The Gaia-ESO Survey: processing FLAMES-UVES spectra

The Gaia-ESO Survey is a large public spectroscopic survey that aims to derive radial velocities and fundamental parameters of about 105 Milky Way stars in the field and in clusters. Observations are carried out with the multi-object optical spectrograph FLAMES, using simultaneously the medium-resolution (R ~ 20 000) GIRAFFE spectrograph and the high-resolution (R ~ 47 000) UVES spectrograph. In this paper we describe the methods and the software used for the data reduction, the derivation of the radial velocities, and the quality control of the FLAMES-UVES spectra. Data reduction has been performed using a workflow specifically developed for this project. This workflow runs the ESO public pipeline optimizing the data reduction for the Gaia-ESO Survey, automatically performs sky subtraction, barycentric correction and normalisation, and calculates radial velocities and a first guess of the rotational velocities. The quality control is performed using the output parameters from the ESO pipeline, by a visual inspection of the spectra and by the analysis of the signal-to-noise ratio of the spectra. Using the observations of the first 18 months, specifically targets observed multiple times at different epochs, stars observed with both GIRAFFE and UVES, and observations of radial velocity standards, we estimated the precision and the accuracy of the radial velocities. The statistical error on the radial velocities is σ ~ 0.4 km s-1 and is mainly due to uncertainties in the zero point of the wavelength calibration. However, we found a systematic bias with respect to the GIRAFFE spectra (~0.9 km s-1) and to the radial velocities of the standard stars (~0.5 km s-1) retrieved from the literature. This bias will be corrected in the future data releases, when a common zero point for all the set-ups and instruments used for the survey is be established.

A VLT/FLAMES survey for massive binaries in Westerlund 1. IV. Wd1-5 – binary product and a pre-supernova companion for the magnetar CXOU J1647-45?

Context. The first soft gamma-ray repeater was discovered over three decades ago, and was subsequently identified as a magnetar, a class of highly magnetised neutron star. It has been hypothesised that these stars power some of the brightest supernovae known, and that they may form the central engines of some long duration gamma-ray bursts. However there is currently no consenus on the formation channel(s) of these objects. Aims. The presence of a magnetar in the starburst cluster Westerlund 1 implies a progenitor with a mass ≥40 M⊙, which favours its formation in a binary that was disrupted at supernova. To test this hypothesis we conducted a search for the putative pre-SN companion. Methods. This was accomplished via a radial velocity survey to identify high-velocity runaways, with subsequent non-LTE model atmosphere analysis of the resultant candidate, Wd1-5. Results. Wd1-5 closely resembles the primaries in the short-period binaries, Wd1-13 and 44, suggesting a similar evolutionary history, although it currently appears single. It is overluminous for its spectroscopic mass and we find evidence of He- and N-enrichement, O-depletion, and critically C-enrichment, a combination of properties that is difficult to explain under single star evolutionary paradigms. We infer a pre-SN history for Wd1-5 which supposes an initial close binary comprising two stars of comparable (~ 41 M⊙ + 35 M⊙) masses. Efficient mass transfer from the initially more massive component leads to the mass-gainer evolving more rapidly, initiating luminous blue variable/common envelope evolution. Reverse, wind-driven mass transfer during its subsequent WC Wolf-Rayet phase leads to the carbon pollution of Wd1-5, before a type Ibc supernova disrupts the binary system. Under the assumption of a physical association between Wd1-5 and J1647-45, the secondary is identified as the magnetar progenitor; its common envelope evolutionary phase prevents spin-down of its core prior to SN and the seed magnetic field for the magnetar forms either in this phase or during the earlier episode of mass transfer in which it was spun-up. Conclusions. Our results suggest that binarity is a key ingredient in the formation of at least a subset of magnetars by preventing spin-down via core-coupling and potentially generating a seed magnetic field. The apparent formation of a magnetar in a Type Ibc supernova is consistent with recent suggestions that superluminous Type Ibc supernovae are powered by the rapid spin-down of these objects.

"A list of the books belonging to the late Library of Harvard College that were in the hands of the Overseers, Governors, & Students of the College & escap'd the flames," ca. 1764

This list appears to be the most comprehensive in this series. Although its contents are very similar to those of the list in Folder 2, there are some discrepancies. Entries are arranged by format (folio, quarto, octavo) and include the date the book was "delivered" (loaned), the name of the individual who borrowed it, and its author, title, and volume number. Many of the books had been out of the library for decades prior to the fire, with some loaned out since as early as 1742.

Report of research and technologic work on explosives, explosions, and flames, fiscal years 1951 and 1952 / by Bernard Lewis.

"December 1953".

Smoldering flames; adventures and emotions of a flapper,

Mode of access: Internet.

An investigation of laminar heat transfer to slender cones in the hypersonic shock tunnel

"Contract no. AF-33(616)-6025. Project no. 7064. Task no. 70169. Aeronautical Research Laboratory, Air Force Research Division, Air Research and Development Command, United States Air Force, Wright-Patterson Air Force Base."

Flammes = Flames : op. 10 /

Caption title.

The science of flames and furnaces.

Mode of access: Internet.

Firemen and their exploits: with some account of the rise and development of fire-brigades, of various appliances for saving life at fires and extinguishing the flames.

Mode of access: Internet.

Implantation of a scaffold following bulbectomy induces laminar organization of regenerating olfactory axons

Primary olfactory axons expressing different odorant receptors are interspersed within the olfactory nerve. However, upon reaching the outer nerve fiber layer of the olfactory bulb they defasciculate, sort out, and refasciculate prior to targeting glomeruli in fixed topographic positions. While odorant receptors are crucial for the final targeting of axons to glomeruli, it is unclear what directs the formation of the nerve fiber and glomerular layers of the olfactory bulb. While the olfactory bulb itself may provide instructive cues for the development of these layers, it is also possible that the incoming axons may simply require the presence of a physical scaffold to establish the outer laminar cytoarchitecture. In order to begin to understand the underlying role of the olfactory bulb in development of the outer layers of the olfactory bulb, we physically ablated the olfactory bulbs in OMP-IRES-LacZ and P2-IRES-tau-LacZ neonatal mice and replaced them with artificial biological scaffolds molded into the shape of an olfactory bulb. Regenerating axons projected around the edge of the cranial cavity at the periphery of the artificial scaffold and were able to form an olfactory nerve fiber layer and, to some extent, a glomerular layer. Our results reveal that olfactory axons are able to form rudimentary cytoarchitectonic layers if they are provided with an appropriately shaped biological scaffold. Thus, the olfactory bulb does not appear to provide any tropic substance that either attracts regenerating olfactory axons into the cranial cavity or induces these axons to form a plexus around its outer surface. (c) 2006 Elsevier B.V. All rights reserved.

A bayesian artificial neural network method to characterise laminar defects using dynamic measurements

This paper reports on the development of an artificial neural network (ANN) method to detect laminar defects following the pattern matching approach utilizing dynamic measurement. Although structural health monitoring (SHM) using ANN has attracted much attention in the last decade, the problem of how to select the optimal class of ANN models has not been investigated in great depth. It turns out that the lack of a rigorous ANN design methodology is one of the main reasons for the delay in the successful application of the promising technique in SHM. In this paper, a Bayesian method is applied in the selection of the optimal class of ANN models for a given set of input/target training data. The ANN design method is demonstrated for the case of the detection and characterisation of laminar defects in carbon fibre-reinforced beams using flexural vibration data for beams with and without non-symmetric delamination damage.