The AMBRE Project: Parameterisation of FGK-type stars from the ESO:HARPS archived spectra

The AMBRE project is a collaboration between the European Southern Observatory (ESO) and the Observatoire de la Cote d'Azur (OCA). It has been established to determine the stellar atmospheric parameters (effective temperature, surface gravity, global metallicities and abundance of alpha-elements over iron) of the archived spectra of four ESO spectrographs. The analysis of the ESO:HARPS archived spectra is presented. The sample being analysed (AMBRE:HARPS) covers the period from 2003 to 2010 and is comprised of 126688 scientific spectra corresponding to 17218 different stars. For the analysis of the spectral sample, the automated pipeline developed for the analysis of the AMBRE:FEROS archived spectra has been adapted to the characteristics of the HARPS spectra. Within the pipeline, the stellar parameters are determined by the MATISSE algorithm, developed at OCA for the analysis of large samples of stellar spectra in the framework of galactic archaeology. In the present application, MATISSE uses the AMBRE grid of synthetic spectra, which covers FGKM-type stars for a range of gravities and metallicities. We first determined the radial velocity and its associated error for the ~15% of the AMBRE:HARPS spectra, for which this velocity had not been derived by the ESO:HARPS reduction pipeline. The stellar atmospheric parameters and the associated chemical index [alpha/Fe] with their associated errors have then been estimated for all the spectra of the AMBRE:HARPS archived sample. Based on quality criteria, we accepted and delivered the parameterisation of ~71% of the total sample to ESO. These spectra correspond to ~10706 stars; each are observed between one and several hundred times. This automatic parameterisation of the AMBRE:HARPS spectra shows that the large majority of these stars are cool main-sequence dwarfs with metallicities greater than -0.5 dex

Machine learning and advanced statistics in astronomy: two applications

In the last decade, the advances in technology have permitted the development of highly automated surveys in many elds of astronomy. One of the most ambitious is the ESA mission Gaia. Mainly devoted to astrometric measurements in the Galaxy, Gaia will provide also spectroscopic and photometric data. All this information will amount to thousands of terabytes. The same goes for surveys designed to observe transient events: the ongoing Panoramic Survey Telescope and Rapid Response System (PanSTARSS) and Dark Energy Survey (DES) (Bernstein et al. 2009), and the planned Large Synoptic Survey Telescope (LSST) (Ivezic et al. 2008), will produce a huge amount of data.1 The data production is thus quickly increasing, and is most likely to increase more with he future surveys. Astronomy is facing an era of data-ooding, where there will be much more data then we are able to analyse with classical methods. The way to deal with this ood, the way in which we can extract scienti c information in a short time scale, is using techniques developed in the eld of statistics and computer science. In this framework, in this work are presented two applications, one using spectroscopic data and the other photometric data. The rst is the use of an automatic method called MATISSE to determine atmospheric parameters from stellar spectra. The second is the development of a data driven classi er for supernovae using photometric information alone

Comparing the Sensitivity of Bank Retreat to Changes in Biophysical Conditions between Two Contrasting River Reaches Using a Coupled Morphodynamic Model

Morphodynamic models of river meandering patterns and dynamics are based on the premise that the integration of biophysical processes matching those operating in natural rivers should result in a better fit with observations. Only a few morphodynamic models have been applied to natural rivers, typically along short reaches, and the relative importance of biophysical parameters remains largely unknown in these cases. Here, a series of numerical simulations were run using the hydrodynamic solver TELEMAC-2D, coupled to an advanced physics-based geotechnical module, to verify if sensitivity to key biophysical conditions differs substantially between two natural meandering reaches of different scale and geomorphological context. The model was calibrated against observed measurements of bank retreat for a 1.5 km semi-alluvial meandering reach incised into glacial till (Medway Creek, Ontario, Canada) and an 8.6 km long sinuous alluvial reach of the St. François River (Quebec, Canada). The two river reaches have contrasting bed and bank composition, and they differ in width by one order of magnitude. Calibration was performed to quantify and contrast the contribution of key geotechnical parameters, such as bank cohesion, to bank retreat. Results indicate that the sensitivity to key geotechnical parameters is dependent on the biophysical context and highly variable at the sub-reach scale. The homogeneous sand-bed St. François River is less sensitive to cohesion and friction angle than the more complex Medway Creek, flowing through glacial-till deposits. The latter highlights the limits of physics-based models for practical purposes, as the amount and spatial resolution of biophysical parameters required to improve the agreement between simulation results and observations may justify the use of a reduced complexity modelling approach

YODA++: A proposal for a semi-automatic space mission control

YODA++ is a proposal for a semi-automated data handling and analysis system for the PAMELA space experiment. The core of the routines have been developed to process a stream of raw data downlinked from the Resurs DK1 satellite (housing PAMELA) to the ground station in Moscow. Raw data consist of scientific data and are complemented by housekeeping information. Housekeeping information will be analyzed within a short time from download (1 h) in order to monitor the status of the experiment and to foreseen the mission acquisition planning. A prototype for the data visualization will run on an APACHE TOMCAT web application server, providing an off-line analysis tool using a browser and part of code for the system maintenance. Data retrieving development is in production phase, while a GUI interface for human friendly monitoring is on preliminary phase as well as a JavaServerPages/JavaServerFaces (JSP/JSF) web application facility. On a longer timescale (1–3 h from download) scientific data are analyzed. The data storage core will be a mix of CERNs ROOT files structure and MySQL as a relational database. YODA++ is currently being used in the integration and testing on ground of PAMELA data. 2005 Published by Elsevier Ltd on behalf of COSPAR

A Latent Dirichlet Allocation Approach using Mixed Graph of Terms for Sentiment Analysis

The spread of generic (as Twitter, Facebook orGoogle+) or specialized (as LinkedIn or Viadeo) social networks allows to millions of users to share opinions on different aspects of life every day. Therefore this information is a rich source of data for opinion mining and sentiment analysis. This paper presents a novel approach to the sentiment analysis based on the Latent Dirichlet Allocation (LDA) approach. The proposed methodology aims to identify a word-based graphical model (we call it a mixed graph of terms) for depicting a positive or negative attitude towards a topic. By the use of this model it will be possible to automatically mine from documents positive and negative sentiments.Experimental evaluation, on standard and real datasets, shows that the proposed approach is effective and furnishes good and reliable results

The IR vibrational properties of six members of the garnet family: A quantum mechanical ab initio study

The IR vibrational properties and the corresponding reflectance spectra of the six most common members of the garnet family (pyrope Mg3Al2Si3O12, almandine Fe3Al2Si3O12, spessartine Mn3Al2Si3O12, grossular Ca3Al2Si3O12, uvarovite Ca3Cr2Si3O12, and andradite Ca3Fe2Si3O12) were simulated at the ab initio level with the CRYSTAL09 code by using a large all-electron Gaussian-type basis set and the B3LYP hybrid functional. The 17 IR active F1u transverse optical (TO) and longitudinal optical (LO) frequencies, the oscillator strengths, the high frequency and static dielectric constants, and the reflectance spectrum were computed. The agreement with experiments for the TO and LO peaks is always excellent, the mean absolute difference for the whole set of data (overall 178 peaks) being 5 cm−1. Oscillator strengths, calculated from the mass-weighted effective Born charges, are found in semi-quantitative agreement with the experimental data. The reflectance spectra, simulated through the classical dispersion relation, reproduce the experimental curves extremely well. The availability of the full set of simulated frequencies and intensities, obtained by using uniform computational tools (computer code, variational basis sets, density functional), permits the establishment of correlations between IR wavenumbers and structural features suggested, but only partially documented, in the past

A hybrid multiagent approach for global trajectory optimization

In this paper we consider a global optimization method for space trajectory design problems. The method, which actually aims at finding not only the global minimizer but a whole set of low-lying local minimizers(corresponding to a set of different design options), is based on a domain decomposition technique where each subdomain is evaluated through a procedure based on the evolution of a population of agents. The method is applied to two space trajectory design problems and compared with existing deterministic and stochastic global optimization methods

Comparison of triple-lumen central venous catheters impregnated with silver nanoparticles (AgTive®) vs conventional catheters in intensive care unit patients

BACKGROUND: Silver-impregnated central venous catheters (CVCs) have been proposed as a means for preventing CVC colonization and related bloodstream infections (CRBSIs). AIM: To evaluate the efficacy of CVCs impregnated with silver nanoparticles in a large group of critically ill patients. METHODS: A prospective, randomized clinical trial was conducted in five intensive care units (ICUs). Three hundred and thirty-eight adult patients requiring CVCs between April 2006 and November 2008 were randomized to receive AgTive silver-nanoparticle-impregnated (SC) or conventional (CC) CVCs. Primary endpoints were CVC colonization (growth of ≥15 colony-forming units from the catheter tip) and incident CRBSIs (meeting the definitions of the Centers for Disease Control and Prevention). Infection-free time (days from initial CVC insertion to initial blood culture positivity) and ICU mortality rates were measured as secondary endpoints. FINDINGS: The SC group (N = 135) and CC group (N = 137) were similar in terms of clinical and laboratory parameters at baseline, reasons for ICU admission, complications during CVC insertion, and total time with CVC (mean ± standard deviation; SC 13 ± 24 vs CC 15 ± 37 days). No significant intergroup differences were found in CVC colonization rates (SC 32.6% vs CC 30%; P = 0.7), CRBSI incidence rates (3.36 infections per 1000 catheter-days in both groups), infection-free times (SC 13 ± 34 vs CC 12 ± 12 days; P = 0.85) or ICU mortality (SC 46% vs CC 43%; P = 0.7). CONCLUSION: In critically ill patients, use of AgTive(®) silver-nanoparticle-impregnated CVCs had no significant effect on CVC colonization, CRBSI incidence or ICU mortality. These CVCs cannot be recommended as an adjunctive tool for control of CRBSIs

Cryo-protective effect of an ice-binding protein derived from Antarctic bacteria

Cold environments are populated by organisms able to contravene deleterious effects of low temperature by diverse adaptive strategies, including the production of ice binding proteins (IBPs) that inhibit the growth of ice crystals inside and outside cells. We describe the properties of such a protein (EfcIBP) identified in the metagenome of an Antarctic biological consortium composed of the ciliate Euplotes focardii and psychrophilic non-cultured bacteria. Recombinant EfcIBP can resist freezing without any conformational damage and is moderately heat stable, with a midpoint temperature of 66.4 °C. Tested for its effects on ice, EfcIBP shows an unusual combination of properties not reported in other bacterial IBPs. First, it is one of the best-performing IBPs described to date in the inhibition of ice recrystallization, with effective concentrations in the nanomolar range. Moreover, EfcIBP has thermal hysteresis activity (0.53 °C at 50 μm) and it can stop a crystal from growing when held at a constant temperature within the thermal hysteresis gap. EfcIBP protects purified proteins and bacterial cells from freezing damage when exposed to challenging temperatures. EfcIBP also possesses a potential N-terminal signal sequence for protein transport and a DUF3494 domain that is common to secreted IBPs. These features lead us to hypothesize that the protein is either anchored at the outer cell surface or concentrated around cells to provide survival advantage to the whole cell consortium