Understanding crack versus cavitation in pressure-sensitive adhesives: the role of kinetics

We perform traction experiments on viscous liquids highly confined between parallel plates, a geometry known as the probe-tack test in the adhesion community. Direct observation during the experiment coupled to force measurement shows the existence of several mechanisms for releasing the stress. Bubble nucleation and instantaneous growth had been observed in a previous work. Upon increasing further the traction velocity or the viscosity, the bubble growth is progressively delayed. At high velocities, cracks at the interface between the plate and the liquid appear before the bubbles have grown to their full size. Bubbles and cracks are thus observed concomitantly. At even higher velocities, cracks develop fully so early that the bubbles are not even visible. We present a theoretical model that describes these regimes, using a Maxwell fluid as a model for the actual fluid, a highly viscous silicon oil. We present the resulting phase diagramme for the different force peak regimes. The predictions are compatible with the data. Our results show that in addition to cavitation, interfacial cracks are encountered in a probe-tack traction test with viscoelastic, \emph{liquid} materials and not solely with viscoelastic solids like adhesives.Comment: 44 page

Traitement automatique des données hétérogènes liées à l'aménagement des territoires

National audienceLa notion d'aménagement du territoire fait référence à différents concepts tels que les informations spatiales et temporelles, les acteurs, les opinions, l'histoire, la politique, etc. Aujourd'hui, avec le développement des technologies numériques (blogs, forums, réseaux sociaux, etc.), l'ensemble des acteurs impliqués s'expriment et tous les documents textuels ainsi produits constituent une source considérable d'informations qu'il est crucial d'analyser. Dans cet article, nous souhaitons poser les premières bases d'une méthode automatique d'extraction de connaissances permettant d'analyser le ressenti (opinion et/ou sentiment) des acteurs impliqués à partir d'un corpus de données totalement hétérogènes constitués spécifiquement pour un territoire. Une telle approche, qui se situe dans le domaine de la science des données, offrira aux décideurs et aux usagers d'un territoire un environnement leur permettant d'en obtenir les clefs de lecture et d'en mesurer tous les enjeux et les contours

Self-replicating cracks: a collaborative fracture mode in thin films

Straight cracks are observed in thin coatings under residual tensile stress, resulting into the classical network pattern observed in china crockery, old paintings or dry mud. Here, we present a novel fracture mechanism where delamination and propagation occur simultaneously, leading to the spontaneous self-replication of an initial template. Surprisingly, this mechanism is active below the standard critical tensile load for channel cracks and selects a robust interaction length scale on the order of 30 times the film thickness. Depending on triggering mechanisms, crescent alleys, spirals or long bands are generated over a wide range of experimental parameters. We describe with a simple physical model the selection of the fracture path and provide a configuration diagram displaying the different failure modes

Motifs Séquentiels Discriminants pour les puces ADN

National audienceDécouvrir de nouvelles informations sur les groupes de gènes impliqués dans une maladie est un véritable challenge. Les puces ADN sont des outils puissants pour l'analyse des expressions de gènes. Elles mesurent l'expression de milliers de gènes dans différentes conditions biologiques. Dans cet article, nous proposons une nouvelle approche mettant en évidence des relations d'ordre entre les expressions de gènes. Tout d'abord, nous extrayons des motifs séquentiels qui peuvent être utilisés comme matériel d'étude par les biologistes. Or, comme la densité des bases issues des puces à ADN rend difficile l'extraction de ces motifs, nous introduisons une source de connaissances pendant le processus de fouille. De cette manière, l'espace de recherche est réduit et les résultats obtenus sont plus pertinents d'un point de vue biologique. Les expérimentations sur des données réelles soulignent la pertinence de notre proposition

Up and Down: Mining Multidimensional Sequential Patterns Using Hierarchies

International audienceData warehouses contain large volumes of time-variant data stored to help analysis. Despite the evolution of OLAP analysis tools and methods, it is still impossible for decision makers to find data mining tools taking the specificity of the data (e.g. multidimensionality, hierarchies, time-variant) into account. In this paper, we propose an original method to automatically extract sequential patterns taking hierar- chies into account. This method extracts patterns that describe the inner trends by displaying patterns that either go from precise knowledge to general knowledge or go from general knowledge to precise knowledge. For instance, one rule exhibited could be data contain first many sales of coke in Paris and lemonade in London for the same date, followed by a large number of sales of soft drinks in Europe, which is said to be divergent (as precise results like coke precede general ones like soft drinks). On the opposite, rules like data contain first many sales of soft drinks in Europe and chips in London for the same date, followed by a large number of sales of coke in Paris are said to be convergent. In this paper, we define the concepts related to this original method as well as the associated algorithms. The experiments which we carried out show the interest of our proposal

Fouille de données complexes : des relevés terrain aux données satellitaires pour la cartographie de paysages agricoles

National audienceDans cet article, nous présentons une approche préliminaire de caractérisation des paysages ruraux et de leurs systèmes de culture à partir de techniques de fouille de données (recherche d'itemsets fréquents). Cette méthode permet de coupler des données de relevé terrain aux indicateurs de texture extraits des images satellites. Sa mise en œuvre sur des données associées au Mali pose les premières bases d'une méthode originale d'extraction de motifs séquentiels à partir de données complexes

OLAP-Sequential Mining: Summarizing Trends from Historical Multidimensional Data using Closed Multidimensional Sequential Patterns

International audienceData warehouses are now well recognized as the way to store historical data that will then be available for future queries and analysis. In this context, some challenges are still open, among which the problem of mining such data. OLAP mining, introduced by J. Han in 1997, aims at coupling data mining techniques and data warehousing. These techniques have to take the specificities of such data into account. One of the specificities that is often not addressed by classical methods for data mining is the fact that data warehouses describe data through several dimensions. Moreover, the data are stored through time, and we thus argue that sequential patterns are one of the best ways to summarize the trends from such databases. Sequential pattern mining aims at discovering correlations among events through time. However, the number of patterns can become very important when taking several analysis dimensions into account, as it is the case in the framework of multidimensional databases. This is why we propose here to define a condensed representation without loss of information: closed multidimensional sequential patterns. This representation introduces properties that allow to deeply prune the search space. In this paper, we also define algorithms that do not require candidate set maintenance. Experiments on synthetic and real data are reported and emphasize the interest of our proposal