715 research outputs found

    Joint Bayesian Estimation of Quasar Continua and the Lyman-Alpha Forest Flux Probability Distribution Function

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    We present a new Bayesian algorithm making use of Markov Chain Monte Carlo sampling that allows us to simultaneously estimate the unknown continuum level of each quasar in an ensemble of high-resolution spectra, as well as their common probability distribution function (PDF) for the transmitted Lyα\alpha forest flux. This fully automated PDF regulated continuum fitting method models the unknown quasar continuum with a linear Principal Component Analysis (PCA) basis, with the PCA coefficients treated as nuisance parameters. The method allows one to estimate parameters governing the thermal state of the intergalactic medium (IGM), such as the slope of the temperature-density relation γ−1\gamma-1, while marginalizing out continuum uncertainties in a fully Bayesian way. Using realistic mock quasar spectra created from a simplified semi-numerical model of the IGM, we show that this method recovers the underlying quasar continua to a precision of ≃7%\simeq7\% and ≃10%\simeq10\% at z=3z=3 and z=5z=5, respectively. Given the number of principal component spectra, this is comparable to the underlying accuracy of the PCA model itself. Most importantly, we show that we can achieve a nearly unbiased estimate of the slope γ−1\gamma-1 of the IGM temperature-density relation with a precision of ±8.6%\pm8.6\% at z=3z=3, ±6.1%\pm6.1\% at z=5z=5, for an ensemble of ten mock high-resolution quasar spectra. Applying this method to real quasar spectra and comparing to a more realistic IGM model from hydrodynamical simulations would enable precise measurements of the thermal and cosmological parameters governing the IGM, albeit with somewhat larger uncertainties given the increased flexibility of the model.Comment: 21 pages (+ Appendix), accepted at Ap

    Identification of TRIB1 as a novel regulator of the secretory pathway

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    Editorial: Genetics, genomics and -omics of thermophiles

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    Presentación de los contenidos de la revista.Facultad de Ciencias ExactasCentro de Investigación y Desarrollo en Fermentaciones Industriale

    Reduced Real-life Affective Well-being and Amygdala Habituation in Unmedicated Community Individuals at Risk for Depression and Anxiety

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    Background: Early identification of risk for depression and anxiety disorders is important for prevention, but real-life affective well-being and its biological underpinnings in the population remain understudied. Here, we combined methods from epidemiology, psychology, ecological momentary assessment, and functional magnetic resonance imaging to study real-life and neural affective functions in individuals with subclinical anxiety and depression from a population-based cohort of young adults. Methods: We examined psychological measures, real-life affective valence, functional magnetic resonance imaging amygdala habituation to negative affective stimuli, and the relevance of neural readouts for daily-life affective function in 132 non–help-seeking community individuals. We compared psychological and ecological momentary assessment measures of 61 unmedicated individuals at clinical risk for depression and anxiety (operationalized as subthreshold depression and anxiety symptoms or a former mood or anxiety disorder) with those of 48 nonrisk individuals and 23 persons with a mood or anxiety disorder. We studied risk-associated functional magnetic resonance imaging signals in subsamples with balanced sociodemographic and image quality parameters (26 nonrisk, 26 at-risk persons). Results: Compared with nonrisk persons, at-risk individuals showed significantly decreased real-life affective valence (p = .038), reduced amygdala habituation (familywise error–corrected p = .024, region of interest corrected), and an intermediate psychological risk profile. Amygdala habituation predicted real-life affective valence in control subjects but not in participants at risk (familywise error–corrected p = .005, region of interest corrected). Conclusions: Our data suggest real-life and neural markers for affective alterations in unmedicated community individuals at risk for depression and anxiety and highlight the significance of amygdala habituation measures for the momentary affective experience in real-world environments

    Charge-state-enhanced ion sputtering of metallic gold nanoislands

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    Experimental results on the charge-state-dependent sputtering of metallic gold nanoislands are presented. Irradiations with slow highly charged ions of metallic targets were previously considered to show no charge state dependent effects on ion-induced material modification, since these materials possess enough free electrons to dissipate the deposited potential energy before electron-phonon coupling can set in. By reducing the size of the target material down to the nanometer regime and thus enabling a geometric energy confinement, a possibility is demonstrated to erode metallic surfaces by charge state related effects in contrast to regular kinetic sputtering

    K-LITE: Learning Transferable Visual Models with External Knowledge

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    Recent state-of-the-art computer vision systems are trained from natural language supervision, ranging from simple object category names to descriptive captions. This free form of supervision ensures high generality and usability of the learned visual models, based on extensive heuristics on data collection to cover as many visual concepts as possible. Alternatively, learning with external knowledge about images is a promising way which leverages a much more structured source of supervision. In this paper, we propose K-LITE (Knowledge-augmented Language-Image Training and Evaluation), a simple strategy to leverage external knowledge to build transferable visual systems: In training, it enriches entities in natural language with WordNet and Wiktionary knowledge, leading to an efficient and scalable approach to learning image representations that can understand both visual concepts and their knowledge; In evaluation, the natural language is also augmented with external knowledge and then used to reference learned visual concepts (or describe new ones) to enable zero-shot and few-shot transfer of the pre-trained models. We study the performance of K-LITE on two important computer vision problems, image classification and object detection, benchmarking on 20 and 13 different existing datasets, respectively. The proposed knowledge-augmented models show significant improvement in transfer learning performance over existing methods.Comment: Preprint. The first three authors contribute equall

    Haemodynamically significant plaque formation and regional endothelial dysfunction in cholesterol-fed ApoE

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    A B S T R A C T Flow-mediated vasodilation is suggested as one of the mechanisms involved in arterial expansive remodelling, which is thought to be a defence mechanism in atherogenesis. In the present study, we tested the hypothesis that lumen obstructive plaque formation is associated with failure of NO (nitric oxide)-dependent vasodilation in conduit vessels. Cardiac function and aortic root flow velocities were assessed using high-resolution echocardiography and two-dimensional-guided pulsed Doppler in ApoE −/− (apolipoprotein E-deficient) mice fed a standard or high-cholesterol diet. Endothelial function in the proximal and mid-descending aortic regions was studied using a myograph technique. Flow velocity at the aortic root of cholesterol-fed ApoE −/− mice was significantly increased as a result of lumen narrowing, detected via histological analysis. NO-dependent vasodilatory responses were selectively impaired in the atherosclerosis-prone vascular regions in cholesterol-fed ApoE −/− mice. In conclusion, consumption of a high-cholesterol diet results in lumen obstructive plaque formation in ApoE −/− mice, which significantly alters aortic root haemodynamics. This phenomenon is associated with impaired NO-dependent vasodilation in vessel segments known to be prone to atherosclerosis

    Lung transplantation for acute respiratory distress syndrome:A multicenter experience

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    Acute respiratory distress syndrome (ARDS) is a rapidly progressive lung disease with a high mortality rate. Although lung transplantation (LTx) is a well-established treatment for a variety of chronic pulmonary diseases, LTx for acute lung failure (due to ARDS) remains controversial. We reviewed posttransplant outcome of ARDS patients from three high-volume European transplant centers. Demographics and clinical data were collected and analyzed. Viral infection was the main reason for ARDS (n = 7/13, 53.8%). All patients were admitted to ICU and required mechanical ventilation, 11/13 were supported with ECMO at the time of listing. They were granted a median LAS of 76 (IQR 50-85) and waited for a median of 3 days (IQR 1.5-14). Postoperatively, median length of mechanical ventilation was 33 days (IQR 17-52.5), median length of ICU and hospital stay were 39 days (IQR 19.5-58.5) and 54 days (IQR 43.5-127). Prolongation of peripheral postoperative ECMO was required in 7/13 (53.8%) patients with a median duration of 2 days (IQR 2-7). 30-day mortality was 7.7%, 1 and 5-year survival rates were calculated as 71.6% and 54.2%, respectively. Given the lack of alternative treatment options, the herein presented results support the concept of offering live-saving LTx to carefully selected ARDS patients
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