965 resultados para Cumulative Distribution Function


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This article reports on a series of experiments with polyethylene terepthalate (PET) treated in a radio frequency plasma reactor using argon and oxygen as a gas fuel, for treatment times equal to 5 s, 20 s, 30 s, and 100 s. The mechanical strength modification of PET fibers, evaluated by tensile tests on monofilaments, showed that oxygen and argon plasma treatment resulted in a decrease in the average tensile strength compared with the untreated fibers. This reduction in tensile strength is more significant for argon plasma and is very sensitive to the treatment time for oxygen plasma. Scanning electron microscopy (SEM) used to analyze the effects of cold plasma treatment on fiber surfaces indicates differences in roughness profiles depending on the type of treatments, which were associated with variations in mechanical strength. Differences in the roughness profile, surveyed through an image analysis method, provided the distance of roughness interval, D-ri. This parameter represents the number of peaks contained in a unit length and was introduced to correlate fiber surface condition, before and after cold plasma treatments, and average tensile strength. Statistical analysis of experimental data, using Weibull cumulative distribution and linear representation, was performed to explain influences of treatment time and environmental effects on mechanical properties. The shape parameter, alpha, and density parameter, beta, from the Weibull distribution function were used to indicate the experimental data range and to confirm the mechanical performance obtained experimentally.

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A mapping that relates the Wigner phase-space distribution function of a given stationary quantum mechani-cal wave function, a solution of the Schrödinger equation, to a specific solution of the Liouville equation, both subject to the same potential, is studied. By making this mapping, bound states are described by semiclassical distribution functions still depending on Planck's constant, whereas for elastic scattering of a particle by a potential they do not depend on it, the classical limit being reached in this case. Following this method, the mapped distributions of a particle bound in the Pöschl-Teller potential and also in a modified oscillator potential are obtained.

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The leading-twist valence-quark distribution function in the pion is obtained at a low normalization scale of an order of the inverse average size of an instanton pc. The momentum dependent quark mass and the quark-pion vertex are constructed in the framework of the instanton liquid model, using a gauge invariant approach. The parameters of instanton vacuum, the effective instanton radius and quark mass, are related to the vacuum expectation values of the lowest dimension quark-gluon operators and to the pion low energy observables. An analytic expression for the quark distribution function in the pion for a general vertex function is derived. The results are QCD evolved to higher momentum-transfer values, and reasonable agreement with phenomenological analyses of the data on parton distributions for the pion is found. ©2000 The American Physical Society.

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Within a QCD-based eikonal model with a dynamical infrared gluon mass scale we discuss how the small x behavior of the gluon distribution function at moderate Q 2 is directly related to the rise of total hadronic cross-sections. In this model the rise of total cross-sections is driven by gluon-gluon semihard scattering processes, where the behavior of the small x gluon distribution function exhibits the power law xg(x, Q 2) = h(Q 2)x( -∈). Assuming that the Q 2 scale is proportional to the dynamical gluon mass one, we show that the values of h(Q 2) obtained in this model are compatible with an earlier result based on a specific nonperturbative Pomeron model. We discuss the implications of this picture for the behavior of input valence-like gluon distributions at low resolution scales. © 2008 World Scientific Publishing Company.

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This study aims to analyze various index stock exchanges around the world, with mathematical methods, analyzing the Product Distribution function (PDF), cumulative distribution and correlation. It is thought that the world economy is connected, as if the financial markets were a network, where the fluctuation of a market generates a variation on another and another, creating a pattern, that this change will affect the entire network, thus creating what we might call the domino effect. From this we intend to study, using as a basis the main index of the major stock exchanges around the world the relationship they have with each other, analyzing the influence and correlation that generates this effect, showing that markets are connected and influence each other. We can see this effect in the crisis of 2008, where the U.S. market from one moment to the other was shaken, affecting the whole world in a few days, creating effects that are felt in the present day

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The study of proportions is a common topic in many fields of study. The standard beta distribution or the inflated beta distribution may be a reasonable choice to fit a proportion in most situations. However, they do not fit well variables that do not assume values in the open interval (0, c), 0 < c < 1. For these variables, the authors introduce the truncated inflated beta distribution (TBEINF). This proposed distribution is a mixture of the beta distribution bounded in the open interval (c, 1) and the trinomial distribution. The authors present the moments of the distribution, its scoring vector, and Fisher information matrix, and discuss estimation of its parameters. The properties of the suggested estimators are studied using Monte Carlo simulation. In addition, the authors present an application of the TBEINF distribution for unemployment insurance data.

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The way mass is distributed in galaxies plays a major role in shaping their evolution across cosmic time. The galaxy's total mass is usually determined by tracing the motion of stars in its potential, which can be probed observationally by measuring stellar spectra at different distances from the galactic centre, whose kinematics is used to constrain dynamical models. A class of such models, commonly used to accurately determine the distribution of luminous and dark matter in galaxies, is that of equilibrium models. In this Thesis, a novel approach to the design of equilibrium dynamical models, in which the distribution function is an analytic function of the action integrals, is presented. Axisymmetric and rotating models are used to explain observations of a sample of nearby early-type galaxies in the Calar Alto Legacy Integral Field Area survey. Photometric and spectroscopic data for round and flattened galaxies are well fitted by the models, which are then used to get the galaxies' total mass distribution and orbital anisotropy. The time evolution of massive early-type galaxies is also investigated with numerical models. Their structural properties (mass, size, velocity dispersion) are observed to evolve, on average, with redshift. In particular, they appear to be significantly more compact at higher redshift, at fixed stellar mass, so it is interesting to investigate what drives such evolution. This Thesis focuses on the role played by dark-matter haloes: their mass-size and mass-velocity dispersion correlations evolve similarly to the analogous correlations of ellipticals; at fixed halo mass, the haloes are more compact at higher redshift, similarly to massive galaxies; a simple model, in which all the galaxy's size and velocity-dispersion evolution is due to the cosmological evolution of the underlying halo population, reproduces the observed size and velocity-dispersion of massive compact early-type galaxies up to redshift of about 2.

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We describe several simulation algorithms that yield random probability distributions with given values of risk measures. In case of vanilla risk measures, the algorithms involve combining and transforming random cumulative distribution functions or random Lorenz curves obtained by simulating rather general random probability distributions on the unit interval. A new algorithm based on the simulation of a weighted barycentres array is suggested to generate random probability distributions with a given value of the spectral risk measure.

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Greenhouse gas emission reduction is the pillar of the Kyoto Protocol and one of the main goals of the European Union (UE) energy policy. National reduction targets for EU member states and an overall target for the EU-15 (8%) were set by the Kyoto Protocol. This reduction target is based on emissions in the reference year (1990) and must be reached by 2012. EU energy policy does not set any national targets, only an overall reduction target of 20% by 2020. This paper transfers global greenhouse gas emission reduction targets in both these documents to the transport sector and specifically to CO2 emissions. It proposes a nonlinear distribution method with objective, dynamic targets for reducing CO2 emissions in the transport sector, according to the context and characteristics of each geographical area. First, we analyse CO2 emissions from transport in the reference year (1990) and their evolution from 1990 to 2007. We then propose a nonlinear methodology for distributing dynamic CO2 emission reduction targets. We have applied the proposed distribution function for 2012 and 2020 at two territorial levels (EU member states and Spanish autonomous regions). The weighted distribution is based on per capita CO2 emissions and CO2 emissions per gross domestic product. Finally, we show the weighted targets found for each EU member state and each Spanish autonomous region, compare them with the real achievements to date, and forecast the situation for the years the Kyoto and EU goals are to be met. The results underline the need for ?weighted? decentralised decisions to be made at different territorial levels with a view to achieving a common goal, so relative convergence of all the geographical areas is reached over time. Copyright © 2011 John Wiley & Sons, Ltd.

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Blue whiting (Micromesistius poutassou, http://www.marinespecies.org/aphia.php?p=taxdetails&id=126439) is a small mesopelagic planktivorous gadoid found throughout the North-East Atlantic. This data contains the results of a model-based analysis of larvae captured by the Continuous Plankton Recorder (CPR) during the period 1951-2005. The observations are analysed using Generalised Additive Models (GAMs) of the the spatial, seasonal and interannual variation in the occurrence of larvae. The best fitting model is chosen using the Aikaike Information Criteria (AIC). The probability of occurrence in the continous plankton recorder is then normalised and converted to a probability distribution function in space (UTM projection Zone 28) and season (day of year). The best fitting model splits the distribution into two separate spawning grounds north and south of a dividing line at 53 N. The probability distribution is therefore normalised in these two regions (ie the space-time integral over each of the two regions is 1). The modelled outputs are on a UTM Zone 28 grid: however, for convenience, the latitude ("lat") and longitude ("lon") of each of these grid points are also included as a variable in the NetCDF file. The assignment of each grid point to either the Northern or Southern component (defined here as north/south of 53 N), is also included as a further variable ("component"). Finally, the day of year ("doy") is stored as the number of days elapsed from and included January 1 (ie doy=1 on January 1) - the year is thereafter divided into 180 grid points.

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v. 1. Wholesale distribution function.--v. 2. Administrative management, the role of the chief executive.--v. 3. Financial management.--v. 4. Marketing management.--v. 5. Inventory control, theory and practice.--v. 6. Applied management techniques.

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A new approach based on the nonlocal density functional theory to determine pore size distribution (PSD) of activated carbons and energetic heterogeneity of the pore wall is proposed. The energetic heterogeneity is modeled with an energy distribution function (EDF), describing the distribution of solid-fluid potential well depth (this distribution is a Dirac delta function for an energetic homogeneous surface). The approach allows simultaneous determining of the PSD (assuming slit shape) and EDF from nitrogen or argon isotherms at their respective boiling points by using a set of local isotherms calculated for a range of pore widths and solid-fluid potential well depths. It is found that the structure of the pore wall surface significantly differs from that of graphitized carbon black. This could be attributed to defects in the crystalline structure of the surface, active oxide centers, finite size of the pore walls (in either wall thickness or pore length), and so forth. Those factors depend on the precursor and the process of carbonization and activation and hence provide a fingerprint for each adsorbent. The approach allows very accurate correlation of the experimental adsorption isotherm and leads to PSDs that are simpler and more realistic than those obtained with the original nonlocal density functional theory.

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We obtain the exact asymptotic result for the disorder-averaged probability distribution function for a random walk in a biased Sinai model and show that it is characterized by a creeping behavior of the displacement moments with time, similar to v(mu n), where mu <1 is dimensionless mean drift. We employ a method originated in quantum diffusion which is based on the exact mapping of the problem to an imaginary-time Schrodinger equation. For nonzero drift such an equation has an isolated lowest eigenvalue separated by a gap from quasicontinuous excited states, and the eigenstate corresponding to the former governs the long-time asymptotic behavior.

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We examined the anatomy of expanding, mature, and senescing leaves of tropical plants for the presence of red pigments: anthocyanins and betacyanins. We studied 463 species in total, 370 genera, belonging to 94 families. This included 21 species from five families in the Caryophyllales, where betacyanins are the basis for red color. We also included 14 species of ferns and gymnosperms in seven families and 29 species with undersurface coloration at maturity. We analyzed 399 angiosperm species (74 families) for factors (especially developmental and evolutionary) influencing anthocyanin production during expansion and senescence. During expansion, 44.9% produced anthocyanins and only 13.5% during senescence. At both stages, relatively few patterns of tissue distributions developed, primarily in the mesophyll, and very few taxa produced anthocyanins in dermal and ground tissue simultaneously. Of the 35 species producing anthocyanins both in development and senescence, most had similar cellular distributions. Anthocyanin distributions were identical in different developing leaves of three heteroblastic taxa. Phylogeny has influenced the distribution of anthocyanins in the epidermis and mesophyll of expanding leaves and the palisade parenchyma during senescence, although these influences are not strong. Betacyanins appear to have similar distributions in leaves of taxa within the Caryophyllales and, perhaps, similar functions. The presence of anthocyanins in the mesophyll of so many species is inconsistent with the hypothesis of protection against UV damage or fungal pathogens, and the differing tissue distributions indicate that the pigments may function in different ways, as in photoprotection and freeradical scavenging.

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Tropical Cyclones are a continuing threat to life and property. Willoughby (2012) found that a Pareto (power-law) cumulative distribution fitted to the most damaging 10% of US hurricane seasons fit their impacts well. Here, we find that damage follows a Pareto distribution because the assets at hazard follow a Zipf distribution, which can be thought of as a Pareto distribution with exponent 1. The Z-CAT model is an idealized hurricane catastrophe model that represents a coastline where populated places with Zipf- distributed assets are randomly scattered and damaged by virtual hurricanes with sizes and intensities generated through a Monte-Carlo process. Results produce realistic Pareto exponents. The ability of the Z-CAT model to simulate different climate scenarios allowed testing of sensitivities to Maximum Potential Intensity, landfall rates and building structure vulnerability. The Z-CAT model results demonstrate that a statistical significant difference in damage is found when only changes in the parameters create a doubling of damage.