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Institution

University of Rennes

EducationRennes, France
About: University of Rennes is a education organization based out in Rennes, France. It is known for research contribution in the topics: Population & Crystal structure. The organization has 18404 authors who have published 40374 publications receiving 995327 citations.


Papers
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Journal ArticleDOI
TL;DR: It is concluded that inbreeding avoidance is likely to be the crucial factor driving male dispersal in this species, and the genetic structure of both nuclear and mitochondrial microsatellites was compared to quantify sex‐specific dispersal rates.
Abstract: Maternity colonies of the communally breeding, nonmigratory Bechstein's bat consist of closely related females that live together with unrelated females, and average colony relatedness is low despite the absence of immigration. We compared the genetic structure of both nuclear and mitochondrial microsatellites in order to quantify sex-specific dispersal rates. More specifically, we aimed at testing whether male dispersal is able to balance the genetic effect of strong (absolute) female philopatry. Absolute female philopatry, indicated by an extreme mitochondrial DNA population differentiation of 96%, was indeed opposed by strong (possibly complete) male dispersal. Based on our knowledge of the biology of Myotis bechsteinii, we conclude that inbreeding avoidance is likely to be the crucial factor driving male dispersal in this species.

160 citations

Journal ArticleDOI
TL;DR: EMD outperformed the three other algorithms for the denoising of data highly contaminated by muscular activity and suggests that the performance of muscle artifact correction methods strongly depend on the level of data contamination, and of the source configuration underlying EEG signals.
Abstract: Electroencephalographic (EEG) recordings are often contaminated with muscle artifacts. This disturbing myogenic activity not only strongly affects the visual analysis of EEG, but also most surely impairs the results of EEG signal processing tools such as source localization. This article focuses on the particular context of the contamination epileptic signals (interictal spikes) by muscle artifact, as EEG is a key diagnosis tool for this pathology. In this context, our aim was to compare the ability of two stochastic approaches of blind source separation, namely independent component analysis (ICA) and canonical correlation analysis (CCA), and of two deterministic approaches namely empirical mode decomposition (EMD) and wavelet transform (WT) to remove muscle artifacts from EEG signals. To quantitatively compare the performance of these four algorithms, epileptic spike-like EEG signals were simulated from two different source configurations and artificially contaminated with different levels of real EEG-recorded myogenic activity. The efficiency of CCA, ICA, EMD, and WT to correct the muscular artifact was evaluated both by calculating the normalized mean-squared error between denoised and original signals and by comparing the results of source localization obtained from artifact-free as well as noisy signals, before and after artifact correction. Tests on real data recorded in an epileptic patient are also presented. The results obtained in the context of simulations and real data show that EMD outperformed the three other algorithms for the denoising of data highly contaminated by muscular activity. For less noisy data, and when spikes arose from a single cortical source, the myogenic artifact was best corrected with CCA and ICA. Otherwise when spikes originated from two distinct sources, either EMD or ICA offered the most reliable denoising result for highly noisy data, while WT offered the better denoising result for less noisy data. These results suggest that the performance of muscle artifact correction methods strongly depend on the level of data contamination, and of the source configuration underlying EEG signals. Eventually, some insights into the numerical complexity of these four algorithms are given.

160 citations

Journal ArticleDOI
TL;DR: In this paper, the authors estimated the composition of Titan lakes by using the direct abundance measurements from the Gas Chromatograph Mass Spectrometer aboard the Huygens probe and recent photochemical models.
Abstract: Hundreds of radar-dark patches interpreted as lakes have been discovered in the north and south polar regions of Titan. We have estimated the composition of these lakes by using the direct abundance measurements from the Gas Chromatograph Mass Spectrometer aboard the Huygens probe and recent photochemical models based on the vertical temperature profile derived by the Huygens Atmospheric Structure Instrument. Thermodynamic equilibrium is assumed between the atmosphere and the lakes, which are also considered nonideal solutions. We find that the main constituents of the lakes are ethane (C2H6) (~76%-79%), propane (C3H8) (~7%-8%), methane (CH4) (~5%-10%), hydrogen cyanide (HCN) (~2%-3%), butene (C4H8) (~1%), butane (C4H10) (~1%), and acetylene (C2H2) (~1%). The calculated composition of lakes is then substantially different from what has been expected from models elaborated prior to the exploration of Titan by the Cassini-Huygens spacecraft.

160 citations

Journal ArticleDOI
TL;DR: There is increasing knowledge on prognostic factors of localized and metastatic RCC and several predictive models have been developed by combining different prognostic features and are valuable tools for patient counseling, treatment decision-making and trial design.
Abstract: Purpose Renal cell carcinoma (RCC) is a very heterogeneous disease with widely varying prognosis. An accurate knowledge of the individual risk of disease progression and mortality after treatment is essential to counsel patients, plan individualized surveillance protocols and select patients for adapted treatment schedules and new clinical trials.

160 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present offshore seismic evidence from the Gulf of Lions and re-visited onshore data from Italy and Turkey that lead to a new concept of a two-step reflooding of the Mediterranean Basin after the Messinian Salinity crisis, where the refilling was first moderate and relatively slow accompanied by transgressive ravinement, and later on very rapid, preserving the subaerial Messinian Erosional Surface.
Abstract: The Messinian Salinity Crisis is well known to have resulted from a significant drop of the Mediterranean sea level. Considering both onshore and offshore observations, the subsequent reflooding is generally thought to have been very sudden. We present here offshore seismic evidence from the Gulf of Lions and re-visited onshore data from Italy and Turkey that lead to a new concept of a two-step reflooding of the Mediterranean Basin after the Messinian Salinity Crisis. The refilling was first moderate and relatively slow accompanied by transgressive ravinement, and later on very rapid, preserving the subaerial Messinian Erosional Surface. The amplitude of these two successive rises of sea level has been estimated at ≤500 m for the first rise and 600-900 m for the second rise. Evaporites from the central Mediterranean basins appear to have been deposited principally at the beginning of the first step of reflooding. After the second step, which preceeded the Zanclean Global Stratotype Section and Point, successive connections with the Paratethyan Dacic Basin, then the Adriatic foredeep, and finally the Euxinian Basin occurred, as a consequence of the continued global rise in sea level. A complex morphology with sills and sub-basins led to diachronous events such as the so-called 'Lago Mare'.This study helps to distinguish events that were synchronous over the entire Mediterranean realm, such as the two-step reflooding, from those that were more local and diachronous. In addition, the shoreline that marks the transition between these two steps of reflooding in the Provence Basin provides a remarkable palaeogeographical marker for subsidence studies.

160 citations


Authors

Showing all 18470 results

NameH-indexPapersCitations
Philippe Froguel166820118816
Bart Staels15282486638
Yi Yang143245692268
Geoffrey Burnstock141148899525
Shahrokh F. Shariat118163758900
Lutz Ackermann11666945066
Douglas R. MacFarlane11086454236
Elliott H. Lieb10751257920
Fu-Yuan Wu10736742039
Didier Sornette104129544157
Stefan Hild10345268228
Pierre I. Karakiewicz101120740072
Philippe Dubois101109848086
François Bondu10044069284
Jean-Michel Savéant9851733518
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202321
2022176
20212,655
20202,735
20192,670
20182,378