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Institution

Mines ParisTech

EducationParis, France
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.


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Journal ArticleDOI
A. Dumay1, J.-P. Chateau1, Sébastien Allain2, S. Migot1, Olivier Bouaziz2 
TL;DR: In this article, a thermochemical model of stacking-fault energy in the Fe-Mn-C system with few percent of Cu, Cr, Al and Si in addition is presented.
Abstract: We present a thermochemical model of the stacking-fault energy (SFE) in the Fe–Mn–C system with few percent of Cu, Cr, Al and Si in addition. Aluminium strongly increases the SFE, contrary to chromium, while the effect of silicon is more complex. Copper also increases the SFE, but strongly decreases the Neel temperature. The SFE is the relevant parameter that controls mechanical twinning, which is known to be at the origin of the excellent mechanical properties of these steels. Using this model, copper containing Fe–Mn–C grades were elaborated with SFE below 18 mJ/m 2 , in the range where ɛ-martensite platelets form instead of microtwins during plastic deformation. This substitution of deformation modes, confirmed by X-ray diffraction, does not significantly damage the mechanical properties, as long as the SFE is greater than 12 mJ/m 2 , which avoids the formation of α′-martensite.

612 citations

Journal ArticleDOI
TL;DR: This work shows that C-K theory captures the generation of new objects and new knowledge and offers a rigorous definition of Design, and interprets Braha and Reich’s topological structures for design modelling as special assumptions about the stability of objects in space K.
Abstract: C-K theory is a unified Design theory and was first introduced in 2003 (Hatchuel and Weil 2003). The name “C-K theory” reflects the assumption that Design can be modelled as the interplay between two interdependent spaces with different structures and logics: the space of concepts (C) and the space of knowledge (K). Both pragmatic views of Design and existing Design theories define Design as a dynamic mapping process between required functions and selected structures. However, dynamic mapping is not sufficient to describe the generation of new objects and new knowledge which are distinctive features of Design. We show that C-K theory captures such generation and offers a rigorous definition of Design. This is illustrated with an example: the design of Magnesium-CO2 engines for Mars explorations. Using C-K theory we also discuss Braha and Reich’s topological structures for design modelling (Braha and Reich 2003). We interpret this approach as special assumptions about the stability of objects in space K. Combining C-K theory and Braha and Reich’s models opens new areas for research about knowledge structures in Design theories. These findings confirm the analytical and interpretative power of C-K theory.

607 citations

Journal ArticleDOI
TL;DR: It is shown that the Amelioration de la Resolution Spatiale par Injection de Structures concept prevents from introducing spectral distortion into fused products and offers a reliable framework for further developments.
Abstract: Our framework is the synthesis of multispectral images (MS) at higher spatial resolution, which should be as close as possible to those that would have been acquired by the corresponding sensors if they had this high resolution. This synthesis is performed with the help of a high spatial but low spectral resolution image: the panchromatic (Pan) image. The fusion of the Pan and MS images is classically referred as pan-sharpening. A fused product reaches good quality only if the characteristics and differences between input images are taken into account. Dissimilarities existing between these two data sets originate from two causes-different times and different spectral bands of acquisition. Remote sensing physics should be carefully considered while designing the fusion process. Because of the complexity of physics and the large number of unknowns, authors are led to make assumptions to drive their development. Weaknesses and strengths of each reported method are raised and confronted to these physical constraints. The conclusion of this critical survey of literature is that the choice in the assumptions for the development of a method is crucial, with the risk to drastically weaken fusion performance. It is also shown that the Amelioration de la Resolution Spatiale par Injection de Structures concept prevents from introducing spectral distortion into fused products and offers a reliable framework for further developments.

583 citations

Journal ArticleDOI
TL;DR: SURFEX as mentioned in this paper is an externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean.
Abstract: . SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.

573 citations

Journal ArticleDOI
TL;DR: A novel supervised inference method, known as bipartite local models to first predict target proteins of a given drug, then to predict drugs targeting a given protein, which gives two independent predictions for each putative drug–target interaction, which can be combined to give a definitive prediction for each interaction.
Abstract: Motivation:In silico prediction of drug–target interactions from heterogeneous biological data is critical in the search for drugs for known diseases. This problem is currently being attacked from many different points of view, a strong indication of its current importance. Precisely, being able to predict new drug–target interactions with both high precision and accuracy is the holy grail, a fundamental requirement for in silico methods to be useful in a biological setting. This, however, remains extremely challenging due to, amongst other things, the rarity of known drug–target interactions. Results: We propose a novel supervised inference method to predict unknown drug–target interactions, represented as a bipartite graph. We use this method, known as bipartite local models to first predict target proteins of a given drug, then to predict drugs targeting a given protein. This gives two independent predictions for each putative drug–target interaction, which we show can be combined to give a definitive prediction for each interaction. We demonstrate the excellent performance of the proposed method in the prediction of four classes of drug–target interaction networks involving enzymes, ion channels, G protein-coupled receptors (GPCRs) and nuclear receptors in human. This enables us to suggest a number of new potential drug–target interactions. Availability: An implementation of the proposed algorithm is available upon request from the authors. Datasets and all prediction results are available at http://cbio.ensmp.fr/~yyamanishi/bipartitelocal/. Contact: kevbleakley@gmail.com Supplementary information:Supplementary data are available at Bioinformatics online.

558 citations


Authors

Showing all 6591 results

NameH-indexPapersCitations
Francis Bach11048454944
Olivier Delattre10349039258
Richard M. Murray9771169016
Bruno Latour9636494864
George G. Malliaras9438228533
George S. Wilson8871633034
Zhong-Ping Jiang8159724279
F. Liu8042823869
Kazu Suenaga7532926287
Carlo Adamo7544436092
Edith Heard7519623899
Enrico Zio73112723809
John J. Jonas7037921544
Bernard Asselain6940923648
Eric Guibal6929416397
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202264
2021274
2020260
2019250
2018249