961 resultados para generalized orthonormal bases of functions (GOBF)
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Kumaraswamy [Generalized probability density-function for double-bounded random-processes, J. Hydrol. 462 (1980), pp. 79-88] introduced a distribution for double-bounded random processes with hydrological applications. For the first time, based on this distribution, we describe a new family of generalized distributions (denoted with the prefix `Kw`) to extend the normal, Weibull, gamma, Gumbel, inverse Gaussian distributions, among several well-known distributions. Some special distributions in the new family such as the Kw-normal, Kw-Weibull, Kw-gamma, Kw-Gumbel and Kw-inverse Gaussian distribution are discussed. We express the ordinary moments of any Kw generalized distribution as linear functions of probability weighted moments (PWMs) of the parent distribution. We also obtain the ordinary moments of order statistics as functions of PWMs of the baseline distribution. We use the method of maximum likelihood to fit the distributions in the new class and illustrate the potentiality of the new model with an application to real data.
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We study the spin Hall conductance fluctuations in ballistic mesoscopic systems. We obtain universal expressions for the spin and charge current fluctuations, cast in terms of current-current autocorrelation functions. We show that the latter are conveniently parametrized as deformed Lorentzian shape lines, functions of an external applied magnetic field and the Fermi energy. We find that the charge current fluctuations show quite unique statistical features at the symplectic-unitary crossover regime. Our findings are based on an evaluation of the generalized transmission coefficients correlation functions within the stub model and are amenable to experimental test. DOI: 10.1103/PhysRevB.86.235112
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The first motivation for this note is to obtain a general version of the following result: let E be a Banach space and f : E → R be a differentiable function, bounded below and satisfying the Palais-Smale condition; then, f is coercive, i.e., f(x) goes to infinity as ||x|| goes to infinity. In recent years, many variants and extensions of this result appeared, see [3], [5], [6], [9], [14], [18], [19] and the references therein. A general result of this type was given in [3, Theorem 5.1] for a lower semicontinuous function defined on a Banach space, through an approach based on an abstract notion of subdifferential operator, and taking into account the “smoothness” of the Banach space. Here, we give (Theorem 1) an extension in a metric setting, based on the notion of slope from [11] and coercivity is considered in a generalized sense, inspired by [9]; our result allows to recover, for example, the coercivity result of [19], where a weakened version of the Palais-Smale condition is used. Our main tool (Proposition 1) is a consequence of Ekeland’s variational principle extending [12, Corollary 3.4], and deals with a function f which is, in some sense, the “uniform” Γ-limit of a sequence of functions.
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2000 Mathematics Subject Classification: Primary 26A33, 30C45; Secondary 33A35
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AMS Subj. Classification: 11M41, 11M26, 11S40
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2000 Mathematics Subject Classification: 62J12, 62F35
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Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.
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In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0⩽tof a poly-random collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where fsi(·)'s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali–Sidney scheme is a special case of this general construction. We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.
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In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0 ≤ t < u ≤ n. The idea behind the Micali-Sidney scheme is to generate and distribute secret seeds S = s1, . . . , sd of a poly-random collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where f s i (·)’s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali-Sidney scheme is a special case of this general construction.We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.
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A modification in the algorithm for the detection of totally symmetric functions as expounded by the author in an earlier note1 is presented here. The modified algorithm takes care of a limited number of functions that escape detection by the previous method.
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In many instances we find it advantageous to display a quantum optical density matrix as a generalized statistical ensemble of coherent wave fields. The weight functions involved in these constructions turn out to belong to a family of distributions, not always smooth functions. In this paper we investigate this question anew and show how it is related to the problem of expanding an arbitrary state in terms of an overcomplete subfamily of the overcomplete set of coherent states. This provides a relatively transparent derivation of the optical equivalence theorem. An interesting by-product is the discovery of a new class of discrete diagonal representations.
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Four new ternary copper(II) complexes of alpha-amino acid having polypyridyl bases of general formulation [Cu(L-ala)(B)(H2O)](X)(1-4), where L-ala is L-alanine, B is an N,N-donor heterocyclic base, viz. 2,2'-bipyridine (bpy, 1), 1,10-phenanthroline (phen, 2) and 5,6-phenanthroline dione (dione, 3), dipyrido[3,2:2',3'-f] quinoxaline (dpq, 4), and X = ClO4-/NO3- are synthesized, characterized by various spectroscopic and X-ray crystallographic methods. The complexes show a distorted square-pyramidal (4 + 1) CuN3O2 coordination geometry. The one-electron paramagnetic complexes (1-4) display a low energy d-d band near 600 nm in aqueous medium and show a quasi-reversible cyclic voltammetric response due to one-electron Cu(II)/Cu(I) reduction near - 100 mV (versus SCE) in DMF-0.1 M TBAP. Binding interactions of the complexes with calf thymus DNA (CT-DNA) were investigated by UV-Vis absorption titration, ethidium bromide displacement assay, viscometric titration experiment and DNA melting studies. All the complexes barring the complexes 1 and 3 are avid binder to the CT-DNA in the DNA minor groove giving an order: 4 > 2 >>>1, 3. The complexes 2 and 4 show appreciable chemical nuclease activity in the presence of 3-mercaptopropionic acid (MPA) as a reducing agent. Hydroxyl radical was investigated to be the DNA cleavage active species. Control experiments in the presence of distamycin-A show primarily minor groove-binding propensity for the complexes 2 and 4 to the DNA.
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Integral membrane proteins have one or more transmembrane a-helical domains and carry out a variety of functions such as enzyme catalysis, transport across membranes, transducing signals as receptors of hormones and growth factors, and energy transfer in ATP synthesis. These transmembrane domains are not mere structural units anchoring the protein to the lipid bilayer but seem to-contribute in the overall activity. Recent findings in support of this are described using some typical examples-LDL receptor, growth factor receptor tyrosine kinase, HMG-CoA reductase, F-0-ATPase and adrenergic receptors. The trends in research indicate that these transmembrane domains participate in a variety of ways such as a linker, a transducer or an exchanger in the overall functions of these proteins in transfer of materials, energy and signals.
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Genetic algorithms (GAs) are search methods that are being employed in a multitude of applications with extremely large search spaces. Recently, there has been considerable interest among GA researchers in understanding and formalizing the working of GAs. In an earlier paper, we have introduced the notion of binomially distributed populations as the central idea behind an exact ''populationary'' model of the large-population dynamics of the GA operators for objective functions called ''functions of unitation.'' In this paper, we extend this populationary model of GA dynamics to a more general class of objective functions called functions of unitation variables. We generalize the notion of a binomially distributed population to a generalized binomially distributed population (GBDP). We show that the effects of selection, crossover, and mutation can be exactly modelled after decomposing the population into GBDPs. Based on this generalized model, we have implemented a GA simulator for functions of two unitation variables-GASIM 2, and the distributions predicted by GASIM 2 match with those obtained from actual GA runs. The generalized populationary model of GA dynamics not only presents a novel and natural way of interpreting the workings of GAs with large populations, but it also provides for an efficient implementation of the model as a GA simulator. (C) Elsevier Science Inc. 1997.
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A generalized top-spin analysis proposed some time ago in the context of the standard model and subsequently studied in varying contexts is now applied primarily to the case of e(+)e(-) -> t (tww) over bar with transversely polarized beams. This extends our recent work with new physics couplings of scalar (S) and tensor (T) types. We carry out a comprehensive analysis assuming only the electron beam to be transversely polarized, which is sufficient to probe these interactions, and also eliminates any azimuthal angular dependence due to the standard model or new physics of the vector (V) and axial-vector (A) type interactions. We then consider new physics of the general four-Fermi type of V and A type with both beams transversely polarized and discuss implications with longitudinal polarization as well. The generalized spin bases are all investigated in the presence of either longitudinal or transverse beam polarization to look for appreciable deviation from the SM prediction in case of the new physics. 90% confidence level limits are obtained on the interactions for the generalized spin bases with realistic integrated luminosity. In order to achieve this we present a general discussion based on helicity amplitudes and derive a general transformation matrix that enables us to treat the spin basis. We find that beamline basis combined with transverse polarization provides an excellent window of opportunity both for S, T and V, A new physics, followed by the off-diagonal basis. The helicity basis is shown to be the best in case of longitudinal polarization to look for new physics effects due to V and A. DOI: 10.1103/PhysRevD.86.114019