3,331 research outputs found
Annual sea level variability of the coastal ocean: The Baltic Sea-North Sea transition zone
The annual cycle is a major contribution to the non-tidal variability in sea level. Its characteristics can vary substantially even at a regional scale, particularly in an area of high variability such as the coastal ocean. This study uses previously validated coastal altimetry solutions (from ALES dataset) and the reference ESA Sea Level Climate Change Initiative dataset to improve the understanding of the annual cycle during the Envisat years (2002-2010) in the North Sea - Baltic Sea transition area. This area of study is chosen because of the complex coastal morphology and the availability of in-situ measurements.
To our knowledge, this is the first time that the improvements brought by coastal satellite altimetry to the description of the annual variability of the sea level have been evaluated and discussed. The findings are interpreted with the help of a local climatology and wind stress from a reanalysis model.
The coastal amplitude of the annual cycle estimated from ALES altimetry data is in better agreement with estimations derived from in-situ data than the one from the reference dataset. Wind stress is found to be the main driver of annual cycle variability throughout the domain, while different steric contributions are responsible for the differences within and among the sub-basins.
We conclude that the ALES coastal altimetry product is a reliable dataset to study the annual cycle of the sea level at a regional scale and the strategy described in this research can be applied to other areas of the coastal ocean where the coverage from the tide gauges is not sufficient
Host-microbe interaction in the gastrointestinal tract
The gastrointestinal tract is a highly complex organ in which multiple dynamic physiological processes are tightly coordinated while interacting with a dense and extremely diverse microbial population. From establishment in early life, through to host-microbe symbiosis in adulthood, the gut microbiota plays a vital role in our development and health. The effect of the microbiota on gut development and physiology is highlighted by anatomical and functional changes in germ-free mice, affecting the gut epithelium, immune system, and enteric nervous system. Microbial colonisation promotes competent innate and acquired mucosal immune systems, epithelial renewal, barrier integrity, and mucosal vascularisation and innervation. Interacting or shared signalling pathways across different physiological systems of the gut could explain how all these changes are coordinated during postnatal colonisation, or after the introduction of microbiota into germ-free models. The application of cell-based in vitro experimental systems and mathematical modelling can shed light on the molecular and signalling pathways which regulate the development and maintenance of homeostasis in the gut and beyond. This article is protected by copyright. All rights reserved
Response to comments on "magnetic resonance spectroscopy identifies neural progenitor cells in the live human brain"
We reported on a neural progenitor cell biomarker, a lipid-based metabolite enriched in these cells, which we detected using spectroscopy both in vitro and in vivo, and singular value decomposition–based signal processing. The study provided an outline of our computational methodology. Herein, we report more extensively on the method of spectrum analysis used, demonstrating the specificity of our findings
A comparative study of two formal semantics of the SIGNAL language
International audienceSIGNAL is a part of the synchronous languages family, which are broadly used in the design of safety-critical real-time systems such as avionics, space systems, and nuclear power plants. There exist several semantics for SIGNAL, such as denotational semantics based on traces (called trace semantics), denotational semantics based on tags (called tagged model semantics), operational semantics presented by structural style through an inductive definition of the set of possible transitions, operational semantics defined by synchronous transition systems (STS), etc. However, there is little research about the equivalence between these semantics.In this work, we would like to prove the equivalence between the trace semantics and the tagged model semantics, to get a determined and precise semantics of the SIGNAL language. These two semantics have several different definitions respectively, we select appropriate ones and mechanize them in the Coq platform, the Coq expressions of the abstract syntax of SIGNAL and the two semantics domains, i.e., the trace model and the tagged model, are also given. The distance between these two semantics discourages a direct proof of equivalence. Instead, we transformthem to an intermediate model, which mixes the features of both the trace semantics and the tagged model semantics. Finally, we get a determined and precise semantics of SIGNAL
Model-based fault detection and diagnosis : cases study for vibration monitoring
A signal processing approach is presented for detection and diagnosis of
fatigues or failures in vibrating mechanical systems subject to natural
excitation . Detection and diagnosis is performed while the system being at
work, so that the excitation is usually not observed and may involve
turbulent phenomena . This is a short report of a 10 years project which
involved more than 2 persons per year in mean . The method is illustrated
on the following case studies : offshore structures, and rotating machinery.On présente une approche de traitement du signal pour la détection et le
diagnostic des fatigues ou usures dans des systèmes mĂ©caniques soumis Ă
une excitation naturelle ou ambiante . La détection et le diagnostic sont
réalisés sur le système en fonctionnement habituel, et donc en général
avec une excitation non mesurée et présentant des phénomènes de turbulence . Cet article est un bref rapport sur un projet de recherche
d'environ 10 ans qui a mobilisé plus de 2 personnes par an en moyenne .
La méthode est illustrée sur les deux cas suivants : structures offshore et
turbo-alternateurs (') .
(') Ce travail a été soutenu pendant 7 ans par 4 contrats avec IFREMER
et pendant 4 ans par 2 contrats avec EDF
Fitting in a complex chi^2 landscape using an optimized hypersurface sampling
Fitting a data set with a parametrized model can be seen geometrically as
finding the global minimum of the chi^2 hypersurface, depending on a set of
parameters {P_i}. This is usually done using the Levenberg-Marquardt algorithm.
The main drawback of this algorithm is that despite of its fast convergence, it
can get stuck if the parameters are not initialized close to the final
solution. We propose a modification of the Metropolis algorithm introducing a
parameter step tuning that optimizes the sampling of parameter space. The
ability of the parameter tuning algorithm together with simulated annealing to
find the global chi^2 hypersurface minimum, jumping across chi^2{P_i} barriers
when necessary, is demonstrated with synthetic functions and with real data
Context-Aided Variable Elimination for Requirement Engineering
Deriving system-level specifications from component specifications usually
involves the elimination of variables that are not part of the interface of the
top-level system. This paper presents algorithms for eliminating variables from
formulas by computing refinements or relaxations of these formulas in a
context. We discuss a connection between this problem and optimization and give
efficient algorithms to compute refinements and relaxations of linear
inequality constraints
An electromagnetic simulator for sentinel-3 sar altimeter waveforms over land part ii: forests
Forests play a crucial role in the climate change mitigation by acting as sinks for carbon and, consequently, reducing the CO2 concentration in the atmosphere and slowing global warming. For this reason, above ground biomass (AGB) estimation is essential for effectively monitoring forest health around the globe. Although remote sensing–based forest AGB quantification can be pursued in different ways, in this work we discuss a new technique for vegetation observation through the use of altimetry data that has been introduced by the ESA-funded ALtimetry for BIOMass (ALBIOM) project. ALBIOM investigates the possibility of retrieving forest biomass through Copernicus Sentinel-3 Synthetic Aperture Radar Altimeter (SRAL) measurements at Ku- and C-bands in low- and high-resolution mode. To reach this goal, a simulator able to reproduce the altimeter acquisition system and the scattering phenomena that occur in the interaction of the radar altimeter pulse with vegetated surfaces has been developed. The Tor Vergata Vegetation Scattering Model (TOVSM) developed at Tor Vergata University has been exploited to simulate the contribution from the vegetation volume via the modelling of the backscattering of forest canopy through a discrete scatterer representation. A modification of the SAVERS (Soil And Vegetation Reflection Simulator) simulator developed by the team for Global Navigation Satellite System Reflectometry over land has also been taken into account to simulate the soil contribution
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