Electronic spectroscopy of biomolecules in solution: fluorescein dianion in water

A combined and sequential Monte Carlo-quantum mechanics methodology is used to describe the electronic absorption spectrum of the fluorescein dianion in water. Different sets of 100 statistically relevant configurations composed of the solute and several solvent molecules are sampled from the Monte Carlo simulation for a posteriori quantum mechanical calculations of the spectra. In the largest case the configurations are composed of fluorescein and 90 explicit water molecules embedded in the electrostatic field of all remaining water molecules within a distance of 11.3 angstrom. These configurations include 305 atoms and 842 valence electrons, justifying the use of a semi-empirical approach. The electronic spectrum is then calculated using the INDO/CIS method. The solvatochromic shift of fluorescein in water, compared with in isolation, is calculated using the discrete and explicit solvent models. The use of electrostatically embedded explicit water molecules, in INDO/CIS calculations, gives a good description of the spectral shift of the fluorescein dianion in aqueous environment. The results are verified to converge both statistically and with respect to the number of explicit solvent molecules used.

Compressible Sherrington-Kirkpatrick spin-glass model

We introduce a Sherrington-Kirkpatrick spin-glass model with the addition of elastic degrees of freedom. The problem is formulated in terms of an effective four-spin Hamiltonian in the pressure ensemble, which can be treated by the replica method. In the replica-symmetric approximation, we analyze the pressure-temperature phase diagram, and obtain expressions for the critical boundaries between the disordered and the ordered (spin-glass and ferromagnetic) phases. The second-order para-ferromagnetic border ends at a tricritical point, beyond which the transition becomes discontinuous. We use these results to make contact with the temperature-concentration phase diagrams of mixtures of hydrogen-bonded crystals.

Absolute determination of soluble potassium in tea infusion by gamma-ray spectroscopy

Potassium content in tea brew was determined by gamma-ray spectroscopy, Using the 1461 keV gamma-ray fro M (40)K, the naturally occurring radioactive isotope of potassium. We measured radiation with a shielded HPGe detector from individual test samples of tea leaves, before and after infusion preparation, and from commercial instant tea powder. The correction factor for the gamma-ray self-absorption in the extended source was determined with the help of Monte-Carlo simulations. This gamma-ray spectroscopy technique enabled the absolute determination of potassium content with a relative uncertainty smaller than 4%, at the one standard deviation confidence level, showing the feasibility of this method. An experiment to evaluate a possible systematic Uncertainty due to K distribution heterogeneity in the sample was performed, with file result that the corresponding relative standard deviation is smaller than 2% at 95% confidence level. (C) 2009 Elsevier Ltd. All rights reserved.

Pseudolikelihood equations for Potts MRF model parameter estimation on higher order neighborhood systems

This letter presents pseudolikelihood equations for the estimation of the Potts Markov random field model parameter on higher order neighborhood systems. The derived equation for second-order systems is a significantly reduced version of a recent result found in the literature (from 67 to 22 terms). Also, with the proposed method, a completely original equation for Potts model parameter estimation in third-order systems was obtained. These equations allow the modeling of less restrictive contextual systems for a large number of applications in a computationally feasible way. Experiments with both simulated and real remote sensing images provided good results.

SPECTRUM OF SCREENING MASSES FOR SU(2) GAUGE THEORY: UNIVERSALITY CLASS

In this work we study the spectrum of the lowest screening masses for Yang-Mills theories on the lattice. We used the SU(2) gauge group in (3 + 1) dmensions. We adopted the multiple exponential method and the so-called ""variational"" method, in order to detect possible excited states. The calculations were done near the critical temperature of the confinement-deconfinement phase transition. We obtained values for the ratios of the screening masses consistent with predictions from universality arguments. A Monte Carlo evolution of the screening masses in the gauge theory confirms the validity of the predictions.

Random number generators for the generalized Birnbaum-Saunders distribution

The generalized Birnbaum-Saunders distribution pertains to a class of lifetime models including both lighter and heavier tailed distributions. This model adapts well to lifetime data, even when outliers exist, and has other good theoretical properties and application perspectives. However, statistical inference tools may not exist in closed form for this model. Hence, simulation and numerical studies are needed, which require a random number generator. Three different ways to generate observations from this model are considered here. These generators are compared by utilizing a goodness-of-fit procedure as well as their effectiveness in predicting the true parameter values by using Monte Carlo simulations. This goodness-of-fit procedure may also be used as an estimation method. The quality of this estimation method is studied here. Finally, through a real data set, the generalized and classical Birnbaum-Saunders models are compared by using this estimation method.

Bayesian inference for a skew-normal IRT model under the centred parameterization

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is interest in studying latent variables. These latent variables are directly considered in the Item Response Models (IRM) and they are usually called latent traits. A usual assumption for parameter estimation of the IRM, considering one group of examinees, is to assume that the latent traits are random variables which follow a standard normal distribution. However, many works suggest that this assumption does not apply in many cases. Furthermore, when this assumption does not hold, the parameter estimates tend to be biased and misleading inference can be obtained. Therefore, it is important to model the distribution of the latent traits properly. In this paper we present an alternative latent traits modeling based on the so-called skew-normal distribution; see Genton (2004). We used the centred parameterization, which was proposed by Azzalini (1985). This approach ensures the model identifiability as pointed out by Azevedo et al. (2009b). Also, a Metropolis Hastings within Gibbs sampling (MHWGS) algorithm was built for parameter estimation by using an augmented data approach. A simulation study was performed in order to assess the parameter recovery in the proposed model and the estimation method, and the effect of the asymmetry level of the latent traits distribution on the parameter estimation. Also, a comparison of our approach with other estimation methods (which consider the assumption of symmetric normality for the latent traits distribution) was considered. The results indicated that our proposed algorithm recovers properly all parameters. Specifically, the greater the asymmetry level, the better the performance of our approach compared with other approaches, mainly in the presence of small sample sizes (number of examinees). Furthermore, we analyzed a real data set which presents indication of asymmetry concerning the latent traits distribution. The results obtained by using our approach confirmed the presence of strong negative asymmetry of the latent traits distribution. (C) 2010 Elsevier B.V. All rights reserved.