New Galactic star clusters discovered in the VVV survey

Context. VISTA Variables in the Via Lactea (VVV) is one of the six ESO Public Surveys operating on the new 4-m Visible and Infrared Survey Telescope for Astronomy (VISTA). VVV is scanning the Milky Way bulge and an adjacent section of the disk, where star formation activity is high. One of the principal goals of the VVV Survey is to find new star clusters of different ages. Aims. In order to trace the early epochs of star cluster formation we concentrated our search in the directions to those of known star formation regions, masers, radio, and infrared sources. Methods. The disk area covered by VVV was visually inspected using the pipeline processed and calibrated K(S)-band tile images for stellar over-densities. Subsequently, we examined the composite JHK(S) and ZJK(S) color images of each candidate. PSF photometry of 15 x 15 arcmin fields centered on the candidates was then performed on the Cambridge Astronomy Survey Unit reduced images. After statistical field-star decontamination, color-magnitude and color-color diagrams were constructed and analyzed. Results. We report the discovery of 96 new infrared open clusters and stellar groups. Most of the new cluster candidates are faint and compact (with small angular sizes), highly reddened, and younger than 5 Myr. For relatively well populated cluster candidates we derived their fundamental parameters such as reddening, distance, and age by fitting the solar-metallicity Padova isochrones to the color-magnitude diagrams.

Spectrally resolved femtosecond Maker fringes technique

We present a femtosecond third-harmonic generation Maker fringes technique capable of simultaneously providing the magnitude of the cubic nonlinearity and the refractive index dispersion of optical materials. This technique takes advantage of the high intensity and broad spectral band of femtosecond pulses, but requires the use of a spectrometer to deconvolute the information contained in Maker fringes produced by the broad band light. (C) 2008 American Institute of Physics.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Bayesian updating rules in continuous opinion dynamics models

Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

Benefits of exercise training in diabetic rats persist after three weeks of detraining

Regarding all benefits of exercise training, a question remains: how long are these benefits kept? This study evaluated the effect of 3-week detraining after 10 weeks of training in STZ-diabetic rats. Male Wistar rats were assigned into: sedentary controls, trained controls, trained-detrained controls. sedentary diabetic, trained diabetic and trained-detrained diabetic. Arterial pressure (AP) and heart rate (HR) were recorded by a data acquisition system. Baroreflex sensitivity (BRS) was evaluated by HR responses to AP changes induced by infusion of vasoactive drugs. Intrinsic heart rate (IHR), sympathetic tonus (ST) and vagal tonus (VT) were evaluated by pharmacological blockade with atenolol and atropine. Spectral analysis of systolic AP and HR variabilities (HRV) was performed to estimate autonomic modulation to the heart and vessels. Diabetes cardiovascular and autonomic dysfunctions were reversed by exercise training and partially maintained in the 3-week detraining period. In controls, training decreased AP and HR and improved BRS. changes that returned to baseline values after detraining. IHR and VT were improved in trained diabetic rats and remained in detrained diabetic ones. LF component of HRV decreased in trained control group. In diabetics. exercise training improved variance, and absolute LF and HF components of HRV. Only HF was maintained in detrained diabetic group. Moreover, there was an inverse relationship between plasma glucose and the absolute HF component of HRV. These changes probably determined the different survival rate of 80% in diabetic detrained and 51% in diabetic sedentary rats. (c) 2008 Elsevier B.V. All rights reserved.

Methods for exploring the morpho-functional relations of the aortic depressor nerve in experimental diabetes

The present study investigated morpho-functional relations of the aortic depressor nerve (ADN) 5, 15 and 120 days after the onset of streptozotocin-induced diabetes in rats. Time control animals received vehicle. Under pentobarbital anesthesia, ADN activity was recorded simultaneously with arterial pressure. After the recordings, nerves were prepared for light microscopy study and morphometry. ADN function was accessed by means of pressure-nerve activity curve (fitted by sigmoidal regression) and cross-spectral analysis between mean arterial pressure (MAP) and ADN activity. The relation between morphological (myelinated fibers number and density, total myelin area, total fiber area and percentage of occupancy) and functional (gain, signal/noise relation, frequency) parameters were accessed by linear regression analysis and correlation coefficient calculations. Functional parameters obtained by means of the sigmoidal regression curve as well as by cross-spectral analysis were similar in diabetic and control rats. Morphometric parameters of the ADN were similar between groups 5 days after the onset of diabetes. Average myelin area and myelinated fiber area were significantly smaller on diabetic rats 15 and 120 days after the onset of diabetes, being the myelinated fiber and respective axons area and diameter also smaller on 120 days group. Nevertheless, G ratio (ratio between axon and fiber diameter) was nearly 0.6 and not different between groups or experimental times. No significant relationship between morphological and functional parameters was detected in all experimental groups. The present study suggests that ADN diabetic neuropathy was time-dependent, with damage to myelinated fibers to be the primary event, not evidenced by physiological methods. (C) 2010 Elsevier B.V. All rights reserved.

TOWARD UNDERSTANDING THE B[e] PHENOMENON. III. PROPERTIES OF THE OPTICAL COUNTERPART OF IRAS 00470+6429

FS CMa type stars are a group of Galactic objects with the B[e] phenomenon. They exhibit strong emission-line spectra and infrared excesses, which are most likely due to recently formed circumstellar dust. The group content and identification criteria were described in the first two papers of the series. In this paper we report our spectroscopic and photometric observations of the optical counterpart of IRAS 00470+6429 obtained in 2003-2008. The optical spectrum is dominated by emission lines, most of which have P Cyg type profiles. We detected significant brightness variations, which may include a regular component, and variable spectral line profiles in both shape and position. The presence of a weak Li I 6708 angstrom line in the spectrum suggests that the object is most likely a binary system with a B2-B3 spectral-type primary companion of a luminosity log L/L(circle dot) = 3.9 +/- 0.3 and a late-type secondary companion. We estimate a distance toward the object to be 2.0 +/- 0.3 kpc from the Sun.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Transformed symmetric models

For the first time, we introduce a class of transformed symmetric models to extend the Box and Cox models to more general symmetric models. The new class of models includes all symmetric continuous distributions with a possible non-linear structure for the mean and enables the fitting of a wide range of models to several data types. The proposed methods offer more flexible alternatives to Box-Cox or other existing procedures. We derive a very simple iterative process for fitting these models by maximum likelihood, whereas a direct unconditional maximization would be more difficult. We give simple formulae to estimate the parameter that indexes the transformation of the response variable and the moments of the original dependent variable which generalize previous published results. We discuss inference on the model parameters. The usefulness of the new class of models is illustrated in one application to a real dataset.

Approach to Equilibrium for a Class of Random Quantum Models of Infinite Range

We consider random generalizations of a quantum model of infinite range introduced by Emch and Radin. The generalizations allow a neat extension from the class l (1) of absolutely summable lattice potentials to the optimal class l (2) of square summable potentials first considered by Khanin and Sinai and generalised by van Enter and van Hemmen. The approach to equilibrium in the case of a Gaussian distribution is proved to be faster than for a Bernoulli distribution for both short-range and long-range lattice potentials. While exponential decay to equilibrium is excluded in the nonrandom l (1) case, it is proved to occur for both short and long range potentials for Gaussian distributions, and for potentials of class l (2) in the Bernoulli case. Open problems are discussed.

Influence of chromium concentration on the optical-electronic properties of ruby microstructures

Films of amorphous aluminium nitride (AlN) were prepared by conventional radio frequency sputtering of an Al + Cr target in a plasma of pure nitrogen. The Cr-to-Al relative area determines the Cr content, which remained in the similar to 0-3.5 at% concentration range in this study. Film deposition was followed by thermal annealing of the samples up to 1050 degrees C in an atmosphere of oxygen and by spectroscopic characterization through energy dispersive x-ray spectrometry, photoluminescence and optical transmission measurements. According to the experimental results, the optical-electronic properties of the Cr-containing AlN films are highly influenced by both the Cr concentration and the temperature of the thermal treatments. In fact, thermal annealing at 1050 degrees C induces the development of structures that, because of their typical size and distinctive spectral characteristics, were designated by ruby microstructures (RbMSs). These RbMSs are surrounded by a N-rich environment in which Cr(3+) ions exhibit luminescent features not present in other Cr(3+)-containing systems such as ruby, emerald or alexandrite. The light emissions shown by the RbMSs and surroundings were investigated according to the Cr concentration and temperature of measurement, allowing the identification of several Cr(3+)-related luminescent lines. The main characteristics of these luminescent lines and corresponding excitation-recombination processes are presented and discussed in view of a detailed spectroscopic analysis.

A study of the relaxation dynamics in a quadrupolar NMR system using Quantum State Tomography

This article reports a relaxation study in an oriented system containing spin 3/2 nuclei using quantum state tomography (QST). The use of QST allowed evaluating the time evolution of all density matrix elements starting from several initial states. Using an appropriated treatment based on the Redfield theory, the relaxation rate of each density matrix element was measured and the reduced spectral densities that describe the system relaxation were determined. All the experimental data could be well described assuming pure quadrupolar relaxation and reduced spectral densities corresponding to a superposition of slow and fast motions. The data were also analyzed in the context of Quantum Information Processing, where the coherence loss of each qubit of the system was determined using the partial trace operation. (C) 2008 Elsevier Inc. All rights reserved.

Distribution of ABCB1 polymorphisms among Brazilians: impact of population admixture

Introduction: Interethnic admixture is a source of cryptic population structure that may lead to spurious genotype-phenotype associations in pharmacogenomic studies. We studied the impact of population stratification on the distribution of ABCB1 polymorphisms (1236C > T, 2677G > T/A and 3435C > T) among Brazilians, a highly admixed population with Amerindian, European and African ancestral roots. Methods: Individual DNA from 320 healthy adults was genotyped with a panel of ancestry informative markers, and the proportions of African component of ancestry (ACA) were estimated. ABCB1 genotypes were determined by the single base extension/termination method. We describe the association between ABCB1 polymorphisms and ACA by fitting a linear proportional odds logistic regression model to the data. Results: The distribution of the ABCB1 2677G > T/A and 3435C > T, but not the 1236C > T, SNPs displayed a significant trend for decreasing frequency of the T alleles and TT genotypes from White to Intermediate to Black individuals. The same trend was observed in the frequency of the T/nonG/T haplotype at the 1236, 2677 and 3435 loci. When the population sample was proportioned in quartiles, according to the individual ACA estimates, the frequency of the T allele and TT genotype at each locus declined progressively from the lowest (< 0.25 ACA) to the highest (> 0.75 ACA) quartile. Linear proportional odds logistic regression analysis confirmed that the odds of having the T allele at each locus decreases in a continuous manner with the increase of the ACA, throughout the ACA range (0.13-0.94) observed in the overall population sample. A significant association was also detected between the individual ACA estimates and the presence of the T/nonG/T haplotype in the overall population. Conclusion: Self-identification according to the racial/color categories proposed by the Brazilian Census is insufficient to properly control for population stratification in pharmacogenomic studies of ABCB1.

THE SPECTRAL EVOLUTION AND EJECTA OF RECURRENT NOVA U Sco IN THE 2010 OUTBURST

Synoptic spectroscopic observations of the U Sco 2010 outburst from maximum light to quiescence as well as a contemporaneous X-ray observation are presented and analyzed. The X-ray spectrum 52 days after outburst indicates a hot source ( kT(bb) similar to 70 eV). Narrow-line components from the irradiated companion atmosphere were observed in hydrogen and helium optical recombination lines. The formation of a nebular spectrum is seen for the first time in this class of recurrent novae, allowing a detailed study of the ejecta using photoionization models. Unusual [O III] auroral-to-nebular line ratios were found and possible scenarios of their origin are discussed. The modeling of the emission line spectrum suggests highly heterogeneous ejecta with masses around or above 3 x 10(-6) M(sun).

Age and metallicity of star clusters in the Small Magellanic Cloud from integrated spectroscopy

Context. Analysis of ages and metallicities of star clusters in the Magellanic Clouds provide information for studies on the chemical evolution of the Clouds and other dwarf irregular galaxies. Aims. The aim is to derive ages and metallicities from integrated spectra of 14 star clusters in the Small Magellanic Cloud, including a few intermediate/old age star clusters. Methods. Making use of a full-spectrum fitting technique, we compared the integrated spectra of the sample clusters to three different sets of single stellar population models, using two fitting codes available in the literature. Results. We derive the ages and metallicities of 9 intermediate/old age clusters, some of them previously unstudied, and 5 young clusters. Conclusions. We point out the interest of the newly identified as intermediate/old age clusters HW1, NGC 152, Lindsay 3, Lindsay 11, and Lindsay 113. We also confirm the old ages of NGC 361, NGC 419, Kron 3, and of the very well-known oldest SMC cluster, NGC 121.