132 resultados para Antennas, Antenna Arrays, Mutual Coupling, Decoupling Networks, Adaptive Arrays


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Hepatitis C virus (HCV) infects 170 million people worldwide, and is a major public health problem in Brazil, where over 1% of the population may be infected and where multiple viral genotypes co-circulate. Chronically infected individuals are both the source of transmission to others and are at risk for HCV-related diseases, such as liver cancer and cirrhosis. Before the adoption of anti-HCV control measures in blood banks, this virus was mainly transmitted via blood transfusion. Today, needle sharing among injecting drug users is the most common form of HCV transmission. Of particular importance is that HCV prevalence is growing in non-risk groups. Since there is no vaccine against HCV, it is important to determine the factors that control viral transmission in order to develop more efficient control measures. However, despite the health costs associated with HCV, the factors that determine the spread of virus at the epidemiological scale are often poorly understood. Here, we sequenced partial NS5b gene sequences sampled from blood samples collected from 591 patients in Sao Paulo state, Brazil. We show that different viral genotypes entered Sao Paulo at different times, grew at different rates, and are associated with different age groups and risk behaviors. In particular, subtype 1b is older and grew more slowly than subtypes 1a and 3a, and is associated with multiple age classes. In contrast, subtypes 1a and 3b are associated with younger people infected more recently, possibly with higher rates of sexual transmission. The transmission dynamics of HCV in Sao Paulo therefore vary by subtype and are determined by a combination of age, risk exposure and underlying social network. We conclude that social factors may play a key role in determining the rate and pattern of HCV spread, and should influence future intervention policies.

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A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel approach which extends from single nodes to the whole network level by considering non-overlapping subgraphs (i.e. connected components) and their interrelationships and distribution through the network. Though such subgraphs can be completely general, our methodology focuses on the cases in which the nodes of these subgraphs share some special feature, such as being critical for the proper operation of the network. The methodology of subgraph characterization involves two main aspects: (i) the generation of histograms of subgraph sizes and distances between subgraphs and (ii) a merging algorithm, developed to assess the relevance of nodes outside subgraphs by progressively merging subgraphs until the whole network is covered. The latter procedure complements the histograms by taking into account the nodes lying between subgraphs, as well as the relevance of these nodes to the overall subgraph interconnectivity. Experiments were carried out using four types of network models and five instances of real-world networks, in order to illustrate how subgraph characterization can help complementing complex network-based studies.

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A great part of the interest in complex networks has been motivated by the presence of structured, frequently nonuniform, connectivity. Because diverse connectivity patterns tend to result in distinct network dynamics, and also because they provide the means to identify and classify several types of complex network, it becomes important to obtain meaningful measurements of the local network topology. In addition to traditional features such as the node degree, clustering coefficient, and shortest path, motifs have been introduced in the literature in order to provide complementary descriptions of the network connectivity. The current work proposes a different type of motif, namely, chains of nodes, that is, sequences of connected nodes with degree 2. These chains have been subdivided into cords, tails, rings, and handles, depending on the type of their extremities (e.g., open or connected). A theoretical analysis of the density of such motifs in random and scale-free networks is described, and an algorithm for identifying these motifs in general networks is presented. The potential of considering chains for network characterization has been illustrated with respect to five categories of real-world networks including 16 cases. Several interesting findings were obtained, including the fact that several chains were observed in real-world networks, especially the world wide web, books, and the power grid. The possibility of chains resulting from incompletely sampled networks is also investigated.

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We evaluate the mass of the B(s0) scalar meson and the coupling constant in the B(s0)BK vertex in the framework of QCD sum rules. We consider the B(s0) as a tetraquark state to evaluate its mass. We get m(Bs0) = (5.85 +/- 0.13) GeV, which is in agreement, considering the uncertainties, with predictions supposing it as a b (s) over bar state or a B (K) over bar bound state with J(P) = 0(+). To evaluate the g(Bs0BK) coupling, we use the three-point correlation functions of the vertex, considering B(s0) as a normal b (s) over bar state. The obtained coupling constant is: g(Bs0BK) = (16.3 +/- 3.2) GeV. This number is in agreement with light-cone QCD sum rules calculation. We have also compared the decay width of the B(s0) -> BK process considering the B(s0) to be a b (s) over bar state and a BK molecular state. The width obtained for the BK molecular state is twice as big as the width obtained for the b (s) over bar state. Therefore, we conclude that with the knowledge of the mass and the decay width of the B(s0) meson, one can discriminate between the different theoretical proposals for its structure.

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We present Monte Carlo simulations for a molecular motor system found in virtually all eukaryotic cells, the acto-myosin motor system, composed of a group of organic macromolecules. Cell motors were mapped to an Ising-like model, where the interaction field is transmitted through a tropomyosin polymer chain. The presence of Ca(2+) induces tropomyosin to block or unblock binding sites of the myosin motor leading to its activation or deactivation. We used the Metropolis algorithm to find the transient and the equilibrium states of the acto-myosin system composed of solvent, actin, tropomyosin, troponin, Ca(2+), and myosin-S1 at a given temperature, including the spatial configuration of tropomyosin on the actin filament surface. Our model describes the short- and long-range cooperativity during actin-myosin binding which emerges from the bending stiffness of the tropomyosin complex. We found all transition rates between the states only using the interaction energy of the constituents. The agreement between our model and experimental data also supports the recent theory of flexible tropomyosin.

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We investigate the influence of couplings among continuum states in collisions of weakly bound nuclei. For this purpose, we compare cross sections for complete fusion, breakup, and elastic scattering evaluated by continuum discretized coupled channel (CDCC) calculations, including and not including these couplings. In our study, we discuss this influence in terms of the polarization potentials that reproduces the elastic wave function of the coupled channel method in single channel calculations. We find that the inclusion of couplings among continuum states renders the real part of the polarization potential more repulsive, whereas it leads to weaker absorption to the breakup channel. We show that the noninclusion of continuum-continuum couplings in CDCC calculations may lead to qualitative and quantitative wrong conclusions.

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The study of spectral behavior of networks has gained enthusiasm over the last few years. In particular, random matrix theory (RMT) concepts have proven to be useful. In discussing transition from regular behavior to fully chaotic behavior it has been found that an extrapolation formula of the Brody type can be used. In the present paper we analyze the regular to chaotic behavior of small world (SW) networks using an extension of the Gaussian orthogonal ensemble. This RMT ensemble, coined the deformed Gaussian orthogonal ensemble (DGOE), supplies a natural foundation of the Brody formula. SW networks follow GOE statistics until a certain range of eigenvalue correlations depending upon the strength of random connections. We show that for these regimes of SW networks where spectral correlations do not follow GOE beyond a certain range, DGOE statistics models the correlations very well. The analysis performed in this paper proves the utility of the DGOE in network physics, as much as it has been useful in other physical systems.

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Magnetoresistance measurements were performed on an n-type PbTe/PbEuTe quantum well and weak antilocalization effects were observed. This indicates the presence of spin orbit coupling phenomena and we showed that the Rashba effect is the main mechanism responsible for this spin orbit coupling. Using the model developed by Iordanskii et al., we fitted the experimental curves and obtained the inelastic and spin orbit scattering times. Thus we could compare the zero field energy spin-splitting predicted by the Rashba theory with the energy spin-splitting obtained from the analysis of the experimental curves. The final result confirms the theoretical prediction of strong Rashba effect on IV-VI based quantum wells.

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Using first-principles calculations it is demonstrated that Co doped graphenelike ZnO sheet presents ferromagnetic coupling. The Co atoms are energetically barrierless absorbed in the Zn sites, suffering a Jahn-Teller distortion. The results reveal that the origin of the ferromagnetic coupling, different from the bulk 3D ZnO stacking, is mainly guided by a direct exchange interaction without any additional defect. This ferromagnetic coupling is due to the system topology, namely, it is a direct consequence of the two-dimensional character of the ZnO monolayer within graphenelike structure. Increasing the number of ZnO layers the ferromagnetic coupling vanishes.

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We present a measurement of pi(+)pi(-)pi(+)pi(-) photonuclear production in ultraperipheral Au-Au collisions at root s(NN) = 200 GeV from the STAR experiment. The pi(+)pi(-)pi(+)pi(-) final states are observed at low transverse momentum and are accompanied by mutual nuclear excitation of the beam particles. The strong enhancement of the production cross section at low transverse momentum is consistent with coherent photoproduction. The pi(+)pi(-)pi(+)pi(-) invariant mass spectrum of the coherent events exhibits a broad peak around 1540 +/- 40 MeV/c(2) with a width of 570 +/- 60 MeV/c(2), in agreement with the photoproduction data for the rho(0)(1700). We do not observe a corresponding peak in the pi(+)pi(-) final state and measure an upper limit for the ratio of the branching fractions of the rho(0)(1700) to pi(+)pi(-) and pi(+)pi(-)pi(+)pi(-) of 2.5% at 90% confidence level. The ratio of rho(0)(1700) and rho(0)(770) coherent production cross sections is measured to be 13.4 +/- 0.8(stat.) +/- 4.4(syst.)%.

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Excitation functions of quasi-elastic scattering at backward angles have been measured for the (6,7)Li + (144)Sm systems at near-barrier energies, and fusion barrier distributions have been extracted from the first derivatives of the experimental cross sections with respect to the bombarding energies. The data have been analyzed in the framework of continuum discretized coupled-channel calculations, and the results have been obtained in terms of the influence exerted by the inclusion of different reaction channels, with emphasis on the role played by the projectile breakup.

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Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).

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A method to determine the effects of the geometry and lateral ordering on the electronic properties of an array of one-dimensional self-assembled quantum dots is discussed. A model that takes into account the valence-band anisotropic effective masses and strain effects must be used to describe the behavior of the photoluminescence emission, proposed as a clean tool for the characterization of dot anisotropy and/or inter-dot coupling. Under special growth conditions, such as substrate temperature and Arsenic background, 1D chains of In(0.4)Ga(0.6) As quantum dots were grown by molecular beam epitaxy. Grazing-incidence X-ray diffraction measurements directly evidence the strong strain anisotropy due to the formation of quantum dot chains, probed by polarization-resolved low-temperature photoluminescence. The results are in fair good agreement with the proposed model.

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We construct and analyze a microscopic model for insulating rocksalt ordered double perovskites, with the chemical formula A(2)BB'O(6), where the B' atom has a 4d(1) or 5d(1) electronic configuration and forms a face-centered-cubic lattice. The combination of the triply degenerate t(2g) orbital and strong spin-orbit coupling forms local quadruplets with an effective spin moment j=3/2. Moreover, due to strongly orbital-dependent exchange, the effective spins have substantial biquadratic and bicubic interactions (fourth and sixth order in the spins, respectively). This leads, at the mean-field level, to three main phases: an unusual antiferromagnet with dominant octupolar order, a ferromagnetic phase with magnetization along the [110] direction, and a nonmagnetic but quadrupolar ordered phase, which is stabilized by thermal fluctuations and intermediate temperatures. All these phases have a two-sublattice structure described by the ordering wave vector Q=2 pi(001). We consider quantum fluctuations and argue that in the regime of dominant antiferromagnetic exchange, a nonmagnetic valence-bond solid or quantum-spin-liquid state may be favored instead. Candidate quantum-spin-liquid states and their basic properties are described. We also address the effect of single-site anisotropy driven by lattice distortions. Existing and possible future experiments are discussed in light of these results.

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We discuss an approximation for the dynamic charge response of nonlinear spin-1/2 Luttinger liquids in the limit of small momentum. Besides accounting for the broadening of the charge peak due to two-holon excitations, the nonlinearity of the dispersion gives rise to a two-spinon peak, which at zero temperature has an asymmetric line shape. At finite temperature the spin peak is broadened by diffusion. As an application, we discuss the density and temperature dependence of the Coulomb drag resistivity due to long-wavelength scattering between quantum wires.