1,683 research outputs found
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 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 in the Nambu-Jona-Lasinio model-based diquark picture
A Bethe-Salpeter-Faddeev (BSF) calculation is performed for the pentaquark
in the diquark picture of Jaffe and Wilczek in which is a
diquark-diquark- three-body system. Nambu-Jona-Lasinio (NJL) model is
used to calculate the lowest order diagrams in the two-body scatterings of
and . With the use of coupling constants determined from the
meson sector, we find that interaction is attractive in s-wave
while interaction is repulsive in p-wave. With only the lowest three-body
channel considered, we do not find a bound pentaquark state.
Instead, a bound pentaquark with 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&
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