System size dependence of associated yields in hadron-triggered jets STAR Collaboration

We present results on the system size dependence of high transverse momentum di-hadron correlations at root s(NN) = 200 GeV as measured by STAR at RHIC. Measurements in d + Au, Cu + Cu and Au + Au collisions reveal similar jet-like near-side correlation yields (correlations at small angular separation Delta phi similar to 0, Delta eta similar to 0) for all systems and centralities. Previous measurements have shown Chat the away-side (Delta phi similar to pi) yield is suppressed in heavy-ion collisions. We present measurements of the away-side Suppression as a function of transverse momentum and centrality in Cu + Cu and Au + Au collisions. The suppression is found to be similar in Cu + Cu and An + An collisions at a similar number of participants. The results are compared to theoretical calculations based on the patron quenching model and the modified fragmentation model. The observed differences between data and theory indicate that the correlated yields presented here will further constrain dynamic energy loss models and provide information about the dynamic density profile in heavy-ion collisions. (C) 2009 Elsevier B.V. All rights reserved.

Chemical abundance analysis of the Be star HD 171054

In this work the results of a spectroscopic study of the southern field narrow-line Be star HD 171054 are presented. High dispersion and signal-to-noise ratio spectra allowed the estimation of the fundamental photospheric parameters such as the projected rotational velocity, effective temperature and superficial gravity from non-LTE stellar atmosphere models. From these parameters and microturbulence, the abundances of He, C, N, O, Mg, Al and Si for this object are estimated. Results show that C is depleted whereas N is overabundant compared with the sun and OB stars in the solar vicinity. Oxygen and helium are close to the solar value. Magnesium is down by 0.43 dex and aluminium and silicon are overabundant. (C) 2010 Elsevier B.V. All rights reserved.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.