Kinematic Clues to Bar Evolution for Galaxies in the Local Universe: Why the Fastest Rotating Bars are Rotating Most Slowly

We have used Spitzer images of a sample of 68 barred spiral galaxies in the local universe to make systematic measurements of bar length and bar strength. We combine these with precise determinations of the corotation radii associated with the bars, taken from our previous study, which used the phase change from radial inflow to radial outflow of gas at corotation, based on high-resolution two-dimensional velocity fields in Hα taken with a Fabry-Pérot spectrometer. After presenting the histograms of the derived bar parameters, we study their dependence on the galaxy morphological type and on the total stellar mass of the host galaxy, and then produce a set of parametric plots. These include the bar pattern speed versus bar length, the pattern speed normalized with the characteristic pattern speed of the outer disk versus the bar strength, and the normalized pattern speed versus R, the ratio of corotation radius to bar length. To provide guidelines for our interpretation, we used recently published simulations, including disk and dark matter halo components. Our most striking conclusion is that bars with values of R < 1.4, previously considered dynamically fast rotators, can be among the slowest rotators both in absolute terms and when their pattern speeds are normalized. The simulations confirm that this is because as the bars are braked, they can grow longer more quickly than the outward drift of the corotation radius. We conclude that dark matter halos have indeed slowed down the rotation of bars on Gyr timescales. © 2017. The American Astronomical Society. All rights reserved.

Comparative internal kinematics of the H II regions in interacting and isolated galaxies: Implications for massive star formation modes

We have observed 12 interacting galaxy pairs using the Fabry-Perot interferometer GH αFaS (GalaxyHα Fabry-Perot system) on the 4.2-mWilliam Herschel Telescope at theObservatorio del Roque de los Muchachos, La Palma. We present here the Hα surface brightness, velocity and velocity dispersion maps for the 10 systems we have not previously observed using this technique, as well as the physical properties (sizes, Hα luminosities and velocity dispersion) of 1259 HII regions from the full sample. We also derive the physical properties of 1054 HII regions in a sample of 28 isolated galaxies observed with the same instrument in order to compare the two populations of HII regions. We find a population of the brightest HII regions for which the scaling relations, for example the relation between the Hα luminosity and the radius, are clearly distinct from the relations for the regions of lower luminosity. The regions in this bright population are more frequent in the interacting galaxies. We find that the turbulence, and also the star formation rate (SFR), are enhanced in the HII regions in the interacting galaxies. We have also extracted the Hα equivalent widths for the HII regions of both samples, and we have found that the distribution of HII region ages coincides for the two samples of galaxies. We suggest that the SFR enhancement is brought about by gas flows induced by the interactions, which give rise to gravitationally bound gas clouds which grow further by accretion from the flowing gas, producing conditions favourable to star formation. Key words: stars: formation -HII regions - galaxies: interactions - galaxies: ISM- galaxies: kinematics and dynamics

The systemic lupus erythematosus IRF5 risk haplotype is associated with systemic sclerosis

Systemic sclerosis (SSc) is a fibrotic autoimmune disease in which the genetic component plays an important role. One of the strongest SSc association signals outside the human leukocyte antigen (HLA) region corresponds to interferon (IFN) regulatory factor 5 (IRF5), a major regulator of the type I IFN pathway. In this study we aimed to evaluate whether three different haplotypic blocks within this locus, which have been shown to alter the protein function influencing systemic lupus erythematosus (SLE) susceptibility, are involved in SSc susceptibility and clinical phenotypes. For that purpose, we genotyped one representative single-nucleotide polymorphism (SNP) of each block (rs10488631, rs2004640, and rs4728142) in a total of 3,361 SSc patients and 4,012 unaffected controls of Caucasian origin from Spain, Germany, The Netherlands, Italy and United Kingdom. A meta-analysis of the allele frequencies was performed to analyse the overall effect of these IRF5 genetic variants on SSc. Allelic combination and dependency tests were also carried out. The three SNPs showed strong associations with the global disease (rs4728142: P = 1.34×10&lt;sup&gt;−8&lt;/sup&gt;, OR = 1.22, CI 95% = 1.14–1.30; rs2004640: P = 4.60×10&lt;sup&gt;−7&lt;/sup&gt;, OR = 0.84, CI 95% = 0.78–0.90; rs10488631: P = 7.53×10&lt;sup&gt;−20&lt;/sup&gt;, OR = 1.63, CI 95% = 1.47–1.81). However, the association of rs2004640 with SSc was not independent of rs4728142 (conditioned P = 0.598). The haplotype containing the risk alleles (rs4728142*A-rs2004640*T-rs10488631*C: P = 9.04×10&lt;sup&gt;−22&lt;/sup&gt;, OR = 1.75, CI 95% = 1.56–1.97) better explained the observed association (likelihood P-value = 1.48×10&lt;sup&gt;−4&lt;/sup&gt;), suggesting an additive effect of the three haplotypic blocks. No statistical significance was observed in the comparisons amongst SSc patients with and without the main clinical characteristics. Our data clearly indicate that the SLE risk haplotype also influences SSc predisposition, and that this association is not sub-phenotype-specific

Portfolio selection problems in practice: a comparison between linear and quadratic optimization models

Several portfolio selection models take into account practical limitations on the number of assets to include and on their weights in the portfolio. We present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional Value-at-Risk (LACVaR) models, where the assets are limited with the introduction of quantity and cardinality constraints. We propose a completely new approach for solving the LAM model, based on reformulation as a Standard Quadratic Program and on some recent theoretical results. With this approach we obtain optimal solutions both for some well-known financial data sets used by several other authors, and for some unsolved large size portfolio problems. We also test our method on five new data sets involving real-world capital market indices from major stock markets. Our computational experience shows that, rather unexpectedly, it is easier to solve the quadratic LAM model with our algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of the best commercial codes for mixed integer linear programming (MILP) problems. Finally, on the new data sets we have also compared, using out-of-sample analysis, the performance of the portfolios obtained by the Limited Asset models with the performance provided by the unconstrained models and with that of the official capital market indices

Deep neck infection complicating lymphadenitis caused by Streptococcus intermedius in an immunocompetent child

BACKGROUND: Streptococcus intermedius belongs to the Streptococcus anginosus group. It is part of the normal flora of the human mouth, but it can be etiologically associated with deep-site infections. CASE PRESENTATION: We present a case of deep neck infection complicating Streptococcus intermedius lymphadenitis, which developed in an immunocompetent 14-year-old boy with a history of recent dental work. The infection was ultimately eradicated by a combined medical and surgical approach. CONCLUSION: Our report suggests that combined medical and surgical therapy is essential for the complete resolution of deep infections caused by Streptococcus intermedius. Molecular biological techniques can be useful in guiding the diagnostic investigation and providing insight into the possibility of occult abscesses, which are particularly common with Streptococcus intermedius infections

Variable order Mittag-Leffler fractional operators on isolated time scales and application to the calculus of variations

We introduce new fractional operators of variable order on isolated time scales with Mittag-Leffler kernels. This allows a general formulation of a class of fractional variational problems involving variable-order difference operators. Main results give fractional integration by parts formulas and necessary optimality conditions of Euler-Lagrange type.Comment: This is a preprint of a paper whose final and definite form is with Springe

A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis

In this paper we propose a novel method for the segmentation of longitudinal brain MRI scans of patients suffering from Multiple Sclerosis. The method builds upon an existing cross-sectional method for simultaneous whole-brain and lesion segmentation, introducing subject-specific latent variables to encourage temporal consistency between longitudinal scans. It is very generally applicable, as it does not make any prior assumptions on the scanner, the MRI protocol, or the number and timing of longitudinal follow-up scans. Preliminary experiments on three longitudinal datasets indicate that the proposed method produces more reliable segmentations and detects disease effects better than the cross-sectional method it is based upon

Leisure time physical activity in middle age predicts the metabolic syndrome in old age: results of a 28-year follow-up of men in the Oslo study

<p>Abstract</p> <p>Background</p> <p>Data are scarce on the long term relationship between leisure time physical activity, smoking and development of metabolic syndrome and diabetes. We wanted to investigate the relationship between leisure time physical activity and smoking measured in middle age and the occurrence of the metabolic syndrome and diabetes in men that participated in two cardiovascular screenings of the Oslo Study 28 years apart.</p> <p>Methods</p> <p>Men residing in Oslo and born in 1923–32 (n = 16 209) were screened for cardiovascular diseases and risk factors in 1972/3. Of the original cohort, those who also lived in same area in 2000 were invited to a repeat screening examination, attended by 6 410 men. The metabolic syndrome was defined according to a modification of the National Cholesterol Education Program criteria. Leisure time physical activity, smoking, educational attendance and the presence of diabetes were self-reported.</p> <p>Results</p> <p>Leisure time physical activity decreased between the first and second screening and tracked only moderately between the two time points (Spearman's ρ = 0.25). Leisure time physical activity adjusted for age and educational attendance was a significant predictor of both the metabolic syndrome and diabetes in 2000 (odds ratio for moderately vigorous versus sedentary/light activity was 0.65 [95% CI, 0.54–0.80] for the metabolic syndrome and 0.68 [0.52–0.91] for diabetes) (test for trend P < 0.05). However, when adjusted for more factors measured in 1972/3 including glucose, triglycerides, body mass index, treated hypertension and systolic blood pressure these associations were markedly attenuated. Smoking was associated with the metabolic syndrome but not with diabetes in 2000.</p> <p>Conclusion</p> <p>Physical activity during leisure recorded in middle age prior to the current waves of obesity and diabetes had an independent predictive association with the presence of the metabolic syndrome but not significantly so with diabetes 28 years later in life, when the subjects were elderly.</p

Reverse Engineering Time Discrete Finite Dynamical Systems: A Feasible Undertaking?

With the advent of high-throughput profiling methods, interest in reverse engineering the structure and dynamics of biochemical networks is high. Recently an algorithm for reverse engineering of biochemical networks was developed by Laubenbacher and Stigler. It is a top-down approach using time discrete dynamical systems. One of its key steps includes the choice of a term order, a technicality imposed by the use of Gröbner-bases calculations. The aim of this paper is to identify minimal requirements on data sets to be used with this algorithm and to characterize optimal data sets. We found minimal requirements on a data set based on how many terms the functions to be reverse engineered display. Furthermore, we identified optimal data sets, which we characterized using a geometric property called “general position”. Moreover, we developed a constructive method to generate optimal data sets, provided a codimensional condition is fulfilled. In addition, we present a generalization of their algorithm that does not depend on the choice of a term order. For this method we derived a formula for the probability of finding the correct model, provided the data set used is optimal. We analyzed the asymptotic behavior of the probability formula for a growing number of variables n (i.e. interacting chemicals). Unfortunately, this formula converges to zero as fast as , where and . Therefore, even if an optimal data set is used and the restrictions in using term orders are overcome, the reverse engineering problem remains unfeasible, unless prodigious amounts of data are available. Such large data sets are experimentally impossible to generate with today's technologies