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Institution

École normale supérieure de Cachan

EducationCachan, Île-de-France, France
About: École normale supérieure de Cachan is a education organization based out in Cachan, Île-de-France, France. It is known for research contribution in the topics: Decidability & Finite element method. The organization has 2717 authors who have published 5585 publications receiving 175925 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, a semi-analytical and fully numerical model is developed in the framework of the inviscid potential flow theory to investigate the dynamics of a wave farm made by flap-type wave energy converters in the nearshore.

59 citations

Journal ArticleDOI
TL;DR: In this paper, the authors focus on the identification of large-scale discrete-event systems for the purpose of fault detection and present an identification algorithm which allows setting the accuracy of the identified model.

59 citations

Journal ArticleDOI
TL;DR: A unified a contrario detection method is proposed to solve three classical problems in clustering analysis to solve the validity of a cluster candidate and a correct merging rule between meaningful clusters.
Abstract: A unified a contrario detection method is proposed to solve three classical problems in clustering analysis. The first one is to evaluate the validity of a cluster candidate. The second problem is that meaningful clusters can contain or be contained in other meaningful clusters. A rule is needed to define locally optimal clusters by inclusion. The third problem is the definition of a correct merging rule between meaningful clusters, permitting to decide whether they should stay separate or unite. The motivation of this theory is shape recognition. Matching algorithms usually compute correspondences between more or less local features (called shape elements) between images to be compared. Each pair of matching shape elements leads to a unique transformation (similarity or affine map.) The present theory is used to group these shape elements into shapes by detecting clusters in the transformation space.

59 citations

Journal ArticleDOI
TL;DR: This work provides the first demonstration that RNase H inhibition by DKAs is due not only to their chelating properties but also to specific interactions with highly conserved amino acid residues in theRNase H domain, leading to effective targeting of HIV retrotranscription in cells and hence offering important insights for the rational design of RNaseH inhibitors.
Abstract: HIV-1 reverse transcriptase (RT)-associated RNase H activity is an essential function in viral genome retrotranscription RNase H is a promising drug target for which no inhibitor is available for therapy Diketo acid (DKA) derivatives are active site Mg2+-binding inhibitors of both HIV-1 RNase H and integrase (IN) activities To investigate the DKA binding site of RNase H and the mechanism of action, six couples of ester and acid DKAs, derived from 6-[1-(4-fluorophenyl)methyl-1H-pyrrol-2-yl)]-2,4-dioxo-5-hexenoic acid ethyl ester (RDS1643), were synthesized and tested on both RNase H and IN functions Most of the ester derivatives showed selectivity for HIV-1 RNase H versus IN, while acids inhibited both functions Molecular modeling and site-directed mutagenesis studies on the RNase H domain demonstrated different binding poses for ester and acid DKAs and proved that DKAs interact with residues (R448, N474, Q475, Y501, and R557) involved not in the catalytic motif but in highly conserved portions of the RNase H primer grip motif The ester derivative RDS1759 selectively inhibited RNase H activity and viral replication in the low micromolar range, making contacts with residues Q475, N474, and Y501 Quantitative PCR studies and fluorescence-activated cell sorting (FACS) analyses showed that RDS1759 selectively inhibited reverse transcription in cell-based assays Overall, we provide the first demonstration that RNase H inhibition by DKAs is due not only to their chelating properties but also to specific interactions with highly conserved amino acid residues in the RNase H domain, leading to effective targeting of HIV retrotranscription in cells and hence offering important insights for the rational design of RNase H inhibitors

59 citations

Journal ArticleDOI
TL;DR: In this article, a survey of 1000 Paris public transport users found that the negative relationship of in-vehicle density on reported satisfaction is similar to previous studies investigating PT crowding costs and stable across most individual characteristics.
Abstract: Crowding on public transport (PT) is a major issue for commuters around the world. Nevertheless, economists have rarely investigated the causes of crowding discomfort. Furthermore, most evidence on the costs of PT crowding is based on trade-offs between crowding, travel time and money. First, this paper assesses discomfort with PT crowding at various density levels across heterogeneous individuals using a different methodology. Based on a survey of 1000 Paris PT users, the negative relationship of in-vehicle density on reported satisfaction is similar to previous studies investigating PT crowding costs and stable across most individual characteristics. We also find a sensitive increase in crowding costs over users’ income. Second, we investigate the causes of this discomfort effect. We identify three key drivers: (a) dissatisfaction with standing and not being seated; (b) less opportunities to make use of the time during the journey; (c) the physical closeness of other travelers per se.

59 citations


Authors

Showing all 2722 results

NameH-indexPapersCitations
Shi Xue Dou122202874031
Olivier Hermine111102643779
John R. Reynolds10560750027
Shaul Mukamel95103040478
Tomás Torres8862528223
Ifor D. W. Samuel7460523151
Serge Abiteboul7327824576
Stéphane Roux6862719123
Zeger Debyser6740416531
Louis Nadjo6426412596
Praveen K. Thallapally6419012110
Andrew Travers6319313537
Shoji Takeuchi6369214704
Bineta Keita6327412053
Yves Mély6236813478
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
202222
202121
202029
201958
201879