Generation of self-similar Gaussian time series by means of the DWT and DWPT variance maps

Due to the several kinds of services that use the Internet and data networks infra-structures, the present networks are characterized by the diversity of types of traffic that have statistical properties as complex temporal correlation and non-gaussian distribution. The networks complex temporal correlation may be characterized by the Short Range Dependence (SRD) and the Long Range Dependence - (LRD). Models as the fGN (Fractional Gaussian Noise) may capture the LRD but not the SRD. This work presents two methods for traffic generation that synthesize approximate realizations of the self-similar fGN with SRD random process. The first one employs the IDWT (Inverse Discrete Wavelet Transform) and the second the IDWPT (Inverse Discrete Wavelet Packet Transform). It has been developed the variance map concept that allows to associate the LRD and SRD behaviors directly to the wavelet transform coefficients. The developed methods are extremely flexible and allow the generation of Gaussian time series with complex statistical behaviors.

Non-linear modal analysis for beams subjected to axial loads: Analytical and finite-element solutions

A rigorous derivation of non-linear equations governing the dynamics of an axially loaded beam is given with a clear focus to develop robust low-dimensional models. Two important loading scenarios were considered, where a structure is subjected to a uniformly distributed axial and a thrust force. These loads are to mimic the main forces acting on an offshore riser, for which an analytical methodology has been developed and applied. In particular, non-linear normal modes (NNMs) and non-linear multi-modes (NMMs) have been constructed by using the method of multiple scales. This is to effectively analyse the transversal vibration responses by monitoring the modal responses and mode interactions. The developed analytical models have been crosschecked against the results from FEM simulation. The FEM model having 26 elements and 77 degrees-of-freedom gave similar results as the low-dimensional (one degree-of-freedom) non-linear oscillator, which was developed by constructing a so-called invariant manifold. The comparisons of the dynamical responses were made in terms of time histories, phase portraits and mode shapes. (C) 2008 Elsevier Ltd. All rights reserved.

Hollow fiber-based liquid-phase microextraction (HF-LPME) of isradipine and its main metabolite followed by chiral HPLC analysis: application to an in vitro biotransformation study

An enantioselective liquid chromatographic method using two-phase hollow fiber liquid-phase microextraction (HF-LPME-HPLC) was developed for the determination of isradipine (ISR) enantiomers and its main metabolite (pyridine derivative of isradipine, PDI) in microsomal fractions isolated from rat liver. The analytes were extracted from 1 mL of microsomal medium using a two-phase HF-LPME procedure with hexyl acetate as the acceptor phase, 30 min of extraction, and sample agitation at 1,500 rpm. For the first time, ISR enantiomers and PDI were resolved. For this separation, a ChiralpakA (R) AD column with hexane/2-propanol/ethanol (94:04:02, v/v/v) as the mobile phase at a flow rate of 1.5 mL min(-1) was used. The column was kept at 23 A +/- 2 A degrees C. The drug and metabolite detection was performed at 325 nm and the internal standard oxybutynin was detected at 225 nm. The recoveries were 23% for PDI and 19% for each ISR enantiomer. The method presented quantification limits (LOQ) of 50 ng mL(-1) and was linear over the concentration range of 50-5,000 and 50-2,500 ng mL(-1) for PDI and each ISR enantiomer, respectively. The validated method was employed to an in vitro biotransformation study of ISR using rat liver microsomal fraction showing that (+)-(S)-ISR is preferentially biotransformed.

Simultaneous determination of rosiglitazone and its metabolites in rat liver microsomal fraction using hollow-fiber liquid-phase microextraction for sample preparation

A three-phase hollow-fiber liquid-phase microextraction method for the analysis of rosiglitazone and its metabolites N-desmethyl rosiglitazone and p-hydroxy rosiglitazone in microsomal preparations is described for the first time. The drug and metabolites HPLC determination was carried out using an X-Terra RP-18 column, at 22 degrees C. The mobile phase was composed of water, acetonitrile and acetic acid (85:15:0.5, v/v/v) and the detection was performed at 245 nm. The hollow-fiber liquid-phase microextraction procedure was optimized using multifactorial experiments and the following optimal condition was established: sample agitation at 1750 rpm, extraction for 30 min, hydrochloric acid 0.01 mol/L as acceptor phase, 1-octanol as organic phase, and donor phase pH adjustment to 8.0. The recovery rates, obtained by using 1 mL of microsomal preparation, were 47-70%. The method presented LOQs of 50 ng/mL and it was linear over the concentration range of 50-6000 ng/mL, with correlation coefficients (r) higher than 0.9960, for all analytes. The validated method was employed to study the in vitro biotransformation of rosiglitazone using rat liver microsomal fraction.

Use of the q-Gaussian mutation in evolutionary algorithms

This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.

Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models

We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

Conservative force fields in non-Gaussian statistics

In this Letter, we determine the kappa-distribution function for a gas in the presence of an external field of force described by a potential U(r). In the case of a dilute gas, we show that the kappa-power law distribution including the potential energy factor term can rigorously be deduced in the framework of kinetic theory with basis on the Vlasov equation. Such a result is significant as a preliminary to the discussion on the role of long range interactions in the Kaniadakis thermostatistics and the underlying kinetic theory. (C) 2008 Elsevier B.V. All rights reserved.

A portable Compton spectrometer for clinical X-ray beams in the energy range 20-150 keV

Primary beam spectra were obtained for an X-ray industrial equipment (40-150 kV), and for a clinical mammography apparatus (25-35 kV) from beams scattered at angles close to 90 degrees, measured with a CdTe Compton spectrometer. Actual scattering angles were determined from the Compton energy shift of characteristic X-rays or spectra end-point energy. Evaluated contribution of coherent scattering amounts to more than 15% of fluence in mammographic beams. This technique can be used in clinical environments. (C) 2010 Elsevier Ltd. All rights reserved.

An analytical relation between entropy production and quantum Lyapunov exponents for Gaussian bipartite systems

We study and compare the information loss of a large class of Gaussian bipartite systems. It includes the usual Caldeira-Leggett-type model as well as Anosov models ( parametric oscillators, the inverted oscillator environment, etc), which exhibit instability, one of the most important characteristics of chaotic systems. We establish a rigorous connection between the quantum Lyapunov exponents and coherence loss, and show that in the case of unstable environments coherence loss is completely determined by the upper quantum Lyapunov exponent, a behavior which is more universal than that of the Caldeira-Leggett-type model.

Single-step chemical synthesis of ferrite hollow nanospheres

We report a single-step chemical synthesis of iron oxide hollow nanospheres with 9.3 nm in diameter. The sample presents a narrow particle diameter distribution and chemical homogeneity. The hollow nature of the particles is confirmed by HRTEM and HAADF STEM analysis. Electron and x-ray diffraction show that the outer material component is constituted by 2 nm ferrite crystals. Mossbauer data provide further evidence for the formation of iron oxide with high structural disorder, magnetically ordered at 4.2 K and superparamagnetism at room temperature. An unusual magnetic behavior under an applied field is reported, which can be explained by the large fraction of atoms existing at both inner and outer surfaces.

Scientific program of the Radioactive Ion Beams Facility in Brasil (RIBRAS)

The RIBRAS facility (Radioactive Ion Beams in Brasil) is installed in connection with the 8MV Pelletron tandem of the University of Sao Paulo Physics Institute. It consists of two superconducting solenoids which focalize light radioactive secondary beams of low energy, produced by transfer reactions. Recent experimental results include the elastic scattering and transfer reactions of (6)He halo nucleus on (9)Be, (27)Al, (51)V and (120)Sn targets. The elastic scattering and transfer of (8)Li and (7)Be on several targets is also being studied. The transfer reaction (8)Li(p,alpha)(5)He of astrophysical interest was also Studied in the E(cm)=0.2-2.5 MeV energy range.

The exponentiated generalized inverse Gaussian distribution

The modeling and analysis of lifetime data is an important aspect of statistical work in a wide variety of scientific and technological fields. Good (1953) introduced a probability distribution which is commonly used in the analysis of lifetime data. For the first time, based on this distribution, we propose the so-called exponentiated generalized inverse Gaussian distribution, which extends the exponentiated standard gamma distribution (Nadarajah and Kotz, 2006). Various structural properties of the new distribution are derived, including expansions for its moments, moment generating function, moments of the order statistics, and so forth. We discuss maximum likelihood estimation of the model parameters. The usefulness of the new model is illustrated by means of a real data set. (c) 2010 Elsevier B.V. All rights reserved.

Analyzing the n→π* Electronic Transition of Formaldehyde in Water. A Sequential Monte Carlo/Time-Dependent Density Functional Theory

The n→π* absorption transition of formaldehyde in water is analyzed using combined and sequential classical Monte Carlo (MC) simulations and quantum mechanics (QM) calculations. MC simulations generate the liquid solute-solvent structures for subsequent QM calculations. Using time-dependent density functional theory in a localized set of gaussian basis functions (TD-DFT/6-311++G(d,p)) calculations are made on statistically relevant configurations to obtain the average solvatochromic shift. All results presented here use the electrostatic embedding of the solvent. The statistically converged average result obtained of 2300 cm-1 is compared to previous theoretical results available. Analysis is made of the effective dipole moment of the hydrogen-bonded shell and how it could be held responsible for the polarization of the solvent molecules in the outer solvation shells.