829 research outputs found

    Massive Dirac surface states in topological insulator/magnetic insulator heterostructures

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    Topological insulators are new states of matter with a bulk gap and robust gapless surface states protected by time-reversal symmetry. When time-reversal symmetry is broken, the surface states are gapped, which induces a topological response of the system to electromagnetic field--the topological magnetoelectric effect. In this paper we study the behavior of topological surface states in heterostructures formed by a topological insulator and a magnetic insulator. Several magnetic insulators with compatible magnetic structure and relatively good lattice matching with topological insulators Bi2Se3,Bi2Se3,Sb2Te3{\rm Bi_2Se_3}, {\rm Bi_2Se_3}, {\rm Sb_2Te_3} are identified, and the best candidate material is found to be MnSe, an anti-ferromagnetic insulator. We perform first-principles calculation in Bi2Se3/MnSe{\rm Bi_2Se_3/MnSe} superlattices and obtain the surface state bandstructure. The magnetic exchange coupling with MnSe induces a gap of ∼\sim54 meV at the surface states. In addition we tune the distance between Mn ions and TI surface to study the distance dependence of the exchange coupling.Comment: 8 pages, 7 figure

    Classification in Networked Data with Heterophily

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    In the real world, a large amount of data can be described by networks using relations between data. The data described by networks can be called networked data. Classification is one of the main tasks in analyzing networked data. Most of the previous methods find the class of the unlabeled node using the classes of its neighbor nodes. However, in the networks with heterophily, most of connected nodes belong to different classes. It is hard to get the correct class using the classes of neighbor nodes, so the previous methods have a low level of performance in the networks with heterophily. In this paper, a probabilistic method is proposed to address this problem. Firstly, the class propagating distribution of the node is proposed to describe the probabilities that its neighbor nodes belong to each class. After that, the class propagating distributions of neighbor nodes are used to calculate the class of the unlabeled node. At last, a classification algorithm based on class propagating distribution is presented in the form of matrix operations. In empirical study, we apply the proposed algorithm to the real-world datasets, compared with some other algorithms. The experimental results show that the proposed algorithm performs better when the networks are of heterophily

    Insertional Mutagenesis of AAV2 Capsid and the Production of Recombinant Virus

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    The structural genes of adeno-associated virus serotype 2 (AAV2) have been altered by linker insertional mutagenesis in order to define critical components of virion assembly and infectivity. An in-frame restriction site linker was inserted across the capsid coding domain of a recombinant plasmid. After complementation in vivo, recombinant AAV2 viruses were generated and assayed for capsid production, packaging, transduction, heparin agarose binding, and morphology. Three classes of capsid mutants where identified. Class I mutants expressed structural proteins but were defective in virion assembly. Class II mutants generated intact virions that protected the viral genome from DNase, but failed to infect target cells. The majority of these mutants bound the heparin affinity matrix, suggesting that attachment to the AAV primary receptor was not rate limiting. One class II mutant, H2634, assembled virions and bound heparin using only Vp3, indicating that this subunit is responsible for mediating AAV receptor attachment. Finally, class III mutants assembled virions, encapsidated DNA, and infected target cells. Infectivity of these mutants ranged from 5 to 100% of that of the wild-type, demonstrating for the first time the ability to alter capsid proteins without interfering with infectivity. These AAV virions with altered capsid subunits will provide critical templates for manipulating AAV vectors for cell-specific gene delivery in vivo. In summary, the AAV capsid variants described here will facilitate further study of virus assembly, entry, and infection, as well as advance the development of this versatile vector system

    Insertional Mutagenesis of AAV2 Capsid and the Production of Recombinant Virus

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    The structural genes of adeno-associated virus serotype 2 (AAV2) have been altered by linker insertional mutagenesis in order to define critical components of virion assembly and infectivity. An in-frame restriction site linker was inserted across the capsid coding domain of a recombinant plasmid. After complementation in vivo, recombinant AAV2 viruses were generated and assayed for capsid production, packaging, transduction, heparin agarose binding, and morphology. Three classes of capsid mutants where identified. Class I mutants expressed structural proteins but were defective in virion assembly. Class II mutants generated intact virions that protected the viral genome from DNase, but failed to infect target cells. The majority of these mutants bound the heparin affinity matrix, suggesting that attachment to the AAV primary receptor was not rate limiting. One class II mutant, H2634, assembled virions and bound heparin using only Vp3, indicating that this subunit is responsible for mediating AAV receptor attachment. Finally, class III mutants assembled virions, encapsidated DNA, and infected target cells. Infectivity of these mutants ranged from 5 to 100% of that of the wild-type, demonstrating for the first time the ability to alter capsid proteins without interfering with infectivity. These AAV virions with altered capsid subunits will provide critical templates for manipulating AAV vectors for cell-specific gene delivery in vivo. In summary, the AAV capsid variants described here will facilitate further study of virus assembly, entry, and infection, as well as advance the development of this versatile vector system

    Modified Beta Algorithm for GMPPT and Partial Shading Detection in Photovoltaic Systems

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