14,127 research outputs found

    The 2015 outburst of the accreting millisecond pulsar IGR J17511-3057 as seen by INTEGRAL, Swift and XMM-Newton

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    We report on INTEGRAL, Swift and XMM-Newton observations of IGR J17511-3057 performed during the outburst that occurred between March 23 and April 25, 2015. The source reached a peak flux of 0.7(2)E-9 erg/cm2^2/s and decayed to quiescence in approximately a month. The X-ray spectrum was dominated by a power-law with photon index between 1.6 and 1.8, which we interpreted as thermal Comptonization in an electron cloud with temperature > 20 keV . A broad ({\sigma} ~ 1 keV) emission line was detected at an energy (E = 6.9‚ąí0.3+0.2^{+0.2}_{-0.3} keV) compatible with the K{\alpha} transition of ionized Fe, suggesting an origin in the inner regions of the accretion disk. The outburst flux and spectral properties shown during this outburst were remarkably similar to those observed during the previous accretion event detected from the source in 2009. Coherent pulsations at the pulsar spin period were detected in the XMM-Newton and INTEGRAL data, at a frequency compatible with the value observed in 2009. Assuming that the source spun up during the 2015 outburst at the same rate observed during the previous outburst, we derive a conservative upper limit on the spin down rate during quiescence of 3.5E-15 Hz/s. Interpreting this value in terms of electromagnetic spin down yields an upper limit of 3.6E26 G/cm3^3 to the pulsar magnetic dipole (assuming a magnetic inclination angle of 30{\deg}). We also report on the detection of five type-I X-ray bursts (three in the XMM-Newton data, two in the INTEGRAL data), none of which indicated photospheric radius expansion.Comment: 10 pages, 7 figures, accepted for publication in A&

    Bridge damage identification under varying environmental and operational conditions combining Deep Learning and numerical simulations

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    This work proposes a novel supervised learning approach to identify damage in operating bridge structures. We propose a method to introduce the effect of environmental and operational conditions into the synthetic damage scenarios employed for training a Deep Neural Network, which is applicable to large-scale complex structures. We apply a clustering technique based on Gaussian Mixtures to effectively select Q representative measurements from a long-term monitoring dataset. We employ these measurements as the target response to solve various Finite Element Model Updating problems before generating different damage scenarios. The synthetic and experimental measurements feed two Deep Neural Networks that assess the structural health condition in terms of damage severity and location. We demonstrate the applicability of the proposed method with a real full-scale case study: the Infante Dom Henrique bridge in Porto. A comparative study reveals that neglecting different environmental and operational conditions during training detracts the damage identification task. By contrast, our method provides successful results during a synthetic validation

    Bayesian variable selection and survival modeling: assessing the Most important comorbidities that impact lung and colorectal cancer survival in Spain

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    ancer survival represents one of the main indicators of interest in cancer epidemiology. However, the survival of cancer patients can be affected by several factors, such as comorbidities, that may interact with the cancer biology. Moreover, it is interesting to understand how different cancer sites and tumour stages are affected by different comorbidities. Identifying the comorbidities that affect cancer survival is thus of interest as it can be used to identify factors driving the survival of cancer patients. This information can also be used to identify vulnerable groups of patients with comorbidities that may lead to worst prognosis of cancer. We address these questions and propose a principled selection and evaluation of the effect of comorbidities on the overall survival of cancer patients. In the first step, we apply a Bayesian variable selection method that can be used to identify the comorbidities that predict overall survival. In the second step, we build a general Bayesian survival model that accounts for time-varying effects. In the third step, we derive several posterior predictive measures to quantify the effect of individual comorbidities on the population overall survival. We present applications to data on lung and colorectal cancers from two Spanish population-based cancer registries. The proposed methodology is implemented with a combination of the R-packages mombf and rstan. We provide the code for reproducibility at https://github.com/migariane/BayesVarImpComorbiCancer

    An XMM-Newton and INTEGRAL view on the hard state of EXO 1745-248 during its 2015 outburst

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    CONTEXT - Transient low-mass X-ray binaries (LMXBs) often show outbursts lasting typically a few-weeks and characterized by a high X-ray luminosity (Lx‚Čą1036‚ąí1038L_{x} \approx 10^{36}-10^{38} erg/sec), while for most of the time they are found in X-ray quiescence (LX‚Čą1031‚ąí1033L_X\approx10^{31} -10^{33} erg/sec). EXO 1745-248 is one of them. AIMS - The broad-band coverage, and the sensitivity of instrument on board of {\xmm} and {\igr}, offers the opportunity to characterize the hard X-ray spectrum during {\exo} outburst. METHODS - In this paper we report on quasi-simultaneous {\xmm} and {\igr} observations of the X-ray transient {\exo} located in the globular cluster Terzan 5, performed ten days after the beginning of the outburst (on 2015 March 16th) shown by the source between March and June 2015. The source was caught in a hard state, emitting a 0.8-100 keV luminosity of ‚ČÉ1037\simeq10^{37}~{\lumcgs}. RESULTS - The spectral continuum was dominated by thermal Comptonization of seed photons with temperature kTin‚ČÉ1.3kT_{in}\simeq1.3 keV, by a cloud with moderate optical depth ŌĄ‚ČÉ2\tau\simeq2 and electron temperature kTe‚ČÉ40kT_e\simeq 40 keV. A weaker soft thermal component at temperature kTth‚ČÉ0.6kT_{th}\simeq0.6--0.7 keV and compatible with a fraction of the neutron star radius was also detected. A rich emission line spectrum was observed by the EPIC-pn on-board {\xmm}; features at energies compatible with K-őĪ\alpha transitions of ionized sulfur, argon, calcium and iron were detected, with a broadness compatible with either thermal Compton broadening or Doppler broadening in the inner parts of an accretion disk truncated at 20¬Ī620\pm6 gravitational radii from the neutron star. Strikingly, at least one narrow emission line ascribed to neutral or mildly ionized iron is needed to model the prominent emission complex detected between 5.5 and 7.5 keV. (Abridged)Comment: 14 pages, 6 figure, 2 tables. Accepted for publication on A&A (21/03/2017

    Multifuncionalidad y Sistemas Agroalimentarios locales: prioridades de investigaci√≥n e innovaci√≥n en medio ambiente, territorio y desarrollo rural en el sector espa√Īol del aceite de oliva

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    Los sistemas agroalimentarios locales (SIAL) de aceite de oliva en Espa√Īa son un buen ejemplo del comportamiento multifuncional y de su contribuci√≥n potencial a la gobernanza territorial. Se detectan cambios significativos en la geograf√≠a del olivar espa√Īol, derivados, por una parte, de la expansi√≥n de nuevas superficies de olivar en regad√≠o de cultivo intensivo y superintensivo y, por otra, de la creciente marginalizaci√≥n a la que se ve abocado el olivar espa√Īol de media y alta pendiente. Por otra parte, el olivar espa√Īol produce un fuerte grado de externalidades ambientales negativas, como la erosi√≥n o la contaminaci√≥n difusa de suelos y acu√≠feros. El principal objetivo del trabajo es detectar las relaciones que se establecen entre la definici√≥n de los principales problemas que ata√Īen a los SIAL de aceite de oliva en Espa√Īa y las prioridades de investigaci√≥n e innovaci√≥n en materia de territorio y medio ambiente, desde una √≥ptica multidisciplinar que integre enfoques procedentes de las Ciencias Sociales y de las Ciencias Agron√≥micas y Ambientales. El marco te√≥rico procede de las teor√≠as sobre la multifuncionalidad de los espacios rurales y sobre los SIAL. La metodolog√≠a utiliza informaci√≥n cualitativa y cuantitativa procedente de dos fuentes primarias: i) un grupo de discusi√≥n integrado en un panel presencial de expertos sobre innovaci√≥n en olivicultura, sostenibilidad y aprovechamiento de residuos; ii) un an√°lisis Delphi dirigido a un conjunto amplio de expertos sobre medio ambiente, territorio y desarrollo rural sostenible en el sector ole√≠cola. En cuanto al an√°lisis de resultados, el grupo de discusi√≥n ha tenido como misi√≥n categorizar las grandes tipolog√≠as de olivicultura en Espa√Īa y sintetizar sus respectivos problemas ambientales y territoriales. Estos resultados sirven como marco de referencia del an√°lisis Delphi, que tiene un doble objetivo: por una parte, el an√°lisis de los principales problemas ambientales y territoriales de los SIAL ole√≠colas en Espa√Īa; por otra, el estudio de las prioridades en materia de programas y de grupos de l√≠neas de investigaci√≥n sobre la materia, as√≠ como las relaciones entre dichas l√≠neas de investigaci√≥n y los problemas a los que se enfrentan los SIAL ole√≠colas.prioridades de investigaci√≥n e innovaci√≥n, medio ambiente y territorio, an√°lisis Delphi., Agribusiness, Agricultural and Food Policy, Community/Rural/Urban Development, Food Consumption/Nutrition/Food Safety, Labor and Human Capital,

    Resolving galaxies in time and space: II: Uncertainties in the spectral synthesis of datacubes

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    In a companion paper we have presented many products derived from the application of the spectral synthesis code STARLIGHT to datacubes from the CALIFA survey, including 2D maps of stellar population properties and 1D averages in the temporal and spatial dimensions. Here we evaluate the uncertainties in these products. Uncertainties due to noise and spectral shape calibration errors and to the synthesis method are investigated by means of a suite of simulations based on 1638 CALIFA spectra for NGC 2916, with perturbations amplitudes gauged in terms of the expected errors. A separate study was conducted to assess uncertainties related to the choice of evolutionary synthesis models. We compare results obtained with the Bruzual & Charlot models, a preliminary update of them, and a combination of spectra derived from the Granada and MILES models. About 100k CALIFA spectra are used in this comparison. Noise and shape-related errors at the level expected for CALIFA propagate to 0.10-0.15 dex uncertainties in stellar masses, mean ages and metallicities. Uncertainties in A_V increase from 0.06 mag in the case of random noise to 0.16 mag for shape errors. Higher order products such as SFHs are more uncertain, but still relatively stable. Due to the large number statistics of datacubes, spatial averaging reduces uncertainties while preserving information on the history and structure of stellar populations. Radial profiles of global properties, as well as SFHs averaged over different regions are much more stable than for individual spaxels. Uncertainties related to the choice of base models are larger than those associated with data and method. Differences in mean age, mass and metallicity are ~ 0.15 to 0.25 dex, and 0.1 mag in A_V. Spectral residuals are ~ 1% on average, but with systematic features of up to 4%. The origin of these features is discussed. (Abridged)Comment: A&A, accepte
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