University of Lorraine

About: University of Lorraine is a education organization based out in Nancy, France. It is known for research contribution in the topics: Population & Nonlinear system. The organization has 11942 authors who have published 25010 publications receiving 425227 citations. The organization is also known as: Lorraine University.

Molecular reactions at aqueous interfaces

Abstract: This Review aims to critically analyse the emerging field of chemical reactivity at aqueous interfaces. The subject has evolved rapidly since the discovery of the so-called ‘on-water catalysis’, alluding to the dramatic acceleration of reactions at the surface of water or at its interface with hydrophobic media. We review critical experimental studies in the fields of atmospheric and synthetic organic chemistry, as well as related research exploring the origins of life, to showcase the importance of this phenomenon. The physico-chemical aspects of these processes, such as the structure, dynamics and thermodynamics of adsorption and solvation processes at aqueous interfaces, are also discussed. We also present the basic theories intended to explain interface catalysis, followed by the results of advanced ab initio molecular-dynamics simulations. Although some topics addressed here have already been the focus of previous reviews, we aim at highlighting their interconnection across diverse disciplines, providing a common perspective that would help us to identify the most fundamental issues still incompletely understood in this fast-moving field. Enhanced chemical reactivity on-water has major implications in many fields, ranging from atmospheric to prebiotic chemistry. This Review analyses recent experimental and theoretical studies in this fast-moving research area and brings together some key findings across diverse fields.

Sound Event Detection in the DCASE 2017 Challenge

Abstract: Each edition of the challenge on Detection and Classification of Acoustic Scenes and Events DCASE contained several tasks involving sound event detection in different setups. DCASE 2017 presented participants with three such tasks, each having specific datasets and detection requirements: Task 2, in which target sound events were very rare in both training and testing data, Task 3 having overlapping events annotated in real-life audio, and Task 4, in which only weakly labeled data were available for training. In this paper, we present three tasks, including the datasets and baseline systems, and analyze the challenge entries for each task. We observe the popularity of methods using deep neural networks, and the still widely used mel frequency-based representations, with only few approaches standing out as radically different. Analysis of the systems behavior reveals that task-specific optimization has a big role in producing good performance; however, often this optimization closely follows the ranking metric, and its maximization/minimization does not result in universally good performance. We also introduce the calculation of confidence intervals based on a jackknife resampling procedure to perform statistical analysis of the challenge results. The analysis indicates that while the 95% confidence intervals for many systems overlap, there are significant differences in performance between the top systems and the baseline for all tasks.

Loss in body weight is an independent prognostic factor for mortality in chronic heart failure: insights from the GISSI‐HF and Val‐HeFT trials

Abstract: Aims Uncertainties remain on the biological and prognostic significance and therapeutic implications of loss in body weight (W-LOSS) in chronic heart failure (HF) patients. We assessed whether W-LOSS added additional prognostic value to classical clinical risk factors in two separate and large cohorts of patients with chronic HF. The factors associated with W-LOSS were studied. Methods and results W-LOSS and estimated plasma volume changes were measured serially in the GISSI-HF (n = 6820) and Val-HeFT trials (n = 4892). In both studies, experiencing at least one episode of ≥5% W-LOSS during the first year of follow-up was considered a sign of wasting. In GISSI-HF, self-reported unintentional W-LOSS ≥2 kg between two consecutive clinical visits within 1 year was also considered a sign of wasting. W-LOSS occurred in 16.4% and 15.7% of the patients enrolled in GISSI-HF and Val-HeFT, respectively (unintentional ≥2 kg W-LOSS occurred in 18.9% in GISSI-HF). In multivariable analyses adjusting for a number of baseline covariates as well as for plasma volume changes, W-LOSS was found to be independently associated with mortality and adverse cardiovascular and non-cardiovascular outcomes, with a significant net reclassification improvement (cfNRI) and an increase in integrated discrimination improvement (IDI). W-LOSS was independently associated with several features representing the severity of HF, including baseline NT-proBNP and high sensitivity C-reactive protein (hsCRP) in Val-HeFT. Conclusions W-LOSS was a frequent finding in the GISSI-HF and Val-HeFT trials, associated with multiple patient features, and added additional prognostic information beyond clinical variables of HF severity, including estimated plasma volume changes.