856 resultados para geometry features


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We apply the master equation technique to calculate shot noise in a system composed of single level quantum dot attached to a normal metal lead and to a ferromagnetic lead (NM-QD-FM). It is known that this system operates as a spin-diode, giving unpolarized currents for forward bias and polarized current for reverse bias. This effect is observed when only one electron can tunnel at a time through the dot, due to the strong intradot Coulomb interaction. We find that the shot noise also presents a signature of this spin-diode effect, with a super-Poissonian shot noise for forward and a sub-Poissonian shot noise for reverse bias voltages. The shot noise thus can provide further experimental evidence of the spin-rectification in the NM-QD-FM geometry.

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Garciniaphenone (=rel-(1R,5R,7R)-3-benzoyl-4-hydroxy-8,8-dimethyl-1,7-bis(3-methylbut-2-en-1-yl)bicyclo[3.3.1]non-3-ene-2,9-dione; 1). a novel natural product, was isolated from a hexane extract of Garcinia brasiliensis fruits. The crystal structure of 1 as well as the selected geometrical and Configurational features were compared with those of known related polyprenylated benzophenones. Garciniaphenone is the first representative of polyprenylated benzophenones without a prenyl substituent at C(5). Notably, the absence of a 5-prenyl substituent has an impact on the molecular geometry. The tautomeric form of 1 in the solid state was readily established by a residual-electronic-density map generated by means of a difference Fourier analysis, and there is an entirely delocalized six-membered chelate ring encompassing the keto-enol moiety. The configuration at C(7) was used to rationalize the nature of the keto-enol tautomeric form within 1. The intermolecular array in the network is maintained by nonclassical intermolecular H-bonds.

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The crystal structure and the vibrational spectrum of a potential drug for Chagas`s disease treatment, the (E)-isomer of phenylethenylbenzofuroxan 1 (5(6)(E)-[(2-phenylethenyl)]benzo[1,2-c]1,2,5-oxadiazole N-oxide), are reported. In order to provide insights into structural relationships, quantum mechanical calculations were employed starting from crystal structure. These results have given theoretical support to state interesting structural features, such as the effect of some intermolecular contacts on the molecule conformation and the electronic delocalization decreasing through atoms of the benzofuroxan moiety. Furthermore, the MOGUL comparative analysis in the Cambridge Structural Database provided additional evidences on these structural behaviors of compound 1. Intermolecular contacts interfere on the intramolecular geometry, as, for instance, on the phenyl group orientation, which is twisted by 12.32(6)A degrees from the ethenylbenzofuroxan plane. The experimental Raman spectrum of compound 1 presents unexpected frequency shift and also anomalous Raman activities. At last, the molecule skeleton deformation and the characteristic vibrational modes were correlated by matching the experimental Raman spectrum to the calculated one.

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The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

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We study the growth of Df `` (f(c)) when f is a Fibonacci critical covering map of the circle with negative Schwarzian derivative, degree d >= 2 and critical point c of order l > 1. As an application we prove that f exhibits exponential decay of geometry if and only if l <= 2, and in this case it has an absolutely continuous invariant probability measure, although not satisfying the so-called Collet-Eckmann condition. (C) 2009 Elsevier Masson SAS. All rights reserved.

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We study the geometry and the periodic geodesics of a compact Lorentzian manifold that has a Killing vector field which is timelike somewhere. Using a compactness argument for subgroups of the isometry group, we prove the existence of one timelike non self-intersecting periodic geodesic. If the Killing vector field is nowhere vanishing, then there are at least two distinct periodic geodesics; as a special case, compact stationary manifolds have at least two periodic timelike geodesics. We also discuss some properties of the topology of such manifolds. In particular, we show that a compact manifold M admits a Lorentzian metric with a nowhere vanishing Killing vector field which is timelike somewhere if and only if M admits a smooth circle action without fixed points.

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We prove an estimate on the difference of Maslov indices relative to the choice of two distinct reference Lagrangians of a continuous path in the Lagrangian Grassmannian of a symplectic space. We discuss some applications to the study of conjugate and focal points along a geodesic in a semi-Riemannian manifold.

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A novel Schiff base-copper(II) complex [Cu(2)L(2)(N(3))(2)](ClO(4))(2) 1, where L = (4-imidazolyl)ethylene-2-amino-1-ethylpyridine (apyhist), containing azide-bridges between adjacent copper ions in a dinuclear arrangement was isolated and characterized both in the solid state and in solution by X-ray crystallography and different spectroscopic techniques. Azide binding constants were estimated from titrations of the precursor [CuL(H(2)O)(2)](2+) solutions with sodium azide, giving rise to the azido-bridged species, [Cu(2)L(2)(N(3))(2)](2+). Raman spectra showed asymmetric stretching band at 2060 cm(-1), indicating the presence of azido ligands with a symmetric mu(1,) (1) binding geometry. EPA spectra, in frozen methanol/water solutions at 77 K, exhibited characteristic features of copper centers in tetragonal pyramidal coordination geometry, exhibiting magnetic interactions between them. Further, in solid state, two different values for magnetic coupling in this species were obtained, J/k = -(5.14 +/- 0.02) cm(-1) attributed to the mu(1, 1) azide-bridge mode, and J`z`/k = -(2.94 +/- 0.11) cm(-1) for the interaction between dinuclear moieties via water/perchorate bridges. Finally, an attempt was made to correlate structure and magnetic data for this dinuclear asymmetric end-on azido bridged-copper(II) 1 complex with those of another correlated dinuclear system, complex [Cu(2)L(2)Cl(2)](ClO(4))(2) 2, containing the same tridentate diimine ligand, but with chloro-bridged groups between the copper centres.

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This paper studies the selectivity of Well-defined Au and Ag nanostructures as substrates for the SERS, (surface-enhanced Raman scattering) detection of simazine (6-chloro-N,N`-diethyl-1,3,5-triazine-2,4-diamine) and atrazine (6-chloro-N-ethyl-N`-isopropyl-1,3,5-triazine-2,4-diamine). Our data showed that simazine and atrazine displayed similar SERS spectra when the Au was employed as substrate. Conversely, distinct SERS signatures were obtained upon the utilization of Ag substrates. Density functional theory (DFT) calculations and vibrational assignments suggested that, while simazine and atrazine adsorbed on Au via the N3 position of the triazine ring, simazine adsorbed on Ag via N3 and atrazine via N5. The results presented herein demonstrated that the adsorption geometry of analyte molecules can play a central role over substrate selectivity in SERS, which is particularly important in applications involving ultrasensitive analysis of mixtures containing structurally similar molecules.

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The conformational features of three 2-sulphur-substituted cyclohexanone derivatives, which differ in the number of sulphur-bound oxygen atoms, i.e. zero (I), one (II) and two (III), were investigated by single crystal X-ray crystallography and geometry optimized structures determined using Hartree-Fock method. In each of (I)-(III) an intramolecular S center dot center dot center dot O(carbonyl) interaction is found with the magnitude correlated with the oxidation state of the sulphur atom, i.e. 2.838(3) angstrom in (I) to 2.924(2) angstrom in (II) to 3.0973(18) angstrom in (III). There is an inverse relationship between the strength of this interaction and the magnitude of the carbonyl bond. The supramolecular aggregation patterns are primarily determined by C-H center dot center dot center dot O contacts and are similarly influenced by the number of oxygen atoms in the molecular structures. Thus, a supramolecular chain is found in the crystal structure of (I). With an additional oxygen atom available to participate in C-H center dot center dot center dot O interactions, as in (II), a two-dimensional array is found. Finally, a three-dimensional network is found for (III). Despite there being differences in conformations between the experimental structures and those calculated in the gas-phase, the S center dot center dot center dot O interactions persist. The presence of intermolecular C-H center dot center dot center dot O interactions involving the cyclohexanone-carbonyl group in the solid-state, disrupts the stabilising intramolecular C-H center dot center dot center dot O interaction in the energetically-favoured conformation. (I): C(12)H(13)NO(3)S, triclinic space group P (1) over bar with a = 5.392(3) angstrom b = 10.731(6) angstrom, c = 11.075(6) angstrom, alpha = 113.424(4)degrees, beta = 94.167(9)degrees, gamma = 98.444(6)degrees, V = 575.5(6) angstrom(3), Z = 2, R(1) = 0.052; (II): C(12)H(13)NO(4)S, monoclinic P2(1)/n, a = 7.3506(15) angstrom, b = 6.7814(14) angstrom, c = 23.479(5) angstrom, beta = 92.94(3)degrees, V = 1168.8(4) angstrom(3), Z = 4, R(1) = 0.046; (III): C(12)H(13)NO(5)S, monoclinic P2(1)/c, a = 5.5491(11) angstrom, b = 24.146(3) angstrom, c = 11.124(3) angstrom, beta = 114.590(10)degrees, V = 1355.3(5) angstrom(3), Z = 4, R(1) = 0.051.

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Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

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This paper studies a special class of vector smooth-transition autoregressive (VSTAR) models that contains common nonlinear features (CNFs), for which we proposed a triangular representation and developed a procedure of testing CNFs in a VSTAR model. We first test a unit root against a stable STAR process for each individual time series and then examine whether CNFs exist in the system by Lagrange Multiplier (LM) test if unit root is rejected in the first step. The LM test has standard Chi-squared asymptotic distribution. The critical values of our unit root tests and small-sample properties of the F form of our LM test are studied by Monte Carlo simulations. We illustrate how to test and model CNFs using the monthly growth of consumption and income data of United States (1985:1 to 2011:11).

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This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

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This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

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The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.