Showing papers by "Mines ParisTech published in 2011"

As-Fabricated and Heat-Treated Microstructures of the Ti-6Al-4V Alloy Processed by Selective Laser Melting

Abstract: Selective laser melting (SLM) is a rapid manufacturing process that enables the buildup of very complex parts in short delays directly from powder beds. Due to the high laser beam energy during very short interaction times and the high solidification rates of the melting pool, the resulting microstructure is out-of-equilibrium and particularly textured. This type of as-fabricated microstructure may not satisfy the aeronautical criterion and requires post heat treatments. Optimized heat treatments are developed, in one side, to homogenize and form the stable phases α and β while preventing exaggerated grain growth. In the other side, heat treatment is investigated to relieve the thermal stresses appearing during cooling. This study is aimed at presenting the various types of microstructure of the Ti-6Al-4V alloy after postfabrication heat treatments below or above the β transus. Tensile tests are then carried out at room temperature in order to assess the effect of the microstructures on the mechanical properties. The fine as-fabricated microstructure presents high yield and ultimate strengths, whereas the ductility is well below the standard. A strong anisotropy of fracture between the two loading directions is noted, which is attributed to the manufacturing defects. Conventional and optimized heat treatments exhibit high yield and ultimate strengths while the ductility is significantly improved. This is due to a new optimization of the process parameters allowing drastic reduction of the number of defects. These two heat treatments enable now a choice of the morphology of the grains between columnar or equiaxial as a function of the type of loading.

MACSE: Multiple Alignment of Coding SEquences accounting for frameshifts and stop codons.

Abstract: Until now the most efficient solution to align nucleotide sequences containing open reading frames was to use indirect procedures that align amino acid translation before reporting the inferred gap positions at the codon level. There are two important pitfalls with this approach. Firstly, any premature stop codon impedes using such a strategy. Secondly, each sequence is translated with the same reading frame from beginning to end, so that the presence of a single additional nucleotide leads to both aberrant translation and alignment. We present an algorithm that has the same space and time complexity as the classical Needleman-Wunsch algorithm while accommodating sequencing errors and other biological deviations from the coding frame. The resulting pairwise coding sequence alignment method was extended to a multiple sequence alignment (MSA) algorithm implemented in a program called MACSE (Multiple Alignment of Coding SEquences accounting for frameshifts and stop codons). MACSE is the first automatic solution to align protein-coding gene datasets containing non-functional sequences (pseudogenes) without disrupting the underlying codon structure. It has also proved useful in detecting undocumented frameshifts in public database sequences and in aligning next-generation sequencing reads/contigs against a reference coding sequence. MACSE is distributed as an open-source java file executable with freely available source code and can be used via a web interface at: http://mbb.univ-montp2.fr/macse.

Invention and Transfer of Climate Change–Mitigation Technologies: A Global Analysis

Abstract: This article uses the European Patent Office Worldwide Patent Statistical Database to examine the geographic distribution and global diffusion of inventions in thirteen climate-mitigation technologies since 1978. The data suggest that until 1990 innovation was driven mostly by energy prices. Since then, environmental policies, and, more recently, climate policies, have accelerated the pace of innovation. The data also indicate that innovation is highly concentrated in three countries-Japan, Germany, and the United States-which together account for 60 percent of total inventions. Surprisingly, the contribution of emerging economies is far from negligible as China and Brazil together account for about 10 percent of total inventions. However, inventions from emerging economies are less likely to find markets beyond their borders, suggesting that inventions from emerging economies have less value. More generally, international transfers occur mostly between developed countries (73 percent of all exported inventions). Exports from developed countries to emerging economies are still limited (22 percent) but are growing rapidly, especially to China.

Stochastic gradient descent on Riemannian manifolds

Abstract: Stochastic gradient descent is a simple approach to find the local minima of a cost function whose evaluations are corrupted by noise. In this paper, we develop a procedure extending stochastic gradient descent algorithms to the case where the function is defined on a Riemannian manifold. We prove that, as in the Euclidian case, the gradient descent algorithm converges to a critical point of the cost function. The algorithm has numerous potential applications, and is illustrated here by four examples. In particular a novel gossip algorithm on the set of covariance matrices is derived and tested numerically.

Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization

Abstract: Summary: We present a tool for control-free copy number alteration (CNA) detection using deep-sequencing data, particularly useful for cancer studies. The tool deals with two frequent problems in the analysis of cancer deep-sequencing data: absence of control sample and possible polyploidy of cancer cells. FREEC (control-FREE Copy number caller) automatically normalizes and segments copy number profiles (CNPs) and calls CNAs. If ploidy is known, FREEC assigns absolute copy number to each predicted CNA. To normalize raw CNPs, the user can provide a control dataset if available; otherwise GC content is used. We demonstrate that for Illumina single-end, mate-pair or paired-end sequencing, GC-contentr normalization provides smooth profiles that can be further segmented and analyzed in order to predict CNAs. Availability: Source code and sample data are available at http://bioinfo-out.curie.fr/projects/freec/. Contact: freec@curie.fr Supplementary information:Supplementary data are available at Bioinformatics online.

Clusterpath: an Algorithm for Clustering using Convex Fusion Penalties

Abstract: We present a new clustering algorithm by proposing a convex relaxation of hierarchical clustering, which results in a family of objective functions with a natural geometric interpretation. We give efficient algorithms for calculating the continuous regularization path of solutions, and discuss relative advantages of the parameters. Our method experimentally gives state-of-the-art results similar to spectral clustering for non-convex clusters, and has the added benefit of learning a tree structure from the data.

Multilevel risk governance and urban adaptation policy

Abstract: Despite a flurry of activity in cities on climate change and growing interest in the research community, climate policy at city-scale remains fragmented and basic tools to facilitate good decision-making are lacking. This paper draws on an interdisciplinary literature review to establish a multilevel risk governance conceptual framework. It situates the local adaptation policy challenge and action within this to explore a range of institutional questions associated with strengthening local adaptation and related functions of local government. It highlights the value of institutional design to include analytic-deliberative practice, focusing on one possible key tool to support local decision-making—that of boundary organizations to facilitate local science-policy assessment. After exploring a number of examples of boundary organisations in place today, the authors conclude that a number of institutional models are valid. A common feature across the different approaches is the establishment of a science-policy competence through active deliberation and shared analysis engaging experts and decision-makers in an iterative exchange of information. Important features that vary include the geographic scope of operation and the origin of funding, the level and form of engagement of different actors, and the relationship with “producers” of scientific information. National and sub-national (regional) governments may play a key role to provide financial and technical assistance to support the creation of such boundary organizations with an explicit mandate to operate at local levels; in turn, in a number of instances boundary organizations have been shown to be able to facilitate local partnerships, engagement and decision-making on adaptation. While the agenda for multi-level governance of climate change is inevitably much broader than this, first steps by national governments to work with sub-national governments, urban authorities and other stakeholders to advance capacity in this area could be an important step for local adaptation policy agenda.

Predicting drug side-effect profiles: a chemical fragment-based approach

Abstract: Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients.

On necessary and sufficient conditions for differential flatness

Abstract: This paper is devoted to the characterization of differentially flat nonlinear systems in implicit representation, after elimination of the input variables, in the differential geometric framework of manifolds of jets of infinite order. We extend the notion of Lie-Backlund equivalence, introduced in Fliess et al. (IEEE Trans Automat Contr 44(5):922–937, 1999), to this implicit context and focus attention on Lie-Backlund isomorphisms associated to flat systems, called trivializations. They can be locally characterized in terms of polynomial matrices of the indeterminate $${\frac{d}{dt}}$$, whose range is equal to the kernel of the polynomial matrix associated to the implicit variational system. Such polynomial matrices are useful to compute the ideal of differential forms generated by the differentials of all possible trivializations. We introduce the notion of a strongly closed ideal of differential forms, and prove that flatness is equivalent to the strong closedness of the latter ideal, which, in turn, is equivalent to the existence of solutions of the so-called generalized moving frame structure equations. Two sequential procedures to effectively compute flat outputs are deduced and various examples and consequences are presented.

River Network Routing on the NHDPlus Dataset

Abstract: The mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into networks. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides streamflow observations at about 20 thousand gauges located on the NHDPlus river network. A river network model called Routing Application for Parallel Computation of Discharge (RAPID) is developed for the NHDPlus river network whose lateral inflow to the river network is calculated by a land surface model. A matrix-based version of the Muskingum method is developed herein, which RAPID uses to calculate flow and volume of water in all reaches of a river network with many thousands of reaches, including at ungauged locations. Gauges situated across river basins (not only at basin outlets) are used to autom...

Phase equilibrium of semiclathrate hydrates of co2, n2, ch4, or h2 + tetra-nbutylammonium bromide aqueous solution

Abstract: Semiclathrate hydrate dissociation conditions measured for the systems including CO2, N2, CH4, or H2 + tetra-n-butylammonium bromide (TBAB) aqueous solution with a wide range of concentrations (0.0...

ProDiGe: Prioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples

Abstract: Elucidating the genetic basis of human diseases is a central goal of genetics and molecular biology. While traditional linkage analysis and modern high-throughput techniques often provide long lists of tens or hundreds of disease gene candidates, the identification of disease genes among the candidates remains time-consuming and expensive. Efficient computational methods are therefore needed to prioritize genes within the list of candidates, by exploiting the wealth of information available about the genes in various databases. We propose ProDiGe, a novel algorithm for Prioritization of Disease Genes. ProDiGe implements a novel machine learning strategy based on learning from positive and unlabeled examples, which allows to integrate various sources of information about the genes, to share information about known disease genes across diseases, and to perform genome-wide searches for new disease genes. Experiments on real data show that ProDiGe outperforms state-of-the-art methods for the prioritization of genes in human diseases. ProDiGe implements a new machine learning paradigm for gene prioritization, which could help the identification of new disease genes. It is freely available at http://cbio.ensmp.fr/prodige .

Generalized continua and non-homogeneous boundary conditions in homogenisation methods

Abstract: Extensions of classical homogenization methods are presented that are used to replace a composite material by an effective generalized continuum model. Homogeneous equivalent second gradient and micromorphic models are considered, establishing links between the macroscopic generalized stress and strain measures and the fields of displacement, strain and stress inside a volume element of composite material. Recently proposed non-homogeneous boundary conditions to be applied to the unit cell, are critically reviewed. In particular, it is shown that such polynomial expansions of the local displacement field must be complemented by a generally non-periodic fluctuation field. A computational strategy is introduced to unambiguously determine this fluctuation. The approach is well-suited for elastic as well as elastoplastic composites.

Traffic sign classification using K-d trees and Random Forests

Abstract: In this paper, we evaluate the performance of K-d trees and Random Forests for traffic sign classification using different size Histogram of Oriented Gradients (HOG) descriptors and Distance Transforms. We use the German Traffic Sign Benchmark data set [1] containing 43 classes and more than 50,000 images. The K-d tree is fast to build and search in. We combine the tree classifiers with the HOG descriptors as well as the Distance Transforms and achieve classification rates of up to 97% and 81.8% respectively.

ProDiGe: PRioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples

Abstract: Elucidating the genetic basis of human diseases is a central goal of genetics and molecular biology. While traditional linkage analysis and modern high-throughput techniques often provide long lists of tens or hundreds of disease gene candidates, the identification of disease genes among the candidates remains time-consuming and expensive. Efficient computational methods are therefore needed to prioritize genes within the list of candidates, by exploiting the wealth of information available about the genes in various databases. Here we propose ProDiGe, a novel algorithm for Prioritization of Disease Genes. ProDiGe implements a novel machine learning strategy based on learning from positive and unlabeled examples, which allows to integrate various sources of information about the genes, to share information about known disease genes across diseases, and to perform genome-wide searches for new disease genes. Experiments on real data show that ProDiGe outperforms state-of-the-art methods for the prioritization of genes in human diseases.