Analysis of the chemical evolution of the Galactic disk via dynamical simulations of the open cluster system

For several decades now, open clusters have been used to study the structure and chemical evolution of the disk of our Galaxy. Due to the fact that their ages and metallicities can be determined with relatively good precision, and since they can be observed even at great distances, they are excellent tracers of the variations in the abundance of heavy chemical elements with age and position in the Galactic disk. In the present work we analyze the star formation history and the chemical evolution of the disk of the Galaxy using numerical simulations of the dynamical evolution of the system of open clusters in the Milky Way. Starting from hypotheses on the history of cluster formation and the chemical enrichment of the disk, we model the present properties of the Galactic open cluster system. The comparison of these models with the observations allows us to examine the validity of the assumed hypotheses and to improve our knowledge about the initial conditions of the chemical evolution of the Galactic disk

Calibration of semi-analytic models of galaxy formation using Particle Swarm Optimization

We present a fast and accurate method to select an optimal set of parameters in semi-analytic models of galaxy formation and evolution (SAMs). Our approach compares the results of a model against a set of observables applying a stochastic technique called Particle Swarm Optimization (PSO), a self-learning algorithm for localizing regions of maximum likelihood in multidimensional spaces that outperforms traditional sampling methods in terms of computational cost. We apply the PSO technique to the SAG semi-analytic model combined with merger trees extracted from a standard $\Lambda$CDM N-body simulation. The calibration is performed using a combination of observed galaxy properties as constraints, including the local stellar mass function and the black hole to bulge mass relation. We test the ability of the PSO algorithm to find the best set of free parameters of the model by comparing the results with those obtained using a MCMC exploration. Both methods find the same maximum likelihood region, however the PSO method requires one order of magnitude less evaluations. This new approach allows a fast estimation of the best-fitting parameter set in multidimensional spaces, providing a practical tool to test the consequences of including other astrophysical processes in SAMs.Comment: 11 pages, 4 figures, 1 table. Accepted for publication in ApJ. Comments are welcom

How accurate is it to update the cosmology of your halo catalogues?

We test and present the application of the full rescaling method by Angulo & White (2010) to change the cosmology of halo catalogues in numerical simulations for cosmological parameter search using semi-analytic galaxy properties. We show that a reduced form of the method can be applied in small simulations with box side of ~50/h Mpc. We perform statistical tests on the accuracy of the properties of rescaled individual haloes, and also on the rescaled population as a whole. We find that individual positions and velocities are recovered with almost no detectable biases. The dispersion in the recovered halo mass does not seem to depend on the resolution of the simulation. Regardless of the halo mass, the individual accretion histories, spin parameter evolution and fraction of mass in substructures are well recovered. The mass of rescaled haloes can be underestimated (overestimated) for negative (positive) variations of either sigma_8 or Omega_m, in a way that does not depend on the halo mass. Statistics of abundances and correlation functions of haloes show also small biases of <10 percent when moving away from the base simulation by up to 2 times the uncertainty in the WMAP7 cosmological parameters. The merger tree properties related to the final galaxy population in haloes also show small biases; the time since the last major merger, the assembly time-scale, and a time-scale related to the stellar ages show correlated biases which indicate that the spectral shapes of galaxies would only be affected by global age changes of ~150 Myr. We show some of these biases for different separations in the cosmological parameters with respect to the desired cosmology so that these can be used to estimate the expected accuracy of the resulting halo population. We also present a way to construct grids of simulations to provide stable accuracy across the Omega_m vs sigma_8 parameter space.Comment: 14 pages, 2 tables, 10 figures. Accepted for publication in MNRA

Advances in Diagnosis and Management of Atypical Spinal Infections: A Comprehensive Review

Atypical spinal infections (ASIs) of the spine are a challenging pathology to management with potentially devastating morbidity and mortality. To identify patients with atypical spinal infections, it is important to recognize the often insidious clinical and radiographic presentations, in the setting of indolent and smoldering organism growth. Trending of inflammatory markers, and culturing of organisms, is essential. Once identified, the spinal infection should be treated with antibiotics and possibly various surgical interventions including decompression and possible fusion depending on spine structural integrity and stability. Early diagnosis of ASIs and immediate treatment of debilitating conditions, such as epidural abscess, correlate with fewer neurological deficits and a shorter duration of medical treatment. There have been great advances in surgical interventions and spinal fusion techniques for patients with spinal infection. Overall, ASIs remain a perplexing pathology that could be successfully treated with early diagnosis and immediate, appropriate medical, and surgical management

Calibration of semi-analytic models of galaxy formation using particle swarm optimization

We present a fast and accurate method to select an optimal set of parameters in semi-analytic models of galaxy formation and evolution (SAMs). Our approach compares the results of a model against a set of observables applying a stochastic technique called Particle Swarm Optimization (PSO), a self-learning algorithm for localizing regions of maximum likelihood in multidimensional spaces that outperforms traditional sampling methods in terms of computational cost. We apply the PSO technique to the SAG semi-analytic model combined with merger trees extracted from a standard Lambda Cold Dark Matter N-body simulation. The calibration is performed using a combination of observed galaxy properties as constraints, including the local stellar mass function and the black hole to bulge mass relation. We test the ability of the PSO algorithm to find the best set of free parameters of the model by comparing the results with those obtained using a MCMC exploration. Both methods find the same maximum likelihood region, however, the PSO method requires one order of magnitude fewer evaluations. This new approach allows a fast estimation of the best-fitting parameter set in multidimensional spaces, providing a practical tool to test the consequences of including other astrophysical processes in SAMs.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plat

Flame quenching by the wall-fundamental characteristics

Knowledge of flame-wall interaction allowed us to understand the phenomena of near wall combustion and flame extinction. The study of near wall flame propagation is important because it is related to engineering applications, such as possible misfiring in internal combustion engines, optimization of combustion, and reduction of unburned hydrocarbons in the combustion products. In the present work different characteristics of the quenching distance were measured in square narrow quenching channels. The channel widths were changed from 2.5mm to 15mm, their length being 30cm. Propane/air mixture was employed in experiments. Direct visualization has been used to observe flame behaviour under quenching conditions. Numerical simulation revealed structure of limit flames during their propagation in quenching channels. It was found satisfactory agreement between numerical calculations and experiments. In conclusions it was confirmed that flame quenching depends on the relation between heat release rate to heat loss rate. Dead space appeared to be larger for rich mixtures in comparison with the lean ones. Flame curvature reached maximum value for stoichiometry and decreased for leaner or richer mixtures