitative estimate of miRNA function