139 resultados para SIZE-RAMSEY NUMBER


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Background: Chemotherapy is still a critical issue in the management of leishmaniasis. Until recently, pentavalent antimonials, amphotericin B or pentamidine compounded the classical arsenal of treatment. All these drugs are toxic and have to be administered by the parenteral route. Tamoxifen has been used as an antiestrogen in the treatment and prevention of breast cancer for many years. Its safety and pharmacological profiles are well established in humans. We have shown that tamoxifen is active as an antileishmanial compound in vitro, and in this paper we analyzed the efficacy of tamoxifen for the treatment of mice infected with Leishmania amazonensis, an etiological agent of localized cutaneous leishmaniasis and the main cause of diffuse cutaneous leishmaniasis in South America. Methodology/Principal Findings: BALB/c mice were infected with L. amazonensis promastigotes. Five weeks post-infection, treatment with 15 daily intraperitoneal injections of 20 mg/kg tamoxifen was administered. Lesion and ulcer sizes were recorded and parasite burden quantified by limiting dilution. A significant decrease in lesion size and ulcer development was noted in mice treated with tamoxifen as compared to control untreated animals. Parasite burden in the inoculation site at the end of treatment was reduced from 10(8.5 +/- 0.7) in control untreated animals to 10(5.0 +/- 0.0) in tamoxifen-treated mice. Parasite load was also reduced in the draining lymph nodes. The reduction in parasite number was sustained: 6 weeks after the end of treatment, 10(15.5 +/- 0.5) parasites were quantified from untreated animals, as opposed to 10(5.1 +/- 0.1) parasites detected in treated mice. Conclusions/Significance: Treatment of BALB/c mice infected with L. amazonensis for 15 days with tamoxifen resulted in significant decrease in lesion size and parasite burden. BALB/c mice infected with L. amazonensis represents a model of extreme susceptibility, and the striking and sustained reduction in the number of parasites in treated animals supports the proposal of further testing of this drug in other models of leishmaniasis.

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The structure of thin films composed of a multilayer of PbTe nanocrystals embedded in SiO(2), named as PbTe(SiO(2)), between homogeneous layers of amorphous SiO(2) deposited on a single-crystal Si( 111) substrate was studied by grazing-incidence small-angle X-ray scattering (GISAXS) as a function of PbTe content. PbTe(SiO(2))/SiO(2) multilayers were produced by alternately applying plasma-enhanced chemical vapour deposition and pulsed laser deposition techniques. From the analysis of the experimental GISAXS patterns, the average radius and radius dispersion of PbTe nanocrystals were determined. With increasing deposition dose the size of the PbTe nanocrystals progressively increases while their number density decreases. Analysis of the GISAXS intensity profiles along the normal to the sample surface allowed the determination of the period parameter of the layers and a structure parameter that characterizes the disorder in the distances between PbTe layers. (C) 2010 International Union of Crystallography Printed in Singapore - all rights reserved

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ZrO(2)-10, 12 and 14 mol% Sc(2)O(3) nanopowders were prepared by using a nitrate-lysine gel-combustion synthesis. These materials were studied by synchrotron X-ray powder diffraction (SXPD) and Raman spectroscopy after calcination at different temperatures from 650 to 1200 degrees C, which led to samples with different average crystallite sizes, up to about 100 nm. The results from SXPD and Raman analyses indicate that, depending on Sc(2)O(3) content, the metastable t ''-form of the tetragonal phase or the cubic phase are fully retained at room temperature in nanocrystalline powders, provided an average crystallite sizes lower than similar to 30 nm. By contrast, powders with larger average crystallite sizes exhibit the stable rhombohedral, beta and gamma, phases and do not retain or very partially retain the metastable t '' and cubic ones.

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Size-resolved vertical aerosol number fluxes of particles in the diameter range 0.25-2.5 mu m were measured with the eddy covariance method from a 53 m high tower over the Amazon rain forest, 60 km NNW of Manaus, Brazil. This study focuses on data measured during the relatively clean wet season, but a shorter measurement period from the more polluted dry season is used as a comparison. Size-resolved net particle fluxes of the five lowest size bins, representing 0.25-0.45 mu m in diameter, were in general dominated by deposition in more or less all wind sectors in the wet season. This is an indication that the source of primary biogenic aerosol particles may be small in this particle size range. Transfer velocities within this particle size range were observed to increase linearly with increasing friction velocity and increasing particle diameter. In the diameter range 0.5-2.5 mu m, vertical particle fluxes were highly dependent on wind direction. In wind sectors where anthropogenic influence was low, net upward fluxes were observed. However, in wind sectors associated with higher anthropogenic influence, deposition fluxes dominated. The net upward fluxes were interpreted as a result of primary biogenic aerosol emission, but deposition of anthropogenic particles seems to have masked this emission in wind sectors with higher anthropogenic influence. The net emission fluxes were at maximum in the afternoon when the mixed layer is well developed, and were best correlated with horizontal wind speed according to the equation log(10)F = 0.48.U + 2.21 where F is the net emission number flux of 0.5-2.5 mu m particles [m(-2) s(-1)] and U is the horizontal wind speed [ms(-1)] at the top of the tower.

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Measurements of polar organic marker compounds were performed on aerosols that were collected at a pasture site in the Amazon basin (Rondonia, Brazil) using a high-volume dichotomous sampler (HVDS) and a Micro-Orifice Uniform Deposit Impactor (MOUDI) within the framework of the 2002 LBA-SMOCC (Large-Scale Biosphere Atmosphere Experiment in Amazonia - Smoke Aerosols, Clouds, Rainfall, and Climate: Aerosols From Biomass Burning Perturb Global and Regional Climate) campaign. The campaign spanned the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). In the present study a more detailed discussion is presented compared to previous reports on the behavior of selected polar marker compounds, including levoglucosan, malic acid, isoprene secondary organic aerosol (SOA) tracers and tracers for fungal spores. The tracer data are discussed taking into account new insights that recently became available into their stability and/or aerosol formation processes. During all three periods, levoglucosan was the most dominant identified organic species in the PM(2.5) size fraction of the HVDS samples. In the dry period levoglucosan reached concentrations of up to 7.5 mu g m(-3) and exhibited diel variations with a nighttime prevalence. It was closely associated with the PM mass in the size-segregated samples and was mainly present in the fine mode, except during the wet period where it peaked in the coarse mode. Isoprene SOA tracers showed an average concentration of 250 ng m(-3) during the dry period versus 157 ng m(-3) during the transition period and 52 ng m(-3) during the wet period. Malic acid and the 2-methyltetrols exhibited a different size distribution pattern, which is consistent with different aerosol formation processes (i.e., gas-to-particle partitioning in the case of malic acid and heterogeneous formation from gas-phase precursors in the case of the 2-methyltetrols). The 2-methyltetrols were mainly associated with the fine mode during all periods, while malic acid was prevalent in the fine mode only during the dry and transition periods, and dominant in the coarse mode during the wet period. The sum of the fungal spore tracers arabitol, mannitol, and erythritol in the PM(2.5) fraction of the HVDS samples during the dry, transition, and wet periods was, on average, 54 ng m(-3), 34 ng m(-3), and 27 ng m(-3), respectively, and revealed minor day/night variation. The mass size distributions of arabitol and mannitol during all periods showed similar patterns and an association with the coarse mode, consistent with their primary origin. The results show that even under the heavy smoke conditions of the dry period a natural background with contributions from bioaerosols and isoprene SOA can be revealed. The enhancement in isoprene SOA in the dry season is mainly attributed to an increased acidity of the aerosols, increased NO(x) concentrations and a decreased wet deposition.

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We consider finite-size particles colliding elastically, advected by a chaotic flow. The collisionless dynamics has a quasiperiodic attractor and particles are advected towards this attractor. We show in this work that the collisions have dramatic effects in the system's dynamics, giving rise to collective phenomena not found in the one-particle dynamics. In particular, the collisions induce a kind of instability, in which particles abruptly spread out from the vicinity of the attractor, reaching the neighborhood of a coexisting chaotic saddle, in an autoexcitable regime. This saddle, not present in the dynamics of a single particle, emerges due to the collective particle interaction. We argue that this phenomenon is general for advected, interacting particles in chaotic flows.

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Noise is an intrinsic feature of population dynamics and plays a crucial role in oscillations called phase-forgetting quasicycles by converting damped into sustained oscillations. This function of noise becomes evident when considering Langevin equations whose deterministic part yields only damped oscillations. We formulate here a consistent and systematic approach to population dynamics, leading to a Fokker-Planck equation and the associate Langevin equations in accordance with this conceptual framework, founded on stochastic lattice-gas models that describe spatially structured predator-prey systems. Langevin equations in the population densities and predator-prey pair density are derived in two stages. First, a birth-and-death stochastic process in the space of prey and predator numbers and predator-prey pair number is obtained by a contraction method that reduces the degrees of freedom. Second, a van Kampen expansion in the inverse of system size is then performed to get the Fokker-Planck equation. We also study the time correlation function, the asymptotic behavior of which is used to characterize the transition from the cyclic coexistence of species to the ordinary coexistence.

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Balance functions have been measured for charged-particle pairs, identified charged-pion pairs, and identified charged-kaon pairs in Au + Au, d + Au, and p + p collisions at root s(NN) = 200 GeV at the Relativistic Heavy Ion Collider using the STAR detector. These balance functions are presented in terms of relative pseudorapidity, Delta eta, relative rapidity, Delta y, relative azimuthal angle, Delta phi, and invariant relative momentum, q(inv). For charged-particle pairs, the width of the balance function in terms of Delta eta scales smoothly with the number of participating nucleons, while HIJING and UrQMD model calculations show no dependence on centrality or system size. For charged-particle and charged-pion pairs, the balance functions widths in terms of Delta eta and Delta y are narrower in central Au + Au collisions than in peripheral collisions. The width for central collisions is consistent with thermal blast-wave models where the balancing charges are highly correlated in coordinate space at breakup. This strong correlation might be explained by either delayed hadronization or limited diffusion during the reaction. Furthermore, the narrowing trend is consistent with the lower kinetic temperatures inherent to more central collisions. In contrast, the width of the balance function for charged-kaon pairs in terms of Delta y shows little centrality dependence, which may signal a different production mechanism for kaons. The widths of the balance functions for charged pions and kaons in terms of q(inv) narrow in central collisions compared to peripheral collisions, which may be driven by the change in the kinetic temperature.

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We present the results of an elliptic flow, v(2), analysis of Cu + Cu collisions recorded with the solenoidal tracker detector (STAR) at the BNL Relativistic Heavy Ion Collider at root s(NN) = 62.4 and 200 GeV. Elliptic flow as a function of transverse momentum, v(2)(p(T)), is reported for different collision centralities for charged hadrons h(+/-) and strangeness-ontaining hadrons K(S)(0), Lambda, Xi, and phi in the midrapidity region vertical bar eta vertical bar < 1.0. Significant reduction in systematic uncertainty of the measurement due to nonflow effects has been achieved by correlating particles at midrapidity, vertical bar eta vertical bar < 1.0, with those at forward rapidity, 2.5 < vertical bar eta vertical bar < 4.0. We also present azimuthal correlations in p + p collisions at root s = 200 GeV to help in estimating nonflow effects. To study the system-size dependence of elliptic flow, we present a detailed comparison with previously published results from Au + Au collisions at root s(NN) = 200 GeV. We observe that v(2)(p(T)) of strange hadrons has similar scaling properties as were first observed in Au + Au collisions, that is, (i) at low transverse momenta, p(T) < 2 GeV/c, v(2) scales with transverse kinetic energy, m(T) - m, and (ii) at intermediate p(T), 2 < p(T) < 4 GeV/c, it scales with the number of constituent quarks, n(q.) We have found that ideal hydrodynamic calculations fail to reproduce the centrality dependence of v(2)(p(T)) for K(S)(0) and Lambda. Eccentricity scaled v(2) values, v(2)/epsilon, are larger in more central collisions, suggesting stronger collective flow develops in more central collisions. The comparison with Au + Au collisions, which go further in density, shows that v(2)/epsilon depends on the system size, that is, the number of participants N(part). This indicates that the ideal hydrodynamic limit is not reached in Cu + Cu collisions, presumably because the assumption of thermalization is not attained.

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Biological neuronal networks constitute a special class of dynamical systems, as they are formed by individual geometrical components, namely the neurons. In the existing literature, relatively little attention has been given to the influence of neuron shape on the overall connectivity and dynamics of the emerging networks. The current work addresses this issue by considering simplified neuronal shapes consisting of circular regions (soma/axons) with spokes (dendrites). Networks are grown by placing these patterns randomly in the two-dimensional (2D) plane and establishing connections whenever a piece of dendrite falls inside an axon. Several topological and dynamical properties of the resulting graph are measured, including the degree distribution, clustering coefficients, symmetry of connections, size of the largest connected component, as well as three hierarchical measurements of the local topology. By varying the number of processes of the individual basic patterns, we can quantify relationships between the individual neuronal shape and the topological and dynamical features of the networks. Integrate-and-fire dynamics on these networks is also investigated with respect to transient activation from a source node, indicating that long-range connections play an important role in the propagation of avalanches.

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With each directed acyclic graph (this includes some D-dimensional lattices) one can associate some Abelian algebras that we call directed Abelian algebras (DAAs). On each site of the graph one attaches a generator of the algebra. These algebras depend on several parameters and are semisimple. Using any DAA, one can define a family of Hamiltonians which give the continuous time evolution of a stochastic process. The calculation of the spectra and ground-state wave functions (stationary state probability distributions) is an easy algebraic exercise. If one considers D-dimensional lattices and chooses Hamiltonians linear in the generators, in finite-size scaling the Hamiltonian spectrum is gapless with a critical dynamic exponent z=D. One possible application of the DAA is to sandpile models. In the paper we present this application, considering one- and two-dimensional lattices. In the one-dimensional case, when the DAA conserves the number of particles, the avalanches belong to the random walker universality class (critical exponent sigma(tau)=3/2). We study the local density of particles inside large avalanches, showing a depletion of particles at the source of the avalanche and an enrichment at its end. In two dimensions we did extensive Monte-Carlo simulations and found sigma(tau)=1.780 +/- 0.005.

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We investigate the performance of a variant of Axelrod's model for dissemination of culture-the Adaptive Culture Heuristic (ACH)-on solving an NP-Complete optimization problem, namely, the classification of binary input patterns of size F by a Boolean Binary Perceptron. In this heuristic, N agents, characterized by binary strings of length F which represent possible solutions to the optimization problem, are fixed at the sites of a square lattice and interact with their nearest neighbors only. The interactions are such that the agents' strings (or cultures) become more similar to the low-cost strings of their neighbors resulting in the dissemination of these strings across the lattice. Eventually the dynamics freezes into a homogeneous absorbing configuration in which all agents exhibit identical solutions to the optimization problem. We find through extensive simulations that the probability of finding the optimal solution is a function of the reduced variable F/N(1/4) so that the number of agents must increase with the fourth power of the problem size, N proportional to F(4), to guarantee a fixed probability of success. In this case, we find that the relaxation time to reach an absorbing configuration scales with F(6) which can be interpreted as the overall computational cost of the ACH to find an optimal set of weights for a Boolean binary perceptron, given a fixed probability of success.

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The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.

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Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

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Post-settlement processes are a major focus in the study of the dynamics of marine populations and communities. Post-settlement movement of juveniles is an important, but often ignored, process which affects local predator-prey and competitive interactions. We used benthic suction sampling and pitfall traps to examine density and locomotory activity of Carcinus maenas juveniles in different intertidal habitat types in the Rio Mira Estuary, Portugal, to better understand intra-specific interactions in a system where density-dependent processes are known to regulate population dynamics. As expected, significantly higher densities of juvenile shore crabs were found from bare mud compared to densely vegetated habitats. At the time of sampling, small and intermediate stages together outnumbered by far the larger juveniles. Conversely, larger crabs were much more frequent than smaller ones in traps. A locomotory index (LI), i.e. the ratio between crab catch in pitfall traps and their density within their moving range, is proposed as a measure of movement. LI analyses indicated that: (1) movement is an order of magnitude higher in large than small juveniles and much higher in sparse than dense vegetation cover; (2) activity of small juveniles is mostly crepuscular, regardless of vegetation cover; and (3) movement of large juveniles is very limited in dense Zostera patches, but very high in sparsely vegetated areas, during the day and night. These results suggest that small juveniles are relatively protected under dense vegetation cover due to lower mobility of larger crabs, and provide evidence of temporal segregation of activity windows between juvenile crabs of different sizes, which may be a key mechanism to reduce cannibalism and therefore increase the carrying capacity of nursery habitats. (C) 2008 Elsevier Ltd. All rights reserved.