X-ray emission from star-forming galaxies - I. High-mass X-ray binaries

Based on a homogeneous set of X-ray, infrared and ultraviolet observations from Chandra, Spitzer, GALEX and 2MASS archives, we study populations of high-mass X-ray binaries (HMXBs) in a sample of 29 nearby star-forming galaxies and their relation with the star formation rate (SFR). In agreement with previous results, we find that HMXBs are a good tracer of the recent star formation activity in the host galaxy and their collective luminosity and number scale with the SFR, in particular, Lx~2.6 10^{39} SFR. However, the scaling relations still bear a rather large dispersion of ~0.4 dex, which we believe is of a physical origin. We present the catalog of 1057 X-ray sources detected within the $D25$ ellipse for galaxies of our sample and construct the average X-ray luminosity function (XLF) of HMXBs with substantially improved statistical accuracy and better control of systematic effects than achieved in previous studies. The XLF follows a power law with slope of 1.6 in the logLx~35-40 luminosity range with a moderately significant evidence for a break or cut-off at Lx~10^{40} erg/s. As before, we did not find any features at the Eddington limit for a neutron star or a stellar mass black hole. We discuss implications of our results for the theory of binary evolution. In particular we estimate the fraction of compact objects that once upon their lifetime experienced an X-ray active phase powered by accretion from a high mass companion and obtain a rather large number, fx~0.2 (0.1 Myr/tau_x) (tau_x is the life time of the X-ray active phase). This is ~4 orders of magnitude more frequent than in LMXBs. We also derive constrains on the mass distribution of the secondary star in HMXBs.Comment: 23 pages, 14 figures, 5 tables, MNRAS - Accepted 2011 September 2

Generalized information criterion for model selection in penalized graphical models

This paper introduces an estimator of the relative directed distance between an estimated model and the true model, based on the Kulback-Leibler divergence and is motivated by the generalized information criterion proposed by Konishi and Kitagawa. This estimator can be used to select model in penalized Gaussian copula graphical models. The use of this estimator is not feasible for high-dimensional cases. However, we derive an efficient way to compute this estimator which is feasible for the latter class of problems. Moreover, this estimator is, generally, appropriate for several penalties such as lasso, adaptive lasso and smoothly clipped absolute deviation penalty. Simulations show that the method performs similarly to KL oracle estimator and it also improves BIC performance in terms of support recovery of the graph. Specifically, we compare our method with Akaike information criterion, Bayesian information criterion and cross validation for band, sparse and dense network structures

Faddeev calculation of pentaquark Θ+\Theta^+ in the Nambu-Jona-Lasinio model-based diquark picture

A Bethe-Salpeter-Faddeev (BSF) calculation is performed for the pentaquark $\Theta^+$ in the diquark picture of Jaffe and Wilczek in which $\Theta^+$ is a diquark-diquark-${\bar s}$ three-body system. Nambu-Jona-Lasinio (NJL) model is used to calculate the lowest order diagrams in the two-body scatterings of ${\bar s}D$ and $D D$. With the use of coupling constants determined from the meson sector, we find that ${\bar s}D$ interaction is attractive in s-wave while $DD$ interaction is repulsive in p-wave. With only the lowest three-body channel considered, we do not find a bound $\frac 12^+$ pentaquark state. Instead, a bound pentaquark $\Theta^+$ with $\frac 12^-$ is obtained with a unphysically strong vector mesonic coupling constants.Comment: 22 pages, 11 figures, accepted version in Phys. Rev. C. Summary of main changes/corrections: 1. "which only holds at tree level" below the eq. (23) is added. 2. In the last paragraph of p.23 we added a remark that the coupling constant obtained from Lambda mass is different from the estimate as obtained from the meson spectru

INFERRING GENE NETWORKS FROM MICROARRAY WITH GRAPHICAL MODELS

ABSTRACT. Microarray technology allows to collect a large amount of genetic data, such as gene expression data. The activity of the genes are coordinate by a complex network that regulates their expressions controlling common functions, such as the formation of a transcriptional complex or the availability of a signalling pathway. Understanding this organization is crucial to explain normal cell physiology as well as to analyse complex pathological phenotypes. Graphical models are a class of statistical models that can be used to infer gene regulatory networks. In this paper, we examine a class of graphical models: the strongly decomposable graphical models for mixed variables. Among oth- ers properties, explicit expressions of maximum likelihood estimators are available for decomposable graphical models. This property makes the use of decomposable model suitable for high-dimensional data. We apply decomposable graphical models to a real dataset example

Effects of lung volume reduction surgery for emphysema on glycolipidic hormones

BACKGROUND: Pulmonary emphysema is associated with cachexia and disregulation of the hormones regulating the glycolipid metabolism, insulin resistance, and altered substrate utilization. This study aimed at identifying the effects of lung volume reduction surgery (LVRS) on glycolipidic hormones compared to respiratory rehabilitation (RR). METHODS: Thirty-three patients with moderate-to-severe emphysema who were undergoing video-assisted thoracoscopic LVRS were compared to 31 similar patients who refused the operation and followed a standardized RR program. All patients were evaluated before and 12 months after treatment for respiratory function, body composition, glycolipidic hormones, metabolic parameters, and insulin resistance, which was calculated using the homeostatic model assessment index for insulin resistance (HOMA-IR). These groups were compared to a matched healthy control population. RESULTS: Only after LVRS significant improvements were obtained in respiratory function (FEV1, +25.2%; p<0.0001; residual volume, -19.5%; p<0.0001), metabolic parameters (total cholesterol, +13.1%; p<0.01; high-density lipoprotein cholesterol, +11.2%; p<0.01; triglycerides, +18.4; p<0.001; nonesterified fatty acid, -19.7%; p<0.001), and body composition (fat-free mass [FFM], +6.5%; p<0.01; fat mass [FM], +11.9%; p<0.01). The leptin/FM ratio (-6.1%; p<0.01) and resistin/FM ratio (-5.6%; p<0.01) decreased, whereas the adiponectin/FM ratio (+6.9%; p<0.01) and ghrelin (+9.2%; p<0.01) increased, together with reductions in glycemia (-8.8%; p<0.01), insulin level (-20.4%; p<0.001), and HOMA-IR (-27.2%; p<0.0001). The decrement in residual volume was correlated with increment of FFM (rho=-0.49; p<0.02), FM (rho=-0.55; p<0.009), and ghrelin (rho=-0.52; p<0.01), and also with decreases in leptin corrected for FM (rho=0.50; p<0.02) and, marginally, HOMA-IR (rho=0.35; p=0.07). CONCLUSIONS: After LVRS, glycolipidic hormone levels and nutritional status significantly improved, along with insulin resistance reduction and more physiologic utilization of substrates. Correlations between residual volume and body composition as well as glycolipidic hormone levels suggest that postoperative recovery in respiratory dynamics may induce favorable clinical changes when compared to RR

A Software Tool for the Exponential Power Distribution: The normalp Package

In this paper we present the normalp package, a package for the statistical environment R that has a set of tools for dealing with the exponential power distribution. In this package there are functions to compute the density function, the distribution function and the quantiles from an exponential power distribution and to generate pseudo\u2013random numbers from the same distribution. Moreover, methods concerning the estimation of the distribution parameters are described and implemented. It is also possible to estimate linear regression models when we assume the random errors distributed according to an exponential power distribution. A set of functions is designed to perform simulation studies to see the suitability of the estimators used. Some examples of use of this package are provided

The complex time behaviour of the microquasar GRS 1915+105 in the \rho-class observed with BeppoSAX. III: The hard X-ray delay and limit cycle mapping

The microquasar GRS1915+105 was observed by BeppoSAX in October 2000 for about ten days while the source was in \rho-mode, which is characterized by a quasi-regular type I bursting activity. This paper presents a systematic analysis of the delay of the hard and soft X-ray emission at the burst peaks. The lag, also apparent from the comparison of the [1.7-3.4] keV light curves with those in the [6.8-10.2] keV range, is evaluated and studied as a function of time, spectral parameters, and flux. We apply the limit cycle mapping technique, using as independent variables the count rate and the mean photon rate. The results using this technique were also cross-checked using a more standard approach with the cross-correlation methods. Data are organized in runs, each relative to a continuous observation interval. The detected hard-soft delay changes in the course of the pointing from about 3 s to about 10 s and presents a clear correlation with the baseline count rate.Comment: accepted for publication in A&