Local matching indicators for transport with concave costs

In this note, we introduce a class of indicators that enable to compute efficiently optimal transport plans associated to arbitrary distributions of $N$ demands and $N$ supplies in $\mathbf{R}$ in the case where the cost function is concave. The computational cost of these indicators is small and independent of $N$. A hierarchical use of them enables to obtain an efficient algorithm

Effects of the Amount of Fillers and of the Crosslink Density on the Mechanical Behavior of Carbon-Black Filled Styrene Butadiene Rubbers

Several carbon-black filled styrene-butadiene rubbers are subjected to monotonic uniaxial tension tests in order to investi-gate the effects of the amount of fillers and of the crosslink density on their mechanical properties. The Young modulus, the volume changes associated with material damage and the stretch to failure are extracted and discussed. Results compare well to the literature results when exist and quantitative analysis are proposed when possible. Results show that filled rubbers are not incompressible when submitted to uniaxial tension tests and their volume changes are strongly dependent of the amount of fillers but are unaffected by the crosslink density. The latter shows strong impact on the filled rubbers stretch to failure but more interestingly this impact is com-parable to what is encountered in unfilled rubbers. The stretch to failure is improved by the addition of fillers with an optimum for material filled around 30 phr

Psychological Characteristics and their Relation to Performance in Professional Golfers

International audienceThis study investigated the psychological characteristics of professional golfers and their relation to golf performance. The aims of the study were (a) to provide descriptive data on professional golfers, (b) to test possible differences between successful and unsuccessful players and (c) to estimate whether psychological characteristics could predict golf performance. The data were collected from 41 male professional golfers the day before an official competition. Results revealed that players who made the cut were characterized by higher scores on performance-approach goal, cognitive and somatic anxiety, relaxation strategies, attentional control, emotional control and lower score on performance-avoidance goal. Subsequently, a multiple regression analysis revealed that higher cognitive anxiety, more frequent use of relaxation strategies and emotional control strategies were associated with better player's ranking at the end of the competition

Automorphisms of rational surfaces with positive entropy

final versionInternational audienceA complex compact surface which carries an automorphism of positive topological entropy has been proved by Cantat to be either a torus, a K3 surface, an Enriques surface or a rational surface. Automorphisms of rational surfaces are quite mysterious and have been recently the object of intensive studies. In this paper, we construct several new examples of automorphisms of rational surfaces with positive topological entropy. We also explain how to define and to count parameters in families of birational maps of the complex projective plane and in families of rational surfaces

Local matching indicators for transport problems with concave costs

In this paper, we introduce a class of indicators that enable to compute efficiently optimal transport plans associated to arbitrary distributions of N demands and M supplies in R in the case where the cost function is concave. The computational cost of these indicators is small and independent of N. A hierarchical use of them enables to obtain an efficient algorithm

Coopération entre Optimisation Combinatoire et Statistiques pour la Sélection animale

National audienceL'objectif de cette étude est d'élaborer des modèles prédictifs permettant, à partir de données génomiques, de déterminer les individus les plus performants selon certains critères quantitatifs. L'approche proposée allie les forces des méthodes statistiques et des méthodes d'optimisation combinatoire

Feature selection in high dimensional regression problems for genomic

International audienceIn the context of genomic selection in animal breeding, an important objective consists in looking for explicative markers for a phe- notype under study. In order to deal with a high number of markers, we propose to use combinatorial optimization to perform variable selection. Results show that our approach outperforms some classical and widely used methods on simulated and "closed to real" datasets

Feature selection for high dimensional regression using local search and statistical criteria

International audienceGenomic selection is a genetic evaluation of animals from their DNA, based on a huge number of markers covering the whole genome. It requires advanced approaches and in particular feature selection methods. Feature selection is a combinatorial problem that may be addressed by combinatorial optimization methods. We propose to combine an iterated local search (ILS) with a statistical evaluation of a multivariate regression and we compared three criteria in order to analyse their impact on the performance of the local search

Combining combinatorial optimization and statistics to mine high-throughput genotyping data

National audienceDepuis quelques années, la génomique a grandement évolué avec le développement de nouvelles technologies telles que le séquençage et le génotypage haut-débit. En ce qui concerne le domaine animal, nous sommes aujourd'hui capables de lire les informations génomiques sur près de 800 000 marqueurs sur des ensembles d'individus de plus en plus larges (de 3 000 à 10 000). Ces données peuvent donner lieu à des études d'association entre les marqueurs (GWAS : Genome-Wide Association Studies). Outre les contraintes biologiques (stockage des échantillons, manipulations longues et coûteuses...), la partie analyse de données (étude et extraction de connaissances) doit aussi être adaptée en terme de méthodologie et d'architecture matérielle et logicielle. L'objectif est d'élaborer des modéles prédictifs permettant, à partir des données génomiques, de déterminer les individus les plus performants selon certains critères quantitatifs de sélection animale. Pour cela, l'objectif théorique est à terme de définir de nouvelles méthodes permettant la coopération entre statistique et optimisation combinatoire spécifiquement dédiées aux données issues de génotypage haut débit en vue d'une implémentation