Mines ParisTech

About: Mines ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Finite element method & Microstructure. The organization has 6564 authors who have published 11676 publications receiving 359898 citations. The organization is also known as: École nationale supérieure des mines de Paris & École des mines de Paris.

Multifractals and extreme rainfall events

Abstract: Based on a multifractal structure hypothesis for temporal rainfall processes, a general formula relating maximum possible point rainfall accumulations is derived as a function of the duration and sample size. This formula appears to be in agreement with empirical observations. Such a result may reconcile some opposite points of view regarding extreme rainfall events, and suggests new ways of exploiting the scaling properties of rain processes.

Investigation of porosity and permeability effects from microstructure changes during limestone dissolution

Abstract: We studied experimentally the dissolution of a porous limestone core during CO2-enriched water injection. We measured the changes in porosity and permeability arising from modifications of the pore network geometry and the fluid-rock interface. A methodology based on periodic X-ray microtomography imaging was implemented to record the evolution of the time- and scale-dependent microstructures with a spatial resolution of 4.91 μm. Two processes were successively involved in the rapid permeability increase of the sample, as documented from microscale to core-scale measurements...

Automatic analysis of DNA microarray images using mathematical morphology.

Abstract: Motivation: DNA microarrays are an experimental technology which consists in arrays of thousands of discrete DNA sequences that are printed on glass microscope slides. Image analysis is an important aspect of microarray experiments. The aim of this step is to reduce an image of spots into a table with a measure of the intensity for each spot. Efficient, accurate and automatic analysis of DNA spot images is essential in order to use this technology in laboratory routines. Results: We present an automatic non-supervised set of algorithms for a fast and accurate spot data extraction from DNA microarrays using morphological operators which are robust to both intensity variation and artefacts. The approach can be summarised as follows. Initially, ag ridding algorithm yields the automatic segmentation of the microarray image into spot quadrants which are later individually analysed. Then the analysis of the spot quadrant images is achieved in five steps. First, a prequantification, the spot size distribution law is calculated. Second, the background noise extraction is performed using a morphological filtering by area. Third, an orthogonal grid provides the first approach to the spot locus. Fourth, the spot segmentation or spot boundaries definition is carried out using the watershed transformation. And fifth, the outline of detected spots allows the signal quantification or spot intensities extraction; in this respect, a noise model has been investigated. The performance of the algorithm has been compared with two packages: ScanAlyze and Genepix, showing its robustness and precision. Availability: Ap rototype system integrated in PDI32 (an image processing software for Windows) may be obtained from the authors on request.