Statistical models of mixtures with a biaxial nematic phase

We consider a simple Maier-Saupe statistical model with the inclusion of disorder degrees of freedom to mimic the phase diagram of a mixture of rodlike and disklike molecules. A quenched distribution of shapes leads to a phase diagram with two uniaxial and a biaxial nematic structure. A thermalized distribution, however, which is more adequate to liquid mixtures, precludes the stability of this biaxial phase. We then use a two-temperature formalism, and assume a separation of relaxation times, to show that a partial degree of annealing is already sufficient to stabilize a biaxial nematic structure.

Accurate prediction of the Si/SiO(2) interface band offset using the self-consistent ab initio DFT/LDA-1/2 method

We use the density functional theory/local-density approximation (DFT/LDA)-1/2 method [L. G. Ferreira , Phys. Rev. B 78, 125116 (2008)], which attempts to fix the electron self-energy deficiency of DFT/LDA by half-ionizing the whole Bloch band of the crystal, to calculate the band offsets of two Si/SiO(2) interface models. Our results are similar to those obtained with a ""state-of-the-art"" GW approach [R. Shaltaf , Phys. Rev. Lett. 100, 186401 (2008)], with the advantage of being as computationally inexpensive as the usual DFT/LDA. Our band gap and band offset predictions are in excellent agreement with experiments.

Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

Precise determination of quantum critical points by the violation of the entropic area law

Finite-size scaling analysis turns out to be a powerful tool to calculate the phase diagram as well as the critical properties of two-dimensional classical statistical mechanics models and quantum Hamiltonians in one dimension. The most used method to locate quantum critical points is the so-called crossing method, where the estimates are obtained by comparing the mass gaps of two distinct lattice sizes. The success of this method is due to its simplicity and the ability to provide accurate results even considering relatively small lattice sizes. In this paper, we introduce an estimator that locates quantum critical points by exploring the known distinct behavior of the entanglement entropy in critical and noncritical systems. As a benchmark test, we use this new estimator to locate the critical point of the quantum Ising chain and the critical line of the spin-1 Blume-Capel quantum chain. The tricritical point of this last model is also obtained. Comparison with the standard crossing method is also presented. The method we propose is simple to implement in practice, particularly in density matrix renormalization group calculations, and provides us, like the crossing method, amazingly accurate results for quite small lattice sizes. Our applications show that the proposed method has several advantages, as compared with the standard crossing method, and we believe it will become popular in future numerical studies.

Musical genres: beating to the rhythms of different drums

Online music databases have increased significantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic single and multi-label music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is built in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multi-variate statistical approaches: principal components analysis (unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under the Gaussian hypothesis (supervised) and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by using the kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method.

Development and validation of a fast RP-HPLC method to determine the analogue of the thyroid hormone, 3,5,3 '-triiodothyroacetic acid (TRIAC), in polymeric nanoparticles

The objective of this work was to develop and validate a rapid Reversed-Phase High-Performance Liquid Chromatography method for the quantification of 3,5,3 '-triiodothyroacetic acid (TRIAC) in nanoparticles delivery system prepared in different polymeric matrices. Special attention was given to developing a reliable reproductive technique for the pretreatment of the samples. Chromatographic runs were performed on an Agilent 1200 Series HPLC with a RP Phenomenex (R) Gemini C18 (150 x 4, 6 mm i.d., 5 mu m) column using acetonitrile and triethylamine buffer 0.1% (TEA) (40 : 60 v/v) as a mobile phase in an isocratic elution, pH 5.6 at a flow rate of 1 ml min(-1). TRIAC was detected at a wavelength of 220 nm. The injection volume was 20 mu l and the column temperature was maintained at 35 degrees C. The validation characteristics included accuracy, precision, specificity, linearity, recovery, and robustness. The standard curve was found to have a linear relationship (r(2) - 0.9996) over the analytical range of 5-100 mu g ml(-1) . The detection and quantitation limits were 1.3 and 3.8 mu g ml(-1), respectively. The recovery and loaded TRIAC in colloidal system delivery was nearly 100% and 98%, respectively. The method was successfully applied in polycaprolactone, polyhydroxybutyrate, and polymethylmethacrylate nanoparticles.

Evolutionary dynamics on rugged fitness landscapes: Exact dynamics and information theoretical aspects

The parallel mutation-selection evolutionary dynamics, in which mutation and replication are independent events, is solved exactly in the case that the Malthusian fitnesses associated to the genomes are described by the random energy model (REM) and by a ferromagnetic version of the REM. The solution method uses the mapping of the evolutionary dynamics into a quantum Ising chain in a transverse field and the Suzuki-Trotter formalism to calculate the transition probabilities between configurations at different times. We find that in the case of the REM landscape the dynamics can exhibit three distinct regimes: pure diffusion or stasis for short times, depending on the fitness of the initial configuration, and a spin-glass regime for large times. The dynamic transition between these dynamical regimes is marked by discontinuities in the mean-fitness as well as in the overlap with the initial reference sequence. The relaxation to equilibrium is described by an inverse time decay. In the ferromagnetic REM, we find in addition to these three regimes, a ferromagnetic regime where the overlap and the mean-fitness are frozen. In this case, the system relaxes to equilibrium in a finite time. The relevance of our results to information processing aspects of evolution is discussed.

Thermal lens and interferometric method for glass transition and thermo physical properties measurements in Nd(2)O(3) doped sodium zincborate glass

In this work the time resolved thermal lens method is combined with interferometric technique, the thermal relaxation calorimetry, photoluminescence and lifetime measurements to determine the thermo physical properties of Nd(2)O(3) doped sodium zincborate glass as a function of temperature up to the glass transition region. Thermal diffusivity, thermal conductivity, fluorescence quantum efficiency, linear thermal expansion coefficient and thermal coefficient of electronic polarizability were determined. In conclusion, the results showed the ability of thermal lens and interferometric methods to perform measurements very close to the phase transition region. These techniques provide absolute values for the measured physical quantities and are advantageous when low scan rates are required. (c) 2008 Optical Society of America

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

Method for cadmium and lead longitudinal profiles determination in hair by solid sampling graphite furnace atomic absorption spectrometry

This paper describes methods for the direct determination of Cd and Pb in hair segments (c.a. 5 mm similar to 80 mu g) by solid sampling graphite furnace atomic absorption spectrometry, becoming possible longitudinal profiles in a single strand of hair. To distinguish endogenous and exogenous content. strands of hair were washed by using two different procedures: IAEA protocol (acetone + water + acetone) and the combination of IAEA protocol with HCl washing (acetone + water + acetone + 0.1 mol l(-1) HCl). The concentration of Cd and Pb increased from the root Until the tip of hair washed according to IAEA protocol. However, when the strand of hair was washed using the combination of IAEA protocol and 0.1 mol l(-1) HCl, Cd concentrations decreased in all segments, and Pb concentrations decreased drastically near to the root (5 to 12 mm) and was systematically higher ill the end. The proposed method showed to be useful to assess the temporal variation to Cd and Pb exposure and call be Used for toxicological and environmental investigations. The limits of detection were 2.8 ng g(-1) for Cd and 40 ng g(-1) for Pb. The characteristic masses based oil integrated absorbance were 2.4 pg for Cd and 22 pg for Pb.

Simultaneous determination of Cr, Fe, Ni and V in crude oil by emulsion sampling graphite furnace atomic absorption spectrometry

In this work a simple and reliable method for the simultaneous determination of Cr, Fe, Ni and V in crude oil, using emulsion sampling graphite furnace atomic absorption spectrometry is proposed. Under the best conditions, sample masses around 50 mg were weighed in polypropylene tubes and emulsified in a mixture of 0.5% (v v(-1)) hexane + 6% (m v(-1)) Triton X-100 (R). Considering the compromised conditions, the pyrolysis an atomization temperatures for the simultaneous determination of Cr, Fe, Ni and V were 1400 degrees C and 2500 degrees C, respectively. Aliquots of 20 mu L of reference solution and sample emulsion were co-injected into the graphite tube with 10 mu L of 1.0 g L(-1) Mg(NO(3))(2) as chemical modifier. The detection limits (n = 10, 3 sigma) and characteristic masses were, respectively: 0.07 mu g g(-1) and 19 pg for Cr; 2.15 mu g g(-1) and 31 pg for Fe; 1.25 mu g g(-1) and 44 pg for Ni; and 1.15 mu g g(-1) and 149 pg for V. The reliability of the proposed method was checked by fuel oil Standard Reference Material (SRMTriton X-100 (R) 1634c - NIST) analysis. The concentrations found presented no statistical differences compared to the certified values at 95% confidence level.

Neutron Activation Analysis: A Primary (Ratio) Method to Determine SI-Traceable Values of Element Content in Complex Samples

The metrological principles of neutron activation analysis are discussed. It has been demonstrated that this method can provide elemental amount of substance with values fully traceable to the SI. The method has been used by several laboratories worldwide in a number of CCQM key comparisons - interlaboratory comparison tests at the highest metrological level - supplying results equivalent to values from other methods for elemental or isotopic analysis in complex samples without the need to perform chemical destruction and dissolution of these samples. The CCOM accepted therefore in April 2007 the claim that neutron activation analysis should have the similar status as the methods originally listed by the CCOM as `primary methods of measurement`. Analytical characteristics and scope of application are given.

Optimization and validation of a LIBS method for the determination of macro and micronutrients in sugar cane leaves

Laser induced breakdown spectrometry (LIBS) was applied for the determination of macro (P, K, Ca, Mg) and micronutrients (B, Cu, Fe, Mn and Zn) in sugar cane leaves, which is one of the most economically important crops in Brazil. Operational conditions were previously optimized by a neuro-genetic approach, by using a laser Nd:YAG at 1064 nm with 110 mJ per pulse focused on a pellet surface prepared with ground plant samples. Emission intensities were measured after 2.0 mu s delay time, with 4.5 mu s integration time gate and 25 accumulated laser pulses. Measurements of LIBS spectra were based on triplicate and each replicate consisted of an average of ten spectra collected in different sites (craters) of the pellet. Quantitative determinations were carried out by using univariate calibration and chemometric methods, such as PLSR and iPLS. The calibration models were obtained by using 26 laboratory samples and the validation was carried out by using 15 test samples. For comparative purpose, these samples were also microwave-assisted digested and further analyzed by ICP OES. In general, most results obtained by LIBS did not differ significantly from ICP OES data by applying a t-test at 95% confidence level. Both LIBS multivariate and univariate calibration methods produced similar results, except for Fe where better results were achieved by the multivariate approach. Repeatability precision varied from 0.7 to 15% and 1.3 to 20% from measurements obtained by multivariate and univariate calibration, respectively. It is demonstrated that LIBS is a powerful tool for analysis of pellets of plant materials for determination of macro and micronutrients by choosing calibration and validation samples with similar matrix composition.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.