352 research outputs found

    Solid confirmation of the broad DIB around 864.8 nm using stacked Gaia–RVS spectra

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    Context. Studies of the correlation between different diffuse interstellar bands (DIBs) are important for exploring their origins. However, the Gaia–RVS spectral window between 846 and 870 nm contains few DIBs, the strong DIB at 862 nm being the only convincingly confirmed one. / Aims. Here we attempt to confirm the existence of a broad DIB around 864.8 nm and estimate its characteristics using the stacked Gaia–RVS spectra of a large number of stars. We study the correlations between the two DIBs at 862 nm (λ862) and 864.8 nm (λ864.8), as well as the interstellar extinction. / Methods. We obtained spectra of the interstellar medium (ISM) absorption by subtracting the stellar components using templates constructed from real spectra at high Galactic latitudes with low extinctions. We then stacked the ISM spectra in Galactic coordinates (ℓ,  b) – pixelized by the HEALPix scheme – to measure the DIBs. The stacked spectrum is modeled by the profiles of the two DIBs, Gaussian for λ862 and Lorentzian for λ864.8, and a linear continuum. We report the fitted central depth (CD), central wavelength, equivalent width (EW), and their uncertainties for the two DIBs. / Results. We obtain 8458 stacked spectra in total, of which 1103 (13%) have reliable fitting results after applying numerous conservative filters. This work is the first of its kind to fit and measure λ862 and λ864.8 simultaneously in cool-star spectra. Based on these measurements, we find that the EWs and CDs of λ862 and λ864.8 are well correlated with each other, with Pearson coefficients (rp) of 0.78 and 0.87, respectively. The full width at half maximum (FWHM) of λ864.8 is estimated as 1.62 ± 0.33 nm which compares to 0.55 ± 0.06 nm for λ862. We also measure the vacuum rest-frame wavelength of λ864.8 to be λ0 = 864.53 ± 0.14 nm, smaller than previous estimates. / Conclusions. We find solid confirmation of the existence of the DIB around 864.8 nm based on an exploration of its correlation with λ862 and estimation of its FWHM. The DIB λ864.8 is very broad and shallow. That at λ862 correlates better with E(BP − RP) than λ864.8. The profiles of the two DIBs could strongly overlap with each other, which contributes to the skew of the λ862 profile

    Determining the effect of drying time on phosphorus solubilization from three agricultural soils under climate change scenarios

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    Climate projections for the future indicate that the United Kingdom will experience hotter, drier summers and warmer, wetter winters, bringing longer dry periods followed by rewetting. This will result in changes in phosphorus (P) mobilization patterns that will influence the transfer of P from land to water. We tested the hypothesis that changes in the future patterns of drying–rewetting will affect the amount of soluble reactive phosphorus (SRP) solubilized from soil. Estimations of dry period characteristics (duration and temperature) under current and predicted climate were determined using data from the UK Climate Projections (UKCP09) Weather Generator tool. Three soils (sieved 25°C are predicted in some places and dry periods of 30 to 90 d extremes are predicted. Combining the frequency of projected dry periods with the SRP concentration in leachate suggests that this may result overall in increased mobilization of P; however, critical breakpoints of 6.9 to 14.5 d dry occur wherein up to 28% more SRP can be solubilized following a rapid rewetting event. The precise cause of this increase could not be identified and warrants further investigation as the process is not currently included in P transfer models

    <i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

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    Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∌3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∌0.3 mas should be added to the parallax uncertainties. For the subset of ∌94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∌10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∌0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

    Skin tribology: Science friction?

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    The application of tribological knowledge is not just restricted to optimizing mechanical and chemical engineering problems. In fact, effective solutions to friction and wear related questions can be found in our everyday life. An important part is related to skin tribology, as the human skin is frequently one of the interacting surfaces in relative motion. People seem to solve these problems related to skin friction based upon a trial-and-error strategy and based upon on our sense for touch. The question of course rises whether or not a trained tribologist would make different choices based upon a science based strategy? In other words: Is skin friction part of the larger knowledge base that has been generated during the last decades by tribology research groups and which could be referred to as Science Friction? This paper discusses the specific nature of tribological systems that include the human skin and argues that the living nature of skin limits the use of conventional methods. Skin tribology requires in vivo, subject and anatomical location specific test methods. Current predictive friction models can only partially be applied to predict in vivo skin friction. The reason for this is found in limited understanding of the contact mechanics at the asperity level of product-skin interactions. A recently developed model gives the building blocks for enhanced understanding of friction at the micro scale. Only largely simplified power law based equations are currently available as general engineering tools. Finally, the need for friction control is illustrated by elaborating on the role of skin friction on discomfort and comfort. Surface texturing and polymer brush coatings are promising directions as they provide way and means to tailor friction in sliding contacts without the need of major changes to the produc

    An Introduction to EEG Source Analysis with an illustration of a study on Error-Related Potentials

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    International audienceOver the last twenty years blind source separation (BSS) has become a fundamental signal processing tool in the study of human electroencephalography (EEG), other biological data, as well as in many other signal processing domains such as speech, images, geophysics and wireless communication (Comon and Jutten, 2010). Without relying on head modeling BSS aims at estimating both the waveform and the scalp spatial pattern of the intracranial dipolar current responsible of the observed EEG, increasing the sensitivity and specificity of the signal received from the electrodes on the scalp. This chapter begins with a short review of brain volume conduction theory, demonstrating that BSS modeling is grounded on current physiological knowledge. We then illustrate a general BSS scheme requiring the estimation of second-order statistics (SOS) only. A simple and efficient implementation based on the approximate joint diagonalization of covariance matrices (AJDC) is described. The method operates in the same way in the time or frequency domain (or both at the same time) and is capable of modeling explicitly physiological and experimental source of variations with remarkable flexibility. Finally, we provide a specific example illustrating the analysis of a new experimental study on error-related potentials

    A Purity Monitoring System for the H1 Liquid Argon Calorimeter

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    The ionization probes used for monitoring the liquid argon purity in the H1 calorimeter are described and results of their operation in tests at CERN and during the period 1992 to the end of 1998 at HERA are given. The high sensitivity of the charge measurements leads to refined charge collection models, and to the observation of a variation of the ionization yield of our electron sources with temperature.Comment: 26 pages, 14 figure

    Liquid Biopsy in Non-Small Cell Lung Cancer (NSCLC)

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    Lung cancer is the leading cause of cancer deaths worldwide. To date, the gold standard for the molecular analysis of a patient affected by NSCLC is the tissue biopsy. The discovery of activating mutations and rearrangements in specific genes has revolutionized the therapeutic approaches of lung cancer over the last years. For this reason, a strict \u201cmolecular follow-up\u201d is mandatory to evaluate patient\u2019s disease evolution. Indeed, liquid biopsy has raised as the \u201cnew ambrosia of researchers\u201d as it could help clinicians to identify both prognostic and predictive biomarkers in a more accessible way. Liquid biopsy analysis can be used in different moments starting from diagnosis to relapse, earning multiple clinical meanings, offering thus a noninvasive but valid method to detect actionable mutations. Although the implementation of both exosomes and CTCs in clinical practice is several steps back, new advances and discoveries make them, together with the ctDNA, a very promising tool. In the following chapter we will discuss the recent advances of liquid biopsy in NSCLC highlighting the possible clinical utility of CTCs, ctDNA and exosomes
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