A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation

Aircraft engine manufacturers collect large amount of engine related data during flights. These data are used to detect anomalies in the engines in order to help companies optimize their maintenance costs. This article introduces and studies a generic methodology that allows one to build automatic early signs of anomaly detection in a way that is understandable by human operators who make the final maintenance decision. The main idea of the method is to generate a very large number of binary indicators based on parametric anomaly scores designed by experts, complemented by simple aggregations of those scores. The best indicators are selected via a classical forward scheme, leading to a much reduced number of indicators that are tuned to a data set. We illustrate the interest of the method on simulated data which contain realistic early signs of anomalies.Comment: Proceedings of the 14th Industrial Conference, ICDM 2014, St. Petersburg : Russian Federation (2014

Crowd Learning with Candidate Labeling: an EM-based Solution

Crowdsourcing is widely used nowadays in machine learning for data labeling. Although in the traditional case annotators are asked to provide a single label for each instance, novel approaches allow annotators, in case of doubt, to choose a subset of labels as a way to extract more information from them. In both the traditional and these novel approaches, the reliability of the labelers can be modeled based on the collections of labels that they provide. In this paper, we propose an Expectation-Maximization-based method for crowdsourced data with candidate sets. Iteratively the likelihood of the parameters that model the reliability of the labelers is maximized, while the ground truth is estimated. The experimental results suggest that the proposed method performs better than the baseline aggregation schemes in terms of estimated accuracy.BES-2016-078095 SVP-2014-068574 IT609-13 TIN2016-78365-

Growth portfolios buffer climate-linked environmental change in marine systems

Large-scale, climate-induced synchrony in the productivity of fish populations is becoming more pronounced in the world's oceans. As synchrony increases, a population's “portfolio” of responses can be diminished, in turn reducing its resilience to strong perturbation. Here we argue that the costs and benefits of trait synchronization, such as the expression of growth rate, are context dependent. Contrary to prevailing views, synchrony among individuals could actually be beneficial for populations if growth synchrony increases during favorable conditions, and then declines under poor conditions when a broader portfolio of responses could be useful. Importantly, growth synchrony among individuals within populations has seldom been measured, despite well-documented evidence of synchrony across populations. Here, we used century-scale time series of annual otolith growth to test for changes in growth synchronization among individuals within multiple populations of a marine keystone species (Atlantic cod, Gadus morhua). On the basis of 74,662 annual growth increments recorded in 13,749 otoliths, we detected a rising conformity in long-term growth rates within five northeast Atlantic cod populations in response to both favorable growth conditions and a large-scale, multidecadal mode of climate variability similar to the East Atlantic Pattern. The within-population synchrony was distinct from the across-population synchrony commonly reported for large-scale environmental drivers. Climate-linked, among-individual growth synchrony was also identified in other Northeast Atlantic pelagic, deep-sea and bivalve species. We hypothesize that growth synchrony in good years and growth asynchrony in poorer years reflects adaptive trait optimization and bet hedging, respectively, that could confer an unexpected, but pervasive and stabilizing, impact on marine population productivity in response to large-scale environmental change.publishedVersio

International Bottom Trawl Survey Working Group (IBTSWG). ICES Scientific Reports, 04:65

The International Bottom Trawl Survey Working Group (IBTSWG) coordinates fishery-independent bottom trawl surveys in the ICES area in the Northeast Atlantic and the North Sea. These long-term monitoring surveys provide data for stock assessments and facilitate examina-tion of changes in fish distribution and relative abundance. The group also promotes the stand-ardization of fishing gears and methods as well as survey coordination. This report summarizes the national contributions in 2021–2022 and plans for the 2022–2023 surveys coordinated by IBTSWG

Characterization of the SNAG and SLUG Domains of Snail2 in the Repression of E-Cadherin and EMT Induction: Modulation by Serine 4 Phosphorylation

Snail1 and Snail2, two highly related members of the Snail superfamily, are direct transcriptional repressors of E-cadherin and EMT inducers. Previous comparative gene profiling analyses have revealed important differences in the gene expression pattern regulated by Snail1 and Snail2, indicating functional differences between both factors. The molecular mechanism of Snail1-mediated repression has been elucidated to some extent, but very little is presently known on the repression mediated by Snail2. In the present work, we report on the characterization of Snail2 repression of E-cadherin and its regulation by phosphorylation. Both the N-terminal SNAG and the central SLUG domains of Snail2 are required for efficient repression of the E-cadherin promoter. The co-repressor NCoR interacts with Snail2 through the SNAG domain, while CtBP1 is recruited through the SLUG domain. Interestingly, the SNAG domain is absolutely required for EMT induction while the SLUG domain plays a negative modulation of Snail2 mediated EMT. Additionally, we identify here novel in vivo phosphorylation sites at serine 4 and serine 88 of Snail2 and demonstrate the functional implication of serine 4 in the regulation of Snail2-mediated repressor activity of E-cadherin and in Snail2 induction of EMT

The Effects of Ash and Black Carbon (Biochar) on Germination of Different Tree Species

Forest fires generate large amounts of ash and biochar, or black carbon (BC), that cover the soil surface, interacting with the soil’s constituents and its seedbank. This study concerns reproductive ecology assessments supported by molecular characterisation to improve our understanding of the effects of fire and fire residues on the germination behaviour of 12 arboreal species with a wide geographic distribution. For this purpose, we analysed the effects of three ash and one BC concentration on the germination of Acacia dealbata Link, A. longifolia (Andrews) Willd., A. mearnsii De Wild., A. melanoxylon R. Br., Pinus nigra Arnold, P. pinaster Aiton, P. radiata D. Don, P. sylvestris L., Quercus ilex L., Q. pyrenaica Willd., Q. robur L., and Q. rubra L. Each tree species was exposed to ash and BC created from its foliage or twigs (except for Q. rubra, which was exposed to ash and BC of Ulex europaeus L.). We monitored germination percentage, the T50 parameter, and tracked the development of germination over time (up to 1 yr). The BC of A. dealbata, P. pinaster, and Q. robur was analysed by pyrolysis-gas chromatography-mass spectrometry (PY-GC-MS) to assess the molecular composition. In six species, ash inhibited the germination, while in another five species, germination was not affected by ash or by BC. In Q. rubra, ash and BC stimulated its germination. This stimulating effect of the BC on Q. rubra is likely to be related to the chemical composition of the ash and BC obtained from Ulex feedstock. The BC of U. europaeus has a very different molecular composition than the other BC samples analysed, which, together with other factors, probably allowed for its germination stimulating effects.This study was carried out within the Project 10MDS200007PR, financed by the Xunta de Galicia; the Project AGL2013-48189-C2-2-R, financed by the Ministerio de Economía y Competitividad, Spain; and FEDERS