967 resultados para Distribution Functions


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This study presents data on myosin Va localization in the central nervous system of rainbow trout. We demonstrate, via immunoblots and immunocytochemistry, the expression of myosin Va in several neuronal populations of forebrain, midbrain, hindbrain and spinal cord. The neuronal populations that express myosin Va in trout constitute a very diverse group that do not seem to have many specific similarities such as neurotransmitters used, cellular size or length of their processes. The intensity of the immunoreactivity and the number of immunoreactive cells differ from region to region. Although there is a broad distribution of myosin Va, it is not present in all neuronal populations. This result is in agreement with a previous report, which indicated that myosin Va is approximately as abundant as conventional myosin II and kinesin, and it is broadly involved in neuronal motility events such as axoplasmatic transport. Furthermore, this distribution pattern is in accordance with what was shown in rats and mice; it indicates phylogenetic maintenance of the myosin Va main functions.

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Here we explore the link between the moments of the Laguerre polynomials or Laguerre moments and the generalized functions (as the Dirac delta-function and its derivatives), presenting several interesting relations. A useful application is related to a procedure for calculating mean values in quantum optics that makes use of the so-called quasi-probabilities. One of them, the P-distribution, can be represented by a sum over Laguerre moments when the electromagnetic field is in a photon-number state. Consequently, the P-distribution can be expressed in terms of Dirac delta-function and derivatives. More specifically, we found a direct relation between P-distributions and the Laguerre factorial moments.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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We defined generalized Heaviside functions for a variable x in R-n, and for variables (x, t) in R-n x R-m. Then study properties such as: composition, invertibility, and association relation (the weak equality). This work is developed in the Colombeau generalized functions context.

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Distribution systems with distributed generation require new analysis methods since networks are not longer passive. Two of the main problems in this new scenario are the network reconfiguration and the loss allocation. This work presents a distribution systems graphic simulator, developed with reconfiguration functions and a special focus on loss allocation, both considering the presence of distributed generation. This simulator uses a fast and robust power flow algorithm based on the current summation backward-forward technique. Reconfiguration problem is solved through a heuristic methodology and the losses allocation function, based on the Zbus method, is presented as an attached result for each obtained configuration. Results are presented and discussed, remarking the easiness of analysis through the graphic simulator as an excellent tool for planning and operation engineers, and very useful for training. © 2004 IEEE.

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Low flexibility and reliability in the operation of radial distribution networks make those systems be constructed with extra equipment as sectionalising switches in order to reconfigure the network, so the operation quality of the network can be improved. Thus, sectionalising switches are used for fault isolation and for configuration management (reconfiguration). Moreover, distribution systems are being impacted by the increasing insertion of distributed generators. Hence, distributed generation became one of the relevant parameters in the evaluation of systems reconfiguration. Distributed generation may affect distribution networks operation in various ways, causing noticeable impacts depending on its location. Thus, the loss allocation problem becomes more important considering the possibility of open access to the distribution networks. In this work, a graphic simulator for distribution networks with reconfiguration and loss allocation functions, is presented. Reconfiguration problem is solved through a heuristic methodology, using a robust power flow algorithm based on the current summation backward-forward technique, considering distributed generation. Four different loss allocation methods (Zbus, Direct Loss Coefficient, Substitution and Marginal Loss Coefficient) are implemented and compared. Results for a 32-bus medium voltage distribution network, are presented and discussed.

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We consider some existing relativistic models for the nucleon structure functions, relying on statistical approaches instead of perturbative ones. These models are based on the Fermi-Dirac distribution for the confined quarks, where a density of energy levels is obtained from an effective confining potential. In this context, it is presented some results obtained with a recent statistical quark model for the sea-quark asymmetry in the nucleon. It is shown, within this model, that experimental available observables, such as the ratio and difference between proton and neutron structure functions, are quite well reproduced with just three parameters: two chemical potentials used to reproduce the valence up and down quark numbers in the nucleon, and a temperature that is being used to reproduce the Gottfried sum rule violation. © 2010 American Institute of Physics.

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This paper presents a mixed-integer linear programming model to solve the conductor size selection and reconductoring problem in radial distribution systems. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. The proposed model and a heuristic are used to obtain the Pareto front of the conductor size selection and reconductoring problem considering two different objective functions. The results of one test system and two real distribution systems are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 1969-2012 IEEE.

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This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.

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During the eights and nineties many statistical/thermodynamical models were proposed to describe the nucleons' structure functions and distribution of the quarks in the hadrons. Most of these models describe the compound quarks and gluons inside the nucleon as a Fermi / Bose gas respectively, confined in a MIT bag[1] with continuous energy levels. Another models considers discrete spectrum. Some interesting features of the nucleons are obtained by these models, like the sea asymmetries d̄/ū and d̄-ū. © 2013 American Institute of Physics.

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This paper presents a mixed integer nonlinear programming multiobjective model for short-term planning of distribution networks that considers in an integrated manner the following planning activities: allocation of capacitor banks; voltage regulators; the cable replacement of branches and feeders. The objective functions considered in the proposed model are: to minimize operational and investment costs and minimize the voltage deviations in the the network buses, subject to a set of technical and operational constraints. A multiobjective genetic algorithm based on a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve this model. The proposed mathematical model and solution methodology is validated testing a medium voltage distribution system with 135 buses. © 2013 Brazilian Society for Automatics - SBA.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The cortical layer 1 contains mainly small interneurons, which have traditionally been classified according to their axonal morphology. The dendritic morphology of these cells, however, has received little attention and remains ill defined. Very little is known about how the dendritic morphology and spatial distribution of these cells may relate to functional neuronal properties. We used biocytin labeling and whole cell patch clamp recordings, associated with digital reconstruction and quantitative morphological analysis, to assess correlations between dendritic morphology, spatial distribution and membrane properties of rat layer 1 neurons. A total of 106 cells were recorded, labeled and subjected to morphological analysis. Based on the quantitative patterns of their dendritic arbor, cells were divided into four major morphotypes: horizontal, radial, ascendant, and descendant cells. Descendant cells exhibited a highly distinct spatial distribution in relation to other morphotypes, suggesting that they may have a distinct function in these cortical circuits. A significant difference was also found in the distribution of firing patterns between each morphotype and between the neuronal populations of each sublayer. Passive membrane properties were, however, statistically homogeneous among all subgroups. We speculate that the differences observed in active membrane properties might be related to differences in the synaptic input of specific types of afferent fibers and to differences in the computational roles of each morphotype in layer 1 circuits. Our findings provide new insights into dendritic morphology and neuronal spatial distribution in layer 1 circuits, indicating that variations in these properties may be correlated with distinct physiological functions.

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A theoretical approach aiming at the prediction of segregation of dopant atoms on nanocrystalline systems is discussed here. It considers the free energy minimization argument in order to provide the most likely dopant distribution as a function of the total doping level. For this, it requires as input (i) a fixed polyhedral geometry with defined facets, and (ii) a set of functions that describe the surface energy as a function of dopant content for different crystallographic planes. Two Sb-doped SnO2 nanocrystalline systems with different morphology and dopant content were selected as a case study, and the calculation of the dopant distributions expected for them is presented in detail. The obtained results were compared to previously reported characterization of this system by a combination of HRTEM and surface energy calculations, and both methods are shown to be equivalent. Considering its application pre-requisites, the present theoretical approach can provide a first estimation of doping atom distribution for a wide range of nanocrystalline systems. We expect that its use will support the reduction of experimental effort for the characterization of doped nanocrystals, and also provide a solution to the characterization of systems where even state-of-art analytical techniques are limited.