982 resultados para topological insulator


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Here, we describe a metal-insulator-insulator nanofocusing structure formed by a high-permittivity dielectric wedge on a metal substrate. The structure is shown to produce nanofocusing of surface plasmon polaritons (SPPs) in the direction opposite to the taper of the wedge, including a range of nanoplasmonic effects such as nanofocusing of SPPs with negative refraction, formation of plasmonic caustics within a nanoscale distance from the wedge tip, mutual transformation of SPP modes, and significant local field enhancements in the adiabatic and strongly nonadiabatic regimes. A combination of approximate analytical and rigorous numerical approaches is used to analyze the strength and position of caustics in the structure. In particular, it is demonstrated that strong SPP localization within spatial regions as small as a few tens of nanometers near the caustic is achievable in the considered structures. Contrary to other nanofocusing configurations, efficient nanofocusing is shown to occur in the strongly nonadiabatic regime with taper angles of the dielectric wedge as large as ∼40° and within uniquely short distances (as small as a few dozens of nanometers) from the tip of the wedge. Physical interpretations of the obtained results are also presented and discussed.

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Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h(q)h(q) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h(2)h(2) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H≈0.5H≈0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h(2)h(2) of MF-DFA on the time series, exponent λλ of the exponential degree distribution and fractal dimension dBdB of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈h(2)〉〈h(2)〉 (from MF-DFA on time series) and 〈dB〉〈dB〉 of the converted HVGs for different energy, pressure and volume.

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In this paper, we introduce a path algebra well suited for navigation in environments that can be abstracted as topological graphs. From this path algebra, we derive algorithms to reduce routes in such environments. The routes are reduced in the sense that they are shorter (contain fewer edges), but still connect the endpoints of the initial routes. Contrary to planning methods descended from Disjktra’s Shortest Path Algorithm like D , the navigation methods derived from our path algebra do not require any graph representation. We prove that the reduced routes are optimal when the graphs are without cycles. In the case of graphs with cycles, we prove that whatever the length of the initial route, the length of the reduced route is bounded by a constant that only depends on the structure of the environment.

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We report the electrical conductivity between 2 and 300 K for LaNi1-xFexO3 across the composition-controlled metal-insulator (m-i) transition. Using a method first suggested by Mobius, we identify the critical concentration x(c) to be 0.3 for the m-i transition. The negative temperature coefficient of resistivity observed at low temperatures in the metallic phase follows a temperature dependence characteristic of disorder effects. The semiconducting compositions (x greater than or equal to 0.3) do not show a simple activation energy but exhibit variable-range hopping at high temperatures confirming that the m-i transition in this system is driven by increasing disorder effects.

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Giant magnetoresistance (GMR), which was until recently confined to magnetic layered and granular materials, as well as doped magnetic semiconductors, occurs in manganate perovskites of the general formula Ln(1-x)A(x)MnO(3) (Ln = rare earth; A = divalent ion). These manganates are ferromagnetic at or above a certain value of x (or Mn4+ content) and become metallic at temperatures below the curie temperature, T-c. GMR is generally a maximum close to T-c or the insulator-metal (I-M) transition temperature, T-im. The T-c and %MR are markedly affected by the size of the A site cation, [r(A)], thereby affording a useful electronic phase diagram when T-c or T-im is plotted against [r(A)]. We discuss GMR and related properties of manganates in polycrystalline, thin-film, and single-crystal forms and point out certain commonalities and correlations. We also examine some unusual features in the electron-transport properties of manganates, in particular charge-ordering effects. Charge ordering is crucially dependent on [r(A)] or the e(g) band width, and the charge-ordered insulating state transforms to a metallic ferromagnetic state on the application of a magnetic field.

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Transition-metal oxides at the metal-insulator boundary, especially those belonging to the perovskite family, exhibit fascinating phenomena such as insulator-metal transitions controlled by composition, high-temperature superconductivity and giant magnetoresistance (GMR), Interestingly, many of these marginally metallic oxides obey the established criteria for metallicity and have a finite density of states at the Fermi;level. The perovskite manganates exhibiting GMR, on the other hand, are unusual in that they possess very high resistivities in the 'metallic' state and show no significant density of states at the Fermi level, Marginal metallicity in oxide systems is a problem of great complexity and contemporary interest and its understanding is of crucial significance to the diverse phenomena exhibited by these materials.

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LaCrO3 is a wide-band-gap insulator which does not evolve to a metallic state even after hole doping. We report electronic structure of this compound and its Sr substituents investigated by photoemission and inverse photoemission spectroscopies in conjunction with various calculations. The results show that LaCrO 3 is close to the Mott-Hubbard insulating regime with a gap of about 2.8 eV. Analysis of Cr 2p core-level spectrum suggests that the intra-atomic Coulomb interaction strength and the charge-transfer energy to be 5.0 and 5.5 eV, respectively, We also estimate the intra-atomic exchange interaction strength and a crystal-field splitting of about 0.7 and 2.0 eV, respectively. Sr substitution leading to hole doping in this system decreases the charge-excitation gap, but never collapses it to give a metallic behavior. The changes in the occupied as well as unoccupied spectral features are discussed in terms of the formation of local Cr4+ configurations arising from strong electron-phonon interactions.

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This thesis studies document signatures, which are small representations of documents and other objects that can be stored compactly and compared for similarity. This research finds that document signatures can be effectively and efficiently used to both search and understand relationships between documents in large collections, scalable enough to search a billion documents in a fraction of a second. Deliverables arising from the research include an investigation of the representational capacity of document signatures, the publication of an open-source signature search platform and an approach for scaling signature retrieval to operate efficiently on collections containing hundreds of millions of documents.

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The Reeb graph tracks topology changes in level sets of a scalar function and finds applications in scientific visualization and geometric modeling. This paper describes a near-optimal two-step algorithm that constructs the Reeb graph of a Morse function defined over manifolds in any dimension. The algorithm first identifies the critical points of the input manifold, and then connects these critical points in the second step to obtain the Reeb graph. A simplification mechanism based on topological persistence aids in the removal of noise and unimportant features. A radial layout scheme results in a feature-directed drawing of the Reeb graph. Experimental results demonstrate the efficiency of the Reeb graph construction in practice and its applications.

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Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

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We have investigated structural transitions in Poly(dG-dC) and Poly(dG-Me5dC) in order to understand the exact role of cations in stabilizing left-handed helical structures in specific sequences andthe biological role, if any, of these structures. From a novel temperature dependent transition it has been shown that a minor fluctuation in Na+ concentration at ambient temperature can bring about Β to Ζ transition. Forthe first time, wehave observed a novel double transition in poly(dG-Me5dC) as the Na+ concentration is gradually increased. This suggests that a minor fluctuation in Na+ concentration in conjunction with methylation may transform small stretches of CG sequences from one conformational state to another. These stretches could probably serve as sites for regulation. Supercoiled formV DNA reconstituted from pBR322 and pßG plasmids have been studied as model systems, in order to understand the nature and role of left-handed helical conformation in natural sequences. A large portion of DNA in form V, obtained by reannealing the two complementary singlestranded circles is forced to adopt left-handed double helical structure due to topological constraints (Lk = 0). Binding studies with Z-DNA specific antibody and spectroscopic studies confirm the presence of left-handed Z-structure in the pßG and pßR322 form V DNA. Cobalt hexamine chloride, which induces Z-form in Poly(dG-dC) stabilizes the Z-conformation in form V DNA even in the non-alternating purine-pyrimidine sequences. A reverse effect is observed with ethidium bromide. Interestingly, both topoisomerase I and II (from wheat germ) act effectively on form V DNA to give rise to a species having an electrophoretic mobility on agarose gel similar to that of open circular (form II) DNA. Whether this molecule is formed as a result of the left-handed helical segments of form V DNA undergoing a transition to the right-handed B-form during the topoisomerase action remains to be solved.

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In this paper we present the resistivity data for Pr and Zn codoped compound Y1-xPrxBa2[Cu1-yZny](3)O7-delta with 0 < y < 0.1 and x = 0.0, 0.1 and 0.2. The data is analysed in terms of the superconducting critical temperature T-c, residual resistivity rho(0) and the resistivity slope d rho/dT corresponding to the linear rho-T region. It is found that for x = 0.1 Pr has a minimal influence on the in-plane processes for Zn impurity alone affecting slightly T-c and rho(0). The slope dp/dT becomes larger for 0.03 < y < 0.06 leading to larger depining effect and hence slower fall of T, as a function of y. For x = 0.2 there is a drastic change, rho(0) becomes abnormally large, d rho/dT becomes negative implying absence of depinning and a totally pinned charge stripes. Superconductivity vanishes at y = 0.03. It is concluded that for x = 0.2 Pr converts the system from overdoped to underdoped region leading to the universal superconductor-insulator transition.

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Studies of valence bands and core levels of solids by photoelectron spectroscopy are described at length. Satellite phenomena in the core level spectra have been discussed in some detail and it has been pointed out that the intensity of satellites appearing next to metal and ligand core levels critically depends on the metal-ligand overlap. Use of photoelectron spectroscopy in investigating metal-insulator transitions and spin-state transitions in solids is examined. It is shown that relative intensities of metal Auger lines in transition metal oxides and other systems provide valuable information on the valence bands. Occurrence of interatomic Auger transitions in competition with intraatomic transitions is discussed. Applications of electron energy loss spectroscopy and other techniques of electron spectroscopy in the study of gas-solid interactions are briefly presented.

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The world is rich with information such as signage and maps to assist humans to navigate. We present a method to extract topological spatial information from a generic bitmap floor plan and build a topometric graph that can be used by a mobile robot for tasks such as path planning and guided exploration. The algorithm first detects and extracts text in an image of the floor plan. Using the locations of the extracted text, flood fill is used to find the rooms and hallways. Doors are found by matching SURF features and these form the connections between rooms, which are the edges of the topological graph. Our system is able to automatically detect doors and differentiate between hallways and rooms, which is important for effective navigation. We show that our method can extract a topometric graph from a floor plan and is robust against ambiguous cases most commonly seen in floor plans including elevators and stairwells.

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Topology-based methods have been successfully used for the analysis and visualization of piecewise-linear functions defined on triangle meshes. This paper describes a mechanism for extending these methods to piecewise-quadratic functions defined on triangulations of surfaces. Each triangular patch is tessellated into monotone regions, so that existing algorithms for computing topological representations of piecewise-linear functions may be applied directly to the piecewise-quadratic function. In particular, the tessellation is used for computing the Reeb graph, a topological data structure that provides a succinct representation of level sets of the function.