919 resultados para power-law distributions


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Darwin observed that multiple, lowly organized, rudimentary, or exaggerated structures show increased relative variability. However, the cellular basis for these laws has never been investigated. Some animals, such as the nematode Caenorhabditis elegans, are famous for having organs that possess the same number of cells in all individuals, a property known as eutely. But for most multicellular creatures, the extent of cell number variability is unknown. Here we estimate variability in organ cell number for a variety of animals, plants, slime moulds, and volvocine algae. We find that the mean and variance in cell number obey a power law with an exponent of 2, comparable to Taylor's law in ecological processes. Relative cell number variability, as measured by the coefficient of variation, differs widely across taxa and tissues, but is generally independent of mean cell number among homologous tissues of closely related species. We show that the power law for cell number variability can be explained by stochastic branching process models based on the properties of cell lineages. We also identify taxa in which the precision of developmental control appears to have evolved. We propose that the scale independence of relative cell number variability is maintained by natural selection.

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Context. Accretion onto supermassive black holes is believed to occur mostly in obscured active galactic nuclei (AGN). Such objects are proving rather elusive in surveys of distant galaxies, including those at X-ray energies. Aims. Our main goal is to determine whether the revised IRAC criteria of Donley et al. (2012, ApJ, 748, 142; objects with an infrared (IR) power-law spectral shape), are effective at selecting X-ray type-2 AGN (i.e., absorbed N_H > 10^22 cm^-2). Methods. We present the results from the X-ray spectral analysis of 147 AGN selected by cross-correlating the highest spectral quality ultra-deep XMM-Newton and the Spitzer/IRAC catalogues in the Chandra Deep Field South. Consequently it is biased towards sources with high S/N X-ray spectra. In order to measure the amount of intrinsic absorption in these sources, we adopt a simple X-ray spectral model that includes a power-law modified by intrinsic absorption at the redshift of each source and a possible soft X-ray component. Results. We find 21/147 sources to be heavily absorbed but the uncertainties in their obscuring column densities do not allow us to confirm their Compton-Thick nature without resorting to additional criteria. Although IR power-law galaxies are less numerous in our sample than IR non-power-law galaxies (60 versus 87 respectively), we find that the fraction of absorbed (N_H^intr > 10^22 cm^-2) AGN is significantly higher (at about 3 sigma level) for IR-power-law sources (similar to 2/3) than for those sources that do not meet this IR selection criteria (~1/2). This behaviour is particularly notable at low luminosities, but it appears to be present, although with a marginal significance, at all luminosities. Conclusions. We therefore conclude that the IR power-law method is efficient in finding X-ray-absorbed sources. We would then expect that the long-sought dominant population of absorbed AGN is abundant among IR power-law spectral shape sources not detected in X-rays.

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Many papers claim that a Log Periodic Power Law (LPPL) model fitted to financial market bubbles that precede large market falls or 'crashes', contains parameters that are confined within certain ranges. Further, it is claimed that the underlying model is based on influence percolation and a martingale condition. This paper examines these claims and their validity for capturing large price falls in the Hang Seng stock market index over the period 1970 to 2008. The fitted LPPLs have parameter values within the ranges specified post hoc by Johansen and Sornette (2001) for only seven of these 11 crashes. Interestingly, the LPPL fit could have predicted the substantial fall in the Hang Seng index during the recent global downturn. Overall, the mechanism posited as underlying the LPPL model does not do so, and the data used to support the fit of the LPPL model to bubbles does so only partially. © 2013.

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We define a sample of 62 galaxies in the Chandra Deep Field-North whose Spitzer IRAC SEDs exhibit the characteristic power-law emission expected of luminous AGNs. We study the multiwavelength properties of this sample and compare the AGNs selected in this way to those selected via other Spitzer color-color criteria. Only 55% of the power-law galaxies are detected in the X-ray catalog at exposures of >0.5 Ms, although a search for faint emission results in the detection of 85% of the power-law galaxies at the ≥2.5 σ detection level. Most of the remaining galaxies are likely to host AGNs that are heavily obscured in the X-ray. Because the power-law selection requires the AGNs to be energetically dominant in the near- and mid-infrared, the power-law galaxies comprise a significant fraction of the Spitzer-detected AGN population at high luminosities and redshifts. The high 24 μm detection fraction also points to a luminous population. The power-law galaxies comprise a subset of color-selected AGN candidates. A comparison with various mid-infrared color selection criteria demonstrates that while the color-selected samples contain a larger fraction of the X-ray-luminous AGNs, there is evidence that these selection techniques also suffer from a higher degree of contamination by star-forming galaxies in the deepest exposures. Considering only those power-law galaxies detected in the X-ray catalog, we derive an obscured fraction of 68% (2 : 1). Including all of the power-law galaxies suggests an obscured fraction of <81% (4 : 1).

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We investigate the influence of viscoelastic nature of the adhesive on the intermittent peel front dynamics by extending a recently introduced model for peeling of an adhesive tape. As time and rate-dependent deformation of the adhesives are measured in stationary conditions, a crucial step in incorporating the viscoelastic effects applicable to unstable intermittent peel dynamics is the introduction of a dynamization scheme that eliminates the explicit time dependence in terms of dynamical variables. We find contrasting influences of viscoelastic contribution in different regions of tape mass, roller inertia, and pull velocity. As the model acoustic energy dissipated depends on the nature of the peel front and its dynamical evolution, the combined effect of the roller inertia and pull velocity makes the acoustic energy noisier for small tape mass and low-pull velocity while it is burstlike for low-tape mass, intermediate values of the roller inertia and high-pull velocity. The changes are quantified by calculating the largest Lyapunov exponent and analyzing the statistical distributions of the amplitudes and durations of the model acoustic energy signals. Both single and two stage power-law distributions are observed. Scaling relations between the exponents are derived which show that the exponents corresponding to large values of event sizes and durations are completely determined by those for small values. Th scaling relations are found to be satisfied in all cases studied. Interestingly, we find only five types of model acoustic emission signals among multitude of possibilities of the peel front configurations.

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Javier G. P. Gamarra and Ricard V. Sole (2002). Biomass-diversity responses and spatial dependencies in disturbed tallgrass prairies. Journal of Theoretical Biology, 215 (4) pp.469-480 RAE2008

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The explosion of WWW traffic necessitates an accurate picture of WWW use, and in particular requires a good understanding of client requests for WWW documents. To address this need, we have collected traces of actual executions of NCSA Mosaic, reflecting over half a million user requests for WWW documents. In this paper we describe the methods we used to collect our traces, and the formats of the collected data. Next, we present a descriptive statistical summary of the traces we collected, which identifies a number of trends and reference patterns in WWW use. In particular, we show that many characteristics of WWW use can be modelled using power-law distributions, including the distribution of document sizes, the popularity of documents as a function of size, the distribution of user requests for documents, and the number of references to documents as a function of their overall rank in popularity (Zipf's law). Finally, we show how the power-law distributions derived from our traces can be used to guide system designers interested in caching WWW documents.

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Fluctuations in the solar wind plasma and magnetic field are well described by the sum of two power law distributions. It has been postulated that these distributions are the result of two independent processes: turbulence, which contributes mainly to the smaller fluctuations, and crossing the boundaries of flux tubes of coronal origin, which dominates the larger variations. In this study we explore the correspondence between changes in the magnetic field with changes in other solar wind properties. Changes in density and temperature may result from either turbulence or coronal structures, whereas changes in composition, such as the alpha-to-proton ratio are unlikely to arise from in-transit effects. Observations spanning the entire ACE dataset are compared with a null hypothesis of no correlation between magnetic field discontinuities and changes in other solar wind parameters. Evidence for coronal structuring is weaker than for in-transit turbulence, with only ∼ 25% of large magnetic field discontinuities associated with a significant change in the alpha-to-proton ratio, compared to ∼ 40% for significant density and temperature changes. However, note that a lack of detectable alpha-to-proton signature is not sufficient to discount a structure as having a solar origin.

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Small propagules like pollen or fungal spores may be dispersed by the wind over distances of hundreds or thousands of kilometres,even though the median dispersal may be only a few metres. Such long-distance dispersal is a stochastic event which may be exceptionally important in shaping a population. It has been found repeatedly in field studies that subpopulations of wind-dispersed fungal pathogens virulent on cultivars with newly introduced, effective resistance genes are dominated by one or very few genotypes. The role of propagule dispersal distributions with distinct behaviour at long distances in generating this characteristic population structure was studied by computer simulation of dispersal of clonal organisms in a heterogeneous environment with fields of unselective and selective hosts. Power-law distributions generated founder events in which new, virulent genotypes rapidly colonized fields of resistant crop varieties and subsequently dominated the pathogen population on both selective and unselective varieties, in agreement with data on rust and powdery mildew fungi. An exponential dispersal function, with extremely rare dispersal over long distances, resulted in slower colonization of resistant varieties by virulent pathogens or even no colonization if the distance between susceptible source and resistant target fields was sufficiently large. The founder events resulting from long-distance dispersal were highly stochastic and exact quantitative prediction of genotype frequencies will therefore always be difficult.

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Considering a quantum gas, the foundations of standard thermostatistics are investigated in the context of non-Gaussian statistical mechanics introduced by Tsallis and Kaniadakis. The new formalism is based on the following generalizations: i) Maxwell- Boltzmann-Gibbs entropy and ii) deduction of H-theorem. Based on this investigation, we calculate a new entropy using a generalization of combinatorial analysis based on two different methods of counting. The basic ingredients used in the H-theorem were: a generalized quantum entropy and a generalization of collisional term of Boltzmann equation. The power law distributions are parameterized by parameters q;, measuring the degree of non-Gaussianity of quantum gas. In the limit q

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Power-law distributions, i.e. Levy flights have been observed in various economical, biological, and physical systems in high-frequency regime. These distributions can be successfully explained via gradually truncated Levy flight (GTLF). In general, these systems converge to a Gaussian distribution in the low-frequency regime. In the present work, we develop a model for the physical basis for the cut-off length in GTLF and its variation with respect to the time interval between successive observations. We observe that GTLF automatically approach a Gaussian distribution in the low-frequency regime. We applied the present method to analyze time series in some physical and financial systems. The agreement between the experimental results and theoretical curves is excellent. The present method can be applied to analyze time series in a variety of fields, which in turn provide a basis for the development of further microscopic models for the system. © 2000 Elsevier Science B.V. All rights reserved.

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Pós-graduação em Física - IGCE

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For taxonomic levels higher than species, the abundance distributions of the number of subtaxa per taxon tend to approximate power laws but often show strong deviations from such laws. Previously, these deviations were attributed to finite-time effects in a continuous-time branching process at the generic level. Instead, we describe herein a simple discrete branching process that generates the observed distributions and find that the distribution's deviation from power law form is not caused by disequilibration, but rather that it is time independent and determined by the evolutionary properties of the taxa of interest. Our model predicts—with no free parameters—the rank-frequency distribution of the number of families in fossil marine animal orders obtained from the fossil record. We find that near power law distributions are statistically almost inevitable for taxa higher than species. The branching model also sheds light on species-abundance patterns, as well as on links between evolutionary processes, self-organized criticality, and fractals.

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An RVE–based stochastic numerical model is used to calculate the permeability of randomly generated porous media at different values of the fiber volume fraction for the case of transverse flow in a unidirectional ply. Analysis of the numerical results shows that the permeability is not normally distributed. With the aim of proposing a new understanding on this particular topic, permeability data are fitted using both a mixture model and a unimodal distribution. Our findings suggest that permeability can be fitted well using a mixture model based on the lognormal and power law distributions. In case of a unimodal distribution, it is found, using the maximum-likelihood estimation method (MLE), that the generalized extreme value (GEV) distribution represents the best fit. Finally, an expression of the permeability as a function of the fiber volume fraction based on the GEV distribution is discussed in light of the previous results.